diff --git a/spaces/101-5/gpt4free/g4f/.v1/gpt4free/forefront/README.md b/spaces/101-5/gpt4free/g4f/.v1/gpt4free/forefront/README.md
deleted file mode 100644
index 7a59fe8e44f90c44854278d5fd673e726684bfce..0000000000000000000000000000000000000000
--- a/spaces/101-5/gpt4free/g4f/.v1/gpt4free/forefront/README.md
+++ /dev/null
@@ -1,19 +0,0 @@
-### Example: `forefront` (use like openai pypi package)
-
-```python
-from gpt4free import forefront
-
-
-# create an account
-account_data = forefront.Account.create(logging=False)
-
-# get a response
-for response in forefront.StreamingCompletion.create(
- account_data=account_data,
- prompt='hello world',
- model='gpt-4'
-):
- print(response.choices[0].text, end='')
-print("")
-
-```
\ No newline at end of file
diff --git a/spaces/1acneusushi/gradio-2dmoleculeeditor/data/Contoh Soal Psikotes Polri dan Jawabannya PDF 18 Panduan Lengkap untuk Calon Bintara Tamtama SIPSS SETUKPA dan SESPIM.md b/spaces/1acneusushi/gradio-2dmoleculeeditor/data/Contoh Soal Psikotes Polri dan Jawabannya PDF 18 Panduan Lengkap untuk Calon Bintara Tamtama SIPSS SETUKPA dan SESPIM.md
deleted file mode 100644
index 00454d4708d7ecd4e7183284be6e0698b5cd4a8d..0000000000000000000000000000000000000000
--- a/spaces/1acneusushi/gradio-2dmoleculeeditor/data/Contoh Soal Psikotes Polri dan Jawabannya PDF 18 Panduan Lengkap untuk Calon Bintara Tamtama SIPSS SETUKPA dan SESPIM.md
+++ /dev/null
@@ -1,157 +0,0 @@
-
-
Contoh Soal Psikotes Polri dan Jawabannya PDF 18
-
Apakah Anda sedang mencari contoh soal psikotes polri dan jawabannya pdf 18? Jika ya, maka Anda berada di tempat yang tepat. Dalam artikel ini, kami akan membahas tentang apa itu psikotes polri, jenis-jenis soal psikotes polri, sistem penilaian psikotes polri, tips dan trik menjawab soal psikotes polri, serta kumpulan contoh soal psikotes polri dan jawabannya pdf 18 yang bisa Anda download secara gratis.
Psikotes polri adalah sebuah tes yang bertujuan untuk mengukur kemampuan intelektual, kepribadian, dan kecermatan calon anggota polisi. Tes ini merupakan salah satu tahapan seleksi yang wajib diikuti oleh para pendaftar yang ingin masuk ke jenjang tamtama, bintara, atau akpol. Psikotes polri juga bermanfaat untuk mengetahui potensi, minat, bakat, serta kesiapan mental calon anggota polisi dalam menghadapi berbagai situasi dan tantangan di lapangan.
-
Jenis-Jenis Soal Psikotes Polri
-
Soal psikotes polri terdiri dari tiga jenis tes utama, yaitu tes kecerdasan, tes kepribadian, dan tes kecermatan. Berikut adalah penjelasan singkat tentang masing-masing jenis tes tersebut.
-
Tes Kecerdasan
-
Tes kecerdasan adalah tes yang menguji kemampuan berpikir logis, analitis, kritis, serta pengetahuan umum calon anggota polisi. Tes ini biasanya terdiri dari 100 soal pilihan ganda yang harus diselesaikan dalam waktu tidak lebih dari 90 menit. Jenis-jenis soal yang muncul dalam tes kecerdasan antara lain adalah:
-
-
Sinonim (persamaan kata)
-
Antonim (lawan kata)
-
Analogi (padanan kata)
-
Perbandingan (proporsi)
-
Pengelompokan kata (kategorisasi)
-
Deret angka/huruf (polanya)
-
Logika aritmatika (hitungan cepat)
-
Logika gambar (spasial)
-
Pengetahuan umum (fakta)
-
Penalaran kata (acak)
-
Matematika dasar (rumus)
-
Logika deduksi (silogisme)
-
Logika analitis (penarikan kesimpulan)
-
Aritmatika sosial (persentase)
-
-
Tes Kepribadian
-
Tes kepribadian adalah tes yang mengukur atau menilai karakteristik pribadi calon anggota polisi. Tes ini tidak ada jawaban benar atau salah, namun hanya ada jawaban yang sesuai atau tidak sesuai dengan diri sendiri. Tes ini biasanya terdiri dari beberapa pernyataan yang harus dipilih tingkat kesetujuannya atau frekuensinya. Jenis-jenis soal yang muncul dalam tes kepribadian antara lain adalah:
-
-
Tes dengan pilihan jawaban dengan kriteria Sangat Setuju (SS), Setuju (S), Ragu-ragu (R), Tidak Setuju (TS), Sangat Tidak Setuju (STS)
-
Tes dengan pilihan jawaban pernyataan frekuensi waktu seperti Tidak Pernah, Selalu, Sering, Jarang, Tidak bisa memutuskan atau Selalu, Sering, Kadang-kadang, diwaktu tertentu
-
Tes dengan jawaban seperti Ya / Tidak
-
Tes Minat EPPS (Edwards Personal Preference Schedule) atau pilihan AB, A-B, A atau B.
-
-
Tes Kecermatan
-
Tes kecermatan adalah tes yang menguji kemampuan konsentrasi, ketelitian, serta daya ingat calon anggota polisi. Tes ini biasanya terdiri dari 100 soal pilihan ganda yang harus diselesaikan dalam waktu tidak lebih dari 90 menit. Jenis-jenis soal yang muncul dalam tes kecermatan antara lain adalah:
-
-
Angka hilang
-
Huruf hilang
-
Simbol hilang
-
Kombinasi angka/huruf/simbol hilang
-
-
Sistem Penilaian Psikotes Polri
-
Psikotes polri memiliki sistem penilaian dengan skala 0-100. Setiap skala memiliki artinya masing-masing yakni:
-
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-google docs contoh soal psikokes
-
-
0 - 40: Kurang Sekali
-
41 - 60: Kurang
-
61 - 80: Cukup
-
81 - 100: Baik
-
-
Psikotes polri memiliki nilai kelulusan yang wajib dipenuhi yakni 61 keatas untuk Memenuhi Syarat (MS). Bila memiliki nilai 60 ke bawah itu artinya Tidak Memenuhi Syarat (TMS).
-
Tips dan Trik Menjawab Soal Psikotes Polri
-
Berikut adalah beberapa tips dan trik yang bisa Anda lakukan untuk menjawab soal psikotes polri dengan baik dan benar.
-
Persiapan sebelum tes
-
-
Berdoa dan berserah diri kepada Tuhan Yang Maha Esa.
-
Beristirahat yang cukup sebelum hari tes.
-
Makan dan minum yang sehat dan bergizi.
-
Membawa perlengkapan yang dibutuhkan seperti pensil 2B, penghapus, penggaris, jam tangan.
-
Mempelajari materi-materi psikotes yang relevan dengan tes polri.
-
Tips dan Trik Menjawab Soal Psikotes Polri
-
Berikut adalah beberapa tips dan trik yang bisa Anda lakukan untuk menjawab soal psikotes polri dengan baik dan benar.
-
Persiapan sebelum tes
-
-
Berdoa dan berserah diri kepada Tuhan Yang Maha Esa.
-
Beristirahat yang cukup sebelum hari tes.
-
Makan dan minum yang sehat dan bergizi.
-
Membawa perlengkapan yang dibutuhkan seperti pensil 2B, penghapus, penggaris, jam tangan.
-
Mempelajari materi-materi psikotes yang relevan dengan tes polri.
-
Mencari referensi contoh soal psikotes polri dan jawabannya pdf 18.
-
-
Strategi menjawab soal
-
-
Membaca soal dengan teliti dan cermat.
-
Memilih jawaban yang paling sesuai dengan diri sendiri atau paling logis dan benar.
-
Menghindari jawaban yang ragu-ragu, tidak bisa memutuskan, atau tidak tahu.
-
Memanfaatkan waktu dengan baik dan efisien.
-
Menjawab soal yang mudah terlebih dahulu, kemudian baru soal yang sulit.
-
Menandai soal yang belum dijawab atau diragukan untuk direview kembali.
-
Menggunakan teknik eliminasi untuk menyempitkan pilihan jawaban.
-
Menggunakan logika, pengetahuan, intuisi, atau kreativitas untuk menyelesaikan soal.
-
-
Sikap saat tes
-
-
Tenang, percaya diri, dan optimis.
-
Fokus, konsentrasi, dan tidak mudah terganggu.
-
Jujur, tidak mencontek, atau berbuat curang.
-
Kooperatif, mengikuti instruksi dan aturan yang diberikan panitia.
-
Bersikap sopan, santun, dan hormat kepada panitia dan peserta lainnya.
-
-
Kumpulan Contoh Soal Psikotes Polri dan Jawabannya PDF 18
-
Berikut adalah tabel contoh soal psikotes polri dan jawabannya pdf 18 yang bisa Anda download secara gratis. Tabel ini berisi nomor soal, jenis soal, sumber soal, serta link download soal. Anda bisa memilih soal yang sesuai dengan kebutuhan dan minat Anda. Selamat belajar!
- | No | Jenis Soal | Sumber Soal | Link Download | |----|------------|-------------|---------------| | 1 | Tes Kecerdasan | Soalskul.com | [KLIK DISINI](https://www.soalskul.com/2022/02/soal-psikotes-polri.html) | | 2 | Tes Kepribadian | BIMBEL MYTENTOR Blog | [KLIK DISINI](https://pascaldaddy512.com/download-kumpulan-contoh-soal-tes-psikologi-polri-tahun-2022/) | | 3 | Tes Kecermatan | Panot Book | [KLIK DISINI](https://panotbook.com/soal-psikotes-polri/) |
Kesimpulan
-
Demikianlah artikel tentang contoh soal psikotes polri dan jawabannya pdf 18. Kami harap artikel ini bisa membantu Anda dalam mempersiapkan diri untuk menghadapi tes psikotes polri. Ingatlah bahwa tes psikotes polri bukanlah hal yang sulit jika Anda sudah belajar dengan baik dan benar. Jangan lupa untuk berdoa dan berserah diri kepada Tuhan Yang Maha Esa. Semoga Anda berhasil menjadi anggota polri yang profesional dan berkualitas. Amin.
-
FAQs
-
Berikut adalah beberapa pertanyaan yang sering diajukan oleh pembaca tentang contoh soal psikotes polri dan jawabannya pdf 18.
-
-
Apa itu psikotes polri?
-Psikotes polri adalah sebuah tes yang bertujuan untuk mengukur kemampuan intelektual, kepribadian, dan kecermatan calon anggota polisi. Tes ini merupakan salah satu tahapan seleksi yang wajib diikuti oleh para pendaftar yang ingin masuk ke jenjang tamtama, bintara, atau akpol.
-
Apa saja jenis-jenis soal psikotes polri?
-Soal psikotes polri terdiri dari tiga jenis tes utama, yaitu tes kecerdasan, tes kepribadian, dan tes kecermatan. Tes kecerdasan menguji kemampuan berpikir logis, analitis, kritis, serta pengetahuan umum calon anggota polisi. Tes kepribadian mengukur atau menilai karakteristik pribadi calon anggota polisi. Tes kecermatan menguji kemampuan konsentrasi, ketelitian, serta daya ingat calon anggota polisi.
-
Bagaimana sistem penilaian psikotes polri?
-Psikotes polri memiliki sistem penilaian dengan skala 0-100. Setiap skala memiliki artinya masing-masing yakni: 0 - 40: Kurang Sekali; 41 - 60: Kurang; 61 - 80: Cukup; 81 - 100: Baik. Psikotes polri memiliki nilai kelulusan yang wajib dipenuhi yakni 61 keatas untuk Memenuhi Syarat (MS). Bila memiliki nilai 60 ke bawah itu artinya Tidak Memenuhi Syarat (TMS).
-
Bagaimana tips dan trik menjawab soal psikotes polri?
-Beberapa tips dan trik yang bisa dilakukan untuk menjawab soal psikotes polri antara lain adalah: berdoa dan berserah diri kepada Tuhan Yang Maha Esa; beristirahat yang cukup sebelum hari tes; makan dan minum yang sehat dan bergizi; membawa perlengkapan yang dibutuhkan seperti pensil 2B, penghapus, penggaris, jam tangan; mempelajari materi-materi psikotes yang relevan dengan tes polri; mencari referensi contoh soal psikotes polri dan jawabannya pdf 18; membaca soal dengan teliti dan cermat; memilih jawaban yang paling sesuai dengan diri sendiri atau paling logis dan benar; menghindari jawaban yang ragu-ragu, tidak bisa memutuskan, atau tidak tahu; memanfaatkan waktu dengan baik dan efisien; menjawab soal yang mudah terlebih dahulu, kemudian baru soal yang sulit; menandai soal yang belum dijawab atau diragukan untuk direview kembali; menggunakan teknik eliminasi untuk menyempitkan pilihan jawaban; menggunakan logika, pengetahuan, intuisi, atau kreativitas untuk menyelesaikan soal; tenang, percaya diri, dan optimis; fokus, konsentrasi, dan tidak mudah terganggu; jujur, tidak mencontek, atau berbuat curang; kooperatif, mengikuti instruksi dan aturan yang diberikan panitia; bersikap sopan, santun, dan hormat kepada panitia dan peserta lainnya.
-
Di mana saya bisa mendapatkan contoh soal psikotes polri dan jawabannya pdf 18?
-Anda bisa mendapatkan contoh soal psikotes polri dan jawabannya pdf 18 secara gratis di internet. Kami telah menyediakan tabel contoh soal psikotes polri dan jawabannya pdf 18 yang bisa Anda download di bagian akhir artikel ini. Anda juga bisa mencari sumber-sumber lainnya di mesin pencari seperti Google atau Bing.
-
- 0a6ba089eb
-
-
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diff --git a/spaces/1acneusushi/gradio-2dmoleculeeditor/data/Easy Classical Ukulele Solos Featuring Music Of Bach Mozart Beethoven Vivaldi And Other Composer ((EXCLUSIVE)).md b/spaces/1acneusushi/gradio-2dmoleculeeditor/data/Easy Classical Ukulele Solos Featuring Music Of Bach Mozart Beethoven Vivaldi And Other Composer ((EXCLUSIVE)).md
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-
-
Easy Classical Ukulele Solos: How to Play Beautiful Music from Bach, Mozart, Beethoven, Vivaldi and More
-
-
If you love classical music and want to play it on your ukulele, you might think that it's too difficult or complicated. But don't worry, there are many easy classical ukulele solos that you can learn and enjoy. In this article, we will show you how to play some of the most famous and beautiful pieces from composers like Bach, Mozart, Beethoven, Vivaldi and more.
-
-
Why Play Classical Music on the Ukulele?
-
-
Classical music is not only a great source of inspiration and enjoyment, but also a wonderful way to improve your ukulele skills. Playing classical music on the ukulele can help you:
-
Easy Classical Ukulele Solos: Featuring music of Bach, Mozart, Beethoven, Vivaldi and other composer
Enhance your musical expression and interpretation
-
Challenge yourself and have fun
-
-
-
Plus, classical music sounds amazing on the ukulele. The warm and sweet tone of the instrument matches perfectly with the melodies and harmonies of the classical repertoire. You can create a soothing and relaxing atmosphere with your ukulele by playing some classical tunes.
-
-
How to Play Easy Classical Ukulele Solos?
-
-
To play easy classical ukulele solos, you need to have some basic skills and knowledge. You should be able to:
-
-
-
Tune your ukulele properly
-
Read tablature or standard notation
-
Play basic chords and scales
-
Fingerpick with your thumb and fingers
-
Follow the tempo and rhythm of the piece
-
-
-
You don't need to be an expert or a virtuoso to play easy classical ukulele solos. You just need to practice regularly and patiently. Start with simple pieces that suit your level and gradually move on to more challenging ones. You can also use online resources like videos, tutorials, books and courses to help you learn and improve.
-
-
What are Some Easy Classical Ukulele Solos to Play?
-
-
There are many easy classical ukulele solos that you can choose from. Here are some examples of popular and beautiful pieces that you can try:
-
-
-
Jesu, Joy of Man's Desiring by J.S. Bach: This is one of the most famous pieces by Bach, composed for choir and orchestra. It has a lovely melody that can be easily played on the ukulele with fingerpicking. You can find the tablature here.
-
Turkish March by W.A. Mozart: This is a lively and catchy piece by Mozart, composed for piano. It has a fast tempo and a rhythmic pattern that can be fun to play on the ukulele with strumming or fingerpicking. You can find the tablature here.
-
Ode to Joy by L.V. Beethoven: This is one of the most famous pieces by Beethoven, composed for symphony orchestra and choir. It has a simple and joyful melody that can be easily played on the ukulele with fingerpicking or strumming. You can find the tablature here.
-
The Four Seasons by A. Vivaldi: This is a set of four concertos by Vivaldi, composed for violin and orchestra. Each concerto represents a different season of the year, with different moods and themes. You can play some of the main themes on the ukulele with fingerpicking or strumming. You can find the tablature https://byltly.com/2uKylp
-
Data recovery can be performed in different scenarios such as:
-
-
Accidental deletion: You may delete some files or folders by mistake or empty the recycle bin without checking its contents.
-
Formatting: You may format your hard drive or partition by accident or intentionally without backing up your data.
-
Virus attack: Your hard drive may get infected by malware or ransomware that encrypts or deletes your data.
-
Logical damage: Your hard drive may suffer from logical errors such as bad sectors, file system corruption, partition loss, etc. that make your data inaccessible.
-
Physical damage: Your hard drive may get damaged by physical factors such as water, fire, shock, etc. that cause mechanical failure or head crash.
-
-
Data recovery can be classified into two types: logical data recovery and physical data recovery. Logical data recovery deals with the software-related issues that cause data loss, while physical data recovery deals with the hardware-related issues that cause data loss. Logical data recovery can be done by using free data recovery software, while physical data recovery requires professional help and may cost a lot of money.
-
How to Recover Data from Hard Drive Free Using Free Data Recovery Software?
-
If you want to recover data from hard drive free using free data recovery software, you need to follow these steps:
-
-
Stop using your hard drive immediately. Do not write any new data to your hard drive or perform any operations that may overwrite your lost data. This will increase the chances of successful data recovery.
-
Download and install a reliable free data recovery software on another computer or device. Do not install the software on the same hard drive where you lost your data. You can search for some of the best free data recovery software online or use the link below.
-
Connect your hard drive to the computer or device where you installed the free data recovery software. You can use a USB cable, an external enclosure, or a SATA adapter to connect your hard drive.
-
Launch the free data recovery software and select your hard drive as the source disk. The software will scan your hard drive and display all the recoverable files and folders.
-
Preview and select the files and folders that you want to recover. You can use the filter and search options to narrow down your selection. You can also preview some of the files before recovering them.
-
Choose a destination folder to save your recovered data. Do not save the recovered data on the same hard drive where you lost it. You can save it on another hard drive, USB flash drive, cloud storage, etc.
-
Click on the Recover button to start the recovery process. Wait for the process to complete and check your recovered data.
-
-
What are the Benefits and Risks of Using Free Data Recovery Software?
-
Using free data recovery software has some benefits and risks that you should be aware of before using it. Here are some of them:
-
Benefits
-
-
You can recover data from hard drive free without spending any money.
-
You can recover various types of files such as photos, videos, documents, music, etc.
-
You can recover data from different scenarios such as accidental deletion, formatting, virus attack, etc.
-
You can recover data from different storage devices such as hard drives, USB flash drives, memory cards, etc.
-
-
Risks
-
-
The free data recovery software may not be able to recover all your lost data or may recover
- ddb901b051
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diff --git a/spaces/1acneusushi/gradio-2dmoleculeeditor/data/HD Online Player (Khamoshiyan hindi 720p free download) - Enjoy the Full Movie in High Quality.md b/spaces/1acneusushi/gradio-2dmoleculeeditor/data/HD Online Player (Khamoshiyan hindi 720p free download) - Enjoy the Full Movie in High Quality.md
deleted file mode 100644
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+++ /dev/null
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-
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HD Online Player (Khamoshiyan hindi 720p free download)
-
Are you looking for a way to watch Khamoshiyan, a romantic horror movie from Bollywood, online for free? If yes, then you have come to the right place. In this article, we will tell you everything you need to know about Khamoshiyan, how to watch it online for free, and what are the benefits of doing so. So, sit back and enjoy this guide on how to stream or download Khamoshiyan in HD quality.
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HD Online Player (Khamoshiyan hindi 720p free download)
Khamoshiyan is a 2015 Hindi movie directed by Karan Darra and produced by Mahesh Bhatt and Mukesh Bhatt. The movie stars Ali Fazal, Gurmeet Choudhary, and Sapna Pabbi in the lead roles. The movie is about a novelist named Kabir who travels to Kashmir in search of inspiration for his next book. There he meets Meera, a mysterious woman who runs a hotel in a secluded location. Kabir falls in love with Meera, but soon discovers that she is hiding a dark secret. She is married to Jaidev, a rich businessman who is now a spirit after his death. Jaidev is obsessed with Meera and does not let her go. Kabir decides to help Meera escape from Jaidev's clutches, but faces many challenges and dangers along the way.
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How to watch Khamoshiyan online for free
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Streaming platforms that offer Khamoshiyan
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One of the easiest ways to watch Khamoshiyan online for free is to use a streaming platform that offers the movie. There are many websites that allow you to watch Hindi movies online for free, but not all of them are reliable or safe. Some of them may have low-quality videos, annoying ads, or malware that can harm your device. Therefore, you need to be careful when choosing a streaming platform for watching Khamoshiyan online.
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One of the best streaming platforms that offer Khamoshiyan online for free is onlinemovieshindi.com. This website has a huge collection of Bollywood movies that you can watch online or download without any hassle. The website has a simple and user-friendly interface that lets you find your favorite movie easily. You can also filter the movies by genre, year, quality, or language. The website also provides subtitles and dubbing options for some movies.
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To watch Khamoshiyan online for free on onlinemovieshindi.com, you just need to follow these steps:
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If you prefer to download Khamoshiyan rather than stream it online, you can also do that on onlinemovieshindi.com. The website allows you to download the movie in HD quality by just clicking on a button below the video player. The downloaded file will be the same as the one used for online streaming.
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Click on the download button and save the file on your device
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Benefits of watching Khamoshiyan online
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High-quality video and audio
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One of the main benefits of watching Khamoshiyan online is that you can enjoy the movie in high-quality video and audio. Onlinemovieshindi.com offers Khamoshiyan in 720p resolution, which is ideal for watching on any device. The video quality is clear and crisp, and the audio quality is also excellent. You can see every detail of the movie and hear every sound effect without any distortion or interruption.
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Another benefit of watching Khamoshiyan online is that you can watch it anytime and anywhere you want. You don't need to go to a theater or buy a DVD to watch the movie. You just need an internet connection and a device that can access the website. You can watch the movie at your own pace and convenience. You can pause, rewind, fast-forward, or skip any part of the movie as you wish. You can also watch it multiple times without any limit.
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A third benefit of watching Khamoshiyan online is that you can save money and avoid legal issues. Onlinemovieshindi.com offers Khamoshiyan online for free, which means you don't need to pay anything to watch the movie. You can enjoy the movie without spending a dime or worrying about piracy laws. The website does not host any illegal content or violate any copyright laws.
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Tips for enjoying Khamoshiyan online
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Choose a reliable and safe website
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As we mentioned earlier, not all websites that offer Hindi movies online are reliable or safe. Some of them may have low-quality videos, annoying ads, or malware that can harm your device. Therefore, you need to be careful when choosing a website for watching Khamoshiyan online.
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We recommend using onlinemovieshindi.com as it is one of the best streaming platforms that offer Khamoshiyan online for free. The website has a huge collection of Bollywood movies that you can watch online or download without any hassle. The website has a simple and user-friendly interface that lets you find your favorite movie easily.
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Use a good internet connection and device
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To enjoy watching Khamoshiyan online in HD quality, you need to have a good internet connection and device that can support it. A slow or unstable internet connection may cause buffering or lagging issues that can ruin your viewing experience.
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You also need to have a device that can play HD videos smoothly without any glitches or errors. A laptop, tablet, smartphone, or smart TV are some of the devices that can play HD videos well.
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Watch with subtitles or dubbing if needed
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If you are not fluent in Hindi or have difficulty understanding some parts of the movie, you can use subtitles or dubbing options to enhance your comprehension.
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Onlinemovieshindi.com provides subtitles and dubbing options for some movies, including Khamoshiyan. You can choose your preferred language from the list available below the video player.
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Conclusion
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Khamoshiyan is a romantic horror movie from Bollywood that tells the story of a novelist who falls in love with a mysterious woman who is haunted by her dead husband's spirit.
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Watching Khamoshiyan online has many benefits, such as high-quality video and audio, convenience and flexibility, and cost-effectiveness and legality. You can enjoy the movie without spending any money or worrying about piracy laws.
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To enjoy Khamoshiyan online, you need to follow some tips, such as choosing a reliable and safe website, using a good internet connection and device, and watching with subtitles or dubbing if needed.
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We hope this article has helped you learn how to watch Khamoshiyan online for free in HD quality. If you liked this article, please share it with your friends and family who are also interested in watching Hindi movies online. And don't forget to watch Khamoshiyan and enjoy the thrilling and romantic story.
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FAQs
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Here are some of the frequently asked questions and answers about Khamoshiyan and online streaming:
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What is the genre of Khamoshiyan?
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Khamoshiyan is a romantic horror movie that combines elements of romance, mystery, and supernatural.
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Who are the actors in Khamoshiyan?
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Khamoshiyan stars Ali Fazal as Kabir, Gurmeet Choudhary as Jaidev, and Sapna Pabbi as Meera.
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When was Khamoshiyan released?
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Khamoshiyan was released on 30 January 2015 in India.
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How long is Khamoshiyan?
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Khamoshiyan has a runtime of 122 minutes.
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Is Khamoshiyan based on a book?
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No, Khamoshiyan is not based on a book. It is an original story written by Vikram Bhatt.
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diff --git a/spaces/1gistliPinn/ChatGPT4/Examples/As Rulas De Bakunin Pdf Download.md b/spaces/1gistliPinn/ChatGPT4/Examples/As Rulas De Bakunin Pdf Download.md
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index 04ef02cf283c784a936c4f7a8fd73273de6350d5..0000000000000000000000000000000000000000
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diff --git a/spaces/1gistliPinn/ChatGPT4/Examples/Bit Che 35 Build 51 Serial Key Keygen !!TOP!!.md b/spaces/1gistliPinn/ChatGPT4/Examples/Bit Che 35 Build 51 Serial Key Keygen !!TOP!!.md
deleted file mode 100644
index 989b4d9be9f231f7b7ee30e6a4dd619a8bd003ac..0000000000000000000000000000000000000000
--- a/spaces/1gistliPinn/ChatGPT4/Examples/Bit Che 35 Build 51 Serial Key Keygen !!TOP!!.md
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Bit Che 35 Build 51 Serial Key Keygen: A Comprehensive Guide
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Are you looking for a fast and easy way to find and download torrents? Do you want to enjoy the benefits of a full version of Bit Che 35 Build 51 without paying a dime? If you answered yes to any of these questions, then this article is for you. In this article, we will show you how to use Bit Che 35 Build 51 Serial Key Keygen to activate the ultimate torrent search tool and get access to millions of torrents in seconds.
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diff --git a/spaces/1gistliPinn/ChatGPT4/Examples/Bluestacks Free TOP Download For Windows 7 32 Bit 1gb Ram.md b/spaces/1gistliPinn/ChatGPT4/Examples/Bluestacks Free TOP Download For Windows 7 32 Bit 1gb Ram.md
deleted file mode 100644
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+++ /dev/null
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diff --git a/spaces/1pelhydcardo/ChatGPT-prompt-generator/assets/Download 0xc000007b for PES 2017 The Best Way to Fix the Application Error.md b/spaces/1pelhydcardo/ChatGPT-prompt-generator/assets/Download 0xc000007b for PES 2017 The Best Way to Fix the Application Error.md
deleted file mode 100644
index cf11b3f060bf3331a526470685563d58cad05fa7..0000000000000000000000000000000000000000
--- a/spaces/1pelhydcardo/ChatGPT-prompt-generator/assets/Download 0xc000007b for PES 2017 The Best Way to Fix the Application Error.md
+++ /dev/null
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How to Download and Fix 0xc00007b Error for PES 2017
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If you are a fan of Pro Evolution Soccer (PES) 2017, you might have encountered a frustrating error that prevents you from launching or playing the game. This error is known as 0xc00007b and it usually appears with a message that says "The application was unable to start correctly". In this article, we will explain what this error means, why it occurs, how to download 0xc00007b for PES 2017, and how to fix it. By following these steps, you will be able to enjoy your favorite soccer game without any hassle.
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What is 0xc00007b Error and Why Does It Occur?
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The meaning and causes of 0xc00007b error
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The 0xc00007b error is a common Windows error that indicates that something is wrong with the application or the system. It can be caused by various factors, such as:
Conflicting or missing Microsoft Visual C++ Redistributable packages
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Incorrect or damaged registry entries
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Mismatch between 32-bit and 64-bit versions of software and Windows operating systems
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These factors can interfere with the proper functioning of the application or the system, resulting in the 0xc00007b error.
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The impact of 0xc00007b error on PES 2017
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The 0xc00007b error can affect any Windows application or game, including PES 2017. When this error occurs, you will not be able to launch or play PES 2017, as the game will crash or freeze. This can be very frustrating, especially if you are looking forward to playing your favorite soccer game. Moreover, this error can also affect your gaming performance, as it can cause lagging, stuttering, or graphical glitches.
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The sources and steps to download 0xc00007b for PES 2017
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One of the possible solutions to fix the 0xc00007b error for PES 2017 is to download and install the 0xc00007b file for the game. This file is a DLL (Dynamic Link Library) file that contains code and data that are used by multiple programs. By downloading and installing this file, you can replace the corrupt or missing file that is causing the error.
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To download 0xc00007b for PES 2017, you can use one of the following sources:
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DLL-files.com: This is a website that provides free downloads of DLL files for various programs and games. You can search for 0xc00007b on the website and download the file that matches your Windows version and system type (32-bit or 64-bit).
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Fix4dll.com: This is another website that offers free downloads of DLL files for different applications and games. You can also search for 0xc00007b on the website and download the file that suits your Windows version and system type (32-bit or 64-bit).
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Microsoft.com: This is the official website of Microsoft, the developer of Windows operating systems. You can download the latest Microsoft Visual C++ Redistributable packages from this website, as they contain the 0xc00007b file and other DLL files that are required by PES 2017 and other programs.
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After downloading 0xc00007b for PES 2017, you need to follow these steps to install it:
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Extract the downloaded file to a folder on your computer.
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Copy the 0xc00007b file from the extracted folder.
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Paste the 0xc00007b file into the installation folder of PES 2017. This is usually located at C:\Program Files (x86)\Steam\steamapps\common\Pro Evolution Soccer 2017.
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Restart your computer and launch PES 2017 to see if the error is fixed.
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While downloading 0xc00007b for PES 2017 can be a quick and easy solution, you need to be careful and follow some precautions and tips to avoid any problems or risks. Here are some of them:
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Make sure you download 0xc00007b from a reliable and trustworthy source, such as the ones mentioned above. Do not download 0xc00007b from unknown or suspicious websites, as they may contain viruses or malware that can harm your computer or steal your personal information.
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Make sure you backup your important data and files before downloading and installing 0xc00007b. This way, you can restore your data and files in case something goes wrong or you lose them during the process.
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Make sure you scan your computer with an antivirus or anti-malware program after downloading and installing 0xc00007b. This way, you can detect and remove any potential threats or infections that may have entered your computer during the process.
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If downloading and installing 0xc00007b does not fix the error for PES 2017, you may need to try other solutions, such as updating your Windows version, reinstalling PES 2017, repairing your registry entries, or contacting Konami for support.
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The methods and instructions to fix 0xc00007b error for PES 2017
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Besides downloading 0xc00007b, there are other methods that can help you fix the error for PES 2017. Here are some of them:
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Method
Description
Instructions
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Update Windows version
This method involves updating your Windows version to the latest one, as it may contain bug fixes and improvements that can resolve the error.
To update your Windows version, follow these steps:
Click on the Start button and select Settings.
Select Update & Security.
Select Windows Update.
Select Check for updates.
If there are any available updates, select Download and install.
Wait for the updates to finish installing and restart your computer
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Reinstall PES 2017
This method involves uninstalling and reinstalling PES 2017, as it may fix any corrupt or missing files that are causing the error.
To reinstall PES 2017, follow these steps:
Open Steam and go to your Library.
Right-click on PES 2017 and select Uninstall.
Wait for the uninstallation to complete and confirm the action.
Go to the Steam Store and search for PES 2017.
Select Add to Cart and Purchase for Myself.
Select Install Game and follow the instructions.
Wait for the installation to finish and launch PES 2017 to see if the error is fixed.
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Repair registry entries
This method involves repairing any incorrect or damaged registry entries that are related to PES 2017 or the error. The registry is a database that stores settings and information for Windows and applications. If the registry is corrupted, it can cause errors and problems.
To repair registry entries, follow these steps:
Click on the Start button and type cmd.
Right-click on Command Prompt and select Run as administrator.
Type sfc /scannow and press Enter.
Wait for the scan to complete and fix any errors it finds.
Type exit and press Enter to close the Command Prompt.
Restart your computer and launch PES 2017 to see if the error is fixed.
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The benefits and advantages of fixing 0xc00007b error for PES 2017
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By fixing the 0xc00007b error for PES 2017, you will be able to enjoy several benefits and advantages, such as:
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You will be able to launch and play PES 2017 without any interruption or frustration.
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You will be able to improve your gaming performance, as the error will not cause any lagging, stuttering, or graphical glitches.
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You will be able to enhance your gaming experience, as you will be able to access all the features and modes of PES 2017.
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You will be able to protect your computer from any potential damage or infection that may result from the error or its causes.
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You will be able to save your time and effort, as you will not have to deal with the error or its solutions repeatedly.
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Conclusion
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A summary of the main points and a call to action
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In conclusion, the 0xc00007b error is a common Windows error that can affect PES 2017 and prevent you from launching or playing the game. It can be caused by various factors, such as corrupt or missing files, incompatible or outdated Windows version, conflicting or missing Microsoft Visual C++ Redistributable packages, incorrect or damaged registry entries, or mismatch between 32-bit and 64-bit versions of software and Windows operating systems. To fix this error, you can download 0xc00007b for PES 2017 from a reliable source and install it in the game folder, or you can try other methods, such as updating your Windows version, reinstalling PES 2017, repairing your registry entries, or contacting Konami for support. By fixing this error, you will be able to enjoy your favorite soccer game without any hassle. If you found this article helpful, please share it with your friends and fellow gamers who may also encounter this error. Thank you for reading!
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FAQs
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What is PES 2017?
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PES 2017 is a soccer simulation game developed by Konami. It is the 16th installment in the Pro Evolution Soccer series. It features improved graphics, gameplay, modes, teams, players, stadiums, and more. It was released in September 2016 for Windows, PlayStation 3, PlayStation 4, Xbox 360, Xbox One, Android, and iOS devices.
-
How can I update PES 2017?
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To update PES 2017, you need to have an internet connection and a Steam account. You can update PES 2017 automatically through Steam by following these steps:
Open Steam and go to your Library.
Select PES 2017 and right-click on it.
Select Properties.
Select Updates.
Select Always keep this game updated option.
Select Close.
Wait for the update to download and install.
You can also update PES 2017 manually by downloading and installing the latest patches and data packs from the official website of Konami or other trusted sources.
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What are the system requirements for PES 2017?
-
The minimum and recommended system requirements for PES 2017 are as follows:
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-
Minimum
Recommended
-
OS: Windows 10, 8.1, 8, 7 SP1, Vista SP2
OS: Windows 10, 8.1, 8, 7 SP1, Vista SP2
-
CPU: Intel Core2 Duo 1.8GHz / AMD Athlon II X2 240 or equivalent processor
CPU: Intel Core i3 530 / AMD Phenom II X4 925 or equivalent processor
-
RAM: 1 GB
RAM: 2 GB
-
GPU: DirectX 9.0c compatible video card. 1024MB Pixel Shader 3.0 (NVIDIA GeForce 8800 / AMD/ATI Radeon X1600 / Intel HD Graphics 3000 or better)
GPU: DirectX 9.0c compatible video card. 1024MB Pixel Shader 3.0 (NVIDIA GeForce GTX 260 / AMD/ATI Radeon HD4850 / Intel HD Graphics 4000 or better)
-
Storage: 8 GB
Storage: 8 GB
-
Sound: DirectX 9.0c compatible sound card
Sound: DirectX 9.0c compatible sound card
-
Network: Broadband Internet connection
Network: Broadband Internet connection
-
Resolution: 800 x 600 monitor resolution
Resolution: 1280 x 720 monitor resolution
-
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How can I contact Konami for support?
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If you have any questions, issues, or feedback regarding PES 2017, you can contact Konami for support by using one of the following methods:
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Email: You can send an email to support@konami.com and describe your problem or inquiry in detail.
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Phone: You can call the Konami customer service number at +1-310-220-8100 and speak to a representative.
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Website: You can visit the official website of Konami at https://www.konami.com/ and access the support section, where you can find FAQs, manuals, forums, and contact forms.
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Social media: You can follow Konami on social media platforms, such as Facebook, Twitter, Instagram, YouTube, and Twitch, and send them a message or comment.
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Where can I find more information about PES 2017?
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If you want to find more information about PES 2017, such as news, updates, features, reviews, tips, tricks, guides, videos, screenshots, and more, you can visit some of the following sources:
I hope this article has helped you to download and fix 0xc00007b error for PES 2017. If you have any comments or suggestions, please feel free to leave them below. Happy gaming!
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diff --git a/spaces/1pelhydcardo/ChatGPT-prompt-generator/assets/Download Gacha Life APK for Android - Create Your Own Anime Characters.md b/spaces/1pelhydcardo/ChatGPT-prompt-generator/assets/Download Gacha Life APK for Android - Create Your Own Anime Characters.md
deleted file mode 100644
index 7d1f5694a47d989207ac72b8855f3130bfb85988..0000000000000000000000000000000000000000
--- a/spaces/1pelhydcardo/ChatGPT-prompt-generator/assets/Download Gacha Life APK for Android - Create Your Own Anime Characters.md
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If you are a fan of anime, chibi, and dress-up games, you might have heard of Gacha Life. It is a popular game that allows you to create your own anime-style characters and stories. You can also interact with other players online, play mini-games, and collect gems. In this article, we will guide you on how to download Gacha Life APK for free on your Android device, how to play the game, what are its features, and what are the reviews from other users.
Gacha Life is a game developed by Lunime, a company that specializes in anime-themed games. It was released in October 2018 for Android and iOS devices, and later for Windows and Mac computers. The game has over 100 million downloads on Google Play Store and has a rating of 4.4 out of 5 stars.
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A game for anime fans
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Gacha Life is inspired by the Japanese concept of "gacha", which is a type of vending machine that dispenses random items, such as toys, stickers, or cards. In the game, you can use gems to "gacha" for various items, such as clothes, accessories, weapons, and more. You can then use these items to dress up your characters in different styles and genres, such as fantasy, horror, sci-fi, or romance. You can also choose from hundreds of hairstyles, eyes, mouths, and other facial features to customize your characters' appearance.
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A game for creative minds
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Gacha Life is not only a game for dressing up your characters, but also a game for creating your own scenes and stories. You can use the Studio mode to arrange up to eight characters in various poses and backgrounds. You can also add text bubbles and dialogue to make your scenes more lively. You can then save your scenes as images or videos, or share them with other players online. You can also use the Skit Maker mode to combine multiple scenes into a skit or a short story.
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How to download Gacha Life APK for Android devices?
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If you want to play Gacha Life on your Android device, you need to download the APK file from a reliable source. An APK file is an application package file that contains all the files and data needed to install an app on your device. However, you need to be careful when downloading APK files from unknown sources, as they may contain malware or viruses that can harm your device or steal your personal information.
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Here are the steps to download and install Gacha Life APK on your Android device:
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Go to a trusted website that offers Gacha Life APK download, such as [Filehippo](^2^) or [APKPure](^4^).
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Tap on the download button and wait for the file to be downloaded on your device.
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Once the download is complete, go to your device's settings and enable the option to install apps from unknown sources. This will allow you to install apps that are not from the Google Play Store.
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Locate the downloaded APK file on your device's file manager and tap on it to start the installation process.
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Follow the instructions on the screen and wait for the app to be installed on your device.
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Once the installation is done, you can launch the app and enjoy playing Gacha Life.
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Tips to avoid malware and viruses
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Here are some tips to avoid malware and viruses when downloading APK files from unknown sources:
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Check the reviews and ratings of the website and the app before downloading. Avoid websites that have low ratings, negative reviews, or suspicious pop-ups.
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Check the file size and name of the APK file before downloading. Avoid files that are too large, too small, or have different names than the app you want to download.
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Scan the APK file with an antivirus or malware scanner before installing. Avoid files that are detected as harmful or infected by the scanner.
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Backup your device's data before installing. In case something goes wrong, you can restore your device to its previous state.
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How to play Gacha Life?
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Gacha Life is a game that lets you unleash your creativity and imagination. You can play the game in different modes, such as Studio, Skit Maker, Life, and Games. Here are some tips on how to play each mode:
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Customize your own characters
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In Studio mode, you can create up to 20 characters and customize their appearance, personality, and relationship. You can choose from hundreds of items and options to dress up your characters in various styles and genres. You can also change their facial expressions, poses, and movements. You can also assign them a name, a birthday, a favorite color, a favorite food, and a favorite hobby. You can also give them a voice by recording your own voice or using a text-to-speech feature.
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Create your own scenes and stories
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Explore different areas and meet new friends
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In Life mode, you can explore different areas in the Gacha World, such as the town, the school, the park, and more. You can meet new characters and interact with them by talking, giving gifts, or playing games. You can also learn more about their stories and secrets by increasing your friendship level with them. You can also join clubs and participate in events.
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Play mini-games and collect gems
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In Games mode, you can play various mini-games, such as Bex's Festival, Duck & Dodge, Phantom's Remix, and more. You can earn gems by playing these games, which you can use to gacha for more items. You can also compete with other players on the leaderboards and win prizes.
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What are the features of Gacha Life?
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Gacha Life is a game that offers many features and benefits for its players. Here are some of them:
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A table of features and benefits
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Feature
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Benefit
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Free to download and play
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No need to pay for anything to enjoy the game
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No internet connection required
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You can play offline anytime and anywhere
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No ads or in-app purchases
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You won't be interrupted or tempted by annoying ads or offers
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User-friendly interface and controls
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You can easily navigate and operate the game without any hassle
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High-quality graphics and sound effects
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You can enjoy the game's visuals and audio without any lag or distortion
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Unlimited customization options
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You can create your own unique characters and stories without any limitations
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Social interaction and community support
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You can chat with other players online, share your creations, and get feedback from others
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Educational and entertaining value
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You can learn new skills, such as creativity, communication, problem-solving, and more while having fun
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A comparison with other similar games
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Gacha Life is not the only game of its kind in the market. There are other similar games that also offer anime-style character creation and story-making, such as Gacha Club, Gacha Studio, Gachaverse, and more. However, Gacha Life stands out from the rest for several reasons, such as:
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It has more items and options to customize your characters and scenes than other games.
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It has more modes and features to play with than other games.
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It has a larger and more active community of players than other games.
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It has better reviews and ratings than other games.
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Therefore, if you are looking for a game that can satisfy your anime and gacha cravings, Gacha Life is the best choice for you.
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What are the reviews of Gacha Life?
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Gacha Life has received many reviews from its users, both positive and negative. Here are some examples of what they have to say about the game:
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Positive reviews from users
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Here are some of the positive reviews from users who love the game:
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"I love this game so much! It's so fun and creative! I can make my own characters and stories and share them with others. The graphics are amazing and the music is catchy. I recommend this game to anyone who likes anime and gacha."
-- A Google user
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"This game is awesome! It has so many things to do and explore. You can customize your characters in any way you want, and create your own scenes and skits. You can also chat with other players online and make new friends. This game is very addictive and entertaining."
-- A Google user
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"This game is the best game ever! It's so easy to use and has so many options. You can create your own characters and stories, or watch other people's creations. You can also play mini-games and collect gems. This game is very educational and fun."
-- A Google user
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Negative reviews from users
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Here are some of the negative reviews from users who dislike the game:
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"I hate this game so much! It's so boring and repetitive! All you do is dress up your characters and make them talk. The graphics are terrible and the music is annoying. I don't recommend this game to anyone who likes anime and gacha."
-- A Google user
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"This game is awful! It has so many bugs and glitches. You can't save your characters or scenes, or share them with others. The game crashes all the time and deletes your progress. This game is very frustrating and disappointing."
-- A Google user
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"This game is the worst game ever! It's so inappropriate and offensive! You can dress up your characters in revealing clothes and make them do inappropriate things. The game also promotes violence, bullying, and stereotypes. This game is very harmful and disgusting."
-- A Google user
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Conclusion
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Gacha Life is a game that allows you to create your own anime-style characters and stories. You can also interact with other players online, play mini-games, and collect gems. You can download Gacha Life APK for free on your Android device from a reliable source, but you need to be careful of malware and viruses. You can play the game in different modes, such as Studio, Skit Maker, Life, and Games. You can also enjoy the game's features and benefits, such as unlimited customization options, high-quality graphics, social interaction, educational value, and more. However, you may also encounter some drawbacks of the game, such as boredom, repetition, bugs, glitches, crashes, inappropriate content, violence, bullying, stereotypes, and more.
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FAQs
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Here are some frequently asked questions about Gacha Life:
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Is Gacha Life safe for kids?
-
Gacha Life is rated 12+ on Google Play Store for moderate violence, suggestive themes, language, crude humor, horror/fear themes, simulated gambling, alcohol/tobacco/drug use or reference. Therefore, it may not be suitable for younger kids or sensitive viewers. Parents should supervise their kids when playing the game or use parental controls to restrict access to certain features or content.
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Is Gacha Life online or offline?
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Gacha Life can be played both online and offline. You can play offline anytime and anywhere without an internet connection. However, you need to play online if you want to chat with other players, share your creations, or access some features or content that require an internet connection.
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How to update Gacha Life?
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Gacha Life is regularly updated by the developers to fix bugs, improve performance, and add new features or content. You can update Gacha Life by going to the Google Play Store and tapping on the update button. However, you may need to uninstall and reinstall the app if you have downloaded the APK file from an unknown source.
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How to delete Gacha Life?
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If you want to delete Gacha Life from your device, you can go to your device's settings and tap on the apps or applications option. Then, find Gacha Life and tap on it. Then, tap on the uninstall button and confirm your action. You can also delete Gacha Life by going to the Google Play Store and tapping on the uninstall button.
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How to contact Gacha Life support?
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If you have any questions, problems, or feedback about Gacha Life, you can contact the developers by emailing them at lunimegames@gmail.com. You can also visit their website at [lunime.com] or follow them on their social media accounts, such as Facebook, Twitter, Instagram, or YouTube.
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diff --git a/spaces/1phancelerku/anime-remove-background/Download Teka-teki Silang Kata Mencari Mod Apk Gratis dan Nikmati Permainan Kata yang Seru.md b/spaces/1phancelerku/anime-remove-background/Download Teka-teki Silang Kata Mencari Mod Apk Gratis dan Nikmati Permainan Kata yang Seru.md
deleted file mode 100644
index ea4fa1374a607f328f3ab29eb134ef296306959d..0000000000000000000000000000000000000000
--- a/spaces/1phancelerku/anime-remove-background/Download Teka-teki Silang Kata Mencari Mod Apk Gratis dan Nikmati Permainan Kata yang Seru.md
+++ /dev/null
@@ -1,152 +0,0 @@
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How to download Teka Teki Silang Kata Mencari mod APK
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Step 2: Enable unknown sources on your device
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The next thing you need to do is to enable unknown sources on your device. This is a setting that allows you to install apps from sources other than the Google Play Store. By default, this setting is disabled to prevent unauthorized or harmful apps from being installed on your device. However, since you are downloading a mod APK file from a third-party website, you need to enable it temporarily to proceed with the installation.
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Go to your device's settings and tap on security or privacy.
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Remember to disable this setting once you are done with the installation, to avoid any potential security issues in the future.
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Now that you have enabled unknown sources on your device, you can proceed to download and install the mod APK file for Teka Teki Silang Kata Mencari. Here are the steps you need to follow:
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Go to the website that you have chosen for downloading the mod APK file, such as [Aptoide].
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Tips and tricks for playing the game
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Use hints wisely. Hints can help you find hidden words or reveal letters in the grid, but they are limited and cost coins. You can get more coins by completing levels, watching ads, or using the mod APK features, but you should still use them sparingly and only when necessary.
-
Learn new words. The game has a huge database of words from various categories and themes, such as animals, food, sports, geography, etc. You can learn new words by playing the game and expanding your vocabulary. You can also tap on any word in the grid to see its definition and pronunciation.
-
Challenge yourself. The game has different difficulty levels, ranging from easy to hard. You can choose the level that suits your skill level and preference, or you can challenge yourself by playing harder levels or using fewer hints. You can also try to beat your own score or time record for each level.
-
-
Features and advantages of the mod APK
-
-
Unlock all levels. The game has hundreds of levels, each with a different theme and difficulty. However, some of them are locked and require coins or stars to unlock them. With the mod APK, you can unlock all levels without spending any coins or stars.
-
Get unlimited coins. Coins are used to buy hints, unlock levels, or access premium content in the game. You can earn coins by completing levels, watching ads, or using real money. With the mod APK, you can get unlimited coins without doing any of these things.
-
Remove ads. Ads are annoying and distracting, especially when they pop up in between levels or gameplay. They also consume data and battery power on your device. With the mod APK, you can remove ads completely and enjoy a smooth and uninterrupted gaming experience.
-
Access premium content. The game also has some premium content, such as themes, wallpapers, stickers, etc. that can enhance your gaming experience. However, these content are not free and require coins or real money to purchase them. With the mod APK, you can access all premium content without paying anything.
-
-
Precautions and limitations of the mod APK
-
-
Be careful of malware. As mentioned earlier, not all mod APKs are safe or reliable. Some of them may contain malware or viruses that can harm your device or steal your personal information. Therefore, you need to be careful and use a reputable website and a scanner tool to download and install the mod APK.
-
Be aware of compatibility issues. Mod APKs may not be compatible with all devices or versions of the original app. They may also cause some glitches or errors in the game or on your device. Therefore, you need to check the compatibility and requirements of the mod APK before downloading and installing it.
-
Be prepared for update problems. Mod APKs may not be updated as frequently or as easily as the original app. They may also lose their functionality or features when the original app is updated or changed by the developers. Therefore, you need to be prepared for update problems and look for new versions of the mod APK when available.
-
Be respectful of legal consequences. Mod APKs may violate the terms and conditions or the intellectual property rights of the original app developers. They may also infringe on the rights of other users or players who use the official app. Therefore, you need to be respectful of legal consequences and use the mod APK responsibly and ethically.
-
-
Conclusion
-
Teka Teki Silang Kata Mencari is a fun and challenging word puzzle game that can test your vocabulary and logic skills. You can also enjoy more features and advantages in the game by using a mod APK. However, you need to be careful and informed before downloading and installing any mod APK on your device.
-
In this article, we have shown you how to download Teka Teki Silang Kata Mencari mod APK safely and easily. We have also given you some tips on how to use it effectively and responsibly. We hope that this article has been helpful and informative for you.
-
If you have any questions or feedback, please feel free to leave a comment below. We would love to hear from you!
-
FAQs
-
What is Teka Teki Silang Kata Mencari?
-
Teka Teki Silang Kata Mencari is a popular word puzzle game that challenges your vocabulary and logic skills. You have to find hidden words in a grid of letters, using clues and hints. The game has hundreds of levels, each with a different theme and difficulty. You can also compete with other players online and earn coins and rewards.
-
What is mod APK?
-
Mod APK is a modified version of an original application that offers additional features or enhancements that are not present in the official release. Mod APKs are usually created by independent developers who alter the original APK files to unlock premium features, remove ads, provide unlimited resources, or even bypass certain restrictions imposed by the app developers.
-
How to download Teka Teki Silang Kata Mencari mod APK?
-
To download Teka Teki Silang Kata Mencari mod APK, you need to follow these steps:
-
-
Find a reliable source for the mod APK file, such as [Aptoide].
-
Enable unknown sources on your device.
-
Download and install the mod APK file.
-
Launch the game and enjoy the features.
-
-
How to use Teka Teki Silang Kata Mencari mod APK?
-
To use Teka Teki Silang Kata Mencari mod APK, you need to follow these tips:
-
-
Use hints wisely.
-
Learn new words.
-
Challenge yourself.
-
-
You can also enjoy these features and advantages:
-
-
Unlock all levels.
-
Get unlimited coins.
-
Remove ads.
-
Access premium content.
-
-
You also need to be aware of these precautions and limitations:
-
-
Be careful of malware.
-
Be aware of compatibility issues.
-
Be prepared for update problems.
-
Be respectful of legal consequences.
-
-
What are the benefits and risks of using mod APK?
-
The benefits of using mod APK are:
-
-
You can enjoy more features and advantages in the game that are not available in the official release, such as unlocking all levels, getting unlimited coins, removing ads, and accessing premium content.
-
You can customize and enhance your gaming experience according to your preferences and requirements.
-
You can save money and time by not having to spend real money or watch ads to get coins or premium content.
-
-
The risks of using mod APK are:
-
-
You may expose your device or personal information to malware or viruses that can harm or steal them.
-
You may face compatibility issues or glitches that can affect the performance or functionality of the game or your device.
-
You may encounter update problems that can make the mod APK obsolete or incompatible with the original app.
-
You may violate the terms and conditions or the intellectual property rights of the original app developers or other users, and face legal consequences.
-
-
Therefore, you need to weigh the benefits and risks of using mod APK before deciding to use it.
-
-
Thank you for reading this article. I hope you have learned something useful and interesting about how to download Teka Teki Silang Kata Mencari mod APK. If you have any questions or feedback, please feel free to leave a comment below. I would love to hear from you!
401be4b1e0
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\ No newline at end of file
diff --git a/spaces/1phancelerku/anime-remove-background/Download Tekken 3D Prime Edition for PC and Experience the Ultimate Fighting Game.md b/spaces/1phancelerku/anime-remove-background/Download Tekken 3D Prime Edition for PC and Experience the Ultimate Fighting Game.md
deleted file mode 100644
index f90407f0ebb39bbe108225663bc8d09fc556b11f..0000000000000000000000000000000000000000
--- a/spaces/1phancelerku/anime-remove-background/Download Tekken 3D Prime Edition for PC and Experience the Ultimate Fighting Game.md
+++ /dev/null
@@ -1,295 +0,0 @@
-
-
Tekken 3D: Prime Edition - A Portable Version of the Popular Fighting Game
-
If you are a fan of fighting games, you might have heard of Tekken, one of the most successful and long-running franchises in the genre. Tekken has been adapted to various platforms, from arcades to consoles to handhelds, and has a loyal fan base around the world. One of the latest entries in the series is Tekken 3D: Prime Edition, a fighting game developed and published by Bandai Namco Entertainment for the Nintendo 3DS. In this article, we will tell you everything you need to know about this game, including what it is, how to play it, how to download it for PC, and what are its reviews and ratings.
Tekken 3D: Prime Edition is a fighting game that brings the arcade-style action and backstory of the Tekken video game series into the 3D gaming realm like never before. Exclusively for Nintendo 3DS, the 3DS cartridge contains both the game and the complete Tekken: Blood Vengeance 3D movie.
-
The game is a graphically updated version of Tekken 6 for the Nintendo 3DS, supporting the handheld's 3D capabilities and maintaining a steady 60 FPS even when running in 3D; however, the 3D is disabled during wireless play. It features 41 playable characters from Tekken 6 and a card collecting mode. It also includes local and online multiplayer for up to two players.
-
The game's development and release history
-
The game was first announced at E3 2011, where Nintendo revealed that Tekken would be coming to the 3DS handheld. At Namco Bandai Games' booth at E3, they showcased a demo of the Tekken in-game engine running on the 3DS. Producer Katsuhiro Harada stated that the game would run in full 60 frames per second with the 3D on.
-
On August 17, 2011, a new trailer for Tekken 3D: Prime Edition was released, along with its name. It was also revealed that the game would include over 40 characters, as well as a 3D version of the film Tekken: Blood Vengeance on the game's cartridge. The game also has more than 700 artwork cards to collect, mostly cutscenes from the Blood Vengeance movie that can be shared via the StreetPass function on the 3DS.
-
The game was released in North America on February 14, 2012, in Japan on February 16, 2012, in Europe on February 17, 2012, and in Australia on February 23, 2012.
-
How to Play Tekken 3D: Prime Edition?
-
The game's modes and gameplay mechanics
-
Tekken 3D: Prime Edition has several modes to choose from, such as Quick Battle mode, Special Survival mode, Versus Battle mode, Online Battle mode, Practice mode, Gallery mode, Card Collection mode, and Options mode.
-
Quick Battle
Quick Battle mode is where the player can fight against various computer-controlled opponents with different ranks and skills. The player can choose their own character and stage, as well as the difficulty level and the number of rounds. The player can also customize their character's appearance and moves with the cards they have collected.
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Special Survival mode is where the player can test their endurance and skills by fighting against a series of opponents with increasing difficulty. The player can only use one character and has a limited amount of health that does not regenerate between matches. The player can earn extra health by performing special moves or finishing moves. The player can also earn extra cards by defeating opponents. The mode ends when the player loses or quits.
-
Versus Battle mode is where the player can fight against another player using the same 3DS system or using the wireless connection. The player can choose their own character and stage, as well as the rules and settings of the match. The player can also use their cards to customize their character.
-
Online Battle mode is where the player can fight against other players from around the world using the Nintendo Wi-Fi Connection. The player can choose to play in ranked matches or friendly matches, as well as create or join lobbies with up to four players. The player can also view their online profile and statistics, as well as send and receive messages and cards from other players.
-
Practice mode is where the player can practice their moves and combos with their chosen character against a dummy opponent. The player can adjust the settings of the practice mode, such as the dummy's behavior, the display of inputs, and the frame data. The player can also access a move list and a command list for their character.
-
Gallery mode is where the player can view various artworks and movies related to Tekken 3D: Prime Edition, such as character illustrations, stage backgrounds, opening movies, ending movies, and trailers. The player can also watch the full-length Tekken: Blood Vengeance 3D movie in this mode.
-
Card Collection mode is where the player can view, manage, and trade their cards with other players. The cards are divided into four categories: Character Cards, Special Cards, Customization Cards, and Movie Cards. The cards have different effects and values depending on their rarity and type. The player can use their cards to enhance their character's abilities, appearance, and moves in other modes. The player can also scan QR codes to obtain new cards or share their own cards with others.
-
Options mode is where the player can adjust various settings of the game, such as the sound, the display, the controls, and the language. The player can also view their game data and achievements in this mode.
-
The game's characters and stages
-
Tekken 3D: Prime Edition features 41 playable characters from Tekken 6, each with their own unique fighting style, moves, and personality. Some of the characters are:
-
-
-
Name
-
Origin
-
Fighting Style
-
-
-
Jin Kazama
-
Japan
-
Karate / Mishima Style Fighting Karate
-
-
-
Ling Xiaoyu
-
China
-
Baguazhang / Piguaquan / Hakkesho
-
-
-
Nina Williams
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Ireland
-
Aikido / Koppojutsu / Sambo / Assassination Arts
-
-
-
Hwoarang
-
Korea
-
Taekwondo
-
-
-
King II
-
Mexico
-
Lucha Libre / Professional Wrestling
-
-
-
Lili Rochefort
-
Monaco
-
Street Fighting / Self-Taught Martial Arts
-
-
-
Lars Alexandersson
-
Sweden / Japan
-
Military Martial Arts / Shorinji Kempo / Karate / Taekwondo / Aikido / Jujutsu / Muay Thai / Boxing / Pro Wrestling / Krav Maga / Jeet Kune Do / Escrima / Capoeira / Silat / Savate / Sambo / Systema / Kung Fu / Ninjutsu
-
-
-
Alisa Bosconovitch
-
Russia (Created in Japan)
-
Destructive Form (Cyborg
Cyborg Fighting Style)
-
-
-
The game also features 19 stages from Tekken 6, each with their own theme, background, and music. Some of the stages are:
-
-
-
Name
-
Location
-
Description
-
-
-
Azazel's Chamber
-
Egypt
-
A dark and ancient chamber with a giant statue of Azazel, the final boss of Tekken 6.
-
-
-
City After Dark
-
China
-
A neon-lit city street with a busy traffic and a large dragon billboard.
-
-
-
Fallen Colony
-
Unknown
-
A futuristic and dystopian colony that has been destroyed by an unknown force.
-
-
-
Fiesta Del Tomate
-
Spain
-
A festive and colorful town square with a tomato-throwing event.
-
-
-
Gargoyle's Perch
-
France
-
A Gothic and gloomy cathedral with gargoyles and stained glass windows.
-
-
-
High Roller's Club
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USA
-
A luxurious and glamorous casino with slot machines and roulette tables.
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-
-
Noh Theater
-
Japan
-
A traditional and elegant theater with a Noh stage and masks.
-
-
Rustic Asia
-
Thailand
-
A rural and scenic village with a river and a temple.
-
-
-
Temple Grounds
-
Japan
-
A serene and peaceful temple with cherry blossoms and a pond.
-
-
-
How to Download Tekken 3D: Prime Edition for PC?
-
The requirements and steps to download the game for PC
-
Tekken 3D: Prime Edition is a Nintendo 3DS exclusive game, which means that it is not officially available for PC. However, there is a way to play the game on your computer using an emulator. An emulator is a software that mimics the functions of another device, such as a console or a handheld. In this case, you will need a Nintendo 3DS emulator to run the game on your PC.
-
Before you download the game and the emulator, you will need to make sure that your PC meets the minimum requirements to run them smoothly. Here are the recommended specifications for playing Tekken 3D: Prime Edition on PC:
-
-
Operating System: Windows 7 or higher, or Linux
-
CPU: Intel Core i5 or AMD Ryzen 5 or higher
-
RAM: 8 GB or more
-
Graphics Card: NVIDIA GeForce GTX 1050 or AMD Radeon RX 560 or higher
-
Storage Space: 4 GB or more
-
Internet Connection: Broadband or faster
-
-
Once you have checked your PC's compatibility, you can follow these steps to download and play Tekken 3D: Prime Edition on PC:
-
-
Download the Nintendo 3DS emulator of your choice. There are several options available online, such as Citra, R4 3DS Emulator, and NO$GBA. You can find them on their official websites or on other trusted sources. Make sure to download the latest version of the emulator and follow the installation instructions.
-
Download the Tekken 3D: Prime Edition ROM file. A ROM file is a digital copy of the game that can be played on an emulator. You can find the ROM file for Tekken 3D: Prime Edition on various websites that offer Nintendo 3DS games, such as Rom Hustler, CoolROM, and Emuparadise. Make sure to download the file from a safe and legal source and scan it for viruses before opening it.
-
Extract the ROM file using a file extractor program, such as WinRAR, 7-Zip, or PeaZip. You will get a .3ds file that contains the game data.
-
Launch the Nintendo 3DS emulator on your PC and load the .3ds file. You can do this by clicking on File > Load File or by dragging and dropping the file into the emulator window.
-
Configure the emulator settings according to your preferences. You can adjust the graphics, sound, controls, and other options in the emulator menu. You can also enable or disable the 3D effect of the game by pressing a hotkey.
-
Enjoy playing Tekken 3D: Prime Edition on your PC!
-
-
The benefits and drawbacks of playing the game on PC
-
Playing Tekken 3D: Prime Edition on PC has some advantages and disadvantages compared to playing it on Nintendo 3DS. Here are some of them:
-
-
-
Benefits
-
Drawbacks
-
-
-
You can play the game in higher resolution and quality than on Nintendo 3DS.
-
You may experience some glitches, bugs, or crashes while playing the game on an emulator.
-
-
-
You can use different controllers or keyboard and mouse to play the game.
-
You may lose some of the original features or functions of the game that are exclusive to Nintendo 3DS, such as StreetPass, SpotPass, or touch screen.
-
-
-
You can save your progress and load it anytime you want.
-
You may violate some copyright laws or terms of service by downloading and playing the game without permission from the developers or publishers.
-
-
You can access more online features and options than on Nintendo 3DS.
-
You may encounter some hackers, cheaters, or trolls while playing online.
-
-
-
What are the Reviews and Ratings of Tekken 3D: Prime Edition?
-
The game's critical reception and user feedback
-
Tekken 3D: Prime Edition received mixed to positive reviews from critics and users alike. The game has an average score of 69/100 on Metacritic, based on 38 reviews. The game also has a user score of 7.1/10 on Metacritic, based on 46 ratings.
-
Some of the positive aspects of the game that were praised by reviewers and players were:
-
-
The game's graphics and performance, especially the smooth 60 FPS and the 3D effect.
-
The game's roster and variety, featuring 41 characters and 19 stages from Tekken 6.
-
The game's inclusion of the Tekken: Blood Vengeance 3D movie, which adds value and entertainment to the package.
-
The game's online mode and functionality, which allows for competitive and cooperative play with other players around the world.
-
-
Some of the negative aspects of the game that were criticized by reviewers and players were:
-
-
The game's lack of content and features, especially compared to other Tekken games or other fighting games on Nintendo 3DS.
-
The game's lack of story and progression, which makes the game feel repetitive and shallow.
-
The game's lack of customization and innovation, which makes the game feel outdated and boring.
-
The game's lack of balance and difficulty, which makes the game feel unfair and frustrating.
-
-
The game's strengths and weaknesses
-
Based on the reviews and ratings of Tekken 3D: Prime Edition, we can summarize the game's strengths and weaknesses as follows:
-
-
-
Strengths
-
Weaknesses
-
-
-
Graphics and Performance
-
Content and Features
-
-
-
Roster and Variety
-
Story and Progression
-
-
-
Movie and Value
-
Customization and Innovation
-
-
-
Online Mode and Functionality
-
Balance and Difficulty
-
-
-
Conclusion
-
A summary of the main points and a recommendation for the game
-
Tekken 3D: Prime Edition is a fighting game that brings the arcade-style action and backstory of the Tekken video game series into the 3D gaming realm like never before. It features 41 playable characters from Tekken 6, a card collecting mode, a full-length movie, and online multiplayer. It also supports the Nintendo 3DS's 3D capabilities and runs at a steady 60 FPS. However, it also suffers from a lack of content and features, a lack of story and progression, a lack of customization and innovation, and a lack of balance and difficulty.
-
If you are a fan of Tekken or fighting games in general, you might enjoy playing Tekken 3D: Prime Edition on your Nintendo 3DS or on your PC using an emulator. It is a decent port of Tekken 6 that offers some fun and fast-paced gameplay with impressive graphics and performance. It also has some extra value with the inclusion of the movie and the card collecting mode. However, if you are looking for a more complete and satisfying experience with more depth and variety, you might want to skip this game or wait for a price drop. It is not a bad game, but it is not a great one either.
-
FAQs
-
Here are some frequently asked questions about Tekken 3D: Prime Edition:
-
-
How long is Tekken 3D: Prime Edition?
-
The length of Tekken 3D: Prime Edition depends on how much you play it and what modes you play. There is no definitive answer to this question, as the game does not have a clear end or goal. However, according to HowLongToBeat.com, the average time to beat the main mode (Quick Battle) is about 4 hours, while the average time to complete all modes (including Special Survival, Versus Battle, Online Battle, Practice, Gallery, Card Collection) is about 11 hours.
-
Is Tekken 3D: Prime Edition Is Tekken 3D: Prime Edition compatible with the New Nintendo 3DS?
-
Yes, Tekken 3D: Prime Edition is compatible with the New Nintendo 3DS, as well as the original Nintendo 3DS, the Nintendo 3DS XL, the Nintendo 2DS, and the New Nintendo 2DS XL. However, the game does not make use of any of the exclusive features of the New Nintendo 3DS, such as the C-Stick, the ZL and ZR buttons, or the enhanced processing power.
-
What is the difference between Tekken 3D: Prime Edition and Tekken 6?
-
Tekken 3D: Prime Edition is a graphically updated version of Tekken 6 for the Nintendo 3DS, with some changes and additions. Some of the differences are:
-
-
Tekken 3D: Prime Edition has a card collecting mode that allows the player to customize their character's appearance and moves with cards they have collected or traded.
-
Tekken 3D: Prime Edition includes the Tekken: Blood Vengeance 3D movie on the game's cartridge, which can be watched in Gallery mode.
-
Tekken 3D: Prime Edition supports the Nintendo 3DS's 3D capabilities and runs at a steady 60 FPS even when running in 3D; however, the 3D is disabled during wireless play.
-
Tekken 3D: Prime Edition does not have a story mode or a scenario campaign mode like Tekken 6.
-
Tekken 3D: Prime Edition does not have a customization mode or an item shop like Tekken 6.
-
Tekken 3D: Prime Edition does not have a rage system or a bound system like Tekken 6.
-
-
How can I unlock more cards in Tekken 3D: Prime Edition?
-
There are several ways to unlock more cards in Tekken 3D: Prime Edition, such as:
-
-
Playing Quick Battle mode or Special Survival mode and defeating opponents.
-
Playing Online Battle mode and winning matches or participating in events.
-
Using StreetPass to exchange cards with other players nearby.
-
Using SpotPass to receive cards from Nintendo via Wi-Fi.
-
Scanning QR codes to obtain new cards or share your own cards with others.
-
-
Who is the strongest character in Tekken 3D: Prime Edition?
-
There is no definitive answer to this question, as different characters have different strengths and weaknesses, and different players have different preferences and skills. However, some of the characters that are generally considered to be strong or popular in Tekken 3D: Prime Edition are:
-
-
Lars Alexandersson
-
Nina Williams
-
Bryan Fury
-
Bruce Irvin
-
Bob Richards
-
197e85843d
-
-
\ No newline at end of file
diff --git a/spaces/1ucii/Lab04/app.py b/spaces/1ucii/Lab04/app.py
deleted file mode 100644
index 3176a77251fb8a6a818ebbc04de67683cd0956dc..0000000000000000000000000000000000000000
--- a/spaces/1ucii/Lab04/app.py
+++ /dev/null
@@ -1,42 +0,0 @@
-import gradio as gr
-import pickle
-
-# Load the decision tree model from the pickle file
-with open('best_tree.pkl', 'rb') as file:
- model = pickle.load(file)
-
-# Define the predict function
-def predict(latitude, longitude, housing_median_age, total_rooms, total_bedrooms, population, households, median_income):
- # Prepare the input features
- features = [[longitude, latitude, housing_median_age, total_rooms, total_bedrooms, population, households, median_income]]
-
- # Make predictions using the loaded model
- prediction = model.predict(features)
-
- # Return the predicted output
- return prediction[0]
-
-# Create the input interface using Gradio
-inputs = [
- gr.inputs.Number(label="Longitude"),
- gr.inputs.Number(label="Latitude"),
- gr.inputs.Number(label="Housing Median Age"),
- gr.inputs.Number(label="Total Rooms"),
- gr.inputs.Number(label="Total Bedrooms"),
- gr.inputs.Number(label="Population"),
- gr.inputs.Number(label="Households"),
- gr.inputs.Number(label="Median Income")
-]
-
-# Create the output interface using Gradio
-output = gr.outputs.Label(num_top_classes=1)
-
-# Define example data for demonstration
-examples = [
- [37.88, -122.23, 41, 880, 129, 322, 126, 8.3252],
- [37.84, -122.27, 48, 1922, 409, 1026, 335, 1.7969],
- [37.83, -122.26, 52, 1656, 420, 718, 382, 2.6768]
-]
-
-# Create the Gradio interface
-interface = gr.Interface(fn=predict, inputs=inputs, outputs=output, title="Decision Tree Predictor", examples=examples).launch()
\ No newline at end of file
diff --git a/spaces/2023Liu2023/bingo/src/components/ui/input.tsx b/spaces/2023Liu2023/bingo/src/components/ui/input.tsx
deleted file mode 100644
index 684a857f3d769b78818fb13de1abaebfb09ca79c..0000000000000000000000000000000000000000
--- a/spaces/2023Liu2023/bingo/src/components/ui/input.tsx
+++ /dev/null
@@ -1,25 +0,0 @@
-import * as React from 'react'
-
-import { cn } from '@/lib/utils'
-
-export interface InputProps
- extends React.InputHTMLAttributes {}
-
-const Input = React.forwardRef(
- ({ className, type, ...props }, ref) => {
- return (
-
- )
- }
-)
-Input.displayName = 'Input'
-
-export { Input }
diff --git a/spaces/4Taps/SadTalker/src/face3d/models/arcface_torch/configs/ms1mv3_r2060.py b/spaces/4Taps/SadTalker/src/face3d/models/arcface_torch/configs/ms1mv3_r2060.py
deleted file mode 100644
index 23ad81e082c4b6390b67b164d0ceb84bb0635684..0000000000000000000000000000000000000000
--- a/spaces/4Taps/SadTalker/src/face3d/models/arcface_torch/configs/ms1mv3_r2060.py
+++ /dev/null
@@ -1,26 +0,0 @@
-from easydict import EasyDict as edict
-
-# make training faster
-# our RAM is 256G
-# mount -t tmpfs -o size=140G tmpfs /train_tmp
-
-config = edict()
-config.loss = "arcface"
-config.network = "r2060"
-config.resume = False
-config.output = None
-config.embedding_size = 512
-config.sample_rate = 1.0
-config.fp16 = True
-config.momentum = 0.9
-config.weight_decay = 5e-4
-config.batch_size = 64
-config.lr = 0.1 # batch size is 512
-
-config.rec = "/train_tmp/ms1m-retinaface-t1"
-config.num_classes = 93431
-config.num_image = 5179510
-config.num_epoch = 25
-config.warmup_epoch = -1
-config.decay_epoch = [10, 16, 22]
-config.val_targets = ["lfw", "cfp_fp", "agedb_30"]
diff --git a/spaces/801artistry/RVC801/infer/lib/uvr5_pack/lib_v5/nets_537227KB.py b/spaces/801artistry/RVC801/infer/lib/uvr5_pack/lib_v5/nets_537227KB.py
deleted file mode 100644
index 823b44fb64898e8dcbb12180ba45d1718f9b03f7..0000000000000000000000000000000000000000
--- a/spaces/801artistry/RVC801/infer/lib/uvr5_pack/lib_v5/nets_537227KB.py
+++ /dev/null
@@ -1,123 +0,0 @@
-import numpy as np
-import torch
-import torch.nn.functional as F
-from torch import nn
-
-from . import layers_537238KB as layers
-
-
-class BaseASPPNet(nn.Module):
- def __init__(self, nin, ch, dilations=(4, 8, 16)):
- super(BaseASPPNet, self).__init__()
- self.enc1 = layers.Encoder(nin, ch, 3, 2, 1)
- self.enc2 = layers.Encoder(ch, ch * 2, 3, 2, 1)
- self.enc3 = layers.Encoder(ch * 2, ch * 4, 3, 2, 1)
- self.enc4 = layers.Encoder(ch * 4, ch * 8, 3, 2, 1)
-
- self.aspp = layers.ASPPModule(ch * 8, ch * 16, dilations)
-
- self.dec4 = layers.Decoder(ch * (8 + 16), ch * 8, 3, 1, 1)
- self.dec3 = layers.Decoder(ch * (4 + 8), ch * 4, 3, 1, 1)
- self.dec2 = layers.Decoder(ch * (2 + 4), ch * 2, 3, 1, 1)
- self.dec1 = layers.Decoder(ch * (1 + 2), ch, 3, 1, 1)
-
- def __call__(self, x):
- h, e1 = self.enc1(x)
- h, e2 = self.enc2(h)
- h, e3 = self.enc3(h)
- h, e4 = self.enc4(h)
-
- h = self.aspp(h)
-
- h = self.dec4(h, e4)
- h = self.dec3(h, e3)
- h = self.dec2(h, e2)
- h = self.dec1(h, e1)
-
- return h
-
-
-class CascadedASPPNet(nn.Module):
- def __init__(self, n_fft):
- super(CascadedASPPNet, self).__init__()
- self.stg1_low_band_net = BaseASPPNet(2, 64)
- self.stg1_high_band_net = BaseASPPNet(2, 64)
-
- self.stg2_bridge = layers.Conv2DBNActiv(66, 32, 1, 1, 0)
- self.stg2_full_band_net = BaseASPPNet(32, 64)
-
- self.stg3_bridge = layers.Conv2DBNActiv(130, 64, 1, 1, 0)
- self.stg3_full_band_net = BaseASPPNet(64, 128)
-
- self.out = nn.Conv2d(128, 2, 1, bias=False)
- self.aux1_out = nn.Conv2d(64, 2, 1, bias=False)
- self.aux2_out = nn.Conv2d(64, 2, 1, bias=False)
-
- self.max_bin = n_fft // 2
- self.output_bin = n_fft // 2 + 1
-
- self.offset = 128
-
- def forward(self, x, aggressiveness=None):
- mix = x.detach()
- x = x.clone()
-
- x = x[:, :, : self.max_bin]
-
- bandw = x.size()[2] // 2
- aux1 = torch.cat(
- [
- self.stg1_low_band_net(x[:, :, :bandw]),
- self.stg1_high_band_net(x[:, :, bandw:]),
- ],
- dim=2,
- )
-
- h = torch.cat([x, aux1], dim=1)
- aux2 = self.stg2_full_band_net(self.stg2_bridge(h))
-
- h = torch.cat([x, aux1, aux2], dim=1)
- h = self.stg3_full_band_net(self.stg3_bridge(h))
-
- mask = torch.sigmoid(self.out(h))
- mask = F.pad(
- input=mask,
- pad=(0, 0, 0, self.output_bin - mask.size()[2]),
- mode="replicate",
- )
-
- if self.training:
- aux1 = torch.sigmoid(self.aux1_out(aux1))
- aux1 = F.pad(
- input=aux1,
- pad=(0, 0, 0, self.output_bin - aux1.size()[2]),
- mode="replicate",
- )
- aux2 = torch.sigmoid(self.aux2_out(aux2))
- aux2 = F.pad(
- input=aux2,
- pad=(0, 0, 0, self.output_bin - aux2.size()[2]),
- mode="replicate",
- )
- return mask * mix, aux1 * mix, aux2 * mix
- else:
- if aggressiveness:
- mask[:, :, : aggressiveness["split_bin"]] = torch.pow(
- mask[:, :, : aggressiveness["split_bin"]],
- 1 + aggressiveness["value"] / 3,
- )
- mask[:, :, aggressiveness["split_bin"] :] = torch.pow(
- mask[:, :, aggressiveness["split_bin"] :],
- 1 + aggressiveness["value"],
- )
-
- return mask * mix
-
- def predict(self, x_mag, aggressiveness=None):
- h = self.forward(x_mag, aggressiveness)
-
- if self.offset > 0:
- h = h[:, :, :, self.offset : -self.offset]
- assert h.size()[3] > 0
-
- return h
diff --git a/spaces/AIConsultant/MusicGen/audiocraft/solvers/audiogen.py b/spaces/AIConsultant/MusicGen/audiocraft/solvers/audiogen.py
deleted file mode 100644
index 1568f97fe7b84b90c7ef760ef5606fe0a475545a..0000000000000000000000000000000000000000
--- a/spaces/AIConsultant/MusicGen/audiocraft/solvers/audiogen.py
+++ /dev/null
@@ -1,19 +0,0 @@
-# Copyright (c) Meta Platforms, Inc. and affiliates.
-# All rights reserved.
-#
-# This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
-
-from . import builders, musicgen
-
-
-class AudioGenSolver(musicgen.MusicGenSolver):
- """Solver for AudioGen re-implementation training task.
-
- Note that this implementation does not strictly follows
- the method proposed in https://arxiv.org/abs/2209.15352
- but is derived from MusicGen's training pipeline.
-
- More information can be found in the AudioGen model card.
- """
- DATASET_TYPE: builders.DatasetType = builders.DatasetType.SOUND
diff --git a/spaces/AIWaves/Software_Company/gradio_config.py b/spaces/AIWaves/Software_Company/gradio_config.py
deleted file mode 100644
index 0250bf3d9860cb9fcf1cda7610725d7bcb66bf64..0000000000000000000000000000000000000000
--- a/spaces/AIWaves/Software_Company/gradio_config.py
+++ /dev/null
@@ -1,437 +0,0 @@
-# coding=utf-8
-# Copyright 2023 The AIWaves Inc. team.
-
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-# http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-import json
-from PIL import Image
-import requests
-from typing import List, Tuple
-
-class GradioConfig:
- # How many avatars are currently registered
- POINTER = 0
-
- # Avatar image. You can add or replace.
- AGENT_HEAD_URL = [
- "https://img.touxiangwu.com/zb_users/upload/2023/06/202306241687579617434043.jpg",
- "https://img.touxiangwu.com/zb_users/upload/2023/06/202306241687592097408547.jpg",
- "https://img.touxiangwu.com/zb_users/upload/2023/06/202306141686726561699613.jpg",
- "https://img.touxiangwu.com/zb_users/upload/2023/06/202306141686726561275758.jpg",
- "https://img.touxiangwu.com/uploads/allimg/2021090300/ry5k31wt33c.jpg",
- "https://img.touxiangwu.com/uploads/allimg/2021090300/0ls2gmwhrf5.jpg",
- "https://img.touxiangwu.com/zb_users/upload/2023/02/202302281677545695326193.jpg",
- "https://img.touxiangwu.com/zb_users/upload/2023/03/202303271679886128550253.jpg",
- "https://img.touxiangwu.com/zb_users/upload/2023/06/202306141686711344407060.jpg",
- "https://img.touxiangwu.com/zb_users/upload/2023/06/202306141686711345834296.jpg",
- "https://img.touxiangwu.com/zb_users/upload/2023/05/202305171684311194291520.jpg",
- "https://img.touxiangwu.com/zb_users/upload/2023/05/202305171684311196958993.jpg",
- "https://img.touxiangwu.com/uploads/allimg/2021082612/vr0bkov0dwl.jpg",
- "https://img.touxiangwu.com/uploads/allimg/2021082612/auqx5zfsv5g.jpg",
- "https://img.touxiangwu.com/uploads/allimg/2021082612/llofpivtwls.jpg",
- "https://img.touxiangwu.com/uploads/allimg/2021082612/3j2sdot3ye0.jpg",
- "https://img.touxiangwu.com/2020/3/nQfYf2.jpg",
- "https://img.touxiangwu.com/zb_users/upload/2023/08/202308131691918068774532.jpg",
- "https://img.touxiangwu.com/zb_users/upload/2023/08/202308131691918068289945.jpg",
- "https://img.touxiangwu.com/zb_users/upload/2023/08/202308131691918069785183.jpg",
- "https://img.touxiangwu.com/zb_users/upload/2023/06/202306141686726561292003.jpg",
- "https://img.touxiangwu.com/zb_users/upload/2023/06/202306141686726561578616.jpg",
- "https://img.touxiangwu.com/zb_users/upload/2023/06/202306141686726564597524.jpg"
- ]
- USER_HEAD_URL = "https://img.touxiangwu.com/zb_users/upload/2023/05/202305301685407468585486.jpg"
-
- # The css style of gradio.Chatbot
- CSS = """
- #chatbot1 .user {
- background-color:transparent;
- border-color:transparent;
- }
- #chatbot1 .bot {
- background-color:transparent;
- border-color:transparent;
- }
- #btn {color: red; border-color: red;}
- """
-
- ID = ["USER", "AGENT", "SYSTEM"]
-
- # Bubble template
- BUBBLE_CSS = {
- # Background-color Name-color Name-content Font-color Font-size Content Avatar-URL
- "USER": """
-
-
-
-"""
-
- STATES_NAME:List[str] = None
-
- @classmethod
- def _generate_template(cls, types:str)->str:
- # normal: A state with no execution.
- # active-show-up: Active state, and content displayed above the horizontal line.
- # active-show-down: Active state, and content displayed below the horizontal line.
- # active-show-both: Active state, and content displayed both above and below the horizontal line.
- # active-show-none: Active state, with no content displayed above the horizontal line.
-
- assert types.lower() in ["normal","active-show-up", "active-show-down", "active-show-both", "active", "active-show-none"]
- both_templates = """
- Streaming / Unlimited conversations / Save history / Preset prompts / Chat with files / Web search
- LaTeX rendering / Table rendering / Code highlighting
- Auto dark mode / Adaptive web interface / WeChat-like theme
- Multi-parameters tuning / Multi-API-Key support / Multi-user support
- Compatible with GPT-4 / Local deployment for LLMs
-
-
-## Usage Tips
-
-- To better control the ChatGPT, use System Prompt.
-- To use a Prompt Template, select the Prompt Template Collection file first, and then choose certain prompt from the drop-down menu.
-- To try again if the response is unsatisfactory, use `🔄 Regenerate` button.
-- To start a new line in the input box, press Shift + Enter keys.
-- To quickly switch between input history, press ↑ and ↓ key in the input box.
-- To deploy the program onto a server, set `"server_name": "0.0.0.0", "server_port" ,` in `config.json`.
-- To get a public shared link, set `"share": true,` in `config.json`. Please be noted that the program must be running in order to be accessed via a public link.
-- To use it in Hugging Face Spaces: It is recommended to **Duplicate Space** and run the program in your own Space for a faster and more secure experience.
-
-## Quickstart
-
-```shell
-git clone https://github.com/GaiZhenbiao/ChuanhuChatGPT.git
-cd ChuanhuChatGPT
-pip install -r requirements.txt
-```
-
-Then make a copy of `config_example.json`, rename it to `config.json`, and then fill in your API-Key and other settings in the file.
-
-```shell
-python app.py
-```
-
-A browser window will open and you will be able to chat with ChatGPT.
-
-> **Note**
->
-> Please check our [wiki page](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/使用教程) for detailed instructions.
-
-## Troubleshooting
-
-When you encounter problems, you should try manually pulling the latest changes of this project first. The steps are as follows:
-
-1. Download the latest code archive by clicking on `Download ZIP` on the webpage, or
- ```shell
- git pull https://github.com/GaiZhenbiao/ChuanhuChatGPT.git main -f
- ```
-2. Try installing the dependencies again (as this project may have introduced new dependencies)
- ```
- pip install -r requirements.txt
- ```
-3. Update Gradio
- ```
- pip install gradio --upgrade --force-reinstall
- ```
-
-Generally, you can solve most problems by following these steps.
-
-If the problem still exists, please refer to this page: [Frequently Asked Questions (FAQ)](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/常见问题)
-
-This page lists almost all the possible problems and solutions. Please read it carefully.
-
-## More Information
-
-More information could be found in our [wiki](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki):
-
-- [How to contribute a translation](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/Localization)
-- [How to make a contribution](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/贡献指南)
-- [How to cite the project](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/使用许可#如何引用该项目)
-- [Project changelog](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/更新日志)
-- [Project license](https://github.com/GaiZhenbiao/ChuanhuChatGPT/wiki/使用许可)
-
-## Starchart
-
-[](https://star-history.com/#GaiZhenbiao/ChuanhuChatGPT&Date)
-
-## Contributors
-
-
-
-
-
-## Sponsor
-
-🐯 If you find this project helpful, feel free to buy me a coke or a cup of coffee~
-
-
-
-
diff --git a/spaces/Alichuan/VITS-Umamusume-voice-synthesizer/ONNXVITS_to_onnx.py b/spaces/Alichuan/VITS-Umamusume-voice-synthesizer/ONNXVITS_to_onnx.py
deleted file mode 100644
index 846e39849535ed08accb10d7001f2431a851d372..0000000000000000000000000000000000000000
--- a/spaces/Alichuan/VITS-Umamusume-voice-synthesizer/ONNXVITS_to_onnx.py
+++ /dev/null
@@ -1,31 +0,0 @@
-import ONNXVITS_models
-import utils
-from text import text_to_sequence
-import torch
-import commons
-
-def get_text(text, hps):
- text_norm = text_to_sequence(text, hps.symbols, hps.data.text_cleaners)
- if hps.data.add_blank:
- text_norm = commons.intersperse(text_norm, 0)
- text_norm = torch.LongTensor(text_norm)
- return text_norm
-
-hps = utils.get_hparams_from_file("../vits/pretrained_models/uma87.json")
-symbols = hps.symbols
-net_g = ONNXVITS_models.SynthesizerTrn(
- len(symbols),
- hps.data.filter_length // 2 + 1,
- hps.train.segment_size // hps.data.hop_length,
- n_speakers=hps.data.n_speakers,
- **hps.model)
-_ = net_g.eval()
-_ = utils.load_checkpoint("../vits/pretrained_models/uma_1153000.pth", net_g)
-
-text1 = get_text("ありがとうございます。", hps)
-stn_tst = text1
-with torch.no_grad():
- x_tst = stn_tst.unsqueeze(0)
- x_tst_lengths = torch.LongTensor([stn_tst.size(0)])
- sid = torch.tensor([0])
- o = net_g(x_tst, x_tst_lengths, sid=sid, noise_scale=.667, noise_scale_w=0.8, length_scale=1)
\ No newline at end of file
diff --git a/spaces/Ameaou/academic-chatgpt3.1/toolbox.py b/spaces/Ameaou/academic-chatgpt3.1/toolbox.py
deleted file mode 100644
index 038d7be858f3b7fbc6ff62f5031dcacdebe4d70c..0000000000000000000000000000000000000000
--- a/spaces/Ameaou/academic-chatgpt3.1/toolbox.py
+++ /dev/null
@@ -1,507 +0,0 @@
-import markdown
-import importlib
-import traceback
-import inspect
-import re
-from latex2mathml.converter import convert as tex2mathml
-from functools import wraps, lru_cache
-############################### 插件输入输出接驳区 #######################################
-class ChatBotWithCookies(list):
- def __init__(self, cookie):
- self._cookies = cookie
-
- def write_list(self, list):
- for t in list:
- self.append(t)
-
- def get_list(self):
- return [t for t in self]
-
- def get_cookies(self):
- return self._cookies
-
-def ArgsGeneralWrapper(f):
- """
- 装饰器函数，用于重组输入参数，改变输入参数的顺序与结构。
- """
- def decorated(cookies, max_length, llm_model, txt, txt2, top_p, temperature, chatbot, history, system_prompt, *args):
- txt_passon = txt
- if txt == "" and txt2 != "": txt_passon = txt2
- # 引入一个有cookie的chatbot
- cookies.update({
- 'top_p':top_p,
- 'temperature':temperature,
- })
- llm_kwargs = {
- 'api_key': cookies['api_key'],
- 'llm_model': llm_model,
- 'top_p':top_p,
- 'max_length': max_length,
- 'temperature':temperature,
- }
- plugin_kwargs = {
- # 目前还没有
- }
- chatbot_with_cookie = ChatBotWithCookies(cookies)
- chatbot_with_cookie.write_list(chatbot)
- yield from f(txt_passon, llm_kwargs, plugin_kwargs, chatbot_with_cookie, history, system_prompt, *args)
- return decorated
-
-def update_ui(chatbot, history, msg='正常', **kwargs): # 刷新界面
- """
- 刷新用户界面
- """
- assert isinstance(chatbot, ChatBotWithCookies), "在传递chatbot的过程中不要将其丢弃。必要时，可用clear将其清空，然后用for+append循环重新赋值。"
- yield chatbot.get_cookies(), chatbot, history, msg
-
-def CatchException(f):
- """
- 装饰器函数，捕捉函数f中的异常并封装到一个生成器中返回，并显示到聊天当中。
- """
- @wraps(f)
- def decorated(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
- try:
- yield from f(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT)
- except Exception as e:
- from check_proxy import check_proxy
- from toolbox import get_conf
- proxies, = get_conf('proxies')
- tb_str = '```\n' + traceback.format_exc() + '```'
- if chatbot is None or len(chatbot) == 0:
- chatbot = [["插件调度异常", "异常原因"]]
- chatbot[-1] = (chatbot[-1][0],
- f"[Local Message] 实验性函数调用出错: \n\n{tb_str} \n\n当前代理可用性: \n\n{check_proxy(proxies)}")
- yield from update_ui(chatbot=chatbot, history=history, msg=f'异常 {e}') # 刷新界面
- return decorated
-
-
-def HotReload(f):
- """
- HotReload的装饰器函数，用于实现Python函数插件的热更新。
- 函数热更新是指在不停止程序运行的情况下，更新函数代码，从而达到实时更新功能。
- 在装饰器内部，使用wraps(f)来保留函数的元信息，并定义了一个名为decorated的内部函数。
- 内部函数通过使用importlib模块的reload函数和inspect模块的getmodule函数来重新加载并获取函数模块，
- 然后通过getattr函数获取函数名，并在新模块中重新加载函数。
- 最后，使用yield from语句返回重新加载过的函数，并在被装饰的函数上执行。
- 最终，装饰器函数返回内部函数。这个内部函数可以将函数的原始定义更新为最新版本，并执行函数的新版本。
- """
- @wraps(f)
- def decorated(*args, **kwargs):
- fn_name = f.__name__
- f_hot_reload = getattr(importlib.reload(inspect.getmodule(f)), fn_name)
- yield from f_hot_reload(*args, **kwargs)
- return decorated
-
-
-####################################### 其他小工具 #####################################
-
-def get_reduce_token_percent(text):
- """
- * 此函数未来将被弃用
- """
- try:
- # text = "maximum context length is 4097 tokens. However, your messages resulted in 4870 tokens"
- pattern = r"(\d+)\s+tokens\b"
- match = re.findall(pattern, text)
- EXCEED_ALLO = 500 # 稍微留一点余地，否则在回复时会因余量太少出问题
- max_limit = float(match[0]) - EXCEED_ALLO
- current_tokens = float(match[1])
- ratio = max_limit/current_tokens
- assert ratio > 0 and ratio < 1
- return ratio, str(int(current_tokens-max_limit))
- except:
- return 0.5, '不详'
-
-
-
-def write_results_to_file(history, file_name=None):
- """
- 将对话记录history以Markdown格式写入文件中。如果没有指定文件名，则使用当前时间生成文件名。
- """
- import os
- import time
- if file_name is None:
- # file_name = time.strftime("chatGPT分析报告%Y-%m-%d-%H-%M-%S", time.localtime()) + '.md'
- file_name = 'chatGPT分析报告' + \
- time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime()) + '.md'
- os.makedirs('./gpt_log/', exist_ok=True)
- with open(f'./gpt_log/{file_name}', 'w', encoding='utf8') as f:
- f.write('# chatGPT 分析报告\n')
- for i, content in enumerate(history):
- try: # 这个bug没找到触发条件，暂时先这样顶一下
- if type(content) != str:
- content = str(content)
- except:
- continue
- if i % 2 == 0:
- f.write('## ')
- f.write(content)
- f.write('\n\n')
- res = '以上材料已经被写入' + os.path.abspath(f'./gpt_log/{file_name}')
- print(res)
- return res
-
-
-def regular_txt_to_markdown(text):
- """
- 将普通文本转换为Markdown格式的文本。
- """
- text = text.replace('\n', '\n\n')
- text = text.replace('\n\n\n', '\n\n')
- text = text.replace('\n\n\n', '\n\n')
- return text
-
-
-
-
-def report_execption(chatbot, history, a, b):
- """
- 向chatbot中添加错误信息
- """
- chatbot.append((a, b))
- history.append(a)
- history.append(b)
-
-
-def text_divide_paragraph(text):
- """
- 将文本按照段落分隔符分割开，生成带有段落标签的HTML代码。
- """
- if '```' in text:
- # careful input
- return text
- else:
- # wtf input
- lines = text.split("\n")
- for i, line in enumerate(lines):
- lines[i] = lines[i].replace(" ", " ")
- text = "".join(lines)
- return text
-
-
-def markdown_convertion(txt):
- """
- 将Markdown格式的文本转换为HTML格式。如果包含数学公式，则先将公式转换为HTML格式。
- """
- pre = '
'
- suf = '
'
- markdown_extension_configs = {
- 'mdx_math': {
- 'enable_dollar_delimiter': True,
- 'use_gitlab_delimiters': False,
- },
- }
- find_equation_pattern = r'\n', '')
- return content
-
-
- if ('$' in txt) and ('```' not in txt): # 有$标识的公式符号，且没有代码段```的标识
- # convert everything to html format
- split = markdown.markdown(text='---')
- convert_stage_1 = markdown.markdown(text=txt, extensions=['mdx_math', 'fenced_code', 'tables', 'sane_lists'], extension_configs=markdown_extension_configs)
- convert_stage_1 = markdown_bug_hunt(convert_stage_1)
- # re.DOTALL: Make the '.' special character match any character at all, including a newline; without this flag, '.' will match anything except a newline. Corresponds to the inline flag (?s).
- # 1. convert to easy-to-copy tex (do not render math)
- convert_stage_2_1, n = re.subn(find_equation_pattern, replace_math_no_render, convert_stage_1, flags=re.DOTALL)
- # 2. convert to rendered equation
- convert_stage_2_2, n = re.subn(find_equation_pattern, replace_math_render, convert_stage_1, flags=re.DOTALL)
- # cat them together
- return pre + convert_stage_2_1 + f'{split}' + convert_stage_2_2 + suf
- else:
- return pre + markdown.markdown(txt, extensions=['fenced_code', 'codehilite', 'tables', 'sane_lists']) + suf
-
-
-def close_up_code_segment_during_stream(gpt_reply):
- """
- 在gpt输出代码的中途（输出了前面的```，但还没输出完后面的```），补上后面的```
-
- Args:
- gpt_reply (str): GPT模型返回的回复字符串。
-
- Returns:
- str: 返回一个新的字符串，将输出代码片段的“后面的```”补上。
-
- """
- if '```' not in gpt_reply:
- return gpt_reply
- if gpt_reply.endswith('```'):
- return gpt_reply
-
- # 排除了以上两个情况，我们
- segments = gpt_reply.split('```')
- n_mark = len(segments) - 1
- if n_mark % 2 == 1:
- # print('输出代码片段中！')
- return gpt_reply+'\n```'
- else:
- return gpt_reply
-
-
-def format_io(self, y):
- """
- 将输入和输出解析为HTML格式。将y中最后一项的输入部分段落化，并将输出部分的Markdown和数学公式转换为HTML格式。
- """
- if y is None or y == []:
- return []
- i_ask, gpt_reply = y[-1]
- i_ask = text_divide_paragraph(i_ask) # 输入部分太自由，预处理一波
- gpt_reply = close_up_code_segment_during_stream(gpt_reply) # 当代码输出半截的时候，试着补上后个```
- y[-1] = (
- None if i_ask is None else markdown.markdown(i_ask, extensions=['fenced_code', 'tables']),
- None if gpt_reply is None else markdown_convertion(gpt_reply)
- )
- return y
-
-
-def find_free_port():
- """
- 返回当前系统中可用的未使用端口。
- """
- import socket
- from contextlib import closing
- with closing(socket.socket(socket.AF_INET, socket.SOCK_STREAM)) as s:
- s.bind(('', 0))
- s.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
- return s.getsockname()[1]
-
-
-def extract_archive(file_path, dest_dir):
- import zipfile
- import tarfile
- import os
- # Get the file extension of the input file
- file_extension = os.path.splitext(file_path)[1]
-
- # Extract the archive based on its extension
- if file_extension == '.zip':
- with zipfile.ZipFile(file_path, 'r') as zipobj:
- zipobj.extractall(path=dest_dir)
- print("Successfully extracted zip archive to {}".format(dest_dir))
-
- elif file_extension in ['.tar', '.gz', '.bz2']:
- with tarfile.open(file_path, 'r:*') as tarobj:
- tarobj.extractall(path=dest_dir)
- print("Successfully extracted tar archive to {}".format(dest_dir))
-
- # 第三方库，需要预先pip install rarfile
- # 此外，Windows上还需要安装winrar软件，配置其Path环境变量，如"C:\Program Files\WinRAR"才可以
- elif file_extension == '.rar':
- try:
- import rarfile
- with rarfile.RarFile(file_path) as rf:
- rf.extractall(path=dest_dir)
- print("Successfully extracted rar archive to {}".format(dest_dir))
- except:
- print("Rar format requires additional dependencies to install")
- return '\n\n需要安装pip install rarfile来解压rar文件'
-
- # 第三方库，需要预先pip install py7zr
- elif file_extension == '.7z':
- try:
- import py7zr
- with py7zr.SevenZipFile(file_path, mode='r') as f:
- f.extractall(path=dest_dir)
- print("Successfully extracted 7z archive to {}".format(dest_dir))
- except:
- print("7z format requires additional dependencies to install")
- return '\n\n需要安装pip install py7zr来解压7z文件'
- else:
- return ''
- return ''
-
-
-def find_recent_files(directory):
- """
- me: find files that is created with in one minutes under a directory with python, write a function
- gpt: here it is!
- """
- import os
- import time
- current_time = time.time()
- one_minute_ago = current_time - 60
- recent_files = []
-
- for filename in os.listdir(directory):
- file_path = os.path.join(directory, filename)
- if file_path.endswith('.log'):
- continue
- created_time = os.path.getmtime(file_path)
- if created_time >= one_minute_ago:
- if os.path.isdir(file_path):
- continue
- recent_files.append(file_path)
-
- return recent_files
-
-
-def on_file_uploaded(files, chatbot, txt, txt2, checkboxes):
- if len(files) == 0:
- return chatbot, txt
- import shutil
- import os
- import time
- import glob
- from toolbox import extract_archive
- try:
- shutil.rmtree('./private_upload/')
- except:
- pass
- time_tag = time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime())
- os.makedirs(f'private_upload/{time_tag}', exist_ok=True)
- err_msg = ''
- for file in files:
- file_origin_name = os.path.basename(file.orig_name)
- shutil.copy(file.name, f'private_upload/{time_tag}/{file_origin_name}')
- err_msg += extract_archive(f'private_upload/{time_tag}/{file_origin_name}',
- dest_dir=f'private_upload/{time_tag}/{file_origin_name}.extract')
- moved_files = [fp for fp in glob.glob(
- 'private_upload/**/*', recursive=True)]
- if "底部输入区" in checkboxes:
- txt = ""
- txt2 = f'private_upload/{time_tag}'
- else:
- txt = f'private_upload/{time_tag}'
- txt2 = ""
- moved_files_str = '\t\n\n'.join(moved_files)
- chatbot.append(['我上传了文件，请查收',
- f'[Local Message] 收到以下文件: \n\n{moved_files_str}' +
- f'\n\n调用路径参数已自动修正到: \n\n{txt}' +
- f'\n\n现在您点击任意“红颜色”标识的函数插件时，以上文件将被作为输入参数'+err_msg])
- return chatbot, txt, txt2
-
-
-def on_report_generated(files, chatbot):
- from toolbox import find_recent_files
- report_files = find_recent_files('gpt_log')
- if len(report_files) == 0:
- return None, chatbot
- # files.extend(report_files)
- chatbot.append(['汇总报告如何远程获取？', '汇总报告已经添加到右侧“文件上传区”（可能处于折叠状态），请查收。'])
- return report_files, chatbot
-
-def is_openai_api_key(key):
- API_MATCH = re.match(r"sk-[a-zA-Z0-9]{48}$", key)
- return bool(API_MATCH)
-
-def is_api2d_key(key):
- if key.startswith('fk') and len(key) == 41:
- return True
- else:
- return False
-
-def is_any_api_key(key):
- if ',' in key:
- keys = key.split(',')
- for k in keys:
- if is_any_api_key(k): return True
- return False
- else:
- return is_openai_api_key(key) or is_api2d_key(key)
-
-
-def select_api_key(keys, llm_model):
- import random
- avail_key_list = []
- key_list = keys.split(',')
-
- if llm_model.startswith('gpt-'):
- for k in key_list:
- if is_openai_api_key(k): avail_key_list.append(k)
-
- if llm_model.startswith('api2d-'):
- for k in key_list:
- if is_api2d_key(k): avail_key_list.append(k)
-
- if len(avail_key_list) == 0:
- raise RuntimeError(f"您提供的api-key不满足要求，不包含任何可用于{llm_model}的api-key。")
-
- api_key = random.choice(avail_key_list) # 随机负载均衡
- return api_key
-
-@lru_cache(maxsize=128)
-def read_single_conf_with_lru_cache(arg):
- from colorful import print亮红, print亮绿
- try:
- r = getattr(importlib.import_module('config_private'), arg)
- except:
- r = getattr(importlib.import_module('config'), arg)
- # 在读取API_KEY时，检查一下是不是忘了改config
- if arg == 'API_KEY':
- if is_any_api_key(r):
- print亮绿(f"[API_KEY] 您的 API_KEY 是: {r[:15]}*** API_KEY 导入成功")
- else:
- print亮红( "[API_KEY] 正确的 API_KEY 是'sk'开头的51位密钥（OpenAI），或者 'fk'开头的41位密钥，请在config文件中修改API密钥之后再运行。")
- if arg == 'proxies':
- if r is None:
- print亮红('[PROXY] 网络代理状态：未配置。无代理状态下很可能无法访问OpenAI家族的模型。建议：检查USE_PROXY选项是否修改。')
- else:
- print亮绿('[PROXY] 网络代理状态：已配置。配置信息如下：', r)
- assert isinstance(r, dict), 'proxies格式错误，请注意proxies选项的格式，不要遗漏括号。'
- return r
-
-
-def get_conf(*args):
- # 建议您复制一个config_private.py放自己的秘密, 如API和代理网址, 避免不小心传github被别人看到
- res = []
- for arg in args:
- r = read_single_conf_with_lru_cache(arg)
- res.append(r)
- return res
-
-
-def clear_line_break(txt):
- txt = txt.replace('\n', ' ')
- txt = txt.replace(' ', ' ')
- txt = txt.replace(' ', ' ')
- return txt
-
-
-class DummyWith():
- """
- 这段代码定义了一个名为DummyWith的空上下文管理器，
- 它的作用是……额……没用，即在代码结构不变得情况下取代其他的上下文管理器。
- 上下文管理器是一种Python对象，用于与with语句一起使用，
- 以确保一些资源在代码块执行期间得到正确的初始化和清理。
- 上下文管理器必须实现两个方法，分别为 __enter__()和 __exit__()。
- 在上下文执行开始的情况下，__enter__()方法会在代码块被执行前被调用，
- 而在上下文执行结束时，__exit__()方法则会被调用。
- """
- def __enter__(self):
- return self
-
- def __exit__(self, exc_type, exc_value, traceback):
- return
diff --git a/spaces/Amrrs/DragGan-Inversion/stylegan_human/dnnlib/tflib/ops/upfirdn_2d.py b/spaces/Amrrs/DragGan-Inversion/stylegan_human/dnnlib/tflib/ops/upfirdn_2d.py
deleted file mode 100644
index 89413336877e0b6fcc5aff0a215cae3a7fe558cf..0000000000000000000000000000000000000000
--- a/spaces/Amrrs/DragGan-Inversion/stylegan_human/dnnlib/tflib/ops/upfirdn_2d.py
+++ /dev/null
@@ -1,391 +0,0 @@
-# Copyright (c) SenseTime Research. All rights reserved.
-
-# Copyright (c) 2019, NVIDIA Corporation. All rights reserved.
-#
-# This work is made available under the Nvidia Source Code License-NC.
-# To view a copy of this license, visit
-# https://nvlabs.github.io/stylegan2/license.html
-
-"""Custom TensorFlow ops for efficient resampling of 2D images."""
-
-import os
-import numpy as np
-import tensorflow as tf
-from .. import custom_ops
-
-
-def _get_plugin():
- return custom_ops.get_plugin(os.path.splitext(__file__)[0] + '.cu')
-
-# ----------------------------------------------------------------------------
-
-
-def upfirdn_2d(x, k, upx=1, upy=1, downx=1, downy=1, padx0=0, padx1=0, pady0=0, pady1=0, impl='cuda'):
- r"""Pad, upsample, FIR filter, and downsample a batch of 2D images.
-
- Accepts a batch of 2D images of the shape `[majorDim, inH, inW, minorDim]`
- and performs the following operations for each image, batched across
- `majorDim` and `minorDim`:
-
- 1. Pad the image with zeros by the specified number of pixels on each side
- (`padx0`, `padx1`, `pady0`, `pady1`). Specifying a negative value
- corresponds to cropping the image.
-
- 2. Upsample the image by inserting the zeros after each pixel (`upx`, `upy`).
-
- 3. Convolve the image with the specified 2D FIR filter (`k`), shrinking the
- image so that the footprint of all output pixels lies within the input image.
-
- 4. Downsample the image by throwing away pixels (`downx`, `downy`).
-
- This sequence of operations bears close resemblance to scipy.signal.upfirdn().
- The fused op is considerably more efficient than performing the same calculation
- using standard TensorFlow ops. It supports gradients of arbitrary order.
-
- Args:
- x: Input tensor of the shape `[majorDim, inH, inW, minorDim]`.
- k: 2D FIR filter of the shape `[firH, firW]`.
- upx: Integer upsampling factor along the X-axis (default: 1).
- upy: Integer upsampling factor along the Y-axis (default: 1).
- downx: Integer downsampling factor along the X-axis (default: 1).
- downy: Integer downsampling factor along the Y-axis (default: 1).
- padx0: Number of pixels to pad on the left side (default: 0).
- padx1: Number of pixels to pad on the right side (default: 0).
- pady0: Number of pixels to pad on the top side (default: 0).
- pady1: Number of pixels to pad on the bottom side (default: 0).
- impl: Name of the implementation to use. Can be `"ref"` or `"cuda"` (default).
-
- Returns:
- Tensor of the shape `[majorDim, outH, outW, minorDim]`, and same datatype as `x`.
- """
-
- impl_dict = {
- 'ref': _upfirdn_2d_ref,
- 'cuda': _upfirdn_2d_cuda,
- }
- return impl_dict[impl](x=x, k=k, upx=upx, upy=upy, downx=downx, downy=downy, padx0=padx0, padx1=padx1, pady0=pady0, pady1=pady1)
-
-# ----------------------------------------------------------------------------
-
-
-def _upfirdn_2d_ref(x, k, upx, upy, downx, downy, padx0, padx1, pady0, pady1):
- """Slow reference implementation of `upfirdn_2d()` using standard TensorFlow ops."""
-
- x = tf.convert_to_tensor(x)
- k = np.asarray(k, dtype=np.float32)
- assert x.shape.rank == 4
- inH = x.shape[1].value
- inW = x.shape[2].value
- minorDim = _shape(x, 3)
- kernelH, kernelW = k.shape
- assert inW >= 1 and inH >= 1
- assert kernelW >= 1 and kernelH >= 1
- assert isinstance(upx, int) and isinstance(upy, int)
- assert isinstance(downx, int) and isinstance(downy, int)
- assert isinstance(padx0, int) and isinstance(padx1, int)
- assert isinstance(pady0, int) and isinstance(pady1, int)
-
- # Upsample (insert zeros).
- x = tf.reshape(x, [-1, inH, 1, inW, 1, minorDim])
- x = tf.pad(x, [[0, 0], [0, 0], [0, upy - 1], [0, 0], [0, upx - 1], [0, 0]])
- x = tf.reshape(x, [-1, inH * upy, inW * upx, minorDim])
-
- # Pad (crop if negative).
- x = tf.pad(x, [[0, 0], [max(pady0, 0), max(pady1, 0)],
- [max(padx0, 0), max(padx1, 0)], [0, 0]])
- x = x[:, max(-pady0, 0): x.shape[1].value - max(-pady1, 0),
- max(-padx0, 0): x.shape[2].value - max(-padx1, 0), :]
-
- # Convolve with filter.
- x = tf.transpose(x, [0, 3, 1, 2])
- x = tf.reshape(x, [-1, 1, inH * upy + pady0 +
- pady1, inW * upx + padx0 + padx1])
- w = tf.constant(k[::-1, ::-1, np.newaxis, np.newaxis], dtype=x.dtype)
- x = tf.nn.conv2d(x, w, strides=[1, 1, 1, 1],
- padding='VALID', data_format='NCHW')
- x = tf.reshape(x, [-1, minorDim, inH * upy + pady0 + pady1 -
- kernelH + 1, inW * upx + padx0 + padx1 - kernelW + 1])
- x = tf.transpose(x, [0, 2, 3, 1])
-
- # Downsample (throw away pixels).
- return x[:, ::downy, ::downx, :]
-
-# ----------------------------------------------------------------------------
-
-
-def _upfirdn_2d_cuda(x, k, upx, upy, downx, downy, padx0, padx1, pady0, pady1):
- """Fast CUDA implementation of `upfirdn_2d()` using custom ops."""
-
- x = tf.convert_to_tensor(x)
- k = np.asarray(k, dtype=np.float32)
- majorDim, inH, inW, minorDim = x.shape.as_list()
- kernelH, kernelW = k.shape
- assert inW >= 1 and inH >= 1
- assert kernelW >= 1 and kernelH >= 1
- assert isinstance(upx, int) and isinstance(upy, int)
- assert isinstance(downx, int) and isinstance(downy, int)
- assert isinstance(padx0, int) and isinstance(padx1, int)
- assert isinstance(pady0, int) and isinstance(pady1, int)
-
- outW = (inW * upx + padx0 + padx1 - kernelW) // downx + 1
- outH = (inH * upy + pady0 + pady1 - kernelH) // downy + 1
- assert outW >= 1 and outH >= 1
-
- kc = tf.constant(k, dtype=x.dtype)
- gkc = tf.constant(k[::-1, ::-1], dtype=x.dtype)
- gpadx0 = kernelW - padx0 - 1
- gpady0 = kernelH - pady0 - 1
- gpadx1 = inW * upx - outW * downx + padx0 - upx + 1
- gpady1 = inH * upy - outH * downy + pady0 - upy + 1
-
- @tf.custom_gradient
- def func(x):
- y = _get_plugin().up_fir_dn2d(x=x, k=kc, upx=upx, upy=upy, downx=downx,
- downy=downy, padx0=padx0, padx1=padx1, pady0=pady0, pady1=pady1)
- y.set_shape([majorDim, outH, outW, minorDim])
-
- @tf.custom_gradient
- def grad(dy):
- dx = _get_plugin().up_fir_dn2d(x=dy, k=gkc, upx=downx, upy=downy, downx=upx,
- downy=upy, padx0=gpadx0, padx1=gpadx1, pady0=gpady0, pady1=gpady1)
- dx.set_shape([majorDim, inH, inW, minorDim])
- return dx, func
- return y, grad
- return func(x)
-
-# ----------------------------------------------------------------------------
-
-
-def filter_2d(x, k, gain=1, data_format='NCHW', impl='cuda'):
- r"""Filter a batch of 2D images with the given FIR filter.
-
- Accepts a batch of 2D images of the shape `[N, C, H, W]` or `[N, H, W, C]`
- and filters each image with the given filter. The filter is normalized so that
- if the input pixels are constant, they will be scaled by the specified `gain`.
- Pixels outside the image are assumed to be zero.
-
- Args:
- x: Input tensor of the shape `[N, C, H, W]` or `[N, H, W, C]`.
- k: FIR filter of the shape `[firH, firW]` or `[firN]` (separable).
- gain: Scaling factor for signal magnitude (default: 1.0).
- data_format: `'NCHW'` or `'NHWC'` (default: `'NCHW'`).
- impl: Name of the implementation to use. Can be `"ref"` or `"cuda"` (default).
-
- Returns:
- Tensor of the same shape and datatype as `x`.
- """
-
- k = _setup_kernel(k) * gain
- p = k.shape[0] - 1
- return _simple_upfirdn_2d(x, k, pad0=(p+1)//2, pad1=p//2, data_format=data_format, impl=impl)
-
-# ----------------------------------------------------------------------------
-
-
-def upsample_2d(x, k=None, factor=2, gain=1, data_format='NCHW', impl='cuda'):
- r"""Upsample a batch of 2D images with the given filter.
-
- Accepts a batch of 2D images of the shape `[N, C, H, W]` or `[N, H, W, C]`
- and upsamples each image with the given filter. The filter is normalized so that
- if the input pixels are constant, they will be scaled by the specified `gain`.
- Pixels outside the image are assumed to be zero, and the filter is padded with
- zeros so that its shape is a multiple of the upsampling factor.
-
- Args:
- x: Input tensor of the shape `[N, C, H, W]` or `[N, H, W, C]`.
- k: FIR filter of the shape `[firH, firW]` or `[firN]` (separable).
- The default is `[1] * factor`, which corresponds to nearest-neighbor
- upsampling.
- factor: Integer upsampling factor (default: 2).
- gain: Scaling factor for signal magnitude (default: 1.0).
- data_format: `'NCHW'` or `'NHWC'` (default: `'NCHW'`).
- impl: Name of the implementation to use. Can be `"ref"` or `"cuda"` (default).
-
- Returns:
- Tensor of the shape `[N, C, H * factor, W * factor]` or
- `[N, H * factor, W * factor, C]`, and same datatype as `x`.
- """
-
- assert isinstance(factor, int) and factor >= 1
- if k is None:
- k = [1] * factor
- k = _setup_kernel(k) * (gain * (factor ** 2))
- p = k.shape[0] - factor
- return _simple_upfirdn_2d(x, k, up=factor, pad0=(p+1)//2+factor-1, pad1=p//2, data_format=data_format, impl=impl)
-
-# ----------------------------------------------------------------------------
-
-
-def downsample_2d(x, k=None, factor=2, gain=1, data_format='NCHW', impl='cuda'):
- r"""Downsample a batch of 2D images with the given filter.
-
- Accepts a batch of 2D images of the shape `[N, C, H, W]` or `[N, H, W, C]`
- and downsamples each image with the given filter. The filter is normalized so that
- if the input pixels are constant, they will be scaled by the specified `gain`.
- Pixels outside the image are assumed to be zero, and the filter is padded with
- zeros so that its shape is a multiple of the downsampling factor.
-
- Args:
- x: Input tensor of the shape `[N, C, H, W]` or `[N, H, W, C]`.
- k: FIR filter of the shape `[firH, firW]` or `[firN]` (separable).
- The default is `[1] * factor`, which corresponds to average pooling.
- factor: Integer downsampling factor (default: 2).
- gain: Scaling factor for signal magnitude (default: 1.0).
- data_format: `'NCHW'` or `'NHWC'` (default: `'NCHW'`).
- impl: Name of the implementation to use. Can be `"ref"` or `"cuda"` (default).
-
- Returns:
- Tensor of the shape `[N, C, H // factor, W // factor]` or
- `[N, H // factor, W // factor, C]`, and same datatype as `x`.
- """
-
- assert isinstance(factor, int) and factor >= 1
- if k is None:
- k = [1] * factor
- k = _setup_kernel(k) * gain
- p = k.shape[0] - factor
- return _simple_upfirdn_2d(x, k, down=factor, pad0=(p+1)//2, pad1=p//2, data_format=data_format, impl=impl)
-
-# ----------------------------------------------------------------------------
-
-
-def upsample_conv_2d(x, w, k=None, factor=2, gain=1, data_format='NCHW', impl='cuda'):
- r"""Fused `upsample_2d()` followed by `tf.nn.conv2d()`.
-
- Padding is performed only once at the beginning, not between the operations.
- The fused op is considerably more efficient than performing the same calculation
- using standard TensorFlow ops. It supports gradients of arbitrary order.
-
- Args:
- x: Input tensor of the shape `[N, C, H, W]` or `[N, H, W, C]`.
- w: Weight tensor of the shape `[filterH, filterW, inChannels, outChannels]`.
- Grouped convolution can be performed by `inChannels = x.shape[0] // numGroups`.
- k: FIR filter of the shape `[firH, firW]` or `[firN]` (separable).
- The default is `[1] * factor`, which corresponds to nearest-neighbor
- upsampling.
- factor: Integer upsampling factor (default: 2).
- gain: Scaling factor for signal magnitude (default: 1.0).
- data_format: `'NCHW'` or `'NHWC'` (default: `'NCHW'`).
- impl: Name of the implementation to use. Can be `"ref"` or `"cuda"` (default).
-
- Returns:
- Tensor of the shape `[N, C, H * factor, W * factor]` or
- `[N, H * factor, W * factor, C]`, and same datatype as `x`.
- """
-
- assert isinstance(factor, int) and factor >= 1
-
- # Check weight shape.
- w = tf.convert_to_tensor(w)
- assert w.shape.rank == 4
- convH = w.shape[0].value
- convW = w.shape[1].value
- inC = _shape(w, 2)
- outC = _shape(w, 3)
- assert convW == convH
-
- # Setup filter kernel.
- if k is None:
- k = [1] * factor
- k = _setup_kernel(k) * (gain * (factor ** 2))
- p = (k.shape[0] - factor) - (convW - 1)
-
- # Determine data dimensions.
- if data_format == 'NCHW':
- stride = [1, 1, factor, factor]
- output_shape = [_shape(x, 0), outC, (_shape(
- x, 2) - 1) * factor + convH, (_shape(x, 3) - 1) * factor + convW]
- num_groups = _shape(x, 1) // inC
- else:
- stride = [1, factor, factor, 1]
- output_shape = [_shape(x, 0), (_shape(
- x, 1) - 1) * factor + convH, (_shape(x, 2) - 1) * factor + convW, outC]
- num_groups = _shape(x, 3) // inC
-
- # Transpose weights.
- w = tf.reshape(w, [convH, convW, inC, num_groups, -1])
- w = tf.transpose(w[::-1, ::-1], [0, 1, 4, 3, 2])
- w = tf.reshape(w, [convH, convW, -1, num_groups * inC])
-
- # Execute.
- x = tf.nn.conv2d_transpose(x, w, output_shape=output_shape,
- strides=stride, padding='VALID', data_format=data_format)
- return _simple_upfirdn_2d(x, k, pad0=(p+1)//2+factor-1, pad1=p//2+1, data_format=data_format, impl=impl)
-
-# ----------------------------------------------------------------------------
-
-
-def conv_downsample_2d(x, w, k=None, factor=2, gain=1, data_format='NCHW', impl='cuda'):
- r"""Fused `tf.nn.conv2d()` followed by `downsample_2d()`.
-
- Padding is performed only once at the beginning, not between the operations.
- The fused op is considerably more efficient than performing the same calculation
- using standard TensorFlow ops. It supports gradients of arbitrary order.
-
- Args:
- x: Input tensor of the shape `[N, C, H, W]` or `[N, H, W, C]`.
- w: Weight tensor of the shape `[filterH, filterW, inChannels, outChannels]`.
- Grouped convolution can be performed by `inChannels = x.shape[0] // numGroups`.
- k: FIR filter of the shape `[firH, firW]` or `[firN]` (separable).
- The default is `[1] * factor`, which corresponds to average pooling.
- factor: Integer downsampling factor (default: 2).
- gain: Scaling factor for signal magnitude (default: 1.0).
- data_format: `'NCHW'` or `'NHWC'` (default: `'NCHW'`).
- impl: Name of the implementation to use. Can be `"ref"` or `"cuda"` (default).
-
- Returns:
- Tensor of the shape `[N, C, H // factor, W // factor]` or
- `[N, H // factor, W // factor, C]`, and same datatype as `x`.
- """
-
- assert isinstance(factor, int) and factor >= 1
- w = tf.convert_to_tensor(w)
- convH, convW, _inC, _outC = w.shape.as_list()
- assert convW == convH
- if k is None:
- k = [1] * factor
- k = _setup_kernel(k) * gain
- p = (k.shape[0] - factor) + (convW - 1)
- if data_format == 'NCHW':
- s = [1, 1, factor, factor]
- else:
- s = [1, factor, factor, 1]
- x = _simple_upfirdn_2d(x, k, pad0=(p+1)//2, pad1=p //
- 2, data_format=data_format, impl=impl)
- return tf.nn.conv2d(x, w, strides=s, padding='VALID', data_format=data_format)
-
-# ----------------------------------------------------------------------------
-# Internal helper funcs.
-
-
-def _shape(tf_expr, dim_idx):
- if tf_expr.shape.rank is not None:
- dim = tf_expr.shape[dim_idx].value
- if dim is not None:
- return dim
- return tf.shape(tf_expr)[dim_idx]
-
-
-def _setup_kernel(k):
- k = np.asarray(k, dtype=np.float32)
- if k.ndim == 1:
- k = np.outer(k, k)
- k /= np.sum(k)
- assert k.ndim == 2
- assert k.shape[0] == k.shape[1]
- return k
-
-
-def _simple_upfirdn_2d(x, k, up=1, down=1, pad0=0, pad1=0, data_format='NCHW', impl='cuda'):
- assert data_format in ['NCHW', 'NHWC']
- assert x.shape.rank == 4
- y = x
- if data_format == 'NCHW':
- y = tf.reshape(y, [-1, _shape(y, 2), _shape(y, 3), 1])
- y = upfirdn_2d(y, k, upx=up, upy=up, downx=down, downy=down,
- padx0=pad0, padx1=pad1, pady0=pad0, pady1=pad1, impl=impl)
- if data_format == 'NCHW':
- y = tf.reshape(y, [-1, _shape(x, 1), _shape(y, 1), _shape(y, 2)])
- return y
-
-# ----------------------------------------------------------------------------
diff --git a/spaces/Andy1621/uniformer_image_detection/configs/mask_rcnn/mask_rcnn_x101_64x4d_fpn_2x_coco.py b/spaces/Andy1621/uniformer_image_detection/configs/mask_rcnn/mask_rcnn_x101_64x4d_fpn_2x_coco.py
deleted file mode 100644
index 9ba92c5b0b6dcaf10746aeacf7a868348133ff80..0000000000000000000000000000000000000000
--- a/spaces/Andy1621/uniformer_image_detection/configs/mask_rcnn/mask_rcnn_x101_64x4d_fpn_2x_coco.py
+++ /dev/null
@@ -1,13 +0,0 @@
-_base_ = './mask_rcnn_x101_32x4d_fpn_2x_coco.py'
-model = dict(
- pretrained='open-mmlab://resnext101_64x4d',
- backbone=dict(
- type='ResNeXt',
- depth=101,
- groups=64,
- base_width=4,
- num_stages=4,
- out_indices=(0, 1, 2, 3),
- frozen_stages=1,
- norm_cfg=dict(type='BN', requires_grad=True),
- style='pytorch'))
diff --git a/spaces/Andy1621/uniformer_image_detection/configs/tridentnet/tridentnet_r50_caffe_mstrain_3x_coco.py b/spaces/Andy1621/uniformer_image_detection/configs/tridentnet/tridentnet_r50_caffe_mstrain_3x_coco.py
deleted file mode 100644
index 0f402826d3a22714078d8c50ed6bd8959018e4e7..0000000000000000000000000000000000000000
--- a/spaces/Andy1621/uniformer_image_detection/configs/tridentnet/tridentnet_r50_caffe_mstrain_3x_coco.py
+++ /dev/null
@@ -1,4 +0,0 @@
-_base_ = 'tridentnet_r50_caffe_mstrain_1x_coco.py'
-
-lr_config = dict(step=[28, 34])
-runner = dict(type='EpochBasedRunner', max_epochs=36)
diff --git a/spaces/Andy1621/uniformer_image_detection/mmdet/core/bbox/assigners/grid_assigner.py b/spaces/Andy1621/uniformer_image_detection/mmdet/core/bbox/assigners/grid_assigner.py
deleted file mode 100644
index 7390ea6370639c939d578c6ebf0f9268499161bc..0000000000000000000000000000000000000000
--- a/spaces/Andy1621/uniformer_image_detection/mmdet/core/bbox/assigners/grid_assigner.py
+++ /dev/null
@@ -1,155 +0,0 @@
-import torch
-
-from ..builder import BBOX_ASSIGNERS
-from ..iou_calculators import build_iou_calculator
-from .assign_result import AssignResult
-from .base_assigner import BaseAssigner
-
-
-@BBOX_ASSIGNERS.register_module()
-class GridAssigner(BaseAssigner):
- """Assign a corresponding gt bbox or background to each bbox.
-
- Each proposals will be assigned with `-1`, `0`, or a positive integer
- indicating the ground truth index.
-
- - -1: don't care
- - 0: negative sample, no assigned gt
- - positive integer: positive sample, index (1-based) of assigned gt
-
- Args:
- pos_iou_thr (float): IoU threshold for positive bboxes.
- neg_iou_thr (float or tuple): IoU threshold for negative bboxes.
- min_pos_iou (float): Minimum iou for a bbox to be considered as a
- positive bbox. Positive samples can have smaller IoU than
- pos_iou_thr due to the 4th step (assign max IoU sample to each gt).
- gt_max_assign_all (bool): Whether to assign all bboxes with the same
- highest overlap with some gt to that gt.
- """
-
- def __init__(self,
- pos_iou_thr,
- neg_iou_thr,
- min_pos_iou=.0,
- gt_max_assign_all=True,
- iou_calculator=dict(type='BboxOverlaps2D')):
- self.pos_iou_thr = pos_iou_thr
- self.neg_iou_thr = neg_iou_thr
- self.min_pos_iou = min_pos_iou
- self.gt_max_assign_all = gt_max_assign_all
- self.iou_calculator = build_iou_calculator(iou_calculator)
-
- def assign(self, bboxes, box_responsible_flags, gt_bboxes, gt_labels=None):
- """Assign gt to bboxes. The process is very much like the max iou
- assigner, except that positive samples are constrained within the cell
- that the gt boxes fell in.
-
- This method assign a gt bbox to every bbox (proposal/anchor), each bbox
- will be assigned with -1, 0, or a positive number. -1 means don't care,
- 0 means negative sample, positive number is the index (1-based) of
- assigned gt.
- The assignment is done in following steps, the order matters.
-
- 1. assign every bbox to -1
- 2. assign proposals whose iou with all gts <= neg_iou_thr to 0
- 3. for each bbox within a cell, if the iou with its nearest gt >
- pos_iou_thr and the center of that gt falls inside the cell,
- assign it to that bbox
- 4. for each gt bbox, assign its nearest proposals within the cell the
- gt bbox falls in to itself.
-
- Args:
- bboxes (Tensor): Bounding boxes to be assigned, shape(n, 4).
- box_responsible_flags (Tensor): flag to indicate whether box is
- responsible for prediction, shape(n, )
- gt_bboxes (Tensor): Groundtruth boxes, shape (k, 4).
- gt_labels (Tensor, optional): Label of gt_bboxes, shape (k, ).
-
- Returns:
- :obj:`AssignResult`: The assign result.
- """
- num_gts, num_bboxes = gt_bboxes.size(0), bboxes.size(0)
-
- # compute iou between all gt and bboxes
- overlaps = self.iou_calculator(gt_bboxes, bboxes)
-
- # 1. assign -1 by default
- assigned_gt_inds = overlaps.new_full((num_bboxes, ),
- -1,
- dtype=torch.long)
-
- if num_gts == 0 or num_bboxes == 0:
- # No ground truth or boxes, return empty assignment
- max_overlaps = overlaps.new_zeros((num_bboxes, ))
- if num_gts == 0:
- # No truth, assign everything to background
- assigned_gt_inds[:] = 0
- if gt_labels is None:
- assigned_labels = None
- else:
- assigned_labels = overlaps.new_full((num_bboxes, ),
- -1,
- dtype=torch.long)
- return AssignResult(
- num_gts,
- assigned_gt_inds,
- max_overlaps,
- labels=assigned_labels)
-
- # 2. assign negative: below
- # for each anchor, which gt best overlaps with it
- # for each anchor, the max iou of all gts
- # shape of max_overlaps == argmax_overlaps == num_bboxes
- max_overlaps, argmax_overlaps = overlaps.max(dim=0)
-
- if isinstance(self.neg_iou_thr, float):
- assigned_gt_inds[(max_overlaps >= 0)
- & (max_overlaps <= self.neg_iou_thr)] = 0
- elif isinstance(self.neg_iou_thr, (tuple, list)):
- assert len(self.neg_iou_thr) == 2
- assigned_gt_inds[(max_overlaps > self.neg_iou_thr[0])
- & (max_overlaps <= self.neg_iou_thr[1])] = 0
-
- # 3. assign positive: falls into responsible cell and above
- # positive IOU threshold, the order matters.
- # the prior condition of comparision is to filter out all
- # unrelated anchors, i.e. not box_responsible_flags
- overlaps[:, ~box_responsible_flags.type(torch.bool)] = -1.
-
- # calculate max_overlaps again, but this time we only consider IOUs
- # for anchors responsible for prediction
- max_overlaps, argmax_overlaps = overlaps.max(dim=0)
-
- # for each gt, which anchor best overlaps with it
- # for each gt, the max iou of all proposals
- # shape of gt_max_overlaps == gt_argmax_overlaps == num_gts
- gt_max_overlaps, gt_argmax_overlaps = overlaps.max(dim=1)
-
- pos_inds = (max_overlaps >
- self.pos_iou_thr) & box_responsible_flags.type(torch.bool)
- assigned_gt_inds[pos_inds] = argmax_overlaps[pos_inds] + 1
-
- # 4. assign positive to max overlapped anchors within responsible cell
- for i in range(num_gts):
- if gt_max_overlaps[i] > self.min_pos_iou:
- if self.gt_max_assign_all:
- max_iou_inds = (overlaps[i, :] == gt_max_overlaps[i]) & \
- box_responsible_flags.type(torch.bool)
- assigned_gt_inds[max_iou_inds] = i + 1
- elif box_responsible_flags[gt_argmax_overlaps[i]]:
- assigned_gt_inds[gt_argmax_overlaps[i]] = i + 1
-
- # assign labels of positive anchors
- if gt_labels is not None:
- assigned_labels = assigned_gt_inds.new_full((num_bboxes, ), -1)
- pos_inds = torch.nonzero(
- assigned_gt_inds > 0, as_tuple=False).squeeze()
- if pos_inds.numel() > 0:
- assigned_labels[pos_inds] = gt_labels[
- assigned_gt_inds[pos_inds] - 1]
-
- else:
- assigned_labels = None
-
- return AssignResult(
- num_gts, assigned_gt_inds, max_overlaps, labels=assigned_labels)
diff --git a/spaces/Andy1621/uniformer_image_detection/mmdet/models/detectors/__init__.py b/spaces/Andy1621/uniformer_image_detection/mmdet/models/detectors/__init__.py
deleted file mode 100644
index 04011130435cf9fdfadeb821919046b1bddab7d4..0000000000000000000000000000000000000000
--- a/spaces/Andy1621/uniformer_image_detection/mmdet/models/detectors/__init__.py
+++ /dev/null
@@ -1,40 +0,0 @@
-from .atss import ATSS
-from .base import BaseDetector
-from .cascade_rcnn import CascadeRCNN
-from .cornernet import CornerNet
-from .detr import DETR
-from .fast_rcnn import FastRCNN
-from .faster_rcnn import FasterRCNN
-from .fcos import FCOS
-from .fovea import FOVEA
-from .fsaf import FSAF
-from .gfl import GFL
-from .grid_rcnn import GridRCNN
-from .htc import HybridTaskCascade
-from .kd_one_stage import KnowledgeDistillationSingleStageDetector
-from .mask_rcnn import MaskRCNN
-from .mask_scoring_rcnn import MaskScoringRCNN
-from .nasfcos import NASFCOS
-from .paa import PAA
-from .point_rend import PointRend
-from .reppoints_detector import RepPointsDetector
-from .retinanet import RetinaNet
-from .rpn import RPN
-from .scnet import SCNet
-from .single_stage import SingleStageDetector
-from .sparse_rcnn import SparseRCNN
-from .trident_faster_rcnn import TridentFasterRCNN
-from .two_stage import TwoStageDetector
-from .vfnet import VFNet
-from .yolact import YOLACT
-from .yolo import YOLOV3
-
-__all__ = [
- 'ATSS', 'BaseDetector', 'SingleStageDetector',
- 'KnowledgeDistillationSingleStageDetector', 'TwoStageDetector', 'RPN',
- 'FastRCNN', 'FasterRCNN', 'MaskRCNN', 'CascadeRCNN', 'HybridTaskCascade',
- 'RetinaNet', 'FCOS', 'GridRCNN', 'MaskScoringRCNN', 'RepPointsDetector',
- 'FOVEA', 'FSAF', 'NASFCOS', 'PointRend', 'GFL', 'CornerNet', 'PAA',
- 'YOLOV3', 'YOLACT', 'VFNet', 'DETR', 'TridentFasterRCNN', 'SparseRCNN',
- 'SCNet'
-]
diff --git a/spaces/Andy1621/uniformer_image_segmentation/configs/_base_/datasets/cityscapes.py b/spaces/Andy1621/uniformer_image_segmentation/configs/_base_/datasets/cityscapes.py
deleted file mode 100644
index f21867c63e1835f6fceb61f066e802fd8fd2a735..0000000000000000000000000000000000000000
--- a/spaces/Andy1621/uniformer_image_segmentation/configs/_base_/datasets/cityscapes.py
+++ /dev/null
@@ -1,54 +0,0 @@
-# dataset settings
-dataset_type = 'CityscapesDataset'
-data_root = 'data/cityscapes/'
-img_norm_cfg = dict(
- mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
-crop_size = (512, 1024)
-train_pipeline = [
- dict(type='LoadImageFromFile'),
- dict(type='LoadAnnotations'),
- dict(type='Resize', img_scale=(2048, 1024), ratio_range=(0.5, 2.0)),
- dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75),
- dict(type='RandomFlip', prob=0.5),
- dict(type='PhotoMetricDistortion'),
- dict(type='Normalize', **img_norm_cfg),
- dict(type='Pad', size=crop_size, pad_val=0, seg_pad_val=255),
- dict(type='DefaultFormatBundle'),
- dict(type='Collect', keys=['img', 'gt_semantic_seg']),
-]
-test_pipeline = [
- dict(type='LoadImageFromFile'),
- dict(
- type='MultiScaleFlipAug',
- img_scale=(2048, 1024),
- # img_ratios=[0.5, 0.75, 1.0, 1.25, 1.5, 1.75],
- flip=False,
- transforms=[
- dict(type='Resize', keep_ratio=True),
- dict(type='RandomFlip'),
- dict(type='Normalize', **img_norm_cfg),
- dict(type='ImageToTensor', keys=['img']),
- dict(type='Collect', keys=['img']),
- ])
-]
-data = dict(
- samples_per_gpu=2,
- workers_per_gpu=2,
- train=dict(
- type=dataset_type,
- data_root=data_root,
- img_dir='leftImg8bit/train',
- ann_dir='gtFine/train',
- pipeline=train_pipeline),
- val=dict(
- type=dataset_type,
- data_root=data_root,
- img_dir='leftImg8bit/val',
- ann_dir='gtFine/val',
- pipeline=test_pipeline),
- test=dict(
- type=dataset_type,
- data_root=data_root,
- img_dir='leftImg8bit/val',
- ann_dir='gtFine/val',
- pipeline=test_pipeline))
diff --git a/spaces/Andy1621/uniformer_image_segmentation/configs/_base_/default_runtime.py b/spaces/Andy1621/uniformer_image_segmentation/configs/_base_/default_runtime.py
deleted file mode 100644
index b564cc4e7e7d9a67dacaaddecb100e4d8f5c005b..0000000000000000000000000000000000000000
--- a/spaces/Andy1621/uniformer_image_segmentation/configs/_base_/default_runtime.py
+++ /dev/null
@@ -1,14 +0,0 @@
-# yapf:disable
-log_config = dict(
- interval=50,
- hooks=[
- dict(type='TextLoggerHook', by_epoch=False),
- # dict(type='TensorboardLoggerHook')
- ])
-# yapf:enable
-dist_params = dict(backend='nccl')
-log_level = 'INFO'
-load_from = None
-resume_from = None
-workflow = [('train', 1)]
-cudnn_benchmark = True
diff --git a/spaces/Andy1621/uniformer_image_segmentation/configs/ccnet/ccnet_r101-d8_769x769_80k_cityscapes.py b/spaces/Andy1621/uniformer_image_segmentation/configs/ccnet/ccnet_r101-d8_769x769_80k_cityscapes.py
deleted file mode 100644
index 654f377b6f6152c9bd98d33824a39a41d7510c3f..0000000000000000000000000000000000000000
--- a/spaces/Andy1621/uniformer_image_segmentation/configs/ccnet/ccnet_r101-d8_769x769_80k_cityscapes.py
+++ /dev/null
@@ -1,2 +0,0 @@
-_base_ = './ccnet_r50-d8_769x769_80k_cityscapes.py'
-model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
diff --git a/spaces/Andy1621/uniformer_image_segmentation/configs/mobilenet_v2/pspnet_m-v2-d8_512x512_160k_ade20k.py b/spaces/Andy1621/uniformer_image_segmentation/configs/mobilenet_v2/pspnet_m-v2-d8_512x512_160k_ade20k.py
deleted file mode 100644
index 5b72ac830be29b865ed52adaf41f2fe800f252cc..0000000000000000000000000000000000000000
--- a/spaces/Andy1621/uniformer_image_segmentation/configs/mobilenet_v2/pspnet_m-v2-d8_512x512_160k_ade20k.py
+++ /dev/null
@@ -1,12 +0,0 @@
-_base_ = '../pspnet/pspnet_r101-d8_512x512_160k_ade20k.py'
-model = dict(
- pretrained='mmcls://mobilenet_v2',
- backbone=dict(
- _delete_=True,
- type='MobileNetV2',
- widen_factor=1.,
- strides=(1, 2, 2, 1, 1, 1, 1),
- dilations=(1, 1, 1, 2, 2, 4, 4),
- out_indices=(1, 2, 4, 6)),
- decode_head=dict(in_channels=320),
- auxiliary_head=dict(in_channels=96))
diff --git a/spaces/AppleQAQ/anime-remove-background/README.md b/spaces/AppleQAQ/anime-remove-background/README.md
deleted file mode 100644
index 1ba3cb5ea0e994e246d57b7d62b8aa5a6331901c..0000000000000000000000000000000000000000
--- a/spaces/AppleQAQ/anime-remove-background/README.md
+++ /dev/null
@@ -1,14 +0,0 @@
----
-title: Anime Remove Background
-emoji: 🪄🖼️
-colorFrom: indigo
-colorTo: pink
-sdk: gradio
-sdk_version: 3.1.4
-app_file: app.py
-pinned: false
-license: apache-2.0
-duplicated_from: skytnt/anime-remove-background
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/Ataturk-Chatbot/HuggingFaceChat/venv/lib/python3.11/site-packages/pip/_vendor/idna/__init__.py b/spaces/Ataturk-Chatbot/HuggingFaceChat/venv/lib/python3.11/site-packages/pip/_vendor/idna/__init__.py
deleted file mode 100644
index a40eeafcc914108ca79c5d83d6e81da1b29c6e80..0000000000000000000000000000000000000000
--- a/spaces/Ataturk-Chatbot/HuggingFaceChat/venv/lib/python3.11/site-packages/pip/_vendor/idna/__init__.py
+++ /dev/null
@@ -1,44 +0,0 @@
-from .package_data import __version__
-from .core import (
- IDNABidiError,
- IDNAError,
- InvalidCodepoint,
- InvalidCodepointContext,
- alabel,
- check_bidi,
- check_hyphen_ok,
- check_initial_combiner,
- check_label,
- check_nfc,
- decode,
- encode,
- ulabel,
- uts46_remap,
- valid_contextj,
- valid_contexto,
- valid_label_length,
- valid_string_length,
-)
-from .intranges import intranges_contain
-
-__all__ = [
- "IDNABidiError",
- "IDNAError",
- "InvalidCodepoint",
- "InvalidCodepointContext",
- "alabel",
- "check_bidi",
- "check_hyphen_ok",
- "check_initial_combiner",
- "check_label",
- "check_nfc",
- "decode",
- "encode",
- "intranges_contain",
- "ulabel",
- "uts46_remap",
- "valid_contextj",
- "valid_contexto",
- "valid_label_length",
- "valid_string_length",
-]
diff --git a/spaces/Ataturk-Chatbot/HuggingFaceChat/venv/lib/python3.11/site-packages/pkg_resources/_vendor/importlib_resources/_common.py b/spaces/Ataturk-Chatbot/HuggingFaceChat/venv/lib/python3.11/site-packages/pkg_resources/_vendor/importlib_resources/_common.py
deleted file mode 100644
index a12e2c75d132c73b556702159d535d15ed9abfd2..0000000000000000000000000000000000000000
--- a/spaces/Ataturk-Chatbot/HuggingFaceChat/venv/lib/python3.11/site-packages/pkg_resources/_vendor/importlib_resources/_common.py
+++ /dev/null
@@ -1,104 +0,0 @@
-import os
-import pathlib
-import tempfile
-import functools
-import contextlib
-import types
-import importlib
-
-from typing import Union, Optional
-from .abc import ResourceReader, Traversable
-
-from ._compat import wrap_spec
-
-Package = Union[types.ModuleType, str]
-
-
-def files(package):
- # type: (Package) -> Traversable
- """
- Get a Traversable resource from a package
- """
- return from_package(get_package(package))
-
-
-def get_resource_reader(package):
- # type: (types.ModuleType) -> Optional[ResourceReader]
- """
- Return the package's loader if it's a ResourceReader.
- """
- # We can't use
- # a issubclass() check here because apparently abc.'s __subclasscheck__()
- # hook wants to create a weak reference to the object, but
- # zipimport.zipimporter does not support weak references, resulting in a
- # TypeError. That seems terrible.
- spec = package.__spec__
- reader = getattr(spec.loader, 'get_resource_reader', None) # type: ignore
- if reader is None:
- return None
- return reader(spec.name) # type: ignore
-
-
-def resolve(cand):
- # type: (Package) -> types.ModuleType
- return cand if isinstance(cand, types.ModuleType) else importlib.import_module(cand)
-
-
-def get_package(package):
- # type: (Package) -> types.ModuleType
- """Take a package name or module object and return the module.
-
- Raise an exception if the resolved module is not a package.
- """
- resolved = resolve(package)
- if wrap_spec(resolved).submodule_search_locations is None:
- raise TypeError(f'{package!r} is not a package')
- return resolved
-
-
-def from_package(package):
- """
- Return a Traversable object for the given package.
-
- """
- spec = wrap_spec(package)
- reader = spec.loader.get_resource_reader(spec.name)
- return reader.files()
-
-
-@contextlib.contextmanager
-def _tempfile(reader, suffix=''):
- # Not using tempfile.NamedTemporaryFile as it leads to deeper 'try'
- # blocks due to the need to close the temporary file to work on Windows
- # properly.
- fd, raw_path = tempfile.mkstemp(suffix=suffix)
- try:
- try:
- os.write(fd, reader())
- finally:
- os.close(fd)
- del reader
- yield pathlib.Path(raw_path)
- finally:
- try:
- os.remove(raw_path)
- except FileNotFoundError:
- pass
-
-
-@functools.singledispatch
-def as_file(path):
- """
- Given a Traversable object, return that object as a
- path on the local file system in a context manager.
- """
- return _tempfile(path.read_bytes, suffix=path.name)
-
-
-@as_file.register(pathlib.Path)
-@contextlib.contextmanager
-def _(path):
- """
- Degenerate behavior for pathlib.Path objects.
- """
- yield path
diff --git a/spaces/Awiny/Image2Paragraph/models/grit_src/third_party/CenterNet2/configs/new_baselines/mask_rcnn_regnety_4gf_dds_FPN_200ep_LSJ.py b/spaces/Awiny/Image2Paragraph/models/grit_src/third_party/CenterNet2/configs/new_baselines/mask_rcnn_regnety_4gf_dds_FPN_200ep_LSJ.py
deleted file mode 100644
index b867cc865e5ac4d7b70221da141894efd7cbd75c..0000000000000000000000000000000000000000
--- a/spaces/Awiny/Image2Paragraph/models/grit_src/third_party/CenterNet2/configs/new_baselines/mask_rcnn_regnety_4gf_dds_FPN_200ep_LSJ.py
+++ /dev/null
@@ -1,14 +0,0 @@
-from .mask_rcnn_regnety_4gf_dds_FPN_100ep_LSJ import (
- dataloader,
- lr_multiplier,
- model,
- optimizer,
- train,
-)
-
-train.max_iter *= 2 # 100ep -> 200ep
-
-lr_multiplier.scheduler.milestones = [
- milestone * 2 for milestone in lr_multiplier.scheduler.milestones
-]
-lr_multiplier.scheduler.num_updates = train.max_iter
diff --git a/spaces/Awiny/Image2Paragraph/models/grit_src/third_party/CenterNet2/tests/modeling/test_fast_rcnn.py b/spaces/Awiny/Image2Paragraph/models/grit_src/third_party/CenterNet2/tests/modeling/test_fast_rcnn.py
deleted file mode 100644
index e29b944bffca1ccbf5b02be59a753f3188d90a4f..0000000000000000000000000000000000000000
--- a/spaces/Awiny/Image2Paragraph/models/grit_src/third_party/CenterNet2/tests/modeling/test_fast_rcnn.py
+++ /dev/null
@@ -1,171 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-import logging
-import unittest
-import torch
-
-from detectron2.layers import ShapeSpec
-from detectron2.modeling.box_regression import Box2BoxTransform, Box2BoxTransformRotated
-from detectron2.modeling.roi_heads.fast_rcnn import FastRCNNOutputLayers
-from detectron2.modeling.roi_heads.rotated_fast_rcnn import RotatedFastRCNNOutputLayers
-from detectron2.structures import Boxes, Instances, RotatedBoxes
-from detectron2.utils.events import EventStorage
-
-logger = logging.getLogger(__name__)
-
-
-class FastRCNNTest(unittest.TestCase):
- def test_fast_rcnn(self):
- torch.manual_seed(132)
-
- box_head_output_size = 8
-
- box_predictor = FastRCNNOutputLayers(
- ShapeSpec(channels=box_head_output_size),
- box2box_transform=Box2BoxTransform(weights=(10, 10, 5, 5)),
- num_classes=5,
- )
- feature_pooled = torch.rand(2, box_head_output_size)
- predictions = box_predictor(feature_pooled)
-
- proposal_boxes = torch.tensor([[0.8, 1.1, 3.2, 2.8], [2.3, 2.5, 7, 8]], dtype=torch.float32)
- gt_boxes = torch.tensor([[1, 1, 3, 3], [2, 2, 6, 6]], dtype=torch.float32)
- proposal = Instances((10, 10))
- proposal.proposal_boxes = Boxes(proposal_boxes)
- proposal.gt_boxes = Boxes(gt_boxes)
- proposal.gt_classes = torch.tensor([1, 2])
-
- with EventStorage(): # capture events in a new storage to discard them
- losses = box_predictor.losses(predictions, [proposal])
-
- expected_losses = {
- "loss_cls": torch.tensor(1.7951188087),
- "loss_box_reg": torch.tensor(4.0357131958),
- }
- for name in expected_losses.keys():
- assert torch.allclose(losses[name], expected_losses[name])
-
- def test_fast_rcnn_empty_batch(self, device="cpu"):
- box_predictor = FastRCNNOutputLayers(
- ShapeSpec(channels=10),
- box2box_transform=Box2BoxTransform(weights=(10, 10, 5, 5)),
- num_classes=8,
- ).to(device=device)
-
- logits = torch.randn(0, 100, requires_grad=True, device=device)
- deltas = torch.randn(0, 4, requires_grad=True, device=device)
- losses = box_predictor.losses([logits, deltas], [])
- for value in losses.values():
- self.assertTrue(torch.allclose(value, torch.zeros_like(value)))
- sum(losses.values()).backward()
- self.assertTrue(logits.grad is not None)
- self.assertTrue(deltas.grad is not None)
-
- predictions, _ = box_predictor.inference([logits, deltas], [])
- self.assertEqual(len(predictions), 0)
-
- @unittest.skipIf(not torch.cuda.is_available(), "CUDA not available")
- def test_fast_rcnn_empty_batch_cuda(self):
- self.test_fast_rcnn_empty_batch(device=torch.device("cuda"))
-
- def test_fast_rcnn_rotated(self):
- torch.manual_seed(132)
- box_head_output_size = 8
-
- box_predictor = RotatedFastRCNNOutputLayers(
- ShapeSpec(channels=box_head_output_size),
- box2box_transform=Box2BoxTransformRotated(weights=(10, 10, 5, 5, 1)),
- num_classes=5,
- )
- feature_pooled = torch.rand(2, box_head_output_size)
- predictions = box_predictor(feature_pooled)
- proposal_boxes = torch.tensor(
- [[2, 1.95, 2.4, 1.7, 0], [4.65, 5.25, 4.7, 5.5, 0]], dtype=torch.float32
- )
- gt_boxes = torch.tensor([[2, 2, 2, 2, 0], [4, 4, 4, 4, 0]], dtype=torch.float32)
- proposal = Instances((10, 10))
- proposal.proposal_boxes = RotatedBoxes(proposal_boxes)
- proposal.gt_boxes = RotatedBoxes(gt_boxes)
- proposal.gt_classes = torch.tensor([1, 2])
-
- with EventStorage(): # capture events in a new storage to discard them
- losses = box_predictor.losses(predictions, [proposal])
-
- # Note: the expected losses are slightly different even if
- # the boxes are essentially the same as in the FastRCNNOutput test, because
- # bbox_pred in FastRCNNOutputLayers have different Linear layers/initialization
- # between the two cases.
- expected_losses = {
- "loss_cls": torch.tensor(1.7920907736),
- "loss_box_reg": torch.tensor(4.0410838127),
- }
- for name in expected_losses.keys():
- assert torch.allclose(losses[name], expected_losses[name])
-
- def test_predict_boxes_tracing(self):
- class Model(torch.nn.Module):
- def __init__(self, output_layer):
- super(Model, self).__init__()
- self._output_layer = output_layer
-
- def forward(self, proposal_deltas, proposal_boxes):
- instances = Instances((10, 10))
- instances.proposal_boxes = Boxes(proposal_boxes)
- return self._output_layer.predict_boxes((None, proposal_deltas), [instances])
-
- box_head_output_size = 8
-
- box_predictor = FastRCNNOutputLayers(
- ShapeSpec(channels=box_head_output_size),
- box2box_transform=Box2BoxTransform(weights=(10, 10, 5, 5)),
- num_classes=5,
- )
-
- model = Model(box_predictor)
-
- from detectron2.export.torchscript_patch import patch_builtin_len
-
- with torch.no_grad(), patch_builtin_len():
- func = torch.jit.trace(model, (torch.randn(10, 20), torch.randn(10, 4)))
-
- o = func(torch.randn(10, 20), torch.randn(10, 4))
- self.assertEqual(o[0].shape, (10, 20))
- o = func(torch.randn(5, 20), torch.randn(5, 4))
- self.assertEqual(o[0].shape, (5, 20))
- o = func(torch.randn(20, 20), torch.randn(20, 4))
- self.assertEqual(o[0].shape, (20, 20))
-
- def test_predict_probs_tracing(self):
- class Model(torch.nn.Module):
- def __init__(self, output_layer):
- super(Model, self).__init__()
- self._output_layer = output_layer
-
- def forward(self, scores, proposal_boxes):
- instances = Instances((10, 10))
- instances.proposal_boxes = Boxes(proposal_boxes)
- return self._output_layer.predict_probs((scores, None), [instances])
-
- box_head_output_size = 8
-
- box_predictor = FastRCNNOutputLayers(
- ShapeSpec(channels=box_head_output_size),
- box2box_transform=Box2BoxTransform(weights=(10, 10, 5, 5)),
- num_classes=5,
- )
-
- model = Model(box_predictor)
-
- from detectron2.export.torchscript_patch import patch_builtin_len
-
- with torch.no_grad(), patch_builtin_len():
- func = torch.jit.trace(model, (torch.randn(10, 6), torch.rand(10, 4)))
- o = func(torch.randn(10, 6), torch.randn(10, 4))
- self.assertEqual(o[0].shape, (10, 6))
- o = func(torch.randn(5, 6), torch.randn(5, 4))
- self.assertEqual(o[0].shape, (5, 6))
- o = func(torch.randn(20, 6), torch.randn(20, 4))
- self.assertEqual(o[0].shape, (20, 6))
-
-
-if __name__ == "__main__":
- unittest.main()
diff --git a/spaces/BL00DY-257/dolle-mini-lol/index.html b/spaces/BL00DY-257/dolle-mini-lol/index.html
deleted file mode 100644
index f548beb27dd81f9f12ab66b56c8cc102f5e1fc3b..0000000000000000000000000000000000000000
--- a/spaces/BL00DY-257/dolle-mini-lol/index.html
+++ /dev/null
@@ -1,295 +0,0 @@
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
diff --git a/spaces/BatuhanYilmaz/Youtube-Transcriber/app.py b/spaces/BatuhanYilmaz/Youtube-Transcriber/app.py
deleted file mode 100644
index ce86dfd889cb8322e0958d30b4576af548306c0c..0000000000000000000000000000000000000000
--- a/spaces/BatuhanYilmaz/Youtube-Transcriber/app.py
+++ /dev/null
@@ -1,168 +0,0 @@
-import whisper
-from pytube import YouTube
-import requests, io
-from urllib.request import urlopen
-from PIL import Image
-import time
-import streamlit as st
-from streamlit_lottie import st_lottie
-import numpy as np
-import os
-from typing import Iterator
-from io import StringIO
-from utils import write_vtt, write_srt
-
-st.set_page_config(page_title="YouTube Transcriber", page_icon="🗣", layout="wide")
-
-# Define a function that we can use to load lottie files from a link.
-@st.cache(allow_output_mutation=True)
-def load_lottieurl(url: str):
- r = requests.get(url)
- if r.status_code != 200:
- return None
- return r.json()
-
-col1, col2 = st.columns([1, 3])
-with col1:
- lottie = load_lottieurl("https://assets9.lottiefiles.com/private_files/lf30_bntlaz7t.json")
- st_lottie(lottie, speed=1, height=200, width=200)
-
-with col2:
- st.write("""
- ## Youtube Transcriber
- ##### This is an app that transcribes YouTube videos into text.""")
-
-
-#def load_model(size):
- #default_size = size
- #if size == default_size:
- #return None
- #else:
- #loaded_model = whisper.load_model(size)
- #return loaded_model
-
-
-@st.cache(allow_output_mutation=True)
-def populate_metadata(link):
- yt = YouTube(link)
- author = yt.author
- title = yt.title
- description = yt.description
- thumbnail = yt.thumbnail_url
- length = yt.length
- views = yt.views
- return author, title, description, thumbnail, length, views
-
-# Uncomment if you want to fetch the thumbnails as well.
-#def fetch_thumbnail(thumbnail):
- #tnail = urlopen(thumbnail)
- #raw_data = tnail.read()
- #image = Image.open(io.BytesIO(raw_data))
- #st.image(image, use_column_width=True)
-
-
-def convert(seconds):
- return time.strftime("%H:%M:%S", time.gmtime(seconds))
-
-
-loaded_model = whisper.load_model("base")
-current_size = "None"
-size = st.selectbox("Model Size", ["tiny", "base", "small", "medium", "large"], index=1)
-
-
-def change_model(current_size, size):
- if current_size != size:
- loaded_model = whisper.load_model(size)
- st.write(f"Model is {'multilingual' if loaded_model.is_multilingual else 'English-only'} "
- f"and has {sum(np.prod(p.shape) for p in loaded_model.parameters()):,} parameters.")
- return loaded_model
- else:
- return None
-
-
-@st.cache(allow_output_mutation=True)
-def inference(link):
- yt = YouTube(link)
- path = yt.streams.filter(only_audio=True)[0].download(filename="audio.mp4")
- results = loaded_model.transcribe(path)
- vtt = getSubs(results["segments"], "vtt", 80)
- srt = getSubs(results["segments"], "srt", 80)
- return results["text"], vtt, srt
-
-def getSubs(segments: Iterator[dict], format: str, maxLineWidth: int) -> str:
- segmentStream = StringIO()
-
- if format == 'vtt':
- write_vtt(segments, file=segmentStream, maxLineWidth=maxLineWidth)
- elif format == 'srt':
- write_srt(segments, file=segmentStream, maxLineWidth=maxLineWidth)
- else:
- raise Exception("Unknown format " + format)
-
- segmentStream.seek(0)
- return segmentStream.read()
-
-
-def main():
- change_model(current_size, size)
- link = st.text_input("YouTube Link")
- if st.button("Transcribe"):
- author, title, description, thumbnail, length, views = populate_metadata(link)
- results = inference(link)
-
- col3, col4 = st.columns(2)
- with col3:
- #fetch_thumbnail(thumbnail)
- st.video(link)
- st.markdown(f"**Channel**: {author}")
- st.markdown(f"**Title**: {title}")
- st.markdown(f"**Length**: {convert(length)}")
- st.markdown(f"**Views**: {views:,}")
-
- with col4:
- with st.expander("Video Description"):
- st.write(description)
- #st.markdown(f"**Video Description**: {description}")
- with st.expander("Video Transcript"):
- st.write(results[0])
- # Write the results to a .txt file and download it.
- with open("transcript.txt", "w+") as f:
- f.writelines(results[0])
- f.close()
- with open(os.path.join(os.getcwd(), "transcript.txt"), "rb") as f:
- datatxt = f.read()
-
-
- with open("transcript.vtt", "w+") as f:
- f.writelines(results[1])
- f.close()
- with open(os.path.join(os.getcwd(), "transcript.vtt"), "rb") as f:
- datavtt = f.read()
-
- with open("transcript.srt", "w+") as f:
- f.writelines(results[2])
- f.close()
- with open(os.path.join(os.getcwd(), "transcript.srt"), "rb") as f:
- datasrt = f.read()
-
- if st.download_button(label="Download Transcript (.txt) ",
- data=datatxt,
- file_name=f"{title}.txt"):
- st.success("Downloaded Successfully!")
-
- elif st.download_button(label="Download Transcript (.vtt)",
- data=datavtt,
- file_name=f"{title}.vtt"):
- st.success("Downloaded Successfully!")
-
- elif st.download_button(label="Download Transcript (.srt)",
- data=datasrt,
- file_name=f"{title}.srt"):
- st.success("Downloaded Successfully! ")
- else:
- st.success("You can download the transcript in .srt format and upload it to YouTube to create subtitles for your video.")
- st.info("Streamlit refreshes after the download button is clicked. The data is cached so you can download the transcript again without having to transcribe the video again.")
-
-
-if __name__ == "__main__":
- main()
\ No newline at end of file
diff --git a/spaces/Benson/text-generation/Examples/Android_6_8_9_10.apk Download.md b/spaces/Benson/text-generation/Examples/Android_6_8_9_10.apk Download.md
deleted file mode 100644
index e7cb61ad1edc9e06f5e8ddf68b894fab40091c54..0000000000000000000000000000000000000000
--- a/spaces/Benson/text-generation/Examples/Android_6_8_9_10.apk Download.md
+++ /dev/null
@@ -1,96 +0,0 @@
-
-
Cómo descargar e instalar android_6_8_9_10.apk en su dispositivo Android
-
Si usted está buscando una manera de descargar e instalar android_6_8_9_10.apk en su dispositivo Android, es posible que se pregunte qué es y por qué lo necesita. En este artículo, explicaremos qué es un archivo APK, cómo descargarlo e instalarlo en su dispositivo Android, cómo verificar la versión de su dispositivo Android, los riesgos de descargar archivos APK y cómo proteger su dispositivo Android de las amenazas APK.
¿Qué es un archivo APK y por qué quieres descargar uno?
-
Un archivo APK (formato de archivo de Android Package Kit) es el formato de archivo utilizado por el sistema operativo Android para la distribución e instalación de aplicaciones móviles, juegos móviles y middleware. Un archivo APK contiene todos los datos que una aplicación necesita, incluyendo todo el código del programa de software, activos, recursos, certificados y archivo de manifiesto.
-
Es posible que desee descargar un archivo APK por varias razones, tales como:
-
-
Desea usar una aplicación que no está disponible en Google Play o que se ha eliminado de ella.
-
Desea utilizar una versión más antigua o más nueva de una aplicación que no es compatible con su dispositivo o tiene errores o características que no le gustan.
-
Desea probar versiones beta o no publicadas de aplicaciones que aún no se han publicado oficialmente.
-
Desea personalizar o modificar su dispositivo con aplicaciones que requieren acceso root o permisos especiales.
-
-
Cómo descargar archivos APK en Android
-
Hay diferentes maneras de descargar archivos APK en Android. Puede descargarlos de varios sitios web que los alojan, como APK Mirror , o puede transferirlos desde su computadora utilizando un cable USB. Sin embargo, antes de que pueda instalar cualquier archivo APK en su dispositivo Android, debe habilitar fuentes desconocidas en su configuración. Esto le permite instalar aplicaciones desde fuentes distintas de Google Play. Para hacer esto:
-
-
-
Toque los tres puntos en la esquina superior derecha.
-
Toque Acceso especial.
-
Toca Instalar aplicaciones desconocidas.
-
Pulse Chrome (o cualquier navegador web que utilice) y mueva Permitir desde esta fuente a la posición On.
-
-
Una vez que haya habilitado fuentes desconocidas, puede descargar e instalar archivos APK de diferentes fuentes:
-
Desde Google Play
-
Si la aplicación que desea descargar está disponible en Google Play, simplemente puede ir a la aplicación Play Store en su dispositivo, buscar el nombre de la aplicación, y pulse Instalar. Esta es la forma más fácil y segura de descargar archivos APK en Android.
-
-
Desde APK Mirror
-
Si la aplicación que desea descargar no está disponible en Google Play o se ha eliminado de ella, puede intentar descargarlo de APK Mirror , un sitio web de buena reputación que alberga archivos APK para muchas aplicaciones populares. Para hacer esto:
-
-
Abra su navegador web y vaya a https://www.apkmirror.com/.
-
Buscar el nombre de la aplicación o navegar por categoría.
-
Seleccione la versión de la aplicación que desea descargar y toque Descargar APK.
-
Acepta cualquier ventana emergente o permisos que aparezcan.
-
Una vez completada la descarga, toque Abrir.
-
Toca Instalar y espera a que la instalación termine.
-
Toque Listo o Abierto para iniciar la aplicación.
-
-
Desde tu ordenador
-
Si tienes el archivo APK en tu computadora, puedes transferirlo a tu dispositivo Android usando un cable USB. Para hacer esto:
-
-
Conecte su dispositivo Android a su computadora usando un cable USB.
-
En tu dispositivo, toca Permitir o Aceptar para conceder acceso a tus archivos.
-
En su computadora, abra la carpeta donde tiene el archivo APK y arrástrelo y suéltelo al almacenamiento de su dispositivo.
-
En su dispositivo, utilice una aplicación de administrador de archivos (como Archivos de Google ) para localizar el archivo APK y toque en él.
-
Toca Instalar y espera a que la instalación termine.
-
Toque Listo o Abierto para iniciar la aplicación.
-
-
-
Si desea descargar un archivo APK que sea compatible con su dispositivo Android, necesita saber qué versión de Android está ejecutando. Diferentes versiones de Android tienen diferentes características, actualizaciones de seguridad y compatibilidad con aplicaciones. Para comprobar la versión de su dispositivo Android:
-
-
Ir a la configuración del dispositivo y toque Acerca del teléfono (o Acerca del dispositivo en versiones anteriores de Android).
-
Pulse Información de software (o Actualización del sistema en versiones anteriores de Android).
-
Busque el número de versión de Android y el nivel de parche de seguridad.
-
-
La última versión de Android a partir de junio de 2023 es Android 12 , que tiene nuevas características como el diseño de Material You, panel de privacidad, hibernación de aplicaciones y más. Si tiene una versión anterior de Android, es posible que desee actualizarlo para obtener las últimas características y parches de seguridad. Para actualizar tu dispositivo Android:
-
-
Ir a la configuración del dispositivo y toque Acerca del teléfono (o Acerca del dispositivo en versiones anteriores de Android).
-
Pulse Actualización de software (o Actualización de sistema en versiones anteriores de Android).
-
Pulse Buscar actualizaciones (o Descargar e instalar en las versiones más recientes de Android).
-
Si hay una actualización disponible, toque Descargar e instalar (o Instalar ahora en versiones anteriores de Android).
-
Espere a que la actualización se descargue e instale. Su dispositivo puede reiniciarse durante el proceso.
-
-
Los riesgos de descargar archivos APK
-
Si bien la descarga de archivos APK puede ser útil para acceder a aplicaciones que no están disponibles en Google Play o el uso de diferentes versiones de aplicaciones, también viene con algunos riesgos. Los archivos APK de fuentes desconocidas o no confiables pueden contener malware, phishing, secuestro de SIM u otro código malicioso que puede dañar su dispositivo o comprometer sus datos personales. Algunas de las posibles consecuencias de descargar archivos APK de fuentes inseguras son:
-
-
-
Sus datos personales pueden estar expuestos a hackers, estafadores o ladrones de identidad que pueden acceder a sus contactos, mensajes, fotos, videos, contraseñas, cuentas bancarias, tarjetas de crédito u otra información confidencial.
-
Su número de teléfono puede ser secuestrado por estafadores de intercambio de SIM que pueden usarlo para evitar la autenticación de dos factores, acceder a sus cuentas en línea, realizar transacciones fraudulentas o hacerse pasar por usted.
-
-
Cómo proteger su dispositivo Android de las amenazas APK
-
Para evitar o mitigar los riesgos de descargar archivos APK de fuentes desconocidas o no confiables, debe seguir algunas de las mejores prácticas , como:
-
Habilitar fuentes desconocidas solo cuando sea necesario
-
Solo debes habilitar fuentes desconocidas en tu configuración cuando necesites instalar un archivo APK desde una fuente distinta de Google Play. Después de haber instalado el archivo APK, debe desactivar fuentes desconocidas de nuevo. Esto evitará que cualquier aplicación no deseada o maliciosa se instale en su dispositivo sin su permiso.
-
Usar una aplicación de administrador de archivos
-
Debes usar una aplicación de administrador de archivos (como Archivos de Google ) para localizar y administrar los archivos APK en tu dispositivo. Una aplicación de administrador de archivos puede ayudarlo a encontrar los archivos APK que ha descargado o transferido desde su computadora, eliminar cualquier archivo APK no deseado o sospechoso y organizar sus archivos por nombre, tamaño, fecha o tipo.
-
Buscar virus
-
Debe escanear cualquier archivo APK que descargue o instale con una aplicación antivirus de buena reputación (como Avast Mobile Security ) antes de abrirlo. Una aplicación antivirus puede detectar y eliminar cualquier malware o código malicioso que pueda estar oculto en el archivo APK. Una aplicación antivirus también puede proteger su dispositivo de otras amenazas, como phishing, spyware, ransomware, etc.
-
Compruebe los permisos de la aplicación
-
-
Leer los comentarios y valoraciones
-
Deberías leer las reseñas y valoraciones de cualquier archivo APK que descargues o instales desde un sitio web que los aloja, como APK Mirror . Las reseñas y valoraciones pueden darte una idea de la calidad, el rendimiento y la fiabilidad de la aplicación. También pueden alertar sobre cualquier problema, problema o queja que otros usuarios hayan experimentado con la aplicación. Debes evitar descargar o instalar cualquier archivo APK que tenga calificaciones bajas, comentarios negativos o ninguna retroalimentación en absoluto.
-
Conclusión
-
Descargar e instalar archivos APK en tu dispositivo Android puede ser una forma útil de acceder a aplicaciones que no están disponibles en Google Play o utilizar diferentes versiones de aplicaciones. Sin embargo, también viene con algunos riesgos que pueden dañar su dispositivo o comprometer sus datos personales. Para descargar e instalar archivos APK de forma segura, debe seguir algunas de las mejores prácticas , como habilitar fuentes desconocidas solo cuando sea necesario, usar una aplicación de administrador de archivos, buscar virus, verificar los permisos de la aplicación y leer las revisiones y calificaciones. Al hacerlo, puede disfrutar de los beneficios de los archivos APK sin exponerse a peligros innecesarios.
-
Preguntas frecuentes
-
¿Qué es android_6_8_9_10.apk?
-
Android_6_8_9_10.apk es un archivo APK que contiene una aplicación que es compatible con dispositivos Android que ejecutan las versiones 6, 8, 9 o 10 del sistema operativo Android. El nombre y la funcionalidad de la aplicación pueden variar dependiendo del origen del archivo APK.
-
¿Cómo puedo descargar android_6_8_10.apk?
-
Puede descargar android_6_8_9_10.apk desde varios sitios web que alojan archivos APK, como APK Mirror , o puede transferirlo desde su ordenador utilizando un cable USB. Sin embargo, antes de que pueda instalarlo en su dispositivo Android, debe habilitar fuentes desconocidas en su configuración.
-
¿Cómo puedo instalar android_6_8_9_10.apk?
-
-
¿Es android_6_8_9_10.apk seguro?
-
Android_6_8_9_10.apk puede o no ser seguro dependiendo de la fuente del archivo APK. Los archivos APK de fuentes desconocidas o no confiables pueden contener malware o código malicioso que puede dañar su dispositivo o comprometer sus datos personales. Solo debe descargar e instalar archivos APK de fuentes confiables y confiables, como Google Play o APK Mirror . También debe escanear cualquier archivo APK con una aplicación antivirus antes de abrirlo.
-
¿Cómo puedo actualizar android_6_8_10.apk?
-
Si hay una versión más reciente de android_6_8_9_10.apk disponible, puede actualizarlo descargándolo e instalándolo desde la misma fuente que antes. Es posible que tenga que desinstalar la versión anterior de la aplicación antes de instalar la nueva. Alternativamente, puedes actualizar tu dispositivo Android a una versión más nueva de Android que admita la última versión de la aplicación.
64aa2da5cf
-
-
\ No newline at end of file
diff --git a/spaces/Big-Web/MMSD/env/Lib/site-packages/pip/_vendor/colorama/tests/utils.py b/spaces/Big-Web/MMSD/env/Lib/site-packages/pip/_vendor/colorama/tests/utils.py
deleted file mode 100644
index 472fafb4403efb9673d5cc724dafd9cf764aac5b..0000000000000000000000000000000000000000
--- a/spaces/Big-Web/MMSD/env/Lib/site-packages/pip/_vendor/colorama/tests/utils.py
+++ /dev/null
@@ -1,49 +0,0 @@
-# Copyright Jonathan Hartley 2013. BSD 3-Clause license, see LICENSE file.
-from contextlib import contextmanager
-from io import StringIO
-import sys
-import os
-
-
-class StreamTTY(StringIO):
- def isatty(self):
- return True
-
-class StreamNonTTY(StringIO):
- def isatty(self):
- return False
-
-@contextmanager
-def osname(name):
- orig = os.name
- os.name = name
- yield
- os.name = orig
-
-@contextmanager
-def replace_by(stream):
- orig_stdout = sys.stdout
- orig_stderr = sys.stderr
- sys.stdout = stream
- sys.stderr = stream
- yield
- sys.stdout = orig_stdout
- sys.stderr = orig_stderr
-
-@contextmanager
-def replace_original_by(stream):
- orig_stdout = sys.__stdout__
- orig_stderr = sys.__stderr__
- sys.__stdout__ = stream
- sys.__stderr__ = stream
- yield
- sys.__stdout__ = orig_stdout
- sys.__stderr__ = orig_stderr
-
-@contextmanager
-def pycharm():
- os.environ["PYCHARM_HOSTED"] = "1"
- non_tty = StreamNonTTY()
- with replace_by(non_tty), replace_original_by(non_tty):
- yield
- del os.environ["PYCHARM_HOSTED"]
diff --git a/spaces/Big-Web/MMSD/env/Lib/site-packages/setuptools/_vendor/pyparsing/results.py b/spaces/Big-Web/MMSD/env/Lib/site-packages/setuptools/_vendor/pyparsing/results.py
deleted file mode 100644
index 00c9421d3b0362526b8f90dc01e8db73841e0b61..0000000000000000000000000000000000000000
--- a/spaces/Big-Web/MMSD/env/Lib/site-packages/setuptools/_vendor/pyparsing/results.py
+++ /dev/null
@@ -1,760 +0,0 @@
-# results.py
-from collections.abc import MutableMapping, Mapping, MutableSequence, Iterator
-import pprint
-from weakref import ref as wkref
-from typing import Tuple, Any
-
-str_type: Tuple[type, ...] = (str, bytes)
-_generator_type = type((_ for _ in ()))
-
-
-class _ParseResultsWithOffset:
- __slots__ = ["tup"]
-
- def __init__(self, p1, p2):
- self.tup = (p1, p2)
-
- def __getitem__(self, i):
- return self.tup[i]
-
- def __getstate__(self):
- return self.tup
-
- def __setstate__(self, *args):
- self.tup = args[0]
-
-
-class ParseResults:
- """Structured parse results, to provide multiple means of access to
- the parsed data:
-
- - as a list (``len(results)``)
- - by list index (``results[0], results[1]``, etc.)
- - by attribute (``results.`` - see :class:`ParserElement.set_results_name`)
-
- Example::
-
- integer = Word(nums)
- date_str = (integer.set_results_name("year") + '/'
- + integer.set_results_name("month") + '/'
- + integer.set_results_name("day"))
- # equivalent form:
- # date_str = (integer("year") + '/'
- # + integer("month") + '/'
- # + integer("day"))
-
- # parse_string returns a ParseResults object
- result = date_str.parse_string("1999/12/31")
-
- def test(s, fn=repr):
- print("{} -> {}".format(s, fn(eval(s))))
- test("list(result)")
- test("result[0]")
- test("result['month']")
- test("result.day")
- test("'month' in result")
- test("'minutes' in result")
- test("result.dump()", str)
-
- prints::
-
- list(result) -> ['1999', '/', '12', '/', '31']
- result[0] -> '1999'
- result['month'] -> '12'
- result.day -> '31'
- 'month' in result -> True
- 'minutes' in result -> False
- result.dump() -> ['1999', '/', '12', '/', '31']
- - day: '31'
- - month: '12'
- - year: '1999'
- """
-
- _null_values: Tuple[Any, ...] = (None, [], "", ())
-
- __slots__ = [
- "_name",
- "_parent",
- "_all_names",
- "_modal",
- "_toklist",
- "_tokdict",
- "__weakref__",
- ]
-
- class List(list):
- """
- Simple wrapper class to distinguish parsed list results that should be preserved
- as actual Python lists, instead of being converted to :class:`ParseResults`:
-
- LBRACK, RBRACK = map(pp.Suppress, "[]")
- element = pp.Forward()
- item = ppc.integer
- element_list = LBRACK + pp.delimited_list(element) + RBRACK
-
- # add parse actions to convert from ParseResults to actual Python collection types
- def as_python_list(t):
- return pp.ParseResults.List(t.as_list())
- element_list.add_parse_action(as_python_list)
-
- element <<= item | element_list
-
- element.run_tests('''
- 100
- [2,3,4]
- [[2, 1],3,4]
- [(2, 1),3,4]
- (2,3,4)
- ''', post_parse=lambda s, r: (r[0], type(r[0])))
-
- prints:
-
- 100
- (100, )
-
- [2,3,4]
- ([2, 3, 4], )
-
- [[2, 1],3,4]
- ([[2, 1], 3, 4], )
-
- (Used internally by :class:`Group` when `aslist=True`.)
- """
-
- def __new__(cls, contained=None):
- if contained is None:
- contained = []
-
- if not isinstance(contained, list):
- raise TypeError(
- "{} may only be constructed with a list,"
- " not {}".format(cls.__name__, type(contained).__name__)
- )
-
- return list.__new__(cls)
-
- def __new__(cls, toklist=None, name=None, **kwargs):
- if isinstance(toklist, ParseResults):
- return toklist
- self = object.__new__(cls)
- self._name = None
- self._parent = None
- self._all_names = set()
-
- if toklist is None:
- self._toklist = []
- elif isinstance(toklist, (list, _generator_type)):
- self._toklist = (
- [toklist[:]]
- if isinstance(toklist, ParseResults.List)
- else list(toklist)
- )
- else:
- self._toklist = [toklist]
- self._tokdict = dict()
- return self
-
- # Performance tuning: we construct a *lot* of these, so keep this
- # constructor as small and fast as possible
- def __init__(
- self, toklist=None, name=None, asList=True, modal=True, isinstance=isinstance
- ):
- self._modal = modal
- if name is not None and name != "":
- if isinstance(name, int):
- name = str(name)
- if not modal:
- self._all_names = {name}
- self._name = name
- if toklist not in self._null_values:
- if isinstance(toklist, (str_type, type)):
- toklist = [toklist]
- if asList:
- if isinstance(toklist, ParseResults):
- self[name] = _ParseResultsWithOffset(
- ParseResults(toklist._toklist), 0
- )
- else:
- self[name] = _ParseResultsWithOffset(
- ParseResults(toklist[0]), 0
- )
- self[name]._name = name
- else:
- try:
- self[name] = toklist[0]
- except (KeyError, TypeError, IndexError):
- if toklist is not self:
- self[name] = toklist
- else:
- self._name = name
-
- def __getitem__(self, i):
- if isinstance(i, (int, slice)):
- return self._toklist[i]
- else:
- if i not in self._all_names:
- return self._tokdict[i][-1][0]
- else:
- return ParseResults([v[0] for v in self._tokdict[i]])
-
- def __setitem__(self, k, v, isinstance=isinstance):
- if isinstance(v, _ParseResultsWithOffset):
- self._tokdict[k] = self._tokdict.get(k, list()) + [v]
- sub = v[0]
- elif isinstance(k, (int, slice)):
- self._toklist[k] = v
- sub = v
- else:
- self._tokdict[k] = self._tokdict.get(k, list()) + [
- _ParseResultsWithOffset(v, 0)
- ]
- sub = v
- if isinstance(sub, ParseResults):
- sub._parent = wkref(self)
-
- def __delitem__(self, i):
- if isinstance(i, (int, slice)):
- mylen = len(self._toklist)
- del self._toklist[i]
-
- # convert int to slice
- if isinstance(i, int):
- if i < 0:
- i += mylen
- i = slice(i, i + 1)
- # get removed indices
- removed = list(range(*i.indices(mylen)))
- removed.reverse()
- # fixup indices in token dictionary
- for name, occurrences in self._tokdict.items():
- for j in removed:
- for k, (value, position) in enumerate(occurrences):
- occurrences[k] = _ParseResultsWithOffset(
- value, position - (position > j)
- )
- else:
- del self._tokdict[i]
-
- def __contains__(self, k) -> bool:
- return k in self._tokdict
-
- def __len__(self) -> int:
- return len(self._toklist)
-
- def __bool__(self) -> bool:
- return not not (self._toklist or self._tokdict)
-
- def __iter__(self) -> Iterator:
- return iter(self._toklist)
-
- def __reversed__(self) -> Iterator:
- return iter(self._toklist[::-1])
-
- def keys(self):
- return iter(self._tokdict)
-
- def values(self):
- return (self[k] for k in self.keys())
-
- def items(self):
- return ((k, self[k]) for k in self.keys())
-
- def haskeys(self) -> bool:
- """
- Since ``keys()`` returns an iterator, this method is helpful in bypassing
- code that looks for the existence of any defined results names."""
- return bool(self._tokdict)
-
- def pop(self, *args, **kwargs):
- """
- Removes and returns item at specified index (default= ``last``).
- Supports both ``list`` and ``dict`` semantics for ``pop()``. If
- passed no argument or an integer argument, it will use ``list``
- semantics and pop tokens from the list of parsed tokens. If passed
- a non-integer argument (most likely a string), it will use ``dict``
- semantics and pop the corresponding value from any defined results
- names. A second default return value argument is supported, just as in
- ``dict.pop()``.
-
- Example::
-
- numlist = Word(nums)[...]
- print(numlist.parse_string("0 123 321")) # -> ['0', '123', '321']
-
- def remove_first(tokens):
- tokens.pop(0)
- numlist.add_parse_action(remove_first)
- print(numlist.parse_string("0 123 321")) # -> ['123', '321']
-
- label = Word(alphas)
- patt = label("LABEL") + Word(nums)[1, ...]
- print(patt.parse_string("AAB 123 321").dump())
-
- # Use pop() in a parse action to remove named result (note that corresponding value is not
- # removed from list form of results)
- def remove_LABEL(tokens):
- tokens.pop("LABEL")
- return tokens
- patt.add_parse_action(remove_LABEL)
- print(patt.parse_string("AAB 123 321").dump())
-
- prints::
-
- ['AAB', '123', '321']
- - LABEL: 'AAB'
-
- ['AAB', '123', '321']
- """
- if not args:
- args = [-1]
- for k, v in kwargs.items():
- if k == "default":
- args = (args[0], v)
- else:
- raise TypeError(
- "pop() got an unexpected keyword argument {!r}".format(k)
- )
- if isinstance(args[0], int) or len(args) == 1 or args[0] in self:
- index = args[0]
- ret = self[index]
- del self[index]
- return ret
- else:
- defaultvalue = args[1]
- return defaultvalue
-
- def get(self, key, default_value=None):
- """
- Returns named result matching the given key, or if there is no
- such name, then returns the given ``default_value`` or ``None`` if no
- ``default_value`` is specified.
-
- Similar to ``dict.get()``.
-
- Example::
-
- integer = Word(nums)
- date_str = integer("year") + '/' + integer("month") + '/' + integer("day")
-
- result = date_str.parse_string("1999/12/31")
- print(result.get("year")) # -> '1999'
- print(result.get("hour", "not specified")) # -> 'not specified'
- print(result.get("hour")) # -> None
- """
- if key in self:
- return self[key]
- else:
- return default_value
-
- def insert(self, index, ins_string):
- """
- Inserts new element at location index in the list of parsed tokens.
-
- Similar to ``list.insert()``.
-
- Example::
-
- numlist = Word(nums)[...]
- print(numlist.parse_string("0 123 321")) # -> ['0', '123', '321']
-
- # use a parse action to insert the parse location in the front of the parsed results
- def insert_locn(locn, tokens):
- tokens.insert(0, locn)
- numlist.add_parse_action(insert_locn)
- print(numlist.parse_string("0 123 321")) # -> [0, '0', '123', '321']
- """
- self._toklist.insert(index, ins_string)
- # fixup indices in token dictionary
- for name, occurrences in self._tokdict.items():
- for k, (value, position) in enumerate(occurrences):
- occurrences[k] = _ParseResultsWithOffset(
- value, position + (position > index)
- )
-
- def append(self, item):
- """
- Add single element to end of ``ParseResults`` list of elements.
-
- Example::
-
- numlist = Word(nums)[...]
- print(numlist.parse_string("0 123 321")) # -> ['0', '123', '321']
-
- # use a parse action to compute the sum of the parsed integers, and add it to the end
- def append_sum(tokens):
- tokens.append(sum(map(int, tokens)))
- numlist.add_parse_action(append_sum)
- print(numlist.parse_string("0 123 321")) # -> ['0', '123', '321', 444]
- """
- self._toklist.append(item)
-
- def extend(self, itemseq):
- """
- Add sequence of elements to end of ``ParseResults`` list of elements.
-
- Example::
-
- patt = Word(alphas)[1, ...]
-
- # use a parse action to append the reverse of the matched strings, to make a palindrome
- def make_palindrome(tokens):
- tokens.extend(reversed([t[::-1] for t in tokens]))
- return ''.join(tokens)
- patt.add_parse_action(make_palindrome)
- print(patt.parse_string("lskdj sdlkjf lksd")) # -> 'lskdjsdlkjflksddsklfjkldsjdksl'
- """
- if isinstance(itemseq, ParseResults):
- self.__iadd__(itemseq)
- else:
- self._toklist.extend(itemseq)
-
- def clear(self):
- """
- Clear all elements and results names.
- """
- del self._toklist[:]
- self._tokdict.clear()
-
- def __getattr__(self, name):
- try:
- return self[name]
- except KeyError:
- if name.startswith("__"):
- raise AttributeError(name)
- return ""
-
- def __add__(self, other) -> "ParseResults":
- ret = self.copy()
- ret += other
- return ret
-
- def __iadd__(self, other) -> "ParseResults":
- if other._tokdict:
- offset = len(self._toklist)
- addoffset = lambda a: offset if a < 0 else a + offset
- otheritems = other._tokdict.items()
- otherdictitems = [
- (k, _ParseResultsWithOffset(v[0], addoffset(v[1])))
- for k, vlist in otheritems
- for v in vlist
- ]
- for k, v in otherdictitems:
- self[k] = v
- if isinstance(v[0], ParseResults):
- v[0]._parent = wkref(self)
-
- self._toklist += other._toklist
- self._all_names |= other._all_names
- return self
-
- def __radd__(self, other) -> "ParseResults":
- if isinstance(other, int) and other == 0:
- # useful for merging many ParseResults using sum() builtin
- return self.copy()
- else:
- # this may raise a TypeError - so be it
- return other + self
-
- def __repr__(self) -> str:
- return "{}({!r}, {})".format(type(self).__name__, self._toklist, self.as_dict())
-
- def __str__(self) -> str:
- return (
- "["
- + ", ".join(
- [
- str(i) if isinstance(i, ParseResults) else repr(i)
- for i in self._toklist
- ]
- )
- + "]"
- )
-
- def _asStringList(self, sep=""):
- out = []
- for item in self._toklist:
- if out and sep:
- out.append(sep)
- if isinstance(item, ParseResults):
- out += item._asStringList()
- else:
- out.append(str(item))
- return out
-
- def as_list(self) -> list:
- """
- Returns the parse results as a nested list of matching tokens, all converted to strings.
-
- Example::
-
- patt = Word(alphas)[1, ...]
- result = patt.parse_string("sldkj lsdkj sldkj")
- # even though the result prints in string-like form, it is actually a pyparsing ParseResults
- print(type(result), result) # -> ['sldkj', 'lsdkj', 'sldkj']
-
- # Use as_list() to create an actual list
- result_list = result.as_list()
- print(type(result_list), result_list) # -> ['sldkj', 'lsdkj', 'sldkj']
- """
- return [
- res.as_list() if isinstance(res, ParseResults) else res
- for res in self._toklist
- ]
-
- def as_dict(self) -> dict:
- """
- Returns the named parse results as a nested dictionary.
-
- Example::
-
- integer = Word(nums)
- date_str = integer("year") + '/' + integer("month") + '/' + integer("day")
-
- result = date_str.parse_string('12/31/1999')
- print(type(result), repr(result)) # -> (['12', '/', '31', '/', '1999'], {'day': [('1999', 4)], 'year': [('12', 0)], 'month': [('31', 2)]})
-
- result_dict = result.as_dict()
- print(type(result_dict), repr(result_dict)) # -> {'day': '1999', 'year': '12', 'month': '31'}
-
- # even though a ParseResults supports dict-like access, sometime you just need to have a dict
- import json
- print(json.dumps(result)) # -> Exception: TypeError: ... is not JSON serializable
- print(json.dumps(result.as_dict())) # -> {"month": "31", "day": "1999", "year": "12"}
- """
-
- def to_item(obj):
- if isinstance(obj, ParseResults):
- return obj.as_dict() if obj.haskeys() else [to_item(v) for v in obj]
- else:
- return obj
-
- return dict((k, to_item(v)) for k, v in self.items())
-
- def copy(self) -> "ParseResults":
- """
- Returns a new copy of a :class:`ParseResults` object.
- """
- ret = ParseResults(self._toklist)
- ret._tokdict = self._tokdict.copy()
- ret._parent = self._parent
- ret._all_names |= self._all_names
- ret._name = self._name
- return ret
-
- def get_name(self):
- r"""
- Returns the results name for this token expression. Useful when several
- different expressions might match at a particular location.
-
- Example::
-
- integer = Word(nums)
- ssn_expr = Regex(r"\d\d\d-\d\d-\d\d\d\d")
- house_number_expr = Suppress('#') + Word(nums, alphanums)
- user_data = (Group(house_number_expr)("house_number")
- | Group(ssn_expr)("ssn")
- | Group(integer)("age"))
- user_info = user_data[1, ...]
-
- result = user_info.parse_string("22 111-22-3333 #221B")
- for item in result:
- print(item.get_name(), ':', item[0])
-
- prints::
-
- age : 22
- ssn : 111-22-3333
- house_number : 221B
- """
- if self._name:
- return self._name
- elif self._parent:
- par = self._parent()
-
- def find_in_parent(sub):
- return next(
- (
- k
- for k, vlist in par._tokdict.items()
- for v, loc in vlist
- if sub is v
- ),
- None,
- )
-
- return find_in_parent(self) if par else None
- elif (
- len(self) == 1
- and len(self._tokdict) == 1
- and next(iter(self._tokdict.values()))[0][1] in (0, -1)
- ):
- return next(iter(self._tokdict.keys()))
- else:
- return None
-
- def dump(self, indent="", full=True, include_list=True, _depth=0) -> str:
- """
- Diagnostic method for listing out the contents of
- a :class:`ParseResults`. Accepts an optional ``indent`` argument so
- that this string can be embedded in a nested display of other data.
-
- Example::
-
- integer = Word(nums)
- date_str = integer("year") + '/' + integer("month") + '/' + integer("day")
-
- result = date_str.parse_string('1999/12/31')
- print(result.dump())
-
- prints::
-
- ['1999', '/', '12', '/', '31']
- - day: '31'
- - month: '12'
- - year: '1999'
- """
- out = []
- NL = "\n"
- out.append(indent + str(self.as_list()) if include_list else "")
-
- if full:
- if self.haskeys():
- items = sorted((str(k), v) for k, v in self.items())
- for k, v in items:
- if out:
- out.append(NL)
- out.append("{}{}- {}: ".format(indent, (" " * _depth), k))
- if isinstance(v, ParseResults):
- if v:
- out.append(
- v.dump(
- indent=indent,
- full=full,
- include_list=include_list,
- _depth=_depth + 1,
- )
- )
- else:
- out.append(str(v))
- else:
- out.append(repr(v))
- if any(isinstance(vv, ParseResults) for vv in self):
- v = self
- for i, vv in enumerate(v):
- if isinstance(vv, ParseResults):
- out.append(
- "\n{}{}[{}]:\n{}{}{}".format(
- indent,
- (" " * (_depth)),
- i,
- indent,
- (" " * (_depth + 1)),
- vv.dump(
- indent=indent,
- full=full,
- include_list=include_list,
- _depth=_depth + 1,
- ),
- )
- )
- else:
- out.append(
- "\n%s%s[%d]:\n%s%s%s"
- % (
- indent,
- (" " * (_depth)),
- i,
- indent,
- (" " * (_depth + 1)),
- str(vv),
- )
- )
-
- return "".join(out)
-
- def pprint(self, *args, **kwargs):
- """
- Pretty-printer for parsed results as a list, using the
- `pprint `_ module.
- Accepts additional positional or keyword args as defined for
- `pprint.pprint `_ .
-
- Example::
-
- ident = Word(alphas, alphanums)
- num = Word(nums)
- func = Forward()
- term = ident | num | Group('(' + func + ')')
- func <<= ident + Group(Optional(delimited_list(term)))
- result = func.parse_string("fna a,b,(fnb c,d,200),100")
- result.pprint(width=40)
-
- prints::
-
- ['fna',
- ['a',
- 'b',
- ['(', 'fnb', ['c', 'd', '200'], ')'],
- '100']]
- """
- pprint.pprint(self.as_list(), *args, **kwargs)
-
- # add support for pickle protocol
- def __getstate__(self):
- return (
- self._toklist,
- (
- self._tokdict.copy(),
- self._parent is not None and self._parent() or None,
- self._all_names,
- self._name,
- ),
- )
-
- def __setstate__(self, state):
- self._toklist, (self._tokdict, par, inAccumNames, self._name) = state
- self._all_names = set(inAccumNames)
- if par is not None:
- self._parent = wkref(par)
- else:
- self._parent = None
-
- def __getnewargs__(self):
- return self._toklist, self._name
-
- def __dir__(self):
- return dir(type(self)) + list(self.keys())
-
- @classmethod
- def from_dict(cls, other, name=None) -> "ParseResults":
- """
- Helper classmethod to construct a ``ParseResults`` from a ``dict``, preserving the
- name-value relations as results names. If an optional ``name`` argument is
- given, a nested ``ParseResults`` will be returned.
- """
-
- def is_iterable(obj):
- try:
- iter(obj)
- except Exception:
- return False
- else:
- return not isinstance(obj, str_type)
-
- ret = cls([])
- for k, v in other.items():
- if isinstance(v, Mapping):
- ret += cls.from_dict(v, name=k)
- else:
- ret += cls([v], name=k, asList=is_iterable(v))
- if name is not None:
- ret = cls([ret], name=name)
- return ret
-
- asList = as_list
- asDict = as_dict
- getName = get_name
-
-
-MutableMapping.register(ParseResults)
-MutableSequence.register(ParseResults)
diff --git a/spaces/Bokanovskii/Image-to-music/README.md b/spaces/Bokanovskii/Image-to-music/README.md
deleted file mode 100644
index e8f8dc6f6e294a471ab4a8ed02a3c487e67f45fe..0000000000000000000000000000000000000000
--- a/spaces/Bokanovskii/Image-to-music/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: Image To Music
-emoji: 🔥
-colorFrom: yellow
-colorTo: green
-sdk: gradio
-sdk_version: 3.18.0
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/BucketHeadP65/confusion_matrix/README.md b/spaces/BucketHeadP65/confusion_matrix/README.md
deleted file mode 100644
index 00496ec8a3c76b4ae93f747eca3636e0cb1c1172..0000000000000000000000000000000000000000
--- a/spaces/BucketHeadP65/confusion_matrix/README.md
+++ /dev/null
@@ -1,109 +0,0 @@
----
-title: Confusion Matrix
-emoji: 📉
-colorFrom: yellow
-colorTo: green
-sdk: gradio
-sdk_version: 3.17.0
-app_file: app.py
-pinned: false
-tags:
-- evaluate
-- metric
-
-description: >-
- Compute confusion matrix to evaluate the accuracy of a classification. By definition a confusion matrix :math:C is such that :math:C_{i, j} is equal to the number of observations known to be in group :math:i and predicted to be in group :math:j.
- Thus in binary classification, the count of true negatives is :math:C_{0,0}, false negatives is :math:C_{1,0}, true positives is :math:C_{1,1} and false positives is :math:C_{0,1}.
----
-
-# Metric Card for Confusion Matrix
-
-
-## Metric Description
-
-Compute confusion matrix to evaluate the accuracy of a classification.
-By definition a confusion matrix :math:`C` is such that :math:`C_{i, j}`
-is equal to the number of observations known to be in group :math:`i` and
-predicted to be in group :math:`j`.
-
-Thus in binary classification, the count of true negatives is
-:math:`C_{0,0}`, false negatives is :math:`C_{1,0}`, true positives is
-:math:`C_{1,1}` and false positives is :math:`C_{0,1}`.
-
-
-## How to Use
-
-At minimum, this metric requires predictions and references as inputs.
-
-```python
->>> cfm_metric = evaluate.load("BucketHeadP65/confusion_matrix")
->>> results = cfm_metric.compute(references=[1, 2, 3, 2, 1, 1, 0, 2], predictions=[1, 0, 3, 2, 2, 1, 0, 3])
->>> print(results)
-{'confusion_matrix': [[1, 0, 0, 0], [0, 2, 1, 0], [1, 0, 1, 1], [0, 0, 0, 1]]}
-```
-
-
-### Inputs
-- **predictions** (`list` of `int`): Predicted labels.
-- **references** (`list` of `int`): Ground truth labels.
-- **normalize** (`str` or `None`): {`true`, `pred`, `all`}, default=None
- Normalizes confusion matrix over the true (rows), predicted (columns)
- conditions or all the population. If None, confusion matrix will not be
- normalized
-- **sample_weight** (`list` of `float`): Sample weights Defaults to None.
-- **labels** (`list` of `float`): default=None
- List of labels to index the matrix. This may be used to reorder
- or select a subset of labels.
- If ``None`` is given, those that appear at least once
- in ``y_true`` or ``y_pred`` are used in sorted order.
-
-### Output Values
-- **confusion_matrix**(`list` of `int`): Confusion matrix. Minimum possible value is 0. Maximum possible value is 1.0, or the number of examples input, if `normalize` is set to `True`.. A higher score means higher accuracy.
-Output Example(s):
-```python
-{'confusion_matrix': [[1, 0, 0, 0], [0, 2, 1, 0], [1, 0, 1, 1], [0, 0, 0, 1]]}
-
-```
-This metric outputs a dictionary, containing the confusion matrix.
-
-### Examples
->>> from sklearn.metrics import confusion_matrix
->>> y_true = [2, 0, 2, 2, 0, 1]
->>> y_pred = [0, 0, 2, 2, 0, 2]
->>> confusion_matrix(y_true, y_pred)
-array([[2, 0, 0],
- [0, 0, 1],
- [1, 0, 2]])
-
->>> y_true = ["cat", "ant", "cat", "cat", "ant", "bird"]
->>> y_pred = ["ant", "ant", "cat", "cat", "ant", "cat"]
->>> confusion_matrix(y_true, y_pred, labels=["ant", "bird", "cat"])
-array([[2, 0, 0],
- [0, 0, 1],
- [1, 0, 2]])
-
-In the binary case, we can extract true positives, etc as follows:
-
->>> tn, fp, fn, tp = confusion_matrix([0, 1, 0, 1], [1, 1, 1, 0]).ravel()
->>> (tn, fp, fn, tp)
-(0, 2, 1, 1)
-
-## Citation(s)
-```bibtex
-@article{scikit-learn,
- title={Scikit-learn: Machine Learning in {P}ython},
- author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
- and Thirion, B. and Grisel, O. and Blondel, M. and Prettenhofer, P.
- and Weiss, R. and Dubourg, V. and Vanderplas, J. and Passos, A. and
- Cournapeau, D. and Brucher, M. and Perrot, M. and Duchesnay, E.},
- journal={Journal of Machine Learning Research},
- volume={12},
- pages={2825--2830},
- year={2011}
-}
-```
-## Further References
-Wikipedia entry for the Confusion matrix
-`_
-(Wikipedia and other references may use a different
-convention for axes).
\ No newline at end of file
diff --git a/spaces/CVPR/WALT/mmdet/models/dense_heads/embedding_rpn_head.py b/spaces/CVPR/WALT/mmdet/models/dense_heads/embedding_rpn_head.py
deleted file mode 100644
index 200ce8d20c5503f98c5c21f30bb9d00437e25f34..0000000000000000000000000000000000000000
--- a/spaces/CVPR/WALT/mmdet/models/dense_heads/embedding_rpn_head.py
+++ /dev/null
@@ -1,100 +0,0 @@
-import torch
-import torch.nn as nn
-
-from mmdet.models.builder import HEADS
-from ...core import bbox_cxcywh_to_xyxy
-
-
-@HEADS.register_module()
-class EmbeddingRPNHead(nn.Module):
- """RPNHead in the `Sparse R-CNN `_ .
-
- Unlike traditional RPNHead, this module does not need FPN input, but just
- decode `init_proposal_bboxes` and expand the first dimension of
- `init_proposal_bboxes` and `init_proposal_features` to the batch_size.
-
- Args:
- num_proposals (int): Number of init_proposals. Default 100.
- proposal_feature_channel (int): Channel number of
- init_proposal_feature. Defaults to 256.
- """
-
- def __init__(self,
- num_proposals=100,
- proposal_feature_channel=256,
- **kwargs):
- super(EmbeddingRPNHead, self).__init__()
- self.num_proposals = num_proposals
- self.proposal_feature_channel = proposal_feature_channel
- self._init_layers()
-
- def _init_layers(self):
- """Initialize a sparse set of proposal boxes and proposal features."""
- self.init_proposal_bboxes = nn.Embedding(self.num_proposals, 4)
- self.init_proposal_features = nn.Embedding(
- self.num_proposals, self.proposal_feature_channel)
-
- def init_weights(self):
- """Initialize the init_proposal_bboxes as normalized.
-
- [c_x, c_y, w, h], and we initialize it to the size of the entire
- image.
- """
- nn.init.constant_(self.init_proposal_bboxes.weight[:, :2], 0.5)
- nn.init.constant_(self.init_proposal_bboxes.weight[:, 2:], 1)
-
- def _decode_init_proposals(self, imgs, img_metas):
- """Decode init_proposal_bboxes according to the size of images and
- expand dimension of init_proposal_features to batch_size.
-
- Args:
- imgs (list[Tensor]): List of FPN features.
- img_metas (list[dict]): List of meta-information of
- images. Need the img_shape to decode the init_proposals.
-
- Returns:
- Tuple(Tensor):
-
- - proposals (Tensor): Decoded proposal bboxes,
- has shape (batch_size, num_proposals, 4).
- - init_proposal_features (Tensor): Expanded proposal
- features, has shape
- (batch_size, num_proposals, proposal_feature_channel).
- - imgs_whwh (Tensor): Tensor with shape
- (batch_size, 4), the dimension means
- [img_width, img_height, img_width, img_height].
- """
- proposals = self.init_proposal_bboxes.weight.clone()
- proposals = bbox_cxcywh_to_xyxy(proposals)
- num_imgs = len(imgs[0])
- imgs_whwh = []
- for meta in img_metas:
- h, w, _ = meta['img_shape']
- imgs_whwh.append(imgs[0].new_tensor([[w, h, w, h]]))
- imgs_whwh = torch.cat(imgs_whwh, dim=0)
- imgs_whwh = imgs_whwh[:, None, :]
-
- # imgs_whwh has shape (batch_size, 1, 4)
- # The shape of proposals change from (num_proposals, 4)
- # to (batch_size ,num_proposals, 4)
- proposals = proposals * imgs_whwh
-
- init_proposal_features = self.init_proposal_features.weight.clone()
- init_proposal_features = init_proposal_features[None].expand(
- num_imgs, *init_proposal_features.size())
- return proposals, init_proposal_features, imgs_whwh
-
- def forward_dummy(self, img, img_metas):
- """Dummy forward function.
-
- Used in flops calculation.
- """
- return self._decode_init_proposals(img, img_metas)
-
- def forward_train(self, img, img_metas):
- """Forward function in training stage."""
- return self._decode_init_proposals(img, img_metas)
-
- def simple_test_rpn(self, img, img_metas):
- """Forward function in testing stage."""
- return self._decode_init_proposals(img, img_metas)
diff --git a/spaces/CVPR/WALT/mmdet/models/dense_heads/retina_sepbn_head.py b/spaces/CVPR/WALT/mmdet/models/dense_heads/retina_sepbn_head.py
deleted file mode 100644
index 6b8ce7f0104b90af4b128e0f245473a1c0219fcd..0000000000000000000000000000000000000000
--- a/spaces/CVPR/WALT/mmdet/models/dense_heads/retina_sepbn_head.py
+++ /dev/null
@@ -1,113 +0,0 @@
-import torch.nn as nn
-from mmcv.cnn import ConvModule, bias_init_with_prob, normal_init
-
-from ..builder import HEADS
-from .anchor_head import AnchorHead
-
-
-@HEADS.register_module()
-class RetinaSepBNHead(AnchorHead):
- """"RetinaHead with separate BN.
-
- In RetinaHead, conv/norm layers are shared across different FPN levels,
- while in RetinaSepBNHead, conv layers are shared across different FPN
- levels, but BN layers are separated.
- """
-
- def __init__(self,
- num_classes,
- num_ins,
- in_channels,
- stacked_convs=4,
- conv_cfg=None,
- norm_cfg=None,
- **kwargs):
- self.stacked_convs = stacked_convs
- self.conv_cfg = conv_cfg
- self.norm_cfg = norm_cfg
- self.num_ins = num_ins
- super(RetinaSepBNHead, self).__init__(num_classes, in_channels,
- **kwargs)
-
- def _init_layers(self):
- """Initialize layers of the head."""
- self.relu = nn.ReLU(inplace=True)
- self.cls_convs = nn.ModuleList()
- self.reg_convs = nn.ModuleList()
- for i in range(self.num_ins):
- cls_convs = nn.ModuleList()
- reg_convs = nn.ModuleList()
- for i in range(self.stacked_convs):
- chn = self.in_channels if i == 0 else self.feat_channels
- cls_convs.append(
- ConvModule(
- chn,
- self.feat_channels,
- 3,
- stride=1,
- padding=1,
- conv_cfg=self.conv_cfg,
- norm_cfg=self.norm_cfg))
- reg_convs.append(
- ConvModule(
- chn,
- self.feat_channels,
- 3,
- stride=1,
- padding=1,
- conv_cfg=self.conv_cfg,
- norm_cfg=self.norm_cfg))
- self.cls_convs.append(cls_convs)
- self.reg_convs.append(reg_convs)
- for i in range(self.stacked_convs):
- for j in range(1, self.num_ins):
- self.cls_convs[j][i].conv = self.cls_convs[0][i].conv
- self.reg_convs[j][i].conv = self.reg_convs[0][i].conv
- self.retina_cls = nn.Conv2d(
- self.feat_channels,
- self.num_anchors * self.cls_out_channels,
- 3,
- padding=1)
- self.retina_reg = nn.Conv2d(
- self.feat_channels, self.num_anchors * 4, 3, padding=1)
-
- def init_weights(self):
- """Initialize weights of the head."""
- for m in self.cls_convs[0]:
- normal_init(m.conv, std=0.01)
- for m in self.reg_convs[0]:
- normal_init(m.conv, std=0.01)
- bias_cls = bias_init_with_prob(0.01)
- normal_init(self.retina_cls, std=0.01, bias=bias_cls)
- normal_init(self.retina_reg, std=0.01)
-
- def forward(self, feats):
- """Forward features from the upstream network.
-
- Args:
- feats (tuple[Tensor]): Features from the upstream network, each is
- a 4D-tensor.
-
- Returns:
- tuple: Usually a tuple of classification scores and bbox prediction
- cls_scores (list[Tensor]): Classification scores for all scale
- levels, each is a 4D-tensor, the channels number is
- num_anchors * num_classes.
- bbox_preds (list[Tensor]): Box energies / deltas for all scale
- levels, each is a 4D-tensor, the channels number is
- num_anchors * 4.
- """
- cls_scores = []
- bbox_preds = []
- for i, x in enumerate(feats):
- cls_feat = feats[i]
- reg_feat = feats[i]
- for cls_conv in self.cls_convs[i]:
- cls_feat = cls_conv(cls_feat)
- for reg_conv in self.reg_convs[i]:
- reg_feat = reg_conv(reg_feat)
- cls_score = self.retina_cls(cls_feat)
- bbox_pred = self.retina_reg(reg_feat)
- cls_scores.append(cls_score)
- bbox_preds.append(bbox_pred)
- return cls_scores, bbox_preds
diff --git a/spaces/CVPR/regionclip-demo/detectron2/data/datasets/lvis_v0_5_categories.py b/spaces/CVPR/regionclip-demo/detectron2/data/datasets/lvis_v0_5_categories.py
deleted file mode 100644
index d3dab6198da614937b08682f4c9edf52bdf1d236..0000000000000000000000000000000000000000
--- a/spaces/CVPR/regionclip-demo/detectron2/data/datasets/lvis_v0_5_categories.py
+++ /dev/null
@@ -1,13 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-# Autogen with
-# with open("lvis_v0.5_val.json", "r") as f:
-# a = json.load(f)
-# c = a["categories"]
-# for x in c:
-# del x["image_count"]
-# del x["instance_count"]
-# LVIS_CATEGORIES = repr(c) + " # noqa"
-
-# fmt: off
-LVIS_CATEGORIES = [{'frequency': 'r', 'id': 1, 'synset': 'acorn.n.01', 'synonyms': ['acorn'], 'def': 'nut from an oak tree', 'name': 'acorn'}, {'frequency': 'c', 'id': 2, 'synset': 'aerosol.n.02', 'synonyms': ['aerosol_can', 'spray_can'], 'def': 'a dispenser that holds a substance under pressure', 'name': 'aerosol_can'}, {'frequency': 'f', 'id': 3, 'synset': 'air_conditioner.n.01', 'synonyms': ['air_conditioner'], 'def': 'a machine that keeps air cool and dry', 'name': 'air_conditioner'}, {'frequency': 'f', 'id': 4, 'synset': 'airplane.n.01', 'synonyms': ['airplane', 'aeroplane'], 'def': 'an aircraft that has a fixed wing and is powered by propellers or jets', 'name': 'airplane'}, {'frequency': 'c', 'id': 5, 'synset': 'alarm_clock.n.01', 'synonyms': ['alarm_clock'], 'def': 'a clock that wakes a sleeper at some preset time', 'name': 'alarm_clock'}, {'frequency': 'c', 'id': 6, 'synset': 'alcohol.n.01', 'synonyms': ['alcohol', 'alcoholic_beverage'], 'def': 'a liquor or brew containing alcohol as the active agent', 'name': 'alcohol'}, {'frequency': 'r', 'id': 7, 'synset': 'alligator.n.02', 'synonyms': ['alligator', 'gator'], 'def': 'amphibious reptiles related to crocodiles but with shorter broader snouts', 'name': 'alligator'}, {'frequency': 'c', 'id': 8, 'synset': 'almond.n.02', 'synonyms': ['almond'], 'def': 'oval-shaped edible seed of the almond tree', 'name': 'almond'}, {'frequency': 'c', 'id': 9, 'synset': 'ambulance.n.01', 'synonyms': ['ambulance'], 'def': 'a vehicle that takes people to and from hospitals', 'name': 'ambulance'}, {'frequency': 'r', 'id': 10, 'synset': 'amplifier.n.01', 'synonyms': ['amplifier'], 'def': 'electronic equipment that increases strength of signals', 'name': 'amplifier'}, {'frequency': 'c', 'id': 11, 'synset': 'anklet.n.03', 'synonyms': ['anklet', 'ankle_bracelet'], 'def': 'an ornament worn around the ankle', 'name': 'anklet'}, {'frequency': 'f', 'id': 12, 'synset': 'antenna.n.01', 'synonyms': ['antenna', 'aerial', 'transmitting_aerial'], 'def': 'an electrical device that sends or receives radio or television signals', 'name': 'antenna'}, {'frequency': 'f', 'id': 13, 'synset': 'apple.n.01', 'synonyms': ['apple'], 'def': 'fruit with red or yellow or green skin and sweet to tart crisp whitish flesh', 'name': 'apple'}, {'frequency': 'r', 'id': 14, 'synset': 'apple_juice.n.01', 'synonyms': ['apple_juice'], 'def': 'the juice of apples', 'name': 'apple_juice'}, {'frequency': 'r', 'id': 15, 'synset': 'applesauce.n.01', 'synonyms': ['applesauce'], 'def': 'puree of stewed apples usually sweetened and spiced', 'name': 'applesauce'}, {'frequency': 'r', 'id': 16, 'synset': 'apricot.n.02', 'synonyms': ['apricot'], 'def': 'downy yellow to rosy-colored fruit resembling a small peach', 'name': 'apricot'}, {'frequency': 'f', 'id': 17, 'synset': 'apron.n.01', 'synonyms': ['apron'], 'def': 'a garment of cloth that is tied about the waist and worn to protect clothing', 'name': 'apron'}, {'frequency': 'c', 'id': 18, 'synset': 'aquarium.n.01', 'synonyms': ['aquarium', 'fish_tank'], 'def': 'a tank/pool/bowl filled with water for keeping live fish and underwater animals', 'name': 'aquarium'}, {'frequency': 'c', 'id': 19, 'synset': 'armband.n.02', 'synonyms': ['armband'], 'def': 'a band worn around the upper arm', 'name': 'armband'}, {'frequency': 'f', 'id': 20, 'synset': 'armchair.n.01', 'synonyms': ['armchair'], 'def': 'chair with a support on each side for arms', 'name': 'armchair'}, {'frequency': 'r', 'id': 21, 'synset': 'armoire.n.01', 'synonyms': ['armoire'], 'def': 'a large wardrobe or cabinet', 'name': 'armoire'}, {'frequency': 'r', 'id': 22, 'synset': 'armor.n.01', 'synonyms': ['armor', 'armour'], 'def': 'protective covering made of metal and used in combat', 'name': 'armor'}, {'frequency': 'c', 'id': 23, 'synset': 'artichoke.n.02', 'synonyms': ['artichoke'], 'def': 'a thistlelike flower head with edible fleshy leaves and heart', 'name': 'artichoke'}, {'frequency': 'f', 'id': 24, 'synset': 'ashcan.n.01', 'synonyms': ['trash_can', 'garbage_can', 'wastebin', 'dustbin', 'trash_barrel', 'trash_bin'], 'def': 'a bin that holds rubbish until it is collected', 'name': 'trash_can'}, {'frequency': 'c', 'id': 25, 'synset': 'ashtray.n.01', 'synonyms': ['ashtray'], 'def': "a receptacle for the ash from smokers' cigars or cigarettes", 'name': 'ashtray'}, {'frequency': 'c', 'id': 26, 'synset': 'asparagus.n.02', 'synonyms': ['asparagus'], 'def': 'edible young shoots of the asparagus plant', 'name': 'asparagus'}, {'frequency': 'c', 'id': 27, 'synset': 'atomizer.n.01', 'synonyms': ['atomizer', 'atomiser', 'spray', 'sprayer', 'nebulizer', 'nebuliser'], 'def': 'a dispenser that turns a liquid (such as perfume) into a fine mist', 'name': 'atomizer'}, {'frequency': 'c', 'id': 28, 'synset': 'avocado.n.01', 'synonyms': ['avocado'], 'def': 'a pear-shaped fruit with green or blackish skin and rich yellowish pulp enclosing a single large seed', 'name': 'avocado'}, {'frequency': 'c', 'id': 29, 'synset': 'award.n.02', 'synonyms': ['award', 'accolade'], 'def': 'a tangible symbol signifying approval or distinction', 'name': 'award'}, {'frequency': 'f', 'id': 30, 'synset': 'awning.n.01', 'synonyms': ['awning'], 'def': 'a canopy made of canvas to shelter people or things from rain or sun', 'name': 'awning'}, {'frequency': 'r', 'id': 31, 'synset': 'ax.n.01', 'synonyms': ['ax', 'axe'], 'def': 'an edge tool with a heavy bladed head mounted across a handle', 'name': 'ax'}, {'frequency': 'f', 'id': 32, 'synset': 'baby_buggy.n.01', 'synonyms': ['baby_buggy', 'baby_carriage', 'perambulator', 'pram', 'stroller'], 'def': 'a small vehicle with four wheels in which a baby or child is pushed around', 'name': 'baby_buggy'}, {'frequency': 'c', 'id': 33, 'synset': 'backboard.n.01', 'synonyms': ['basketball_backboard'], 'def': 'a raised vertical board with basket attached; used to play basketball', 'name': 'basketball_backboard'}, {'frequency': 'f', 'id': 34, 'synset': 'backpack.n.01', 'synonyms': ['backpack', 'knapsack', 'packsack', 'rucksack', 'haversack'], 'def': 'a bag carried by a strap on your back or shoulder', 'name': 'backpack'}, {'frequency': 'f', 'id': 35, 'synset': 'bag.n.04', 'synonyms': ['handbag', 'purse', 'pocketbook'], 'def': 'a container used for carrying money and small personal items or accessories', 'name': 'handbag'}, {'frequency': 'f', 'id': 36, 'synset': 'bag.n.06', 'synonyms': ['suitcase', 'baggage', 'luggage'], 'def': 'cases used to carry belongings when traveling', 'name': 'suitcase'}, {'frequency': 'c', 'id': 37, 'synset': 'bagel.n.01', 'synonyms': ['bagel', 'beigel'], 'def': 'glazed yeast-raised doughnut-shaped roll with hard crust', 'name': 'bagel'}, {'frequency': 'r', 'id': 38, 'synset': 'bagpipe.n.01', 'synonyms': ['bagpipe'], 'def': 'a tubular wind instrument; the player blows air into a bag and squeezes it out', 'name': 'bagpipe'}, {'frequency': 'r', 'id': 39, 'synset': 'baguet.n.01', 'synonyms': ['baguet', 'baguette'], 'def': 'narrow French stick loaf', 'name': 'baguet'}, {'frequency': 'r', 'id': 40, 'synset': 'bait.n.02', 'synonyms': ['bait', 'lure'], 'def': 'something used to lure fish or other animals into danger so they can be trapped or killed', 'name': 'bait'}, {'frequency': 'f', 'id': 41, 'synset': 'ball.n.06', 'synonyms': ['ball'], 'def': 'a spherical object used as a plaything', 'name': 'ball'}, {'frequency': 'r', 'id': 42, 'synset': 'ballet_skirt.n.01', 'synonyms': ['ballet_skirt', 'tutu'], 'def': 'very short skirt worn by ballerinas', 'name': 'ballet_skirt'}, {'frequency': 'f', 'id': 43, 'synset': 'balloon.n.01', 'synonyms': ['balloon'], 'def': 'large tough nonrigid bag filled with gas or heated air', 'name': 'balloon'}, {'frequency': 'c', 'id': 44, 'synset': 'bamboo.n.02', 'synonyms': ['bamboo'], 'def': 'woody tropical grass having hollow woody stems', 'name': 'bamboo'}, {'frequency': 'f', 'id': 45, 'synset': 'banana.n.02', 'synonyms': ['banana'], 'def': 'elongated crescent-shaped yellow fruit with soft sweet flesh', 'name': 'banana'}, {'frequency': 'r', 'id': 46, 'synset': 'band_aid.n.01', 'synonyms': ['Band_Aid'], 'def': 'trade name for an adhesive bandage to cover small cuts or blisters', 'name': 'Band_Aid'}, {'frequency': 'c', 'id': 47, 'synset': 'bandage.n.01', 'synonyms': ['bandage'], 'def': 'a piece of soft material that covers and protects an injured part of the body', 'name': 'bandage'}, {'frequency': 'c', 'id': 48, 'synset': 'bandanna.n.01', 'synonyms': ['bandanna', 'bandana'], 'def': 'large and brightly colored handkerchief; often used as a neckerchief', 'name': 'bandanna'}, {'frequency': 'r', 'id': 49, 'synset': 'banjo.n.01', 'synonyms': ['banjo'], 'def': 'a stringed instrument of the guitar family with a long neck and circular body', 'name': 'banjo'}, {'frequency': 'f', 'id': 50, 'synset': 'banner.n.01', 'synonyms': ['banner', 'streamer'], 'def': 'long strip of cloth or paper used for decoration or advertising', 'name': 'banner'}, {'frequency': 'r', 'id': 51, 'synset': 'barbell.n.01', 'synonyms': ['barbell'], 'def': 'a bar to which heavy discs are attached at each end; used in weightlifting', 'name': 'barbell'}, {'frequency': 'r', 'id': 52, 'synset': 'barge.n.01', 'synonyms': ['barge'], 'def': 'a flatbottom boat for carrying heavy loads (especially on canals)', 'name': 'barge'}, {'frequency': 'f', 'id': 53, 'synset': 'barrel.n.02', 'synonyms': ['barrel', 'cask'], 'def': 'a cylindrical container that holds liquids', 'name': 'barrel'}, {'frequency': 'c', 'id': 54, 'synset': 'barrette.n.01', 'synonyms': ['barrette'], 'def': "a pin for holding women's hair in place", 'name': 'barrette'}, {'frequency': 'c', 'id': 55, 'synset': 'barrow.n.03', 'synonyms': ['barrow', 'garden_cart', 'lawn_cart', 'wheelbarrow'], 'def': 'a cart for carrying small loads; has handles and one or more wheels', 'name': 'barrow'}, {'frequency': 'f', 'id': 56, 'synset': 'base.n.03', 'synonyms': ['baseball_base'], 'def': 'a place that the runner must touch before scoring', 'name': 'baseball_base'}, {'frequency': 'f', 'id': 57, 'synset': 'baseball.n.02', 'synonyms': ['baseball'], 'def': 'a ball used in playing baseball', 'name': 'baseball'}, {'frequency': 'f', 'id': 58, 'synset': 'baseball_bat.n.01', 'synonyms': ['baseball_bat'], 'def': 'an implement used in baseball by the batter', 'name': 'baseball_bat'}, {'frequency': 'f', 'id': 59, 'synset': 'baseball_cap.n.01', 'synonyms': ['baseball_cap', 'jockey_cap', 'golf_cap'], 'def': 'a cap with a bill', 'name': 'baseball_cap'}, {'frequency': 'f', 'id': 60, 'synset': 'baseball_glove.n.01', 'synonyms': ['baseball_glove', 'baseball_mitt'], 'def': 'the handwear used by fielders in playing baseball', 'name': 'baseball_glove'}, {'frequency': 'f', 'id': 61, 'synset': 'basket.n.01', 'synonyms': ['basket', 'handbasket'], 'def': 'a container that is usually woven and has handles', 'name': 'basket'}, {'frequency': 'c', 'id': 62, 'synset': 'basket.n.03', 'synonyms': ['basketball_hoop'], 'def': 'metal hoop supporting a net through which players try to throw the basketball', 'name': 'basketball_hoop'}, {'frequency': 'c', 'id': 63, 'synset': 'basketball.n.02', 'synonyms': ['basketball'], 'def': 'an inflated ball used in playing basketball', 'name': 'basketball'}, {'frequency': 'r', 'id': 64, 'synset': 'bass_horn.n.01', 'synonyms': ['bass_horn', 'sousaphone', 'tuba'], 'def': 'the lowest brass wind instrument', 'name': 'bass_horn'}, {'frequency': 'r', 'id': 65, 'synset': 'bat.n.01', 'synonyms': ['bat_(animal)'], 'def': 'nocturnal mouselike mammal with forelimbs modified to form membranous wings', 'name': 'bat_(animal)'}, {'frequency': 'f', 'id': 66, 'synset': 'bath_mat.n.01', 'synonyms': ['bath_mat'], 'def': 'a heavy towel or mat to stand on while drying yourself after a bath', 'name': 'bath_mat'}, {'frequency': 'f', 'id': 67, 'synset': 'bath_towel.n.01', 'synonyms': ['bath_towel'], 'def': 'a large towel; to dry yourself after a bath', 'name': 'bath_towel'}, {'frequency': 'c', 'id': 68, 'synset': 'bathrobe.n.01', 'synonyms': ['bathrobe'], 'def': 'a loose-fitting robe of towelling; worn after a bath or swim', 'name': 'bathrobe'}, {'frequency': 'f', 'id': 69, 'synset': 'bathtub.n.01', 'synonyms': ['bathtub', 'bathing_tub'], 'def': 'a large open container that you fill with water and use to wash the body', 'name': 'bathtub'}, {'frequency': 'r', 'id': 70, 'synset': 'batter.n.02', 'synonyms': ['batter_(food)'], 'def': 'a liquid or semiliquid mixture, as of flour, eggs, and milk, used in cooking', 'name': 'batter_(food)'}, {'frequency': 'c', 'id': 71, 'synset': 'battery.n.02', 'synonyms': ['battery'], 'def': 'a portable device that produces electricity', 'name': 'battery'}, {'frequency': 'r', 'id': 72, 'synset': 'beach_ball.n.01', 'synonyms': ['beachball'], 'def': 'large and light ball; for play at the seaside', 'name': 'beachball'}, {'frequency': 'c', 'id': 73, 'synset': 'bead.n.01', 'synonyms': ['bead'], 'def': 'a small ball with a hole through the middle used for ornamentation, jewellery, etc.', 'name': 'bead'}, {'frequency': 'r', 'id': 74, 'synset': 'beaker.n.01', 'synonyms': ['beaker'], 'def': 'a flatbottomed jar made of glass or plastic; used for chemistry', 'name': 'beaker'}, {'frequency': 'c', 'id': 75, 'synset': 'bean_curd.n.01', 'synonyms': ['bean_curd', 'tofu'], 'def': 'cheeselike food made of curdled soybean milk', 'name': 'bean_curd'}, {'frequency': 'c', 'id': 76, 'synset': 'beanbag.n.01', 'synonyms': ['beanbag'], 'def': 'a bag filled with dried beans or similar items; used in games or to sit on', 'name': 'beanbag'}, {'frequency': 'f', 'id': 77, 'synset': 'beanie.n.01', 'synonyms': ['beanie', 'beany'], 'def': 'a small skullcap; formerly worn by schoolboys and college freshmen', 'name': 'beanie'}, {'frequency': 'f', 'id': 78, 'synset': 'bear.n.01', 'synonyms': ['bear'], 'def': 'large carnivorous or omnivorous mammals with shaggy coats and claws', 'name': 'bear'}, {'frequency': 'f', 'id': 79, 'synset': 'bed.n.01', 'synonyms': ['bed'], 'def': 'a piece of furniture that provides a place to sleep', 'name': 'bed'}, {'frequency': 'c', 'id': 80, 'synset': 'bedspread.n.01', 'synonyms': ['bedspread', 'bedcover', 'bed_covering', 'counterpane', 'spread'], 'def': 'decorative cover for a bed', 'name': 'bedspread'}, {'frequency': 'f', 'id': 81, 'synset': 'beef.n.01', 'synonyms': ['cow'], 'def': 'cattle that are reared for their meat', 'name': 'cow'}, {'frequency': 'c', 'id': 82, 'synset': 'beef.n.02', 'synonyms': ['beef_(food)', 'boeuf_(food)'], 'def': 'meat from an adult domestic bovine', 'name': 'beef_(food)'}, {'frequency': 'r', 'id': 83, 'synset': 'beeper.n.01', 'synonyms': ['beeper', 'pager'], 'def': 'an device that beeps when the person carrying it is being paged', 'name': 'beeper'}, {'frequency': 'f', 'id': 84, 'synset': 'beer_bottle.n.01', 'synonyms': ['beer_bottle'], 'def': 'a bottle that holds beer', 'name': 'beer_bottle'}, {'frequency': 'c', 'id': 85, 'synset': 'beer_can.n.01', 'synonyms': ['beer_can'], 'def': 'a can that holds beer', 'name': 'beer_can'}, {'frequency': 'r', 'id': 86, 'synset': 'beetle.n.01', 'synonyms': ['beetle'], 'def': 'insect with hard wing covers', 'name': 'beetle'}, {'frequency': 'f', 'id': 87, 'synset': 'bell.n.01', 'synonyms': ['bell'], 'def': 'a hollow device made of metal that makes a ringing sound when struck', 'name': 'bell'}, {'frequency': 'f', 'id': 88, 'synset': 'bell_pepper.n.02', 'synonyms': ['bell_pepper', 'capsicum'], 'def': 'large bell-shaped sweet pepper in green or red or yellow or orange or black varieties', 'name': 'bell_pepper'}, {'frequency': 'f', 'id': 89, 'synset': 'belt.n.02', 'synonyms': ['belt'], 'def': 'a band to tie or buckle around the body (usually at the waist)', 'name': 'belt'}, {'frequency': 'f', 'id': 90, 'synset': 'belt_buckle.n.01', 'synonyms': ['belt_buckle'], 'def': 'the buckle used to fasten a belt', 'name': 'belt_buckle'}, {'frequency': 'f', 'id': 91, 'synset': 'bench.n.01', 'synonyms': ['bench'], 'def': 'a long seat for more than one person', 'name': 'bench'}, {'frequency': 'c', 'id': 92, 'synset': 'beret.n.01', 'synonyms': ['beret'], 'def': 'a cap with no brim or bill; made of soft cloth', 'name': 'beret'}, {'frequency': 'c', 'id': 93, 'synset': 'bib.n.02', 'synonyms': ['bib'], 'def': 'a napkin tied under the chin of a child while eating', 'name': 'bib'}, {'frequency': 'r', 'id': 94, 'synset': 'bible.n.01', 'synonyms': ['Bible'], 'def': 'the sacred writings of the Christian religions', 'name': 'Bible'}, {'frequency': 'f', 'id': 95, 'synset': 'bicycle.n.01', 'synonyms': ['bicycle', 'bike_(bicycle)'], 'def': 'a wheeled vehicle that has two wheels and is moved by foot pedals', 'name': 'bicycle'}, {'frequency': 'f', 'id': 96, 'synset': 'bill.n.09', 'synonyms': ['visor', 'vizor'], 'def': 'a brim that projects to the front to shade the eyes', 'name': 'visor'}, {'frequency': 'c', 'id': 97, 'synset': 'binder.n.03', 'synonyms': ['binder', 'ring-binder'], 'def': 'holds loose papers or magazines', 'name': 'binder'}, {'frequency': 'c', 'id': 98, 'synset': 'binoculars.n.01', 'synonyms': ['binoculars', 'field_glasses', 'opera_glasses'], 'def': 'an optical instrument designed for simultaneous use by both eyes', 'name': 'binoculars'}, {'frequency': 'f', 'id': 99, 'synset': 'bird.n.01', 'synonyms': ['bird'], 'def': 'animal characterized by feathers and wings', 'name': 'bird'}, {'frequency': 'r', 'id': 100, 'synset': 'bird_feeder.n.01', 'synonyms': ['birdfeeder'], 'def': 'an outdoor device that supplies food for wild birds', 'name': 'birdfeeder'}, {'frequency': 'r', 'id': 101, 'synset': 'birdbath.n.01', 'synonyms': ['birdbath'], 'def': 'an ornamental basin (usually in a garden) for birds to bathe in', 'name': 'birdbath'}, {'frequency': 'c', 'id': 102, 'synset': 'birdcage.n.01', 'synonyms': ['birdcage'], 'def': 'a cage in which a bird can be kept', 'name': 'birdcage'}, {'frequency': 'c', 'id': 103, 'synset': 'birdhouse.n.01', 'synonyms': ['birdhouse'], 'def': 'a shelter for birds', 'name': 'birdhouse'}, {'frequency': 'f', 'id': 104, 'synset': 'birthday_cake.n.01', 'synonyms': ['birthday_cake'], 'def': 'decorated cake served at a birthday party', 'name': 'birthday_cake'}, {'frequency': 'r', 'id': 105, 'synset': 'birthday_card.n.01', 'synonyms': ['birthday_card'], 'def': 'a card expressing a birthday greeting', 'name': 'birthday_card'}, {'frequency': 'r', 'id': 106, 'synset': 'biscuit.n.01', 'synonyms': ['biscuit_(bread)'], 'def': 'small round bread leavened with baking-powder or soda', 'name': 'biscuit_(bread)'}, {'frequency': 'r', 'id': 107, 'synset': 'black_flag.n.01', 'synonyms': ['pirate_flag'], 'def': 'a flag usually bearing a white skull and crossbones on a black background', 'name': 'pirate_flag'}, {'frequency': 'c', 'id': 108, 'synset': 'black_sheep.n.02', 'synonyms': ['black_sheep'], 'def': 'sheep with a black coat', 'name': 'black_sheep'}, {'frequency': 'c', 'id': 109, 'synset': 'blackboard.n.01', 'synonyms': ['blackboard', 'chalkboard'], 'def': 'sheet of slate; for writing with chalk', 'name': 'blackboard'}, {'frequency': 'f', 'id': 110, 'synset': 'blanket.n.01', 'synonyms': ['blanket'], 'def': 'bedding that keeps a person warm in bed', 'name': 'blanket'}, {'frequency': 'c', 'id': 111, 'synset': 'blazer.n.01', 'synonyms': ['blazer', 'sport_jacket', 'sport_coat', 'sports_jacket', 'sports_coat'], 'def': 'lightweight jacket; often striped in the colors of a club or school', 'name': 'blazer'}, {'frequency': 'f', 'id': 112, 'synset': 'blender.n.01', 'synonyms': ['blender', 'liquidizer', 'liquidiser'], 'def': 'an electrically powered mixer that mix or chop or liquefy foods', 'name': 'blender'}, {'frequency': 'r', 'id': 113, 'synset': 'blimp.n.02', 'synonyms': ['blimp'], 'def': 'a small nonrigid airship used for observation or as a barrage balloon', 'name': 'blimp'}, {'frequency': 'c', 'id': 114, 'synset': 'blinker.n.01', 'synonyms': ['blinker', 'flasher'], 'def': 'a light that flashes on and off; used as a signal or to send messages', 'name': 'blinker'}, {'frequency': 'c', 'id': 115, 'synset': 'blueberry.n.02', 'synonyms': ['blueberry'], 'def': 'sweet edible dark-blue berries of blueberry plants', 'name': 'blueberry'}, {'frequency': 'r', 'id': 116, 'synset': 'boar.n.02', 'synonyms': ['boar'], 'def': 'an uncastrated male hog', 'name': 'boar'}, {'frequency': 'r', 'id': 117, 'synset': 'board.n.09', 'synonyms': ['gameboard'], 'def': 'a flat portable surface (usually rectangular) designed for board games', 'name': 'gameboard'}, {'frequency': 'f', 'id': 118, 'synset': 'boat.n.01', 'synonyms': ['boat', 'ship_(boat)'], 'def': 'a vessel for travel on water', 'name': 'boat'}, {'frequency': 'c', 'id': 119, 'synset': 'bobbin.n.01', 'synonyms': ['bobbin', 'spool', 'reel'], 'def': 'a thing around which thread/tape/film or other flexible materials can be wound', 'name': 'bobbin'}, {'frequency': 'r', 'id': 120, 'synset': 'bobby_pin.n.01', 'synonyms': ['bobby_pin', 'hairgrip'], 'def': 'a flat wire hairpin used to hold bobbed hair in place', 'name': 'bobby_pin'}, {'frequency': 'c', 'id': 121, 'synset': 'boiled_egg.n.01', 'synonyms': ['boiled_egg', 'coddled_egg'], 'def': 'egg cooked briefly in the shell in gently boiling water', 'name': 'boiled_egg'}, {'frequency': 'r', 'id': 122, 'synset': 'bolo_tie.n.01', 'synonyms': ['bolo_tie', 'bolo', 'bola_tie', 'bola'], 'def': 'a cord fastened around the neck with an ornamental clasp and worn as a necktie', 'name': 'bolo_tie'}, {'frequency': 'c', 'id': 123, 'synset': 'bolt.n.03', 'synonyms': ['deadbolt'], 'def': 'the part of a lock that is engaged or withdrawn with a key', 'name': 'deadbolt'}, {'frequency': 'f', 'id': 124, 'synset': 'bolt.n.06', 'synonyms': ['bolt'], 'def': 'a screw that screws into a nut to form a fastener', 'name': 'bolt'}, {'frequency': 'r', 'id': 125, 'synset': 'bonnet.n.01', 'synonyms': ['bonnet'], 'def': 'a hat tied under the chin', 'name': 'bonnet'}, {'frequency': 'f', 'id': 126, 'synset': 'book.n.01', 'synonyms': ['book'], 'def': 'a written work or composition that has been published', 'name': 'book'}, {'frequency': 'r', 'id': 127, 'synset': 'book_bag.n.01', 'synonyms': ['book_bag'], 'def': 'a bag in which students carry their books', 'name': 'book_bag'}, {'frequency': 'c', 'id': 128, 'synset': 'bookcase.n.01', 'synonyms': ['bookcase'], 'def': 'a piece of furniture with shelves for storing books', 'name': 'bookcase'}, {'frequency': 'c', 'id': 129, 'synset': 'booklet.n.01', 'synonyms': ['booklet', 'brochure', 'leaflet', 'pamphlet'], 'def': 'a small book usually having a paper cover', 'name': 'booklet'}, {'frequency': 'r', 'id': 130, 'synset': 'bookmark.n.01', 'synonyms': ['bookmark', 'bookmarker'], 'def': 'a marker (a piece of paper or ribbon) placed between the pages of a book', 'name': 'bookmark'}, {'frequency': 'r', 'id': 131, 'synset': 'boom.n.04', 'synonyms': ['boom_microphone', 'microphone_boom'], 'def': 'a pole carrying an overhead microphone projected over a film or tv set', 'name': 'boom_microphone'}, {'frequency': 'f', 'id': 132, 'synset': 'boot.n.01', 'synonyms': ['boot'], 'def': 'footwear that covers the whole foot and lower leg', 'name': 'boot'}, {'frequency': 'f', 'id': 133, 'synset': 'bottle.n.01', 'synonyms': ['bottle'], 'def': 'a glass or plastic vessel used for storing drinks or other liquids', 'name': 'bottle'}, {'frequency': 'c', 'id': 134, 'synset': 'bottle_opener.n.01', 'synonyms': ['bottle_opener'], 'def': 'an opener for removing caps or corks from bottles', 'name': 'bottle_opener'}, {'frequency': 'c', 'id': 135, 'synset': 'bouquet.n.01', 'synonyms': ['bouquet'], 'def': 'an arrangement of flowers that is usually given as a present', 'name': 'bouquet'}, {'frequency': 'r', 'id': 136, 'synset': 'bow.n.04', 'synonyms': ['bow_(weapon)'], 'def': 'a weapon for shooting arrows', 'name': 'bow_(weapon)'}, {'frequency': 'f', 'id': 137, 'synset': 'bow.n.08', 'synonyms': ['bow_(decorative_ribbons)'], 'def': 'a decorative interlacing of ribbons', 'name': 'bow_(decorative_ribbons)'}, {'frequency': 'f', 'id': 138, 'synset': 'bow_tie.n.01', 'synonyms': ['bow-tie', 'bowtie'], 'def': "a man's tie that ties in a bow", 'name': 'bow-tie'}, {'frequency': 'f', 'id': 139, 'synset': 'bowl.n.03', 'synonyms': ['bowl'], 'def': 'a dish that is round and open at the top for serving foods', 'name': 'bowl'}, {'frequency': 'r', 'id': 140, 'synset': 'bowl.n.08', 'synonyms': ['pipe_bowl'], 'def': 'a small round container that is open at the top for holding tobacco', 'name': 'pipe_bowl'}, {'frequency': 'c', 'id': 141, 'synset': 'bowler_hat.n.01', 'synonyms': ['bowler_hat', 'bowler', 'derby_hat', 'derby', 'plug_hat'], 'def': 'a felt hat that is round and hard with a narrow brim', 'name': 'bowler_hat'}, {'frequency': 'r', 'id': 142, 'synset': 'bowling_ball.n.01', 'synonyms': ['bowling_ball'], 'def': 'a large ball with finger holes used in the sport of bowling', 'name': 'bowling_ball'}, {'frequency': 'r', 'id': 143, 'synset': 'bowling_pin.n.01', 'synonyms': ['bowling_pin'], 'def': 'a club-shaped wooden object used in bowling', 'name': 'bowling_pin'}, {'frequency': 'r', 'id': 144, 'synset': 'boxing_glove.n.01', 'synonyms': ['boxing_glove'], 'def': 'large glove coverings the fists of a fighter worn for the sport of boxing', 'name': 'boxing_glove'}, {'frequency': 'c', 'id': 145, 'synset': 'brace.n.06', 'synonyms': ['suspenders'], 'def': 'elastic straps that hold trousers up (usually used in the plural)', 'name': 'suspenders'}, {'frequency': 'f', 'id': 146, 'synset': 'bracelet.n.02', 'synonyms': ['bracelet', 'bangle'], 'def': 'jewelry worn around the wrist for decoration', 'name': 'bracelet'}, {'frequency': 'r', 'id': 147, 'synset': 'brass.n.07', 'synonyms': ['brass_plaque'], 'def': 'a memorial made of brass', 'name': 'brass_plaque'}, {'frequency': 'c', 'id': 148, 'synset': 'brassiere.n.01', 'synonyms': ['brassiere', 'bra', 'bandeau'], 'def': 'an undergarment worn by women to support their breasts', 'name': 'brassiere'}, {'frequency': 'c', 'id': 149, 'synset': 'bread-bin.n.01', 'synonyms': ['bread-bin', 'breadbox'], 'def': 'a container used to keep bread or cake in', 'name': 'bread-bin'}, {'frequency': 'r', 'id': 150, 'synset': 'breechcloth.n.01', 'synonyms': ['breechcloth', 'breechclout', 'loincloth'], 'def': 'a garment that provides covering for the loins', 'name': 'breechcloth'}, {'frequency': 'c', 'id': 151, 'synset': 'bridal_gown.n.01', 'synonyms': ['bridal_gown', 'wedding_gown', 'wedding_dress'], 'def': 'a gown worn by the bride at a wedding', 'name': 'bridal_gown'}, {'frequency': 'c', 'id': 152, 'synset': 'briefcase.n.01', 'synonyms': ['briefcase'], 'def': 'a case with a handle; for carrying papers or files or books', 'name': 'briefcase'}, {'frequency': 'c', 'id': 153, 'synset': 'bristle_brush.n.01', 'synonyms': ['bristle_brush'], 'def': 'a brush that is made with the short stiff hairs of an animal or plant', 'name': 'bristle_brush'}, {'frequency': 'f', 'id': 154, 'synset': 'broccoli.n.01', 'synonyms': ['broccoli'], 'def': 'plant with dense clusters of tight green flower buds', 'name': 'broccoli'}, {'frequency': 'r', 'id': 155, 'synset': 'brooch.n.01', 'synonyms': ['broach'], 'def': 'a decorative pin worn by women', 'name': 'broach'}, {'frequency': 'c', 'id': 156, 'synset': 'broom.n.01', 'synonyms': ['broom'], 'def': 'bundle of straws or twigs attached to a long handle; used for cleaning', 'name': 'broom'}, {'frequency': 'c', 'id': 157, 'synset': 'brownie.n.03', 'synonyms': ['brownie'], 'def': 'square or bar of very rich chocolate cake usually with nuts', 'name': 'brownie'}, {'frequency': 'c', 'id': 158, 'synset': 'brussels_sprouts.n.01', 'synonyms': ['brussels_sprouts'], 'def': 'the small edible cabbage-like buds growing along a stalk', 'name': 'brussels_sprouts'}, {'frequency': 'r', 'id': 159, 'synset': 'bubble_gum.n.01', 'synonyms': ['bubble_gum'], 'def': 'a kind of chewing gum that can be blown into bubbles', 'name': 'bubble_gum'}, {'frequency': 'f', 'id': 160, 'synset': 'bucket.n.01', 'synonyms': ['bucket', 'pail'], 'def': 'a roughly cylindrical vessel that is open at the top', 'name': 'bucket'}, {'frequency': 'r', 'id': 161, 'synset': 'buggy.n.01', 'synonyms': ['horse_buggy'], 'def': 'a small lightweight carriage; drawn by a single horse', 'name': 'horse_buggy'}, {'frequency': 'c', 'id': 162, 'synset': 'bull.n.11', 'synonyms': ['bull'], 'def': 'mature male cow', 'name': 'bull'}, {'frequency': 'r', 'id': 163, 'synset': 'bulldog.n.01', 'synonyms': ['bulldog'], 'def': 'a thickset short-haired dog with a large head and strong undershot lower jaw', 'name': 'bulldog'}, {'frequency': 'r', 'id': 164, 'synset': 'bulldozer.n.01', 'synonyms': ['bulldozer', 'dozer'], 'def': 'large powerful tractor; a large blade in front flattens areas of ground', 'name': 'bulldozer'}, {'frequency': 'c', 'id': 165, 'synset': 'bullet_train.n.01', 'synonyms': ['bullet_train'], 'def': 'a high-speed passenger train', 'name': 'bullet_train'}, {'frequency': 'c', 'id': 166, 'synset': 'bulletin_board.n.02', 'synonyms': ['bulletin_board', 'notice_board'], 'def': 'a board that hangs on a wall; displays announcements', 'name': 'bulletin_board'}, {'frequency': 'r', 'id': 167, 'synset': 'bulletproof_vest.n.01', 'synonyms': ['bulletproof_vest'], 'def': 'a vest capable of resisting the impact of a bullet', 'name': 'bulletproof_vest'}, {'frequency': 'c', 'id': 168, 'synset': 'bullhorn.n.01', 'synonyms': ['bullhorn', 'megaphone'], 'def': 'a portable loudspeaker with built-in microphone and amplifier', 'name': 'bullhorn'}, {'frequency': 'r', 'id': 169, 'synset': 'bully_beef.n.01', 'synonyms': ['corned_beef', 'corn_beef'], 'def': 'beef cured or pickled in brine', 'name': 'corned_beef'}, {'frequency': 'f', 'id': 170, 'synset': 'bun.n.01', 'synonyms': ['bun', 'roll'], 'def': 'small rounded bread either plain or sweet', 'name': 'bun'}, {'frequency': 'c', 'id': 171, 'synset': 'bunk_bed.n.01', 'synonyms': ['bunk_bed'], 'def': 'beds built one above the other', 'name': 'bunk_bed'}, {'frequency': 'f', 'id': 172, 'synset': 'buoy.n.01', 'synonyms': ['buoy'], 'def': 'a float attached by rope to the seabed to mark channels in a harbor or underwater hazards', 'name': 'buoy'}, {'frequency': 'r', 'id': 173, 'synset': 'burrito.n.01', 'synonyms': ['burrito'], 'def': 'a flour tortilla folded around a filling', 'name': 'burrito'}, {'frequency': 'f', 'id': 174, 'synset': 'bus.n.01', 'synonyms': ['bus_(vehicle)', 'autobus', 'charabanc', 'double-decker', 'motorbus', 'motorcoach'], 'def': 'a vehicle carrying many passengers; used for public transport', 'name': 'bus_(vehicle)'}, {'frequency': 'c', 'id': 175, 'synset': 'business_card.n.01', 'synonyms': ['business_card'], 'def': "a card on which are printed the person's name and business affiliation", 'name': 'business_card'}, {'frequency': 'c', 'id': 176, 'synset': 'butcher_knife.n.01', 'synonyms': ['butcher_knife'], 'def': 'a large sharp knife for cutting or trimming meat', 'name': 'butcher_knife'}, {'frequency': 'c', 'id': 177, 'synset': 'butter.n.01', 'synonyms': ['butter'], 'def': 'an edible emulsion of fat globules made by churning milk or cream; for cooking and table use', 'name': 'butter'}, {'frequency': 'c', 'id': 178, 'synset': 'butterfly.n.01', 'synonyms': ['butterfly'], 'def': 'insect typically having a slender body with knobbed antennae and broad colorful wings', 'name': 'butterfly'}, {'frequency': 'f', 'id': 179, 'synset': 'button.n.01', 'synonyms': ['button'], 'def': 'a round fastener sewn to shirts and coats etc to fit through buttonholes', 'name': 'button'}, {'frequency': 'f', 'id': 180, 'synset': 'cab.n.03', 'synonyms': ['cab_(taxi)', 'taxi', 'taxicab'], 'def': 'a car that takes passengers where they want to go in exchange for money', 'name': 'cab_(taxi)'}, {'frequency': 'r', 'id': 181, 'synset': 'cabana.n.01', 'synonyms': ['cabana'], 'def': 'a small tent used as a dressing room beside the sea or a swimming pool', 'name': 'cabana'}, {'frequency': 'r', 'id': 182, 'synset': 'cabin_car.n.01', 'synonyms': ['cabin_car', 'caboose'], 'def': 'a car on a freight train for use of the train crew; usually the last car on the train', 'name': 'cabin_car'}, {'frequency': 'f', 'id': 183, 'synset': 'cabinet.n.01', 'synonyms': ['cabinet'], 'def': 'a piece of furniture resembling a cupboard with doors and shelves and drawers', 'name': 'cabinet'}, {'frequency': 'r', 'id': 184, 'synset': 'cabinet.n.03', 'synonyms': ['locker', 'storage_locker'], 'def': 'a storage compartment for clothes and valuables; usually it has a lock', 'name': 'locker'}, {'frequency': 'f', 'id': 185, 'synset': 'cake.n.03', 'synonyms': ['cake'], 'def': 'baked goods made from or based on a mixture of flour, sugar, eggs, and fat', 'name': 'cake'}, {'frequency': 'c', 'id': 186, 'synset': 'calculator.n.02', 'synonyms': ['calculator'], 'def': 'a small machine that is used for mathematical calculations', 'name': 'calculator'}, {'frequency': 'f', 'id': 187, 'synset': 'calendar.n.02', 'synonyms': ['calendar'], 'def': 'a list or register of events (appointments/social events/court cases, etc)', 'name': 'calendar'}, {'frequency': 'c', 'id': 188, 'synset': 'calf.n.01', 'synonyms': ['calf'], 'def': 'young of domestic cattle', 'name': 'calf'}, {'frequency': 'c', 'id': 189, 'synset': 'camcorder.n.01', 'synonyms': ['camcorder'], 'def': 'a portable television camera and videocassette recorder', 'name': 'camcorder'}, {'frequency': 'c', 'id': 190, 'synset': 'camel.n.01', 'synonyms': ['camel'], 'def': 'cud-chewing mammal used as a draft or saddle animal in desert regions', 'name': 'camel'}, {'frequency': 'f', 'id': 191, 'synset': 'camera.n.01', 'synonyms': ['camera'], 'def': 'equipment for taking photographs', 'name': 'camera'}, {'frequency': 'c', 'id': 192, 'synset': 'camera_lens.n.01', 'synonyms': ['camera_lens'], 'def': 'a lens that focuses the image in a camera', 'name': 'camera_lens'}, {'frequency': 'c', 'id': 193, 'synset': 'camper.n.02', 'synonyms': ['camper_(vehicle)', 'camping_bus', 'motor_home'], 'def': 'a recreational vehicle equipped for camping out while traveling', 'name': 'camper_(vehicle)'}, {'frequency': 'f', 'id': 194, 'synset': 'can.n.01', 'synonyms': ['can', 'tin_can'], 'def': 'airtight sealed metal container for food or drink or paint etc.', 'name': 'can'}, {'frequency': 'c', 'id': 195, 'synset': 'can_opener.n.01', 'synonyms': ['can_opener', 'tin_opener'], 'def': 'a device for cutting cans open', 'name': 'can_opener'}, {'frequency': 'r', 'id': 196, 'synset': 'candelabrum.n.01', 'synonyms': ['candelabrum', 'candelabra'], 'def': 'branched candlestick; ornamental; has several lights', 'name': 'candelabrum'}, {'frequency': 'f', 'id': 197, 'synset': 'candle.n.01', 'synonyms': ['candle', 'candlestick'], 'def': 'stick of wax with a wick in the middle', 'name': 'candle'}, {'frequency': 'f', 'id': 198, 'synset': 'candlestick.n.01', 'synonyms': ['candle_holder'], 'def': 'a holder with sockets for candles', 'name': 'candle_holder'}, {'frequency': 'r', 'id': 199, 'synset': 'candy_bar.n.01', 'synonyms': ['candy_bar'], 'def': 'a candy shaped as a bar', 'name': 'candy_bar'}, {'frequency': 'c', 'id': 200, 'synset': 'candy_cane.n.01', 'synonyms': ['candy_cane'], 'def': 'a hard candy in the shape of a rod (usually with stripes)', 'name': 'candy_cane'}, {'frequency': 'c', 'id': 201, 'synset': 'cane.n.01', 'synonyms': ['walking_cane'], 'def': 'a stick that people can lean on to help them walk', 'name': 'walking_cane'}, {'frequency': 'c', 'id': 202, 'synset': 'canister.n.02', 'synonyms': ['canister', 'cannister'], 'def': 'metal container for storing dry foods such as tea or flour', 'name': 'canister'}, {'frequency': 'r', 'id': 203, 'synset': 'cannon.n.02', 'synonyms': ['cannon'], 'def': 'heavy gun fired from a tank', 'name': 'cannon'}, {'frequency': 'c', 'id': 204, 'synset': 'canoe.n.01', 'synonyms': ['canoe'], 'def': 'small and light boat; pointed at both ends; propelled with a paddle', 'name': 'canoe'}, {'frequency': 'r', 'id': 205, 'synset': 'cantaloup.n.02', 'synonyms': ['cantaloup', 'cantaloupe'], 'def': 'the fruit of a cantaloup vine; small to medium-sized melon with yellowish flesh', 'name': 'cantaloup'}, {'frequency': 'r', 'id': 206, 'synset': 'canteen.n.01', 'synonyms': ['canteen'], 'def': 'a flask for carrying water; used by soldiers or travelers', 'name': 'canteen'}, {'frequency': 'c', 'id': 207, 'synset': 'cap.n.01', 'synonyms': ['cap_(headwear)'], 'def': 'a tight-fitting headwear', 'name': 'cap_(headwear)'}, {'frequency': 'f', 'id': 208, 'synset': 'cap.n.02', 'synonyms': ['bottle_cap', 'cap_(container_lid)'], 'def': 'a top (as for a bottle)', 'name': 'bottle_cap'}, {'frequency': 'r', 'id': 209, 'synset': 'cape.n.02', 'synonyms': ['cape'], 'def': 'a sleeveless garment like a cloak but shorter', 'name': 'cape'}, {'frequency': 'c', 'id': 210, 'synset': 'cappuccino.n.01', 'synonyms': ['cappuccino', 'coffee_cappuccino'], 'def': 'equal parts of espresso and steamed milk', 'name': 'cappuccino'}, {'frequency': 'f', 'id': 211, 'synset': 'car.n.01', 'synonyms': ['car_(automobile)', 'auto_(automobile)', 'automobile'], 'def': 'a motor vehicle with four wheels', 'name': 'car_(automobile)'}, {'frequency': 'f', 'id': 212, 'synset': 'car.n.02', 'synonyms': ['railcar_(part_of_a_train)', 'railway_car_(part_of_a_train)', 'railroad_car_(part_of_a_train)'], 'def': 'a wheeled vehicle adapted to the rails of railroad', 'name': 'railcar_(part_of_a_train)'}, {'frequency': 'r', 'id': 213, 'synset': 'car.n.04', 'synonyms': ['elevator_car'], 'def': 'where passengers ride up and down', 'name': 'elevator_car'}, {'frequency': 'r', 'id': 214, 'synset': 'car_battery.n.01', 'synonyms': ['car_battery', 'automobile_battery'], 'def': 'a battery in a motor vehicle', 'name': 'car_battery'}, {'frequency': 'c', 'id': 215, 'synset': 'card.n.02', 'synonyms': ['identity_card'], 'def': 'a card certifying the identity of the bearer', 'name': 'identity_card'}, {'frequency': 'c', 'id': 216, 'synset': 'card.n.03', 'synonyms': ['card'], 'def': 'a rectangular piece of paper used to send messages (e.g. greetings or pictures)', 'name': 'card'}, {'frequency': 'r', 'id': 217, 'synset': 'cardigan.n.01', 'synonyms': ['cardigan'], 'def': 'knitted jacket that is fastened up the front with buttons or a zipper', 'name': 'cardigan'}, {'frequency': 'r', 'id': 218, 'synset': 'cargo_ship.n.01', 'synonyms': ['cargo_ship', 'cargo_vessel'], 'def': 'a ship designed to carry cargo', 'name': 'cargo_ship'}, {'frequency': 'r', 'id': 219, 'synset': 'carnation.n.01', 'synonyms': ['carnation'], 'def': 'plant with pink to purple-red spice-scented usually double flowers', 'name': 'carnation'}, {'frequency': 'c', 'id': 220, 'synset': 'carriage.n.02', 'synonyms': ['horse_carriage'], 'def': 'a vehicle with wheels drawn by one or more horses', 'name': 'horse_carriage'}, {'frequency': 'f', 'id': 221, 'synset': 'carrot.n.01', 'synonyms': ['carrot'], 'def': 'deep orange edible root of the cultivated carrot plant', 'name': 'carrot'}, {'frequency': 'c', 'id': 222, 'synset': 'carryall.n.01', 'synonyms': ['tote_bag'], 'def': 'a capacious bag or basket', 'name': 'tote_bag'}, {'frequency': 'c', 'id': 223, 'synset': 'cart.n.01', 'synonyms': ['cart'], 'def': 'a heavy open wagon usually having two wheels and drawn by an animal', 'name': 'cart'}, {'frequency': 'c', 'id': 224, 'synset': 'carton.n.02', 'synonyms': ['carton'], 'def': 'a box made of cardboard; opens by flaps on top', 'name': 'carton'}, {'frequency': 'c', 'id': 225, 'synset': 'cash_register.n.01', 'synonyms': ['cash_register', 'register_(for_cash_transactions)'], 'def': 'a cashbox with an adding machine to register transactions', 'name': 'cash_register'}, {'frequency': 'r', 'id': 226, 'synset': 'casserole.n.01', 'synonyms': ['casserole'], 'def': 'food cooked and served in a casserole', 'name': 'casserole'}, {'frequency': 'r', 'id': 227, 'synset': 'cassette.n.01', 'synonyms': ['cassette'], 'def': 'a container that holds a magnetic tape used for recording or playing sound or video', 'name': 'cassette'}, {'frequency': 'c', 'id': 228, 'synset': 'cast.n.05', 'synonyms': ['cast', 'plaster_cast', 'plaster_bandage'], 'def': 'bandage consisting of a firm covering that immobilizes broken bones while they heal', 'name': 'cast'}, {'frequency': 'f', 'id': 229, 'synset': 'cat.n.01', 'synonyms': ['cat'], 'def': 'a domestic house cat', 'name': 'cat'}, {'frequency': 'c', 'id': 230, 'synset': 'cauliflower.n.02', 'synonyms': ['cauliflower'], 'def': 'edible compact head of white undeveloped flowers', 'name': 'cauliflower'}, {'frequency': 'r', 'id': 231, 'synset': 'caviar.n.01', 'synonyms': ['caviar', 'caviare'], 'def': "salted roe of sturgeon or other large fish; usually served as an hors d'oeuvre", 'name': 'caviar'}, {'frequency': 'c', 'id': 232, 'synset': 'cayenne.n.02', 'synonyms': ['cayenne_(spice)', 'cayenne_pepper_(spice)', 'red_pepper_(spice)'], 'def': 'ground pods and seeds of pungent red peppers of the genus Capsicum', 'name': 'cayenne_(spice)'}, {'frequency': 'c', 'id': 233, 'synset': 'cd_player.n.01', 'synonyms': ['CD_player'], 'def': 'electronic equipment for playing compact discs (CDs)', 'name': 'CD_player'}, {'frequency': 'c', 'id': 234, 'synset': 'celery.n.01', 'synonyms': ['celery'], 'def': 'widely cultivated herb with aromatic leaf stalks that are eaten raw or cooked', 'name': 'celery'}, {'frequency': 'f', 'id': 235, 'synset': 'cellular_telephone.n.01', 'synonyms': ['cellular_telephone', 'cellular_phone', 'cellphone', 'mobile_phone', 'smart_phone'], 'def': 'a hand-held mobile telephone', 'name': 'cellular_telephone'}, {'frequency': 'r', 'id': 236, 'synset': 'chain_mail.n.01', 'synonyms': ['chain_mail', 'ring_mail', 'chain_armor', 'chain_armour', 'ring_armor', 'ring_armour'], 'def': '(Middle Ages) flexible armor made of interlinked metal rings', 'name': 'chain_mail'}, {'frequency': 'f', 'id': 237, 'synset': 'chair.n.01', 'synonyms': ['chair'], 'def': 'a seat for one person, with a support for the back', 'name': 'chair'}, {'frequency': 'r', 'id': 238, 'synset': 'chaise_longue.n.01', 'synonyms': ['chaise_longue', 'chaise', 'daybed'], 'def': 'a long chair; for reclining', 'name': 'chaise_longue'}, {'frequency': 'r', 'id': 239, 'synset': 'champagne.n.01', 'synonyms': ['champagne'], 'def': 'a white sparkling wine produced in Champagne or resembling that produced there', 'name': 'champagne'}, {'frequency': 'f', 'id': 240, 'synset': 'chandelier.n.01', 'synonyms': ['chandelier'], 'def': 'branched lighting fixture; often ornate; hangs from the ceiling', 'name': 'chandelier'}, {'frequency': 'r', 'id': 241, 'synset': 'chap.n.04', 'synonyms': ['chap'], 'def': 'leather leggings without a seat; worn over trousers by cowboys to protect their legs', 'name': 'chap'}, {'frequency': 'r', 'id': 242, 'synset': 'checkbook.n.01', 'synonyms': ['checkbook', 'chequebook'], 'def': 'a book issued to holders of checking accounts', 'name': 'checkbook'}, {'frequency': 'r', 'id': 243, 'synset': 'checkerboard.n.01', 'synonyms': ['checkerboard'], 'def': 'a board having 64 squares of two alternating colors', 'name': 'checkerboard'}, {'frequency': 'c', 'id': 244, 'synset': 'cherry.n.03', 'synonyms': ['cherry'], 'def': 'a red fruit with a single hard stone', 'name': 'cherry'}, {'frequency': 'r', 'id': 245, 'synset': 'chessboard.n.01', 'synonyms': ['chessboard'], 'def': 'a checkerboard used to play chess', 'name': 'chessboard'}, {'frequency': 'r', 'id': 246, 'synset': 'chest_of_drawers.n.01', 'synonyms': ['chest_of_drawers_(furniture)', 'bureau_(furniture)', 'chest_(furniture)'], 'def': 'furniture with drawers for keeping clothes', 'name': 'chest_of_drawers_(furniture)'}, {'frequency': 'c', 'id': 247, 'synset': 'chicken.n.02', 'synonyms': ['chicken_(animal)'], 'def': 'a domestic fowl bred for flesh or eggs', 'name': 'chicken_(animal)'}, {'frequency': 'c', 'id': 248, 'synset': 'chicken_wire.n.01', 'synonyms': ['chicken_wire'], 'def': 'a galvanized wire network with a hexagonal mesh; used to build fences', 'name': 'chicken_wire'}, {'frequency': 'r', 'id': 249, 'synset': 'chickpea.n.01', 'synonyms': ['chickpea', 'garbanzo'], 'def': 'the seed of the chickpea plant; usually dried', 'name': 'chickpea'}, {'frequency': 'r', 'id': 250, 'synset': 'chihuahua.n.03', 'synonyms': ['Chihuahua'], 'def': 'an old breed of tiny short-haired dog with protruding eyes from Mexico', 'name': 'Chihuahua'}, {'frequency': 'r', 'id': 251, 'synset': 'chili.n.02', 'synonyms': ['chili_(vegetable)', 'chili_pepper_(vegetable)', 'chilli_(vegetable)', 'chilly_(vegetable)', 'chile_(vegetable)'], 'def': 'very hot and finely tapering pepper of special pungency', 'name': 'chili_(vegetable)'}, {'frequency': 'r', 'id': 252, 'synset': 'chime.n.01', 'synonyms': ['chime', 'gong'], 'def': 'an instrument consisting of a set of bells that are struck with a hammer', 'name': 'chime'}, {'frequency': 'r', 'id': 253, 'synset': 'chinaware.n.01', 'synonyms': ['chinaware'], 'def': 'dishware made of high quality porcelain', 'name': 'chinaware'}, {'frequency': 'c', 'id': 254, 'synset': 'chip.n.04', 'synonyms': ['crisp_(potato_chip)', 'potato_chip'], 'def': 'a thin crisp slice of potato fried in deep fat', 'name': 'crisp_(potato_chip)'}, {'frequency': 'r', 'id': 255, 'synset': 'chip.n.06', 'synonyms': ['poker_chip'], 'def': 'a small disk-shaped counter used to represent money when gambling', 'name': 'poker_chip'}, {'frequency': 'c', 'id': 256, 'synset': 'chocolate_bar.n.01', 'synonyms': ['chocolate_bar'], 'def': 'a bar of chocolate candy', 'name': 'chocolate_bar'}, {'frequency': 'c', 'id': 257, 'synset': 'chocolate_cake.n.01', 'synonyms': ['chocolate_cake'], 'def': 'cake containing chocolate', 'name': 'chocolate_cake'}, {'frequency': 'r', 'id': 258, 'synset': 'chocolate_milk.n.01', 'synonyms': ['chocolate_milk'], 'def': 'milk flavored with chocolate syrup', 'name': 'chocolate_milk'}, {'frequency': 'r', 'id': 259, 'synset': 'chocolate_mousse.n.01', 'synonyms': ['chocolate_mousse'], 'def': 'dessert mousse made with chocolate', 'name': 'chocolate_mousse'}, {'frequency': 'f', 'id': 260, 'synset': 'choker.n.03', 'synonyms': ['choker', 'collar', 'neckband'], 'def': 'necklace that fits tightly around the neck', 'name': 'choker'}, {'frequency': 'f', 'id': 261, 'synset': 'chopping_board.n.01', 'synonyms': ['chopping_board', 'cutting_board', 'chopping_block'], 'def': 'a wooden board where meats or vegetables can be cut', 'name': 'chopping_board'}, {'frequency': 'c', 'id': 262, 'synset': 'chopstick.n.01', 'synonyms': ['chopstick'], 'def': 'one of a pair of slender sticks used as oriental tableware to eat food with', 'name': 'chopstick'}, {'frequency': 'f', 'id': 263, 'synset': 'christmas_tree.n.05', 'synonyms': ['Christmas_tree'], 'def': 'an ornamented evergreen used as a Christmas decoration', 'name': 'Christmas_tree'}, {'frequency': 'c', 'id': 264, 'synset': 'chute.n.02', 'synonyms': ['slide'], 'def': 'sloping channel through which things can descend', 'name': 'slide'}, {'frequency': 'r', 'id': 265, 'synset': 'cider.n.01', 'synonyms': ['cider', 'cyder'], 'def': 'a beverage made from juice pressed from apples', 'name': 'cider'}, {'frequency': 'r', 'id': 266, 'synset': 'cigar_box.n.01', 'synonyms': ['cigar_box'], 'def': 'a box for holding cigars', 'name': 'cigar_box'}, {'frequency': 'c', 'id': 267, 'synset': 'cigarette.n.01', 'synonyms': ['cigarette'], 'def': 'finely ground tobacco wrapped in paper; for smoking', 'name': 'cigarette'}, {'frequency': 'c', 'id': 268, 'synset': 'cigarette_case.n.01', 'synonyms': ['cigarette_case', 'cigarette_pack'], 'def': 'a small flat case for holding cigarettes', 'name': 'cigarette_case'}, {'frequency': 'f', 'id': 269, 'synset': 'cistern.n.02', 'synonyms': ['cistern', 'water_tank'], 'def': 'a tank that holds the water used to flush a toilet', 'name': 'cistern'}, {'frequency': 'r', 'id': 270, 'synset': 'clarinet.n.01', 'synonyms': ['clarinet'], 'def': 'a single-reed instrument with a straight tube', 'name': 'clarinet'}, {'frequency': 'r', 'id': 271, 'synset': 'clasp.n.01', 'synonyms': ['clasp'], 'def': 'a fastener (as a buckle or hook) that is used to hold two things together', 'name': 'clasp'}, {'frequency': 'c', 'id': 272, 'synset': 'cleansing_agent.n.01', 'synonyms': ['cleansing_agent', 'cleanser', 'cleaner'], 'def': 'a preparation used in cleaning something', 'name': 'cleansing_agent'}, {'frequency': 'r', 'id': 273, 'synset': 'clementine.n.01', 'synonyms': ['clementine'], 'def': 'a variety of mandarin orange', 'name': 'clementine'}, {'frequency': 'c', 'id': 274, 'synset': 'clip.n.03', 'synonyms': ['clip'], 'def': 'any of various small fasteners used to hold loose articles together', 'name': 'clip'}, {'frequency': 'c', 'id': 275, 'synset': 'clipboard.n.01', 'synonyms': ['clipboard'], 'def': 'a small writing board with a clip at the top for holding papers', 'name': 'clipboard'}, {'frequency': 'f', 'id': 276, 'synset': 'clock.n.01', 'synonyms': ['clock', 'timepiece', 'timekeeper'], 'def': 'a timepiece that shows the time of day', 'name': 'clock'}, {'frequency': 'f', 'id': 277, 'synset': 'clock_tower.n.01', 'synonyms': ['clock_tower'], 'def': 'a tower with a large clock visible high up on an outside face', 'name': 'clock_tower'}, {'frequency': 'c', 'id': 278, 'synset': 'clothes_hamper.n.01', 'synonyms': ['clothes_hamper', 'laundry_basket', 'clothes_basket'], 'def': 'a hamper that holds dirty clothes to be washed or wet clothes to be dried', 'name': 'clothes_hamper'}, {'frequency': 'c', 'id': 279, 'synset': 'clothespin.n.01', 'synonyms': ['clothespin', 'clothes_peg'], 'def': 'wood or plastic fastener; for holding clothes on a clothesline', 'name': 'clothespin'}, {'frequency': 'r', 'id': 280, 'synset': 'clutch_bag.n.01', 'synonyms': ['clutch_bag'], 'def': "a woman's strapless purse that is carried in the hand", 'name': 'clutch_bag'}, {'frequency': 'f', 'id': 281, 'synset': 'coaster.n.03', 'synonyms': ['coaster'], 'def': 'a covering (plate or mat) that protects the surface of a table', 'name': 'coaster'}, {'frequency': 'f', 'id': 282, 'synset': 'coat.n.01', 'synonyms': ['coat'], 'def': 'an outer garment that has sleeves and covers the body from shoulder down', 'name': 'coat'}, {'frequency': 'c', 'id': 283, 'synset': 'coat_hanger.n.01', 'synonyms': ['coat_hanger', 'clothes_hanger', 'dress_hanger'], 'def': "a hanger that is shaped like a person's shoulders", 'name': 'coat_hanger'}, {'frequency': 'r', 'id': 284, 'synset': 'coatrack.n.01', 'synonyms': ['coatrack', 'hatrack'], 'def': 'a rack with hooks for temporarily holding coats and hats', 'name': 'coatrack'}, {'frequency': 'c', 'id': 285, 'synset': 'cock.n.04', 'synonyms': ['cock', 'rooster'], 'def': 'adult male chicken', 'name': 'cock'}, {'frequency': 'c', 'id': 286, 'synset': 'coconut.n.02', 'synonyms': ['coconut', 'cocoanut'], 'def': 'large hard-shelled brown oval nut with a fibrous husk', 'name': 'coconut'}, {'frequency': 'r', 'id': 287, 'synset': 'coffee_filter.n.01', 'synonyms': ['coffee_filter'], 'def': 'filter (usually of paper) that passes the coffee and retains the coffee grounds', 'name': 'coffee_filter'}, {'frequency': 'f', 'id': 288, 'synset': 'coffee_maker.n.01', 'synonyms': ['coffee_maker', 'coffee_machine'], 'def': 'a kitchen appliance for brewing coffee automatically', 'name': 'coffee_maker'}, {'frequency': 'f', 'id': 289, 'synset': 'coffee_table.n.01', 'synonyms': ['coffee_table', 'cocktail_table'], 'def': 'low table where magazines can be placed and coffee or cocktails are served', 'name': 'coffee_table'}, {'frequency': 'c', 'id': 290, 'synset': 'coffeepot.n.01', 'synonyms': ['coffeepot'], 'def': 'tall pot in which coffee is brewed', 'name': 'coffeepot'}, {'frequency': 'r', 'id': 291, 'synset': 'coil.n.05', 'synonyms': ['coil'], 'def': 'tubing that is wound in a spiral', 'name': 'coil'}, {'frequency': 'c', 'id': 292, 'synset': 'coin.n.01', 'synonyms': ['coin'], 'def': 'a flat metal piece (usually a disc) used as money', 'name': 'coin'}, {'frequency': 'r', 'id': 293, 'synset': 'colander.n.01', 'synonyms': ['colander', 'cullender'], 'def': 'bowl-shaped strainer; used to wash or drain foods', 'name': 'colander'}, {'frequency': 'c', 'id': 294, 'synset': 'coleslaw.n.01', 'synonyms': ['coleslaw', 'slaw'], 'def': 'basically shredded cabbage', 'name': 'coleslaw'}, {'frequency': 'r', 'id': 295, 'synset': 'coloring_material.n.01', 'synonyms': ['coloring_material', 'colouring_material'], 'def': 'any material used for its color', 'name': 'coloring_material'}, {'frequency': 'r', 'id': 296, 'synset': 'combination_lock.n.01', 'synonyms': ['combination_lock'], 'def': 'lock that can be opened only by turning dials in a special sequence', 'name': 'combination_lock'}, {'frequency': 'c', 'id': 297, 'synset': 'comforter.n.04', 'synonyms': ['pacifier', 'teething_ring'], 'def': 'device used for an infant to suck or bite on', 'name': 'pacifier'}, {'frequency': 'r', 'id': 298, 'synset': 'comic_book.n.01', 'synonyms': ['comic_book'], 'def': 'a magazine devoted to comic strips', 'name': 'comic_book'}, {'frequency': 'f', 'id': 299, 'synset': 'computer_keyboard.n.01', 'synonyms': ['computer_keyboard', 'keyboard_(computer)'], 'def': 'a keyboard that is a data input device for computers', 'name': 'computer_keyboard'}, {'frequency': 'r', 'id': 300, 'synset': 'concrete_mixer.n.01', 'synonyms': ['concrete_mixer', 'cement_mixer'], 'def': 'a machine with a large revolving drum in which cement/concrete is mixed', 'name': 'concrete_mixer'}, {'frequency': 'f', 'id': 301, 'synset': 'cone.n.01', 'synonyms': ['cone', 'traffic_cone'], 'def': 'a cone-shaped object used to direct traffic', 'name': 'cone'}, {'frequency': 'f', 'id': 302, 'synset': 'control.n.09', 'synonyms': ['control', 'controller'], 'def': 'a mechanism that controls the operation of a machine', 'name': 'control'}, {'frequency': 'r', 'id': 303, 'synset': 'convertible.n.01', 'synonyms': ['convertible_(automobile)'], 'def': 'a car that has top that can be folded or removed', 'name': 'convertible_(automobile)'}, {'frequency': 'r', 'id': 304, 'synset': 'convertible.n.03', 'synonyms': ['sofa_bed'], 'def': 'a sofa that can be converted into a bed', 'name': 'sofa_bed'}, {'frequency': 'c', 'id': 305, 'synset': 'cookie.n.01', 'synonyms': ['cookie', 'cooky', 'biscuit_(cookie)'], 'def': "any of various small flat sweet cakes (`biscuit' is the British term)", 'name': 'cookie'}, {'frequency': 'r', 'id': 306, 'synset': 'cookie_jar.n.01', 'synonyms': ['cookie_jar', 'cooky_jar'], 'def': 'a jar in which cookies are kept (and sometimes money is hidden)', 'name': 'cookie_jar'}, {'frequency': 'r', 'id': 307, 'synset': 'cooking_utensil.n.01', 'synonyms': ['cooking_utensil'], 'def': 'a kitchen utensil made of material that does not melt easily; used for cooking', 'name': 'cooking_utensil'}, {'frequency': 'f', 'id': 308, 'synset': 'cooler.n.01', 'synonyms': ['cooler_(for_food)', 'ice_chest'], 'def': 'an insulated box for storing food often with ice', 'name': 'cooler_(for_food)'}, {'frequency': 'c', 'id': 309, 'synset': 'cork.n.04', 'synonyms': ['cork_(bottle_plug)', 'bottle_cork'], 'def': 'the plug in the mouth of a bottle (especially a wine bottle)', 'name': 'cork_(bottle_plug)'}, {'frequency': 'r', 'id': 310, 'synset': 'corkboard.n.01', 'synonyms': ['corkboard'], 'def': 'a sheet consisting of cork granules', 'name': 'corkboard'}, {'frequency': 'r', 'id': 311, 'synset': 'corkscrew.n.01', 'synonyms': ['corkscrew', 'bottle_screw'], 'def': 'a bottle opener that pulls corks', 'name': 'corkscrew'}, {'frequency': 'c', 'id': 312, 'synset': 'corn.n.03', 'synonyms': ['edible_corn', 'corn', 'maize'], 'def': 'ears of corn that can be prepared and served for human food', 'name': 'edible_corn'}, {'frequency': 'r', 'id': 313, 'synset': 'cornbread.n.01', 'synonyms': ['cornbread'], 'def': 'bread made primarily of cornmeal', 'name': 'cornbread'}, {'frequency': 'c', 'id': 314, 'synset': 'cornet.n.01', 'synonyms': ['cornet', 'horn', 'trumpet'], 'def': 'a brass musical instrument with a narrow tube and a flared bell and many valves', 'name': 'cornet'}, {'frequency': 'c', 'id': 315, 'synset': 'cornice.n.01', 'synonyms': ['cornice', 'valance', 'valance_board', 'pelmet'], 'def': 'a decorative framework to conceal curtain fixtures at the top of a window casing', 'name': 'cornice'}, {'frequency': 'r', 'id': 316, 'synset': 'cornmeal.n.01', 'synonyms': ['cornmeal'], 'def': 'coarsely ground corn', 'name': 'cornmeal'}, {'frequency': 'r', 'id': 317, 'synset': 'corset.n.01', 'synonyms': ['corset', 'girdle'], 'def': "a woman's close-fitting foundation garment", 'name': 'corset'}, {'frequency': 'r', 'id': 318, 'synset': 'cos.n.02', 'synonyms': ['romaine_lettuce'], 'def': 'lettuce with long dark-green leaves in a loosely packed elongated head', 'name': 'romaine_lettuce'}, {'frequency': 'c', 'id': 319, 'synset': 'costume.n.04', 'synonyms': ['costume'], 'def': 'the attire characteristic of a country or a time or a social class', 'name': 'costume'}, {'frequency': 'r', 'id': 320, 'synset': 'cougar.n.01', 'synonyms': ['cougar', 'puma', 'catamount', 'mountain_lion', 'panther'], 'def': 'large American feline resembling a lion', 'name': 'cougar'}, {'frequency': 'r', 'id': 321, 'synset': 'coverall.n.01', 'synonyms': ['coverall'], 'def': 'a loose-fitting protective garment that is worn over other clothing', 'name': 'coverall'}, {'frequency': 'r', 'id': 322, 'synset': 'cowbell.n.01', 'synonyms': ['cowbell'], 'def': 'a bell hung around the neck of cow so that the cow can be easily located', 'name': 'cowbell'}, {'frequency': 'f', 'id': 323, 'synset': 'cowboy_hat.n.01', 'synonyms': ['cowboy_hat', 'ten-gallon_hat'], 'def': 'a hat with a wide brim and a soft crown; worn by American ranch hands', 'name': 'cowboy_hat'}, {'frequency': 'r', 'id': 324, 'synset': 'crab.n.01', 'synonyms': ['crab_(animal)'], 'def': 'decapod having eyes on short stalks and a broad flattened shell and pincers', 'name': 'crab_(animal)'}, {'frequency': 'c', 'id': 325, 'synset': 'cracker.n.01', 'synonyms': ['cracker'], 'def': 'a thin crisp wafer', 'name': 'cracker'}, {'frequency': 'r', 'id': 326, 'synset': 'crape.n.01', 'synonyms': ['crape', 'crepe', 'French_pancake'], 'def': 'small very thin pancake', 'name': 'crape'}, {'frequency': 'f', 'id': 327, 'synset': 'crate.n.01', 'synonyms': ['crate'], 'def': 'a rugged box (usually made of wood); used for shipping', 'name': 'crate'}, {'frequency': 'r', 'id': 328, 'synset': 'crayon.n.01', 'synonyms': ['crayon', 'wax_crayon'], 'def': 'writing or drawing implement made of a colored stick of composition wax', 'name': 'crayon'}, {'frequency': 'r', 'id': 329, 'synset': 'cream_pitcher.n.01', 'synonyms': ['cream_pitcher'], 'def': 'a small pitcher for serving cream', 'name': 'cream_pitcher'}, {'frequency': 'r', 'id': 330, 'synset': 'credit_card.n.01', 'synonyms': ['credit_card', 'charge_card', 'debit_card'], 'def': 'a card, usually plastic, used to pay for goods and services', 'name': 'credit_card'}, {'frequency': 'c', 'id': 331, 'synset': 'crescent_roll.n.01', 'synonyms': ['crescent_roll', 'croissant'], 'def': 'very rich flaky crescent-shaped roll', 'name': 'crescent_roll'}, {'frequency': 'c', 'id': 332, 'synset': 'crib.n.01', 'synonyms': ['crib', 'cot'], 'def': 'baby bed with high sides made of slats', 'name': 'crib'}, {'frequency': 'c', 'id': 333, 'synset': 'crock.n.03', 'synonyms': ['crock_pot', 'earthenware_jar'], 'def': 'an earthen jar (made of baked clay)', 'name': 'crock_pot'}, {'frequency': 'f', 'id': 334, 'synset': 'crossbar.n.01', 'synonyms': ['crossbar'], 'def': 'a horizontal bar that goes across something', 'name': 'crossbar'}, {'frequency': 'r', 'id': 335, 'synset': 'crouton.n.01', 'synonyms': ['crouton'], 'def': 'a small piece of toasted or fried bread; served in soup or salads', 'name': 'crouton'}, {'frequency': 'r', 'id': 336, 'synset': 'crow.n.01', 'synonyms': ['crow'], 'def': 'black birds having a raucous call', 'name': 'crow'}, {'frequency': 'c', 'id': 337, 'synset': 'crown.n.04', 'synonyms': ['crown'], 'def': 'an ornamental jeweled headdress signifying sovereignty', 'name': 'crown'}, {'frequency': 'c', 'id': 338, 'synset': 'crucifix.n.01', 'synonyms': ['crucifix'], 'def': 'representation of the cross on which Jesus died', 'name': 'crucifix'}, {'frequency': 'c', 'id': 339, 'synset': 'cruise_ship.n.01', 'synonyms': ['cruise_ship', 'cruise_liner'], 'def': 'a passenger ship used commercially for pleasure cruises', 'name': 'cruise_ship'}, {'frequency': 'c', 'id': 340, 'synset': 'cruiser.n.01', 'synonyms': ['police_cruiser', 'patrol_car', 'police_car', 'squad_car'], 'def': 'a car in which policemen cruise the streets', 'name': 'police_cruiser'}, {'frequency': 'c', 'id': 341, 'synset': 'crumb.n.03', 'synonyms': ['crumb'], 'def': 'small piece of e.g. bread or cake', 'name': 'crumb'}, {'frequency': 'r', 'id': 342, 'synset': 'crutch.n.01', 'synonyms': ['crutch'], 'def': 'a wooden or metal staff that fits under the armpit and reaches to the ground', 'name': 'crutch'}, {'frequency': 'c', 'id': 343, 'synset': 'cub.n.03', 'synonyms': ['cub_(animal)'], 'def': 'the young of certain carnivorous mammals such as the bear or wolf or lion', 'name': 'cub_(animal)'}, {'frequency': 'r', 'id': 344, 'synset': 'cube.n.05', 'synonyms': ['cube', 'square_block'], 'def': 'a block in the (approximate) shape of a cube', 'name': 'cube'}, {'frequency': 'f', 'id': 345, 'synset': 'cucumber.n.02', 'synonyms': ['cucumber', 'cuke'], 'def': 'cylindrical green fruit with thin green rind and white flesh eaten as a vegetable', 'name': 'cucumber'}, {'frequency': 'c', 'id': 346, 'synset': 'cufflink.n.01', 'synonyms': ['cufflink'], 'def': 'jewelry consisting of linked buttons used to fasten the cuffs of a shirt', 'name': 'cufflink'}, {'frequency': 'f', 'id': 347, 'synset': 'cup.n.01', 'synonyms': ['cup'], 'def': 'a small open container usually used for drinking; usually has a handle', 'name': 'cup'}, {'frequency': 'c', 'id': 348, 'synset': 'cup.n.08', 'synonyms': ['trophy_cup'], 'def': 'a metal vessel with handles that is awarded as a trophy to a competition winner', 'name': 'trophy_cup'}, {'frequency': 'c', 'id': 349, 'synset': 'cupcake.n.01', 'synonyms': ['cupcake'], 'def': 'small cake baked in a muffin tin', 'name': 'cupcake'}, {'frequency': 'r', 'id': 350, 'synset': 'curler.n.01', 'synonyms': ['hair_curler', 'hair_roller', 'hair_crimper'], 'def': 'a cylindrical tube around which the hair is wound to curl it', 'name': 'hair_curler'}, {'frequency': 'r', 'id': 351, 'synset': 'curling_iron.n.01', 'synonyms': ['curling_iron'], 'def': 'a cylindrical home appliance that heats hair that has been curled around it', 'name': 'curling_iron'}, {'frequency': 'f', 'id': 352, 'synset': 'curtain.n.01', 'synonyms': ['curtain', 'drapery'], 'def': 'hanging cloth used as a blind (especially for a window)', 'name': 'curtain'}, {'frequency': 'f', 'id': 353, 'synset': 'cushion.n.03', 'synonyms': ['cushion'], 'def': 'a soft bag filled with air or padding such as feathers or foam rubber', 'name': 'cushion'}, {'frequency': 'r', 'id': 354, 'synset': 'custard.n.01', 'synonyms': ['custard'], 'def': 'sweetened mixture of milk and eggs baked or boiled or frozen', 'name': 'custard'}, {'frequency': 'c', 'id': 355, 'synset': 'cutter.n.06', 'synonyms': ['cutting_tool'], 'def': 'a cutting implement; a tool for cutting', 'name': 'cutting_tool'}, {'frequency': 'r', 'id': 356, 'synset': 'cylinder.n.04', 'synonyms': ['cylinder'], 'def': 'a cylindrical container', 'name': 'cylinder'}, {'frequency': 'r', 'id': 357, 'synset': 'cymbal.n.01', 'synonyms': ['cymbal'], 'def': 'a percussion instrument consisting of a concave brass disk', 'name': 'cymbal'}, {'frequency': 'r', 'id': 358, 'synset': 'dachshund.n.01', 'synonyms': ['dachshund', 'dachsie', 'badger_dog'], 'def': 'small long-bodied short-legged breed of dog having a short sleek coat and long drooping ears', 'name': 'dachshund'}, {'frequency': 'r', 'id': 359, 'synset': 'dagger.n.01', 'synonyms': ['dagger'], 'def': 'a short knife with a pointed blade used for piercing or stabbing', 'name': 'dagger'}, {'frequency': 'r', 'id': 360, 'synset': 'dartboard.n.01', 'synonyms': ['dartboard'], 'def': 'a circular board of wood or cork used as the target in the game of darts', 'name': 'dartboard'}, {'frequency': 'r', 'id': 361, 'synset': 'date.n.08', 'synonyms': ['date_(fruit)'], 'def': 'sweet edible fruit of the date palm with a single long woody seed', 'name': 'date_(fruit)'}, {'frequency': 'f', 'id': 362, 'synset': 'deck_chair.n.01', 'synonyms': ['deck_chair', 'beach_chair'], 'def': 'a folding chair for use outdoors; a wooden frame supports a length of canvas', 'name': 'deck_chair'}, {'frequency': 'c', 'id': 363, 'synset': 'deer.n.01', 'synonyms': ['deer', 'cervid'], 'def': "distinguished from Bovidae by the male's having solid deciduous antlers", 'name': 'deer'}, {'frequency': 'c', 'id': 364, 'synset': 'dental_floss.n.01', 'synonyms': ['dental_floss', 'floss'], 'def': 'a soft thread for cleaning the spaces between the teeth', 'name': 'dental_floss'}, {'frequency': 'f', 'id': 365, 'synset': 'desk.n.01', 'synonyms': ['desk'], 'def': 'a piece of furniture with a writing surface and usually drawers or other compartments', 'name': 'desk'}, {'frequency': 'r', 'id': 366, 'synset': 'detergent.n.01', 'synonyms': ['detergent'], 'def': 'a surface-active chemical widely used in industry and laundering', 'name': 'detergent'}, {'frequency': 'c', 'id': 367, 'synset': 'diaper.n.01', 'synonyms': ['diaper'], 'def': 'garment consisting of a folded cloth drawn up between the legs and fastened at the waist', 'name': 'diaper'}, {'frequency': 'r', 'id': 368, 'synset': 'diary.n.01', 'synonyms': ['diary', 'journal'], 'def': 'a daily written record of (usually personal) experiences and observations', 'name': 'diary'}, {'frequency': 'r', 'id': 369, 'synset': 'die.n.01', 'synonyms': ['die', 'dice'], 'def': 'a small cube with 1 to 6 spots on the six faces; used in gambling', 'name': 'die'}, {'frequency': 'r', 'id': 370, 'synset': 'dinghy.n.01', 'synonyms': ['dinghy', 'dory', 'rowboat'], 'def': 'a small boat of shallow draft with seats and oars with which it is propelled', 'name': 'dinghy'}, {'frequency': 'f', 'id': 371, 'synset': 'dining_table.n.01', 'synonyms': ['dining_table'], 'def': 'a table at which meals are served', 'name': 'dining_table'}, {'frequency': 'r', 'id': 372, 'synset': 'dinner_jacket.n.01', 'synonyms': ['tux', 'tuxedo'], 'def': 'semiformal evening dress for men', 'name': 'tux'}, {'frequency': 'c', 'id': 373, 'synset': 'dish.n.01', 'synonyms': ['dish'], 'def': 'a piece of dishware normally used as a container for holding or serving food', 'name': 'dish'}, {'frequency': 'c', 'id': 374, 'synset': 'dish.n.05', 'synonyms': ['dish_antenna'], 'def': 'directional antenna consisting of a parabolic reflector', 'name': 'dish_antenna'}, {'frequency': 'c', 'id': 375, 'synset': 'dishrag.n.01', 'synonyms': ['dishrag', 'dishcloth'], 'def': 'a cloth for washing dishes', 'name': 'dishrag'}, {'frequency': 'c', 'id': 376, 'synset': 'dishtowel.n.01', 'synonyms': ['dishtowel', 'tea_towel'], 'def': 'a towel for drying dishes', 'name': 'dishtowel'}, {'frequency': 'f', 'id': 377, 'synset': 'dishwasher.n.01', 'synonyms': ['dishwasher', 'dishwashing_machine'], 'def': 'a machine for washing dishes', 'name': 'dishwasher'}, {'frequency': 'r', 'id': 378, 'synset': 'dishwasher_detergent.n.01', 'synonyms': ['dishwasher_detergent', 'dishwashing_detergent', 'dishwashing_liquid'], 'def': 'a low-sudsing detergent designed for use in dishwashers', 'name': 'dishwasher_detergent'}, {'frequency': 'r', 'id': 379, 'synset': 'diskette.n.01', 'synonyms': ['diskette', 'floppy', 'floppy_disk'], 'def': 'a small plastic magnetic disk enclosed in a stiff envelope used to store data', 'name': 'diskette'}, {'frequency': 'c', 'id': 380, 'synset': 'dispenser.n.01', 'synonyms': ['dispenser'], 'def': 'a container so designed that the contents can be used in prescribed amounts', 'name': 'dispenser'}, {'frequency': 'c', 'id': 381, 'synset': 'dixie_cup.n.01', 'synonyms': ['Dixie_cup', 'paper_cup'], 'def': 'a disposable cup made of paper; for holding drinks', 'name': 'Dixie_cup'}, {'frequency': 'f', 'id': 382, 'synset': 'dog.n.01', 'synonyms': ['dog'], 'def': 'a common domesticated dog', 'name': 'dog'}, {'frequency': 'f', 'id': 383, 'synset': 'dog_collar.n.01', 'synonyms': ['dog_collar'], 'def': 'a collar for a dog', 'name': 'dog_collar'}, {'frequency': 'c', 'id': 384, 'synset': 'doll.n.01', 'synonyms': ['doll'], 'def': 'a toy replica of a HUMAN (NOT AN ANIMAL)', 'name': 'doll'}, {'frequency': 'r', 'id': 385, 'synset': 'dollar.n.02', 'synonyms': ['dollar', 'dollar_bill', 'one_dollar_bill'], 'def': 'a piece of paper money worth one dollar', 'name': 'dollar'}, {'frequency': 'r', 'id': 386, 'synset': 'dolphin.n.02', 'synonyms': ['dolphin'], 'def': 'any of various small toothed whales with a beaklike snout; larger than porpoises', 'name': 'dolphin'}, {'frequency': 'c', 'id': 387, 'synset': 'domestic_ass.n.01', 'synonyms': ['domestic_ass', 'donkey'], 'def': 'domestic beast of burden descended from the African wild ass; patient but stubborn', 'name': 'domestic_ass'}, {'frequency': 'r', 'id': 388, 'synset': 'domino.n.03', 'synonyms': ['eye_mask'], 'def': 'a mask covering the upper part of the face but with holes for the eyes', 'name': 'eye_mask'}, {'frequency': 'r', 'id': 389, 'synset': 'doorbell.n.01', 'synonyms': ['doorbell', 'buzzer'], 'def': 'a button at an outer door that gives a ringing or buzzing signal when pushed', 'name': 'doorbell'}, {'frequency': 'f', 'id': 390, 'synset': 'doorknob.n.01', 'synonyms': ['doorknob', 'doorhandle'], 'def': "a knob used to open a door (often called `doorhandle' in Great Britain)", 'name': 'doorknob'}, {'frequency': 'c', 'id': 391, 'synset': 'doormat.n.02', 'synonyms': ['doormat', 'welcome_mat'], 'def': 'a mat placed outside an exterior door for wiping the shoes before entering', 'name': 'doormat'}, {'frequency': 'f', 'id': 392, 'synset': 'doughnut.n.02', 'synonyms': ['doughnut', 'donut'], 'def': 'a small ring-shaped friedcake', 'name': 'doughnut'}, {'frequency': 'r', 'id': 393, 'synset': 'dove.n.01', 'synonyms': ['dove'], 'def': 'any of numerous small pigeons', 'name': 'dove'}, {'frequency': 'r', 'id': 394, 'synset': 'dragonfly.n.01', 'synonyms': ['dragonfly'], 'def': 'slender-bodied non-stinging insect having iridescent wings that are outspread at rest', 'name': 'dragonfly'}, {'frequency': 'f', 'id': 395, 'synset': 'drawer.n.01', 'synonyms': ['drawer'], 'def': 'a boxlike container in a piece of furniture; made so as to slide in and out', 'name': 'drawer'}, {'frequency': 'c', 'id': 396, 'synset': 'drawers.n.01', 'synonyms': ['underdrawers', 'boxers', 'boxershorts'], 'def': 'underpants worn by men', 'name': 'underdrawers'}, {'frequency': 'f', 'id': 397, 'synset': 'dress.n.01', 'synonyms': ['dress', 'frock'], 'def': 'a one-piece garment for a woman; has skirt and bodice', 'name': 'dress'}, {'frequency': 'c', 'id': 398, 'synset': 'dress_hat.n.01', 'synonyms': ['dress_hat', 'high_hat', 'opera_hat', 'silk_hat', 'top_hat'], 'def': "a man's hat with a tall crown; usually covered with silk or with beaver fur", 'name': 'dress_hat'}, {'frequency': 'c', 'id': 399, 'synset': 'dress_suit.n.01', 'synonyms': ['dress_suit'], 'def': 'formalwear consisting of full evening dress for men', 'name': 'dress_suit'}, {'frequency': 'c', 'id': 400, 'synset': 'dresser.n.05', 'synonyms': ['dresser'], 'def': 'a cabinet with shelves', 'name': 'dresser'}, {'frequency': 'c', 'id': 401, 'synset': 'drill.n.01', 'synonyms': ['drill'], 'def': 'a tool with a sharp rotating point for making holes in hard materials', 'name': 'drill'}, {'frequency': 'r', 'id': 402, 'synset': 'drinking_fountain.n.01', 'synonyms': ['drinking_fountain'], 'def': 'a public fountain to provide a jet of drinking water', 'name': 'drinking_fountain'}, {'frequency': 'r', 'id': 403, 'synset': 'drone.n.04', 'synonyms': ['drone'], 'def': 'an aircraft without a pilot that is operated by remote control', 'name': 'drone'}, {'frequency': 'r', 'id': 404, 'synset': 'dropper.n.01', 'synonyms': ['dropper', 'eye_dropper'], 'def': 'pipet consisting of a small tube with a vacuum bulb at one end for drawing liquid in and releasing it a drop at a time', 'name': 'dropper'}, {'frequency': 'c', 'id': 405, 'synset': 'drum.n.01', 'synonyms': ['drum_(musical_instrument)'], 'def': 'a musical percussion instrument; usually consists of a hollow cylinder with a membrane stretched across each end', 'name': 'drum_(musical_instrument)'}, {'frequency': 'r', 'id': 406, 'synset': 'drumstick.n.02', 'synonyms': ['drumstick'], 'def': 'a stick used for playing a drum', 'name': 'drumstick'}, {'frequency': 'f', 'id': 407, 'synset': 'duck.n.01', 'synonyms': ['duck'], 'def': 'small web-footed broad-billed swimming bird', 'name': 'duck'}, {'frequency': 'r', 'id': 408, 'synset': 'duckling.n.02', 'synonyms': ['duckling'], 'def': 'young duck', 'name': 'duckling'}, {'frequency': 'c', 'id': 409, 'synset': 'duct_tape.n.01', 'synonyms': ['duct_tape'], 'def': 'a wide silvery adhesive tape', 'name': 'duct_tape'}, {'frequency': 'f', 'id': 410, 'synset': 'duffel_bag.n.01', 'synonyms': ['duffel_bag', 'duffle_bag', 'duffel', 'duffle'], 'def': 'a large cylindrical bag of heavy cloth', 'name': 'duffel_bag'}, {'frequency': 'r', 'id': 411, 'synset': 'dumbbell.n.01', 'synonyms': ['dumbbell'], 'def': 'an exercising weight with two ball-like ends connected by a short handle', 'name': 'dumbbell'}, {'frequency': 'c', 'id': 412, 'synset': 'dumpster.n.01', 'synonyms': ['dumpster'], 'def': 'a container designed to receive and transport and dump waste', 'name': 'dumpster'}, {'frequency': 'r', 'id': 413, 'synset': 'dustpan.n.02', 'synonyms': ['dustpan'], 'def': 'a short-handled receptacle into which dust can be swept', 'name': 'dustpan'}, {'frequency': 'r', 'id': 414, 'synset': 'dutch_oven.n.02', 'synonyms': ['Dutch_oven'], 'def': 'iron or earthenware cooking pot; used for stews', 'name': 'Dutch_oven'}, {'frequency': 'c', 'id': 415, 'synset': 'eagle.n.01', 'synonyms': ['eagle'], 'def': 'large birds of prey noted for their broad wings and strong soaring flight', 'name': 'eagle'}, {'frequency': 'f', 'id': 416, 'synset': 'earphone.n.01', 'synonyms': ['earphone', 'earpiece', 'headphone'], 'def': 'device for listening to audio that is held over or inserted into the ear', 'name': 'earphone'}, {'frequency': 'r', 'id': 417, 'synset': 'earplug.n.01', 'synonyms': ['earplug'], 'def': 'a soft plug that is inserted into the ear canal to block sound', 'name': 'earplug'}, {'frequency': 'f', 'id': 418, 'synset': 'earring.n.01', 'synonyms': ['earring'], 'def': 'jewelry to ornament the ear', 'name': 'earring'}, {'frequency': 'c', 'id': 419, 'synset': 'easel.n.01', 'synonyms': ['easel'], 'def': "an upright tripod for displaying something (usually an artist's canvas)", 'name': 'easel'}, {'frequency': 'r', 'id': 420, 'synset': 'eclair.n.01', 'synonyms': ['eclair'], 'def': 'oblong cream puff', 'name': 'eclair'}, {'frequency': 'r', 'id': 421, 'synset': 'eel.n.01', 'synonyms': ['eel'], 'def': 'an elongate fish with fatty flesh', 'name': 'eel'}, {'frequency': 'f', 'id': 422, 'synset': 'egg.n.02', 'synonyms': ['egg', 'eggs'], 'def': 'oval reproductive body of a fowl (especially a hen) used as food', 'name': 'egg'}, {'frequency': 'r', 'id': 423, 'synset': 'egg_roll.n.01', 'synonyms': ['egg_roll', 'spring_roll'], 'def': 'minced vegetables and meat wrapped in a pancake and fried', 'name': 'egg_roll'}, {'frequency': 'c', 'id': 424, 'synset': 'egg_yolk.n.01', 'synonyms': ['egg_yolk', 'yolk_(egg)'], 'def': 'the yellow spherical part of an egg', 'name': 'egg_yolk'}, {'frequency': 'c', 'id': 425, 'synset': 'eggbeater.n.02', 'synonyms': ['eggbeater', 'eggwhisk'], 'def': 'a mixer for beating eggs or whipping cream', 'name': 'eggbeater'}, {'frequency': 'c', 'id': 426, 'synset': 'eggplant.n.01', 'synonyms': ['eggplant', 'aubergine'], 'def': 'egg-shaped vegetable having a shiny skin typically dark purple', 'name': 'eggplant'}, {'frequency': 'r', 'id': 427, 'synset': 'electric_chair.n.01', 'synonyms': ['electric_chair'], 'def': 'a chair-shaped instrument of execution by electrocution', 'name': 'electric_chair'}, {'frequency': 'f', 'id': 428, 'synset': 'electric_refrigerator.n.01', 'synonyms': ['refrigerator'], 'def': 'a refrigerator in which the coolant is pumped around by an electric motor', 'name': 'refrigerator'}, {'frequency': 'f', 'id': 429, 'synset': 'elephant.n.01', 'synonyms': ['elephant'], 'def': 'a common elephant', 'name': 'elephant'}, {'frequency': 'r', 'id': 430, 'synset': 'elk.n.01', 'synonyms': ['elk', 'moose'], 'def': 'large northern deer with enormous flattened antlers in the male', 'name': 'elk'}, {'frequency': 'c', 'id': 431, 'synset': 'envelope.n.01', 'synonyms': ['envelope'], 'def': 'a flat (usually rectangular) container for a letter, thin package, etc.', 'name': 'envelope'}, {'frequency': 'c', 'id': 432, 'synset': 'eraser.n.01', 'synonyms': ['eraser'], 'def': 'an implement used to erase something', 'name': 'eraser'}, {'frequency': 'r', 'id': 433, 'synset': 'escargot.n.01', 'synonyms': ['escargot'], 'def': 'edible snail usually served in the shell with a sauce of melted butter and garlic', 'name': 'escargot'}, {'frequency': 'r', 'id': 434, 'synset': 'eyepatch.n.01', 'synonyms': ['eyepatch'], 'def': 'a protective cloth covering for an injured eye', 'name': 'eyepatch'}, {'frequency': 'r', 'id': 435, 'synset': 'falcon.n.01', 'synonyms': ['falcon'], 'def': 'birds of prey having long pointed powerful wings adapted for swift flight', 'name': 'falcon'}, {'frequency': 'f', 'id': 436, 'synset': 'fan.n.01', 'synonyms': ['fan'], 'def': 'a device for creating a current of air by movement of a surface or surfaces', 'name': 'fan'}, {'frequency': 'f', 'id': 437, 'synset': 'faucet.n.01', 'synonyms': ['faucet', 'spigot', 'tap'], 'def': 'a regulator for controlling the flow of a liquid from a reservoir', 'name': 'faucet'}, {'frequency': 'r', 'id': 438, 'synset': 'fedora.n.01', 'synonyms': ['fedora'], 'def': 'a hat made of felt with a creased crown', 'name': 'fedora'}, {'frequency': 'r', 'id': 439, 'synset': 'ferret.n.02', 'synonyms': ['ferret'], 'def': 'domesticated albino variety of the European polecat bred for hunting rats and rabbits', 'name': 'ferret'}, {'frequency': 'c', 'id': 440, 'synset': 'ferris_wheel.n.01', 'synonyms': ['Ferris_wheel'], 'def': 'a large wheel with suspended seats that remain upright as the wheel rotates', 'name': 'Ferris_wheel'}, {'frequency': 'r', 'id': 441, 'synset': 'ferry.n.01', 'synonyms': ['ferry', 'ferryboat'], 'def': 'a boat that transports people or vehicles across a body of water and operates on a regular schedule', 'name': 'ferry'}, {'frequency': 'r', 'id': 442, 'synset': 'fig.n.04', 'synonyms': ['fig_(fruit)'], 'def': 'fleshy sweet pear-shaped yellowish or purple fruit eaten fresh or preserved or dried', 'name': 'fig_(fruit)'}, {'frequency': 'c', 'id': 443, 'synset': 'fighter.n.02', 'synonyms': ['fighter_jet', 'fighter_aircraft', 'attack_aircraft'], 'def': 'a high-speed military or naval airplane designed to destroy enemy targets', 'name': 'fighter_jet'}, {'frequency': 'f', 'id': 444, 'synset': 'figurine.n.01', 'synonyms': ['figurine'], 'def': 'a small carved or molded figure', 'name': 'figurine'}, {'frequency': 'c', 'id': 445, 'synset': 'file.n.03', 'synonyms': ['file_cabinet', 'filing_cabinet'], 'def': 'office furniture consisting of a container for keeping papers in order', 'name': 'file_cabinet'}, {'frequency': 'r', 'id': 446, 'synset': 'file.n.04', 'synonyms': ['file_(tool)'], 'def': 'a steel hand tool with small sharp teeth on some or all of its surfaces; used for smoothing wood or metal', 'name': 'file_(tool)'}, {'frequency': 'f', 'id': 447, 'synset': 'fire_alarm.n.02', 'synonyms': ['fire_alarm', 'smoke_alarm'], 'def': 'an alarm that is tripped off by fire or smoke', 'name': 'fire_alarm'}, {'frequency': 'c', 'id': 448, 'synset': 'fire_engine.n.01', 'synonyms': ['fire_engine', 'fire_truck'], 'def': 'large trucks that carry firefighters and equipment to the site of a fire', 'name': 'fire_engine'}, {'frequency': 'c', 'id': 449, 'synset': 'fire_extinguisher.n.01', 'synonyms': ['fire_extinguisher', 'extinguisher'], 'def': 'a manually operated device for extinguishing small fires', 'name': 'fire_extinguisher'}, {'frequency': 'c', 'id': 450, 'synset': 'fire_hose.n.01', 'synonyms': ['fire_hose'], 'def': 'a large hose that carries water from a fire hydrant to the site of the fire', 'name': 'fire_hose'}, {'frequency': 'f', 'id': 451, 'synset': 'fireplace.n.01', 'synonyms': ['fireplace'], 'def': 'an open recess in a wall at the base of a chimney where a fire can be built', 'name': 'fireplace'}, {'frequency': 'f', 'id': 452, 'synset': 'fireplug.n.01', 'synonyms': ['fireplug', 'fire_hydrant', 'hydrant'], 'def': 'an upright hydrant for drawing water to use in fighting a fire', 'name': 'fireplug'}, {'frequency': 'c', 'id': 453, 'synset': 'fish.n.01', 'synonyms': ['fish'], 'def': 'any of various mostly cold-blooded aquatic vertebrates usually having scales and breathing through gills', 'name': 'fish'}, {'frequency': 'r', 'id': 454, 'synset': 'fish.n.02', 'synonyms': ['fish_(food)'], 'def': 'the flesh of fish used as food', 'name': 'fish_(food)'}, {'frequency': 'r', 'id': 455, 'synset': 'fishbowl.n.02', 'synonyms': ['fishbowl', 'goldfish_bowl'], 'def': 'a transparent bowl in which small fish are kept', 'name': 'fishbowl'}, {'frequency': 'r', 'id': 456, 'synset': 'fishing_boat.n.01', 'synonyms': ['fishing_boat', 'fishing_vessel'], 'def': 'a vessel for fishing', 'name': 'fishing_boat'}, {'frequency': 'c', 'id': 457, 'synset': 'fishing_rod.n.01', 'synonyms': ['fishing_rod', 'fishing_pole'], 'def': 'a rod that is used in fishing to extend the fishing line', 'name': 'fishing_rod'}, {'frequency': 'f', 'id': 458, 'synset': 'flag.n.01', 'synonyms': ['flag'], 'def': 'emblem usually consisting of a rectangular piece of cloth of distinctive design (do not include pole)', 'name': 'flag'}, {'frequency': 'f', 'id': 459, 'synset': 'flagpole.n.02', 'synonyms': ['flagpole', 'flagstaff'], 'def': 'a tall staff or pole on which a flag is raised', 'name': 'flagpole'}, {'frequency': 'c', 'id': 460, 'synset': 'flamingo.n.01', 'synonyms': ['flamingo'], 'def': 'large pink web-footed bird with down-bent bill', 'name': 'flamingo'}, {'frequency': 'c', 'id': 461, 'synset': 'flannel.n.01', 'synonyms': ['flannel'], 'def': 'a soft light woolen fabric; used for clothing', 'name': 'flannel'}, {'frequency': 'r', 'id': 462, 'synset': 'flash.n.10', 'synonyms': ['flash', 'flashbulb'], 'def': 'a lamp for providing momentary light to take a photograph', 'name': 'flash'}, {'frequency': 'c', 'id': 463, 'synset': 'flashlight.n.01', 'synonyms': ['flashlight', 'torch'], 'def': 'a small portable battery-powered electric lamp', 'name': 'flashlight'}, {'frequency': 'r', 'id': 464, 'synset': 'fleece.n.03', 'synonyms': ['fleece'], 'def': 'a soft bulky fabric with deep pile; used chiefly for clothing', 'name': 'fleece'}, {'frequency': 'f', 'id': 465, 'synset': 'flip-flop.n.02', 'synonyms': ['flip-flop_(sandal)'], 'def': 'a backless sandal held to the foot by a thong between two toes', 'name': 'flip-flop_(sandal)'}, {'frequency': 'c', 'id': 466, 'synset': 'flipper.n.01', 'synonyms': ['flipper_(footwear)', 'fin_(footwear)'], 'def': 'a shoe to aid a person in swimming', 'name': 'flipper_(footwear)'}, {'frequency': 'f', 'id': 467, 'synset': 'flower_arrangement.n.01', 'synonyms': ['flower_arrangement', 'floral_arrangement'], 'def': 'a decorative arrangement of flowers', 'name': 'flower_arrangement'}, {'frequency': 'c', 'id': 468, 'synset': 'flute.n.02', 'synonyms': ['flute_glass', 'champagne_flute'], 'def': 'a tall narrow wineglass', 'name': 'flute_glass'}, {'frequency': 'r', 'id': 469, 'synset': 'foal.n.01', 'synonyms': ['foal'], 'def': 'a young horse', 'name': 'foal'}, {'frequency': 'c', 'id': 470, 'synset': 'folding_chair.n.01', 'synonyms': ['folding_chair'], 'def': 'a chair that can be folded flat for storage', 'name': 'folding_chair'}, {'frequency': 'c', 'id': 471, 'synset': 'food_processor.n.01', 'synonyms': ['food_processor'], 'def': 'a kitchen appliance for shredding, blending, chopping, or slicing food', 'name': 'food_processor'}, {'frequency': 'c', 'id': 472, 'synset': 'football.n.02', 'synonyms': ['football_(American)'], 'def': 'the inflated oblong ball used in playing American football', 'name': 'football_(American)'}, {'frequency': 'r', 'id': 473, 'synset': 'football_helmet.n.01', 'synonyms': ['football_helmet'], 'def': 'a padded helmet with a face mask to protect the head of football players', 'name': 'football_helmet'}, {'frequency': 'c', 'id': 474, 'synset': 'footstool.n.01', 'synonyms': ['footstool', 'footrest'], 'def': 'a low seat or a stool to rest the feet of a seated person', 'name': 'footstool'}, {'frequency': 'f', 'id': 475, 'synset': 'fork.n.01', 'synonyms': ['fork'], 'def': 'cutlery used for serving and eating food', 'name': 'fork'}, {'frequency': 'r', 'id': 476, 'synset': 'forklift.n.01', 'synonyms': ['forklift'], 'def': 'an industrial vehicle with a power operated fork in front that can be inserted under loads to lift and move them', 'name': 'forklift'}, {'frequency': 'r', 'id': 477, 'synset': 'freight_car.n.01', 'synonyms': ['freight_car'], 'def': 'a railway car that carries freight', 'name': 'freight_car'}, {'frequency': 'r', 'id': 478, 'synset': 'french_toast.n.01', 'synonyms': ['French_toast'], 'def': 'bread slice dipped in egg and milk and fried', 'name': 'French_toast'}, {'frequency': 'c', 'id': 479, 'synset': 'freshener.n.01', 'synonyms': ['freshener', 'air_freshener'], 'def': 'anything that freshens', 'name': 'freshener'}, {'frequency': 'f', 'id': 480, 'synset': 'frisbee.n.01', 'synonyms': ['frisbee'], 'def': 'a light, plastic disk propelled with a flip of the wrist for recreation or competition', 'name': 'frisbee'}, {'frequency': 'c', 'id': 481, 'synset': 'frog.n.01', 'synonyms': ['frog', 'toad', 'toad_frog'], 'def': 'a tailless stout-bodied amphibians with long hind limbs for leaping', 'name': 'frog'}, {'frequency': 'c', 'id': 482, 'synset': 'fruit_juice.n.01', 'synonyms': ['fruit_juice'], 'def': 'drink produced by squeezing or crushing fruit', 'name': 'fruit_juice'}, {'frequency': 'r', 'id': 483, 'synset': 'fruit_salad.n.01', 'synonyms': ['fruit_salad'], 'def': 'salad composed of fruits', 'name': 'fruit_salad'}, {'frequency': 'c', 'id': 484, 'synset': 'frying_pan.n.01', 'synonyms': ['frying_pan', 'frypan', 'skillet'], 'def': 'a pan used for frying foods', 'name': 'frying_pan'}, {'frequency': 'r', 'id': 485, 'synset': 'fudge.n.01', 'synonyms': ['fudge'], 'def': 'soft creamy candy', 'name': 'fudge'}, {'frequency': 'r', 'id': 486, 'synset': 'funnel.n.02', 'synonyms': ['funnel'], 'def': 'a cone-shaped utensil used to channel a substance into a container with a small mouth', 'name': 'funnel'}, {'frequency': 'c', 'id': 487, 'synset': 'futon.n.01', 'synonyms': ['futon'], 'def': 'a pad that is used for sleeping on the floor or on a raised frame', 'name': 'futon'}, {'frequency': 'r', 'id': 488, 'synset': 'gag.n.02', 'synonyms': ['gag', 'muzzle'], 'def': "restraint put into a person's mouth to prevent speaking or shouting", 'name': 'gag'}, {'frequency': 'r', 'id': 489, 'synset': 'garbage.n.03', 'synonyms': ['garbage'], 'def': 'a receptacle where waste can be discarded', 'name': 'garbage'}, {'frequency': 'c', 'id': 490, 'synset': 'garbage_truck.n.01', 'synonyms': ['garbage_truck'], 'def': 'a truck for collecting domestic refuse', 'name': 'garbage_truck'}, {'frequency': 'c', 'id': 491, 'synset': 'garden_hose.n.01', 'synonyms': ['garden_hose'], 'def': 'a hose used for watering a lawn or garden', 'name': 'garden_hose'}, {'frequency': 'c', 'id': 492, 'synset': 'gargle.n.01', 'synonyms': ['gargle', 'mouthwash'], 'def': 'a medicated solution used for gargling and rinsing the mouth', 'name': 'gargle'}, {'frequency': 'r', 'id': 493, 'synset': 'gargoyle.n.02', 'synonyms': ['gargoyle'], 'def': 'an ornament consisting of a grotesquely carved figure of a person or animal', 'name': 'gargoyle'}, {'frequency': 'c', 'id': 494, 'synset': 'garlic.n.02', 'synonyms': ['garlic', 'ail'], 'def': 'aromatic bulb used as seasoning', 'name': 'garlic'}, {'frequency': 'r', 'id': 495, 'synset': 'gasmask.n.01', 'synonyms': ['gasmask', 'respirator', 'gas_helmet'], 'def': 'a protective face mask with a filter', 'name': 'gasmask'}, {'frequency': 'r', 'id': 496, 'synset': 'gazelle.n.01', 'synonyms': ['gazelle'], 'def': 'small swift graceful antelope of Africa and Asia having lustrous eyes', 'name': 'gazelle'}, {'frequency': 'c', 'id': 497, 'synset': 'gelatin.n.02', 'synonyms': ['gelatin', 'jelly'], 'def': 'an edible jelly made with gelatin and used as a dessert or salad base or a coating for foods', 'name': 'gelatin'}, {'frequency': 'r', 'id': 498, 'synset': 'gem.n.02', 'synonyms': ['gemstone'], 'def': 'a crystalline rock that can be cut and polished for jewelry', 'name': 'gemstone'}, {'frequency': 'c', 'id': 499, 'synset': 'giant_panda.n.01', 'synonyms': ['giant_panda', 'panda', 'panda_bear'], 'def': 'large black-and-white herbivorous mammal of bamboo forests of China and Tibet', 'name': 'giant_panda'}, {'frequency': 'c', 'id': 500, 'synset': 'gift_wrap.n.01', 'synonyms': ['gift_wrap'], 'def': 'attractive wrapping paper suitable for wrapping gifts', 'name': 'gift_wrap'}, {'frequency': 'c', 'id': 501, 'synset': 'ginger.n.03', 'synonyms': ['ginger', 'gingerroot'], 'def': 'the root of the common ginger plant; used fresh as a seasoning', 'name': 'ginger'}, {'frequency': 'f', 'id': 502, 'synset': 'giraffe.n.01', 'synonyms': ['giraffe'], 'def': 'tall animal having a spotted coat and small horns and very long neck and legs', 'name': 'giraffe'}, {'frequency': 'c', 'id': 503, 'synset': 'girdle.n.02', 'synonyms': ['cincture', 'sash', 'waistband', 'waistcloth'], 'def': 'a band of material around the waist that strengthens a skirt or trousers', 'name': 'cincture'}, {'frequency': 'f', 'id': 504, 'synset': 'glass.n.02', 'synonyms': ['glass_(drink_container)', 'drinking_glass'], 'def': 'a container for holding liquids while drinking', 'name': 'glass_(drink_container)'}, {'frequency': 'c', 'id': 505, 'synset': 'globe.n.03', 'synonyms': ['globe'], 'def': 'a sphere on which a map (especially of the earth) is represented', 'name': 'globe'}, {'frequency': 'f', 'id': 506, 'synset': 'glove.n.02', 'synonyms': ['glove'], 'def': 'handwear covering the hand', 'name': 'glove'}, {'frequency': 'c', 'id': 507, 'synset': 'goat.n.01', 'synonyms': ['goat'], 'def': 'a common goat', 'name': 'goat'}, {'frequency': 'f', 'id': 508, 'synset': 'goggles.n.01', 'synonyms': ['goggles'], 'def': 'tight-fitting spectacles worn to protect the eyes', 'name': 'goggles'}, {'frequency': 'r', 'id': 509, 'synset': 'goldfish.n.01', 'synonyms': ['goldfish'], 'def': 'small golden or orange-red freshwater fishes used as pond or aquarium pets', 'name': 'goldfish'}, {'frequency': 'r', 'id': 510, 'synset': 'golf_club.n.02', 'synonyms': ['golf_club', 'golf-club'], 'def': 'golf equipment used by a golfer to hit a golf ball', 'name': 'golf_club'}, {'frequency': 'c', 'id': 511, 'synset': 'golfcart.n.01', 'synonyms': ['golfcart'], 'def': 'a small motor vehicle in which golfers can ride between shots', 'name': 'golfcart'}, {'frequency': 'r', 'id': 512, 'synset': 'gondola.n.02', 'synonyms': ['gondola_(boat)'], 'def': 'long narrow flat-bottomed boat propelled by sculling; traditionally used on canals of Venice', 'name': 'gondola_(boat)'}, {'frequency': 'c', 'id': 513, 'synset': 'goose.n.01', 'synonyms': ['goose'], 'def': 'loud, web-footed long-necked aquatic birds usually larger than ducks', 'name': 'goose'}, {'frequency': 'r', 'id': 514, 'synset': 'gorilla.n.01', 'synonyms': ['gorilla'], 'def': 'largest ape', 'name': 'gorilla'}, {'frequency': 'r', 'id': 515, 'synset': 'gourd.n.02', 'synonyms': ['gourd'], 'def': 'any of numerous inedible fruits with hard rinds', 'name': 'gourd'}, {'frequency': 'r', 'id': 516, 'synset': 'gown.n.04', 'synonyms': ['surgical_gown', 'scrubs_(surgical_clothing)'], 'def': 'protective garment worn by surgeons during operations', 'name': 'surgical_gown'}, {'frequency': 'f', 'id': 517, 'synset': 'grape.n.01', 'synonyms': ['grape'], 'def': 'any of various juicy fruit with green or purple skins; grow in clusters', 'name': 'grape'}, {'frequency': 'r', 'id': 518, 'synset': 'grasshopper.n.01', 'synonyms': ['grasshopper'], 'def': 'plant-eating insect with hind legs adapted for leaping', 'name': 'grasshopper'}, {'frequency': 'c', 'id': 519, 'synset': 'grater.n.01', 'synonyms': ['grater'], 'def': 'utensil with sharp perforations for shredding foods (as vegetables or cheese)', 'name': 'grater'}, {'frequency': 'c', 'id': 520, 'synset': 'gravestone.n.01', 'synonyms': ['gravestone', 'headstone', 'tombstone'], 'def': 'a stone that is used to mark a grave', 'name': 'gravestone'}, {'frequency': 'r', 'id': 521, 'synset': 'gravy_boat.n.01', 'synonyms': ['gravy_boat', 'gravy_holder'], 'def': 'a dish (often boat-shaped) for serving gravy or sauce', 'name': 'gravy_boat'}, {'frequency': 'c', 'id': 522, 'synset': 'green_bean.n.02', 'synonyms': ['green_bean'], 'def': 'a common bean plant cultivated for its slender green edible pods', 'name': 'green_bean'}, {'frequency': 'c', 'id': 523, 'synset': 'green_onion.n.01', 'synonyms': ['green_onion', 'spring_onion', 'scallion'], 'def': 'a young onion before the bulb has enlarged', 'name': 'green_onion'}, {'frequency': 'r', 'id': 524, 'synset': 'griddle.n.01', 'synonyms': ['griddle'], 'def': 'cooking utensil consisting of a flat heated surface on which food is cooked', 'name': 'griddle'}, {'frequency': 'r', 'id': 525, 'synset': 'grillroom.n.01', 'synonyms': ['grillroom', 'grill_(restaurant)'], 'def': 'a restaurant where food is cooked on a grill', 'name': 'grillroom'}, {'frequency': 'r', 'id': 526, 'synset': 'grinder.n.04', 'synonyms': ['grinder_(tool)'], 'def': 'a machine tool that polishes metal', 'name': 'grinder_(tool)'}, {'frequency': 'r', 'id': 527, 'synset': 'grits.n.01', 'synonyms': ['grits', 'hominy_grits'], 'def': 'coarsely ground corn boiled as a breakfast dish', 'name': 'grits'}, {'frequency': 'c', 'id': 528, 'synset': 'grizzly.n.01', 'synonyms': ['grizzly', 'grizzly_bear'], 'def': 'powerful brownish-yellow bear of the uplands of western North America', 'name': 'grizzly'}, {'frequency': 'c', 'id': 529, 'synset': 'grocery_bag.n.01', 'synonyms': ['grocery_bag'], 'def': "a sack for holding customer's groceries", 'name': 'grocery_bag'}, {'frequency': 'r', 'id': 530, 'synset': 'guacamole.n.01', 'synonyms': ['guacamole'], 'def': 'a dip made of mashed avocado mixed with chopped onions and other seasonings', 'name': 'guacamole'}, {'frequency': 'f', 'id': 531, 'synset': 'guitar.n.01', 'synonyms': ['guitar'], 'def': 'a stringed instrument usually having six strings; played by strumming or plucking', 'name': 'guitar'}, {'frequency': 'c', 'id': 532, 'synset': 'gull.n.02', 'synonyms': ['gull', 'seagull'], 'def': 'mostly white aquatic bird having long pointed wings and short legs', 'name': 'gull'}, {'frequency': 'c', 'id': 533, 'synset': 'gun.n.01', 'synonyms': ['gun'], 'def': 'a weapon that discharges a bullet at high velocity from a metal tube', 'name': 'gun'}, {'frequency': 'r', 'id': 534, 'synset': 'hair_spray.n.01', 'synonyms': ['hair_spray'], 'def': 'substance sprayed on the hair to hold it in place', 'name': 'hair_spray'}, {'frequency': 'c', 'id': 535, 'synset': 'hairbrush.n.01', 'synonyms': ['hairbrush'], 'def': "a brush used to groom a person's hair", 'name': 'hairbrush'}, {'frequency': 'c', 'id': 536, 'synset': 'hairnet.n.01', 'synonyms': ['hairnet'], 'def': 'a small net that someone wears over their hair to keep it in place', 'name': 'hairnet'}, {'frequency': 'c', 'id': 537, 'synset': 'hairpin.n.01', 'synonyms': ['hairpin'], 'def': "a double pronged pin used to hold women's hair in place", 'name': 'hairpin'}, {'frequency': 'f', 'id': 538, 'synset': 'ham.n.01', 'synonyms': ['ham', 'jambon', 'gammon'], 'def': 'meat cut from the thigh of a hog (usually smoked)', 'name': 'ham'}, {'frequency': 'c', 'id': 539, 'synset': 'hamburger.n.01', 'synonyms': ['hamburger', 'beefburger', 'burger'], 'def': 'a sandwich consisting of a patty of minced beef served on a bun', 'name': 'hamburger'}, {'frequency': 'c', 'id': 540, 'synset': 'hammer.n.02', 'synonyms': ['hammer'], 'def': 'a hand tool with a heavy head and a handle; used to deliver an impulsive force by striking', 'name': 'hammer'}, {'frequency': 'r', 'id': 541, 'synset': 'hammock.n.02', 'synonyms': ['hammock'], 'def': 'a hanging bed of canvas or rope netting (usually suspended between two trees)', 'name': 'hammock'}, {'frequency': 'r', 'id': 542, 'synset': 'hamper.n.02', 'synonyms': ['hamper'], 'def': 'a basket usually with a cover', 'name': 'hamper'}, {'frequency': 'r', 'id': 543, 'synset': 'hamster.n.01', 'synonyms': ['hamster'], 'def': 'short-tailed burrowing rodent with large cheek pouches', 'name': 'hamster'}, {'frequency': 'c', 'id': 544, 'synset': 'hand_blower.n.01', 'synonyms': ['hair_dryer'], 'def': 'a hand-held electric blower that can blow warm air onto the hair', 'name': 'hair_dryer'}, {'frequency': 'r', 'id': 545, 'synset': 'hand_glass.n.01', 'synonyms': ['hand_glass', 'hand_mirror'], 'def': 'a mirror intended to be held in the hand', 'name': 'hand_glass'}, {'frequency': 'f', 'id': 546, 'synset': 'hand_towel.n.01', 'synonyms': ['hand_towel', 'face_towel'], 'def': 'a small towel used to dry the hands or face', 'name': 'hand_towel'}, {'frequency': 'c', 'id': 547, 'synset': 'handcart.n.01', 'synonyms': ['handcart', 'pushcart', 'hand_truck'], 'def': 'wheeled vehicle that can be pushed by a person', 'name': 'handcart'}, {'frequency': 'r', 'id': 548, 'synset': 'handcuff.n.01', 'synonyms': ['handcuff'], 'def': 'shackle that consists of a metal loop that can be locked around the wrist', 'name': 'handcuff'}, {'frequency': 'c', 'id': 549, 'synset': 'handkerchief.n.01', 'synonyms': ['handkerchief'], 'def': 'a square piece of cloth used for wiping the eyes or nose or as a costume accessory', 'name': 'handkerchief'}, {'frequency': 'f', 'id': 550, 'synset': 'handle.n.01', 'synonyms': ['handle', 'grip', 'handgrip'], 'def': 'the appendage to an object that is designed to be held in order to use or move it', 'name': 'handle'}, {'frequency': 'r', 'id': 551, 'synset': 'handsaw.n.01', 'synonyms': ['handsaw', "carpenter's_saw"], 'def': 'a saw used with one hand for cutting wood', 'name': 'handsaw'}, {'frequency': 'r', 'id': 552, 'synset': 'hardback.n.01', 'synonyms': ['hardback_book', 'hardcover_book'], 'def': 'a book with cardboard or cloth or leather covers', 'name': 'hardback_book'}, {'frequency': 'r', 'id': 553, 'synset': 'harmonium.n.01', 'synonyms': ['harmonium', 'organ_(musical_instrument)', 'reed_organ_(musical_instrument)'], 'def': 'a free-reed instrument in which air is forced through the reeds by bellows', 'name': 'harmonium'}, {'frequency': 'f', 'id': 554, 'synset': 'hat.n.01', 'synonyms': ['hat'], 'def': 'headwear that protects the head from bad weather, sun, or worn for fashion', 'name': 'hat'}, {'frequency': 'r', 'id': 555, 'synset': 'hatbox.n.01', 'synonyms': ['hatbox'], 'def': 'a round piece of luggage for carrying hats', 'name': 'hatbox'}, {'frequency': 'r', 'id': 556, 'synset': 'hatch.n.03', 'synonyms': ['hatch'], 'def': 'a movable barrier covering a hatchway', 'name': 'hatch'}, {'frequency': 'c', 'id': 557, 'synset': 'head_covering.n.01', 'synonyms': ['veil'], 'def': 'a garment that covers the head and face', 'name': 'veil'}, {'frequency': 'f', 'id': 558, 'synset': 'headband.n.01', 'synonyms': ['headband'], 'def': 'a band worn around or over the head', 'name': 'headband'}, {'frequency': 'f', 'id': 559, 'synset': 'headboard.n.01', 'synonyms': ['headboard'], 'def': 'a vertical board or panel forming the head of a bedstead', 'name': 'headboard'}, {'frequency': 'f', 'id': 560, 'synset': 'headlight.n.01', 'synonyms': ['headlight', 'headlamp'], 'def': 'a powerful light with reflector; attached to the front of an automobile or locomotive', 'name': 'headlight'}, {'frequency': 'c', 'id': 561, 'synset': 'headscarf.n.01', 'synonyms': ['headscarf'], 'def': 'a kerchief worn over the head and tied under the chin', 'name': 'headscarf'}, {'frequency': 'r', 'id': 562, 'synset': 'headset.n.01', 'synonyms': ['headset'], 'def': 'receiver consisting of a pair of headphones', 'name': 'headset'}, {'frequency': 'c', 'id': 563, 'synset': 'headstall.n.01', 'synonyms': ['headstall_(for_horses)', 'headpiece_(for_horses)'], 'def': "the band that is the part of a bridle that fits around a horse's head", 'name': 'headstall_(for_horses)'}, {'frequency': 'r', 'id': 564, 'synset': 'hearing_aid.n.02', 'synonyms': ['hearing_aid'], 'def': 'an acoustic device used to direct sound to the ear of a hearing-impaired person', 'name': 'hearing_aid'}, {'frequency': 'c', 'id': 565, 'synset': 'heart.n.02', 'synonyms': ['heart'], 'def': 'a muscular organ; its contractions move the blood through the body', 'name': 'heart'}, {'frequency': 'c', 'id': 566, 'synset': 'heater.n.01', 'synonyms': ['heater', 'warmer'], 'def': 'device that heats water or supplies warmth to a room', 'name': 'heater'}, {'frequency': 'c', 'id': 567, 'synset': 'helicopter.n.01', 'synonyms': ['helicopter'], 'def': 'an aircraft without wings that obtains its lift from the rotation of overhead blades', 'name': 'helicopter'}, {'frequency': 'f', 'id': 568, 'synset': 'helmet.n.02', 'synonyms': ['helmet'], 'def': 'a protective headgear made of hard material to resist blows', 'name': 'helmet'}, {'frequency': 'r', 'id': 569, 'synset': 'heron.n.02', 'synonyms': ['heron'], 'def': 'grey or white wading bird with long neck and long legs and (usually) long bill', 'name': 'heron'}, {'frequency': 'c', 'id': 570, 'synset': 'highchair.n.01', 'synonyms': ['highchair', 'feeding_chair'], 'def': 'a chair for feeding a very young child', 'name': 'highchair'}, {'frequency': 'f', 'id': 571, 'synset': 'hinge.n.01', 'synonyms': ['hinge'], 'def': 'a joint that holds two parts together so that one can swing relative to the other', 'name': 'hinge'}, {'frequency': 'r', 'id': 572, 'synset': 'hippopotamus.n.01', 'synonyms': ['hippopotamus'], 'def': 'massive thick-skinned animal living in or around rivers of tropical Africa', 'name': 'hippopotamus'}, {'frequency': 'r', 'id': 573, 'synset': 'hockey_stick.n.01', 'synonyms': ['hockey_stick'], 'def': 'sports implement consisting of a stick used by hockey players to move the puck', 'name': 'hockey_stick'}, {'frequency': 'c', 'id': 574, 'synset': 'hog.n.03', 'synonyms': ['hog', 'pig'], 'def': 'domestic swine', 'name': 'hog'}, {'frequency': 'f', 'id': 575, 'synset': 'home_plate.n.01', 'synonyms': ['home_plate_(baseball)', 'home_base_(baseball)'], 'def': '(baseball) a rubber slab where the batter stands; it must be touched by a base runner in order to score', 'name': 'home_plate_(baseball)'}, {'frequency': 'c', 'id': 576, 'synset': 'honey.n.01', 'synonyms': ['honey'], 'def': 'a sweet yellow liquid produced by bees', 'name': 'honey'}, {'frequency': 'f', 'id': 577, 'synset': 'hood.n.06', 'synonyms': ['fume_hood', 'exhaust_hood'], 'def': 'metal covering leading to a vent that exhausts smoke or fumes', 'name': 'fume_hood'}, {'frequency': 'f', 'id': 578, 'synset': 'hook.n.05', 'synonyms': ['hook'], 'def': 'a curved or bent implement for suspending or pulling something', 'name': 'hook'}, {'frequency': 'f', 'id': 579, 'synset': 'horse.n.01', 'synonyms': ['horse'], 'def': 'a common horse', 'name': 'horse'}, {'frequency': 'f', 'id': 580, 'synset': 'hose.n.03', 'synonyms': ['hose', 'hosepipe'], 'def': 'a flexible pipe for conveying a liquid or gas', 'name': 'hose'}, {'frequency': 'r', 'id': 581, 'synset': 'hot-air_balloon.n.01', 'synonyms': ['hot-air_balloon'], 'def': 'balloon for travel through the air in a basket suspended below a large bag of heated air', 'name': 'hot-air_balloon'}, {'frequency': 'r', 'id': 582, 'synset': 'hot_plate.n.01', 'synonyms': ['hotplate'], 'def': 'a portable electric appliance for heating or cooking or keeping food warm', 'name': 'hotplate'}, {'frequency': 'c', 'id': 583, 'synset': 'hot_sauce.n.01', 'synonyms': ['hot_sauce'], 'def': 'a pungent peppery sauce', 'name': 'hot_sauce'}, {'frequency': 'r', 'id': 584, 'synset': 'hourglass.n.01', 'synonyms': ['hourglass'], 'def': 'a sandglass timer that runs for sixty minutes', 'name': 'hourglass'}, {'frequency': 'r', 'id': 585, 'synset': 'houseboat.n.01', 'synonyms': ['houseboat'], 'def': 'a barge that is designed and equipped for use as a dwelling', 'name': 'houseboat'}, {'frequency': 'r', 'id': 586, 'synset': 'hummingbird.n.01', 'synonyms': ['hummingbird'], 'def': 'tiny American bird having brilliant iridescent plumage and long slender bills', 'name': 'hummingbird'}, {'frequency': 'r', 'id': 587, 'synset': 'hummus.n.01', 'synonyms': ['hummus', 'humus', 'hommos', 'hoummos', 'humous'], 'def': 'a thick spread made from mashed chickpeas', 'name': 'hummus'}, {'frequency': 'c', 'id': 588, 'synset': 'ice_bear.n.01', 'synonyms': ['polar_bear'], 'def': 'white bear of Arctic regions', 'name': 'polar_bear'}, {'frequency': 'c', 'id': 589, 'synset': 'ice_cream.n.01', 'synonyms': ['icecream'], 'def': 'frozen dessert containing cream and sugar and flavoring', 'name': 'icecream'}, {'frequency': 'r', 'id': 590, 'synset': 'ice_lolly.n.01', 'synonyms': ['popsicle'], 'def': 'ice cream or water ice on a small wooden stick', 'name': 'popsicle'}, {'frequency': 'c', 'id': 591, 'synset': 'ice_maker.n.01', 'synonyms': ['ice_maker'], 'def': 'an appliance included in some electric refrigerators for making ice cubes', 'name': 'ice_maker'}, {'frequency': 'r', 'id': 592, 'synset': 'ice_pack.n.01', 'synonyms': ['ice_pack', 'ice_bag'], 'def': 'a waterproof bag filled with ice: applied to the body (especially the head) to cool or reduce swelling', 'name': 'ice_pack'}, {'frequency': 'r', 'id': 593, 'synset': 'ice_skate.n.01', 'synonyms': ['ice_skate'], 'def': 'skate consisting of a boot with a steel blade fitted to the sole', 'name': 'ice_skate'}, {'frequency': 'r', 'id': 594, 'synset': 'ice_tea.n.01', 'synonyms': ['ice_tea', 'iced_tea'], 'def': 'strong tea served over ice', 'name': 'ice_tea'}, {'frequency': 'c', 'id': 595, 'synset': 'igniter.n.01', 'synonyms': ['igniter', 'ignitor', 'lighter'], 'def': 'a substance or device used to start a fire', 'name': 'igniter'}, {'frequency': 'r', 'id': 596, 'synset': 'incense.n.01', 'synonyms': ['incense'], 'def': 'a substance that produces a fragrant odor when burned', 'name': 'incense'}, {'frequency': 'r', 'id': 597, 'synset': 'inhaler.n.01', 'synonyms': ['inhaler', 'inhalator'], 'def': 'a dispenser that produces a chemical vapor to be inhaled through mouth or nose', 'name': 'inhaler'}, {'frequency': 'c', 'id': 598, 'synset': 'ipod.n.01', 'synonyms': ['iPod'], 'def': 'a pocket-sized device used to play music files', 'name': 'iPod'}, {'frequency': 'c', 'id': 599, 'synset': 'iron.n.04', 'synonyms': ['iron_(for_clothing)', 'smoothing_iron_(for_clothing)'], 'def': 'home appliance consisting of a flat metal base that is heated and used to smooth cloth', 'name': 'iron_(for_clothing)'}, {'frequency': 'r', 'id': 600, 'synset': 'ironing_board.n.01', 'synonyms': ['ironing_board'], 'def': 'narrow padded board on collapsible supports; used for ironing clothes', 'name': 'ironing_board'}, {'frequency': 'f', 'id': 601, 'synset': 'jacket.n.01', 'synonyms': ['jacket'], 'def': 'a waist-length coat', 'name': 'jacket'}, {'frequency': 'r', 'id': 602, 'synset': 'jam.n.01', 'synonyms': ['jam'], 'def': 'preserve of crushed fruit', 'name': 'jam'}, {'frequency': 'f', 'id': 603, 'synset': 'jean.n.01', 'synonyms': ['jean', 'blue_jean', 'denim'], 'def': '(usually plural) close-fitting trousers of heavy denim for manual work or casual wear', 'name': 'jean'}, {'frequency': 'c', 'id': 604, 'synset': 'jeep.n.01', 'synonyms': ['jeep', 'landrover'], 'def': 'a car suitable for traveling over rough terrain', 'name': 'jeep'}, {'frequency': 'r', 'id': 605, 'synset': 'jelly_bean.n.01', 'synonyms': ['jelly_bean', 'jelly_egg'], 'def': 'sugar-glazed jellied candy', 'name': 'jelly_bean'}, {'frequency': 'f', 'id': 606, 'synset': 'jersey.n.03', 'synonyms': ['jersey', 'T-shirt', 'tee_shirt'], 'def': 'a close-fitting pullover shirt', 'name': 'jersey'}, {'frequency': 'c', 'id': 607, 'synset': 'jet.n.01', 'synonyms': ['jet_plane', 'jet-propelled_plane'], 'def': 'an airplane powered by one or more jet engines', 'name': 'jet_plane'}, {'frequency': 'c', 'id': 608, 'synset': 'jewelry.n.01', 'synonyms': ['jewelry', 'jewellery'], 'def': 'an adornment (as a bracelet or ring or necklace) made of precious metals and set with gems (or imitation gems)', 'name': 'jewelry'}, {'frequency': 'r', 'id': 609, 'synset': 'joystick.n.02', 'synonyms': ['joystick'], 'def': 'a control device for computers consisting of a vertical handle that can move freely in two directions', 'name': 'joystick'}, {'frequency': 'r', 'id': 610, 'synset': 'jump_suit.n.01', 'synonyms': ['jumpsuit'], 'def': "one-piece garment fashioned after a parachutist's uniform", 'name': 'jumpsuit'}, {'frequency': 'c', 'id': 611, 'synset': 'kayak.n.01', 'synonyms': ['kayak'], 'def': 'a small canoe consisting of a light frame made watertight with animal skins', 'name': 'kayak'}, {'frequency': 'r', 'id': 612, 'synset': 'keg.n.02', 'synonyms': ['keg'], 'def': 'small cask or barrel', 'name': 'keg'}, {'frequency': 'r', 'id': 613, 'synset': 'kennel.n.01', 'synonyms': ['kennel', 'doghouse'], 'def': 'outbuilding that serves as a shelter for a dog', 'name': 'kennel'}, {'frequency': 'c', 'id': 614, 'synset': 'kettle.n.01', 'synonyms': ['kettle', 'boiler'], 'def': 'a metal pot for stewing or boiling; usually has a lid', 'name': 'kettle'}, {'frequency': 'f', 'id': 615, 'synset': 'key.n.01', 'synonyms': ['key'], 'def': 'metal instrument used to unlock a lock', 'name': 'key'}, {'frequency': 'r', 'id': 616, 'synset': 'keycard.n.01', 'synonyms': ['keycard'], 'def': 'a plastic card used to gain access typically to a door', 'name': 'keycard'}, {'frequency': 'r', 'id': 617, 'synset': 'kilt.n.01', 'synonyms': ['kilt'], 'def': 'a knee-length pleated tartan skirt worn by men as part of the traditional dress in the Highlands of northern Scotland', 'name': 'kilt'}, {'frequency': 'c', 'id': 618, 'synset': 'kimono.n.01', 'synonyms': ['kimono'], 'def': 'a loose robe; imitated from robes originally worn by Japanese', 'name': 'kimono'}, {'frequency': 'f', 'id': 619, 'synset': 'kitchen_sink.n.01', 'synonyms': ['kitchen_sink'], 'def': 'a sink in a kitchen', 'name': 'kitchen_sink'}, {'frequency': 'c', 'id': 620, 'synset': 'kitchen_table.n.01', 'synonyms': ['kitchen_table'], 'def': 'a table in the kitchen', 'name': 'kitchen_table'}, {'frequency': 'f', 'id': 621, 'synset': 'kite.n.03', 'synonyms': ['kite'], 'def': 'plaything consisting of a light frame covered with tissue paper; flown in wind at end of a string', 'name': 'kite'}, {'frequency': 'c', 'id': 622, 'synset': 'kitten.n.01', 'synonyms': ['kitten', 'kitty'], 'def': 'young domestic cat', 'name': 'kitten'}, {'frequency': 'c', 'id': 623, 'synset': 'kiwi.n.03', 'synonyms': ['kiwi_fruit'], 'def': 'fuzzy brown egg-shaped fruit with slightly tart green flesh', 'name': 'kiwi_fruit'}, {'frequency': 'f', 'id': 624, 'synset': 'knee_pad.n.01', 'synonyms': ['knee_pad'], 'def': 'protective garment consisting of a pad worn by football or baseball or hockey players', 'name': 'knee_pad'}, {'frequency': 'f', 'id': 625, 'synset': 'knife.n.01', 'synonyms': ['knife'], 'def': 'tool with a blade and point used as a cutting instrument', 'name': 'knife'}, {'frequency': 'r', 'id': 626, 'synset': 'knight.n.02', 'synonyms': ['knight_(chess_piece)', 'horse_(chess_piece)'], 'def': 'a chess game piece shaped to resemble the head of a horse', 'name': 'knight_(chess_piece)'}, {'frequency': 'r', 'id': 627, 'synset': 'knitting_needle.n.01', 'synonyms': ['knitting_needle'], 'def': 'needle consisting of a slender rod with pointed ends; usually used in pairs', 'name': 'knitting_needle'}, {'frequency': 'f', 'id': 628, 'synset': 'knob.n.02', 'synonyms': ['knob'], 'def': 'a round handle often found on a door', 'name': 'knob'}, {'frequency': 'r', 'id': 629, 'synset': 'knocker.n.05', 'synonyms': ['knocker_(on_a_door)', 'doorknocker'], 'def': 'a device (usually metal and ornamental) attached by a hinge to a door', 'name': 'knocker_(on_a_door)'}, {'frequency': 'r', 'id': 630, 'synset': 'koala.n.01', 'synonyms': ['koala', 'koala_bear'], 'def': 'sluggish tailless Australian marsupial with grey furry ears and coat', 'name': 'koala'}, {'frequency': 'r', 'id': 631, 'synset': 'lab_coat.n.01', 'synonyms': ['lab_coat', 'laboratory_coat'], 'def': 'a light coat worn to protect clothing from substances used while working in a laboratory', 'name': 'lab_coat'}, {'frequency': 'f', 'id': 632, 'synset': 'ladder.n.01', 'synonyms': ['ladder'], 'def': 'steps consisting of two parallel members connected by rungs', 'name': 'ladder'}, {'frequency': 'c', 'id': 633, 'synset': 'ladle.n.01', 'synonyms': ['ladle'], 'def': 'a spoon-shaped vessel with a long handle frequently used to transfer liquids', 'name': 'ladle'}, {'frequency': 'r', 'id': 634, 'synset': 'ladybug.n.01', 'synonyms': ['ladybug', 'ladybeetle', 'ladybird_beetle'], 'def': 'small round bright-colored and spotted beetle, typically red and black', 'name': 'ladybug'}, {'frequency': 'c', 'id': 635, 'synset': 'lamb.n.01', 'synonyms': ['lamb_(animal)'], 'def': 'young sheep', 'name': 'lamb_(animal)'}, {'frequency': 'r', 'id': 636, 'synset': 'lamb_chop.n.01', 'synonyms': ['lamb-chop', 'lambchop'], 'def': 'chop cut from a lamb', 'name': 'lamb-chop'}, {'frequency': 'f', 'id': 637, 'synset': 'lamp.n.02', 'synonyms': ['lamp'], 'def': 'a piece of furniture holding one or more electric light bulbs', 'name': 'lamp'}, {'frequency': 'f', 'id': 638, 'synset': 'lamppost.n.01', 'synonyms': ['lamppost'], 'def': 'a metal post supporting an outdoor lamp (such as a streetlight)', 'name': 'lamppost'}, {'frequency': 'f', 'id': 639, 'synset': 'lampshade.n.01', 'synonyms': ['lampshade'], 'def': 'a protective ornamental shade used to screen a light bulb from direct view', 'name': 'lampshade'}, {'frequency': 'c', 'id': 640, 'synset': 'lantern.n.01', 'synonyms': ['lantern'], 'def': 'light in a transparent protective case', 'name': 'lantern'}, {'frequency': 'f', 'id': 641, 'synset': 'lanyard.n.02', 'synonyms': ['lanyard', 'laniard'], 'def': 'a cord worn around the neck to hold a knife or whistle, etc.', 'name': 'lanyard'}, {'frequency': 'f', 'id': 642, 'synset': 'laptop.n.01', 'synonyms': ['laptop_computer', 'notebook_computer'], 'def': 'a portable computer small enough to use in your lap', 'name': 'laptop_computer'}, {'frequency': 'r', 'id': 643, 'synset': 'lasagna.n.01', 'synonyms': ['lasagna', 'lasagne'], 'def': 'baked dish of layers of lasagna pasta with sauce and cheese and meat or vegetables', 'name': 'lasagna'}, {'frequency': 'c', 'id': 644, 'synset': 'latch.n.02', 'synonyms': ['latch'], 'def': 'a bar that can be lowered or slid into a groove to fasten a door or gate', 'name': 'latch'}, {'frequency': 'r', 'id': 645, 'synset': 'lawn_mower.n.01', 'synonyms': ['lawn_mower'], 'def': 'garden tool for mowing grass on lawns', 'name': 'lawn_mower'}, {'frequency': 'r', 'id': 646, 'synset': 'leather.n.01', 'synonyms': ['leather'], 'def': 'an animal skin made smooth and flexible by removing the hair and then tanning', 'name': 'leather'}, {'frequency': 'c', 'id': 647, 'synset': 'legging.n.01', 'synonyms': ['legging_(clothing)', 'leging_(clothing)', 'leg_covering'], 'def': 'a garment covering the leg (usually extending from the knee to the ankle)', 'name': 'legging_(clothing)'}, {'frequency': 'c', 'id': 648, 'synset': 'lego.n.01', 'synonyms': ['Lego', 'Lego_set'], 'def': "a child's plastic construction set for making models from blocks", 'name': 'Lego'}, {'frequency': 'f', 'id': 649, 'synset': 'lemon.n.01', 'synonyms': ['lemon'], 'def': 'yellow oval fruit with juicy acidic flesh', 'name': 'lemon'}, {'frequency': 'r', 'id': 650, 'synset': 'lemonade.n.01', 'synonyms': ['lemonade'], 'def': 'sweetened beverage of diluted lemon juice', 'name': 'lemonade'}, {'frequency': 'f', 'id': 651, 'synset': 'lettuce.n.02', 'synonyms': ['lettuce'], 'def': 'leafy plant commonly eaten in salad or on sandwiches', 'name': 'lettuce'}, {'frequency': 'f', 'id': 652, 'synset': 'license_plate.n.01', 'synonyms': ['license_plate', 'numberplate'], 'def': "a plate mounted on the front and back of car and bearing the car's registration number", 'name': 'license_plate'}, {'frequency': 'f', 'id': 653, 'synset': 'life_buoy.n.01', 'synonyms': ['life_buoy', 'lifesaver', 'life_belt', 'life_ring'], 'def': 'a ring-shaped life preserver used to prevent drowning (NOT a life-jacket or vest)', 'name': 'life_buoy'}, {'frequency': 'f', 'id': 654, 'synset': 'life_jacket.n.01', 'synonyms': ['life_jacket', 'life_vest'], 'def': 'life preserver consisting of a sleeveless jacket of buoyant or inflatable design', 'name': 'life_jacket'}, {'frequency': 'f', 'id': 655, 'synset': 'light_bulb.n.01', 'synonyms': ['lightbulb'], 'def': 'glass bulb or tube shaped electric device that emits light (DO NOT MARK LAMPS AS A WHOLE)', 'name': 'lightbulb'}, {'frequency': 'r', 'id': 656, 'synset': 'lightning_rod.n.02', 'synonyms': ['lightning_rod', 'lightning_conductor'], 'def': 'a metallic conductor that is attached to a high point and leads to the ground', 'name': 'lightning_rod'}, {'frequency': 'c', 'id': 657, 'synset': 'lime.n.06', 'synonyms': ['lime'], 'def': 'the green acidic fruit of any of various lime trees', 'name': 'lime'}, {'frequency': 'r', 'id': 658, 'synset': 'limousine.n.01', 'synonyms': ['limousine'], 'def': 'long luxurious car; usually driven by a chauffeur', 'name': 'limousine'}, {'frequency': 'r', 'id': 659, 'synset': 'linen.n.02', 'synonyms': ['linen_paper'], 'def': 'a high-quality paper made of linen fibers or with a linen finish', 'name': 'linen_paper'}, {'frequency': 'c', 'id': 660, 'synset': 'lion.n.01', 'synonyms': ['lion'], 'def': 'large gregarious predatory cat of Africa and India', 'name': 'lion'}, {'frequency': 'c', 'id': 661, 'synset': 'lip_balm.n.01', 'synonyms': ['lip_balm'], 'def': 'a balm applied to the lips', 'name': 'lip_balm'}, {'frequency': 'c', 'id': 662, 'synset': 'lipstick.n.01', 'synonyms': ['lipstick', 'lip_rouge'], 'def': 'makeup that is used to color the lips', 'name': 'lipstick'}, {'frequency': 'r', 'id': 663, 'synset': 'liquor.n.01', 'synonyms': ['liquor', 'spirits', 'hard_liquor', 'liqueur', 'cordial'], 'def': 'an alcoholic beverage that is distilled rather than fermented', 'name': 'liquor'}, {'frequency': 'r', 'id': 664, 'synset': 'lizard.n.01', 'synonyms': ['lizard'], 'def': 'a reptile with usually two pairs of legs and a tapering tail', 'name': 'lizard'}, {'frequency': 'r', 'id': 665, 'synset': 'loafer.n.02', 'synonyms': ['Loafer_(type_of_shoe)'], 'def': 'a low leather step-in shoe', 'name': 'Loafer_(type_of_shoe)'}, {'frequency': 'f', 'id': 666, 'synset': 'log.n.01', 'synonyms': ['log'], 'def': 'a segment of the trunk of a tree when stripped of branches', 'name': 'log'}, {'frequency': 'c', 'id': 667, 'synset': 'lollipop.n.02', 'synonyms': ['lollipop'], 'def': 'hard candy on a stick', 'name': 'lollipop'}, {'frequency': 'c', 'id': 668, 'synset': 'lotion.n.01', 'synonyms': ['lotion'], 'def': 'any of various cosmetic preparations that are applied to the skin', 'name': 'lotion'}, {'frequency': 'f', 'id': 669, 'synset': 'loudspeaker.n.01', 'synonyms': ['speaker_(stero_equipment)'], 'def': 'electronic device that produces sound often as part of a stereo system', 'name': 'speaker_(stero_equipment)'}, {'frequency': 'c', 'id': 670, 'synset': 'love_seat.n.01', 'synonyms': ['loveseat'], 'def': 'small sofa that seats two people', 'name': 'loveseat'}, {'frequency': 'r', 'id': 671, 'synset': 'machine_gun.n.01', 'synonyms': ['machine_gun'], 'def': 'a rapidly firing automatic gun', 'name': 'machine_gun'}, {'frequency': 'f', 'id': 672, 'synset': 'magazine.n.02', 'synonyms': ['magazine'], 'def': 'a paperback periodic publication', 'name': 'magazine'}, {'frequency': 'f', 'id': 673, 'synset': 'magnet.n.01', 'synonyms': ['magnet'], 'def': 'a device that attracts iron and produces a magnetic field', 'name': 'magnet'}, {'frequency': 'r', 'id': 674, 'synset': 'mail_slot.n.01', 'synonyms': ['mail_slot'], 'def': 'a slot (usually in a door) through which mail can be delivered', 'name': 'mail_slot'}, {'frequency': 'c', 'id': 675, 'synset': 'mailbox.n.01', 'synonyms': ['mailbox_(at_home)', 'letter_box_(at_home)'], 'def': 'a private box for delivery of mail', 'name': 'mailbox_(at_home)'}, {'frequency': 'r', 'id': 676, 'synset': 'mallet.n.01', 'synonyms': ['mallet'], 'def': 'a sports implement with a long handle and a hammer-like head used to hit a ball', 'name': 'mallet'}, {'frequency': 'r', 'id': 677, 'synset': 'mammoth.n.01', 'synonyms': ['mammoth'], 'def': 'any of numerous extinct elephants widely distributed in the Pleistocene', 'name': 'mammoth'}, {'frequency': 'c', 'id': 678, 'synset': 'mandarin.n.05', 'synonyms': ['mandarin_orange'], 'def': 'a somewhat flat reddish-orange loose skinned citrus of China', 'name': 'mandarin_orange'}, {'frequency': 'c', 'id': 679, 'synset': 'manger.n.01', 'synonyms': ['manger', 'trough'], 'def': 'a container (usually in a barn or stable) from which cattle or horses feed', 'name': 'manger'}, {'frequency': 'f', 'id': 680, 'synset': 'manhole.n.01', 'synonyms': ['manhole'], 'def': 'a hole (usually with a flush cover) through which a person can gain access to an underground structure', 'name': 'manhole'}, {'frequency': 'c', 'id': 681, 'synset': 'map.n.01', 'synonyms': ['map'], 'def': "a diagrammatic representation of the earth's surface (or part of it)", 'name': 'map'}, {'frequency': 'c', 'id': 682, 'synset': 'marker.n.03', 'synonyms': ['marker'], 'def': 'a writing implement for making a mark', 'name': 'marker'}, {'frequency': 'r', 'id': 683, 'synset': 'martini.n.01', 'synonyms': ['martini'], 'def': 'a cocktail made of gin (or vodka) with dry vermouth', 'name': 'martini'}, {'frequency': 'r', 'id': 684, 'synset': 'mascot.n.01', 'synonyms': ['mascot'], 'def': 'a person or animal that is adopted by a team or other group as a symbolic figure', 'name': 'mascot'}, {'frequency': 'c', 'id': 685, 'synset': 'mashed_potato.n.01', 'synonyms': ['mashed_potato'], 'def': 'potato that has been peeled and boiled and then mashed', 'name': 'mashed_potato'}, {'frequency': 'r', 'id': 686, 'synset': 'masher.n.02', 'synonyms': ['masher'], 'def': 'a kitchen utensil used for mashing (e.g. potatoes)', 'name': 'masher'}, {'frequency': 'f', 'id': 687, 'synset': 'mask.n.04', 'synonyms': ['mask', 'facemask'], 'def': 'a protective covering worn over the face', 'name': 'mask'}, {'frequency': 'f', 'id': 688, 'synset': 'mast.n.01', 'synonyms': ['mast'], 'def': 'a vertical spar for supporting sails', 'name': 'mast'}, {'frequency': 'c', 'id': 689, 'synset': 'mat.n.03', 'synonyms': ['mat_(gym_equipment)', 'gym_mat'], 'def': 'sports equipment consisting of a piece of thick padding on the floor for gymnastics', 'name': 'mat_(gym_equipment)'}, {'frequency': 'r', 'id': 690, 'synset': 'matchbox.n.01', 'synonyms': ['matchbox'], 'def': 'a box for holding matches', 'name': 'matchbox'}, {'frequency': 'f', 'id': 691, 'synset': 'mattress.n.01', 'synonyms': ['mattress'], 'def': 'a thick pad filled with resilient material used as a bed or part of a bed', 'name': 'mattress'}, {'frequency': 'c', 'id': 692, 'synset': 'measuring_cup.n.01', 'synonyms': ['measuring_cup'], 'def': 'graduated cup used to measure liquid or granular ingredients', 'name': 'measuring_cup'}, {'frequency': 'c', 'id': 693, 'synset': 'measuring_stick.n.01', 'synonyms': ['measuring_stick', 'ruler_(measuring_stick)', 'measuring_rod'], 'def': 'measuring instrument having a sequence of marks at regular intervals', 'name': 'measuring_stick'}, {'frequency': 'c', 'id': 694, 'synset': 'meatball.n.01', 'synonyms': ['meatball'], 'def': 'ground meat formed into a ball and fried or simmered in broth', 'name': 'meatball'}, {'frequency': 'c', 'id': 695, 'synset': 'medicine.n.02', 'synonyms': ['medicine'], 'def': 'something that treats or prevents or alleviates the symptoms of disease', 'name': 'medicine'}, {'frequency': 'r', 'id': 696, 'synset': 'melon.n.01', 'synonyms': ['melon'], 'def': 'fruit of the gourd family having a hard rind and sweet juicy flesh', 'name': 'melon'}, {'frequency': 'f', 'id': 697, 'synset': 'microphone.n.01', 'synonyms': ['microphone'], 'def': 'device for converting sound waves into electrical energy', 'name': 'microphone'}, {'frequency': 'r', 'id': 698, 'synset': 'microscope.n.01', 'synonyms': ['microscope'], 'def': 'magnifier of the image of small objects', 'name': 'microscope'}, {'frequency': 'f', 'id': 699, 'synset': 'microwave.n.02', 'synonyms': ['microwave_oven'], 'def': 'kitchen appliance that cooks food by passing an electromagnetic wave through it', 'name': 'microwave_oven'}, {'frequency': 'r', 'id': 700, 'synset': 'milestone.n.01', 'synonyms': ['milestone', 'milepost'], 'def': 'stone post at side of a road to show distances', 'name': 'milestone'}, {'frequency': 'c', 'id': 701, 'synset': 'milk.n.01', 'synonyms': ['milk'], 'def': 'a white nutritious liquid secreted by mammals and used as food by human beings', 'name': 'milk'}, {'frequency': 'f', 'id': 702, 'synset': 'minivan.n.01', 'synonyms': ['minivan'], 'def': 'a small box-shaped passenger van', 'name': 'minivan'}, {'frequency': 'r', 'id': 703, 'synset': 'mint.n.05', 'synonyms': ['mint_candy'], 'def': 'a candy that is flavored with a mint oil', 'name': 'mint_candy'}, {'frequency': 'f', 'id': 704, 'synset': 'mirror.n.01', 'synonyms': ['mirror'], 'def': 'polished surface that forms images by reflecting light', 'name': 'mirror'}, {'frequency': 'c', 'id': 705, 'synset': 'mitten.n.01', 'synonyms': ['mitten'], 'def': 'glove that encases the thumb separately and the other four fingers together', 'name': 'mitten'}, {'frequency': 'c', 'id': 706, 'synset': 'mixer.n.04', 'synonyms': ['mixer_(kitchen_tool)', 'stand_mixer'], 'def': 'a kitchen utensil that is used for mixing foods', 'name': 'mixer_(kitchen_tool)'}, {'frequency': 'c', 'id': 707, 'synset': 'money.n.03', 'synonyms': ['money'], 'def': 'the official currency issued by a government or national bank', 'name': 'money'}, {'frequency': 'f', 'id': 708, 'synset': 'monitor.n.04', 'synonyms': ['monitor_(computer_equipment) computer_monitor'], 'def': 'a computer monitor', 'name': 'monitor_(computer_equipment) computer_monitor'}, {'frequency': 'c', 'id': 709, 'synset': 'monkey.n.01', 'synonyms': ['monkey'], 'def': 'any of various long-tailed primates', 'name': 'monkey'}, {'frequency': 'f', 'id': 710, 'synset': 'motor.n.01', 'synonyms': ['motor'], 'def': 'machine that converts other forms of energy into mechanical energy and so imparts motion', 'name': 'motor'}, {'frequency': 'f', 'id': 711, 'synset': 'motor_scooter.n.01', 'synonyms': ['motor_scooter', 'scooter'], 'def': 'a wheeled vehicle with small wheels and a low-powered engine', 'name': 'motor_scooter'}, {'frequency': 'r', 'id': 712, 'synset': 'motor_vehicle.n.01', 'synonyms': ['motor_vehicle', 'automotive_vehicle'], 'def': 'a self-propelled wheeled vehicle that does not run on rails', 'name': 'motor_vehicle'}, {'frequency': 'r', 'id': 713, 'synset': 'motorboat.n.01', 'synonyms': ['motorboat', 'powerboat'], 'def': 'a boat propelled by an internal-combustion engine', 'name': 'motorboat'}, {'frequency': 'f', 'id': 714, 'synset': 'motorcycle.n.01', 'synonyms': ['motorcycle'], 'def': 'a motor vehicle with two wheels and a strong frame', 'name': 'motorcycle'}, {'frequency': 'f', 'id': 715, 'synset': 'mound.n.01', 'synonyms': ['mound_(baseball)', "pitcher's_mound"], 'def': '(baseball) the slight elevation on which the pitcher stands', 'name': 'mound_(baseball)'}, {'frequency': 'r', 'id': 716, 'synset': 'mouse.n.01', 'synonyms': ['mouse_(animal_rodent)'], 'def': 'a small rodent with pointed snouts and small ears on elongated bodies with slender usually hairless tails', 'name': 'mouse_(animal_rodent)'}, {'frequency': 'f', 'id': 717, 'synset': 'mouse.n.04', 'synonyms': ['mouse_(computer_equipment)', 'computer_mouse'], 'def': 'a computer input device that controls an on-screen pointer', 'name': 'mouse_(computer_equipment)'}, {'frequency': 'f', 'id': 718, 'synset': 'mousepad.n.01', 'synonyms': ['mousepad'], 'def': 'a small portable pad that provides an operating surface for a computer mouse', 'name': 'mousepad'}, {'frequency': 'c', 'id': 719, 'synset': 'muffin.n.01', 'synonyms': ['muffin'], 'def': 'a sweet quick bread baked in a cup-shaped pan', 'name': 'muffin'}, {'frequency': 'f', 'id': 720, 'synset': 'mug.n.04', 'synonyms': ['mug'], 'def': 'with handle and usually cylindrical', 'name': 'mug'}, {'frequency': 'f', 'id': 721, 'synset': 'mushroom.n.02', 'synonyms': ['mushroom'], 'def': 'a common mushroom', 'name': 'mushroom'}, {'frequency': 'r', 'id': 722, 'synset': 'music_stool.n.01', 'synonyms': ['music_stool', 'piano_stool'], 'def': 'a stool for piano players; usually adjustable in height', 'name': 'music_stool'}, {'frequency': 'r', 'id': 723, 'synset': 'musical_instrument.n.01', 'synonyms': ['musical_instrument', 'instrument_(musical)'], 'def': 'any of various devices or contrivances that can be used to produce musical tones or sounds', 'name': 'musical_instrument'}, {'frequency': 'r', 'id': 724, 'synset': 'nailfile.n.01', 'synonyms': ['nailfile'], 'def': 'a small flat file for shaping the nails', 'name': 'nailfile'}, {'frequency': 'r', 'id': 725, 'synset': 'nameplate.n.01', 'synonyms': ['nameplate'], 'def': 'a plate bearing a name', 'name': 'nameplate'}, {'frequency': 'f', 'id': 726, 'synset': 'napkin.n.01', 'synonyms': ['napkin', 'table_napkin', 'serviette'], 'def': 'a small piece of table linen or paper that is used to wipe the mouth and to cover the lap in order to protect clothing', 'name': 'napkin'}, {'frequency': 'r', 'id': 727, 'synset': 'neckerchief.n.01', 'synonyms': ['neckerchief'], 'def': 'a kerchief worn around the neck', 'name': 'neckerchief'}, {'frequency': 'f', 'id': 728, 'synset': 'necklace.n.01', 'synonyms': ['necklace'], 'def': 'jewelry consisting of a cord or chain (often bearing gems) worn about the neck as an ornament', 'name': 'necklace'}, {'frequency': 'f', 'id': 729, 'synset': 'necktie.n.01', 'synonyms': ['necktie', 'tie_(necktie)'], 'def': 'neckwear consisting of a long narrow piece of material worn under a collar and tied in knot at the front', 'name': 'necktie'}, {'frequency': 'r', 'id': 730, 'synset': 'needle.n.03', 'synonyms': ['needle'], 'def': 'a sharp pointed implement (usually metal)', 'name': 'needle'}, {'frequency': 'c', 'id': 731, 'synset': 'nest.n.01', 'synonyms': ['nest'], 'def': 'a structure in which animals lay eggs or give birth to their young', 'name': 'nest'}, {'frequency': 'r', 'id': 732, 'synset': 'newsstand.n.01', 'synonyms': ['newsstand'], 'def': 'a stall where newspapers and other periodicals are sold', 'name': 'newsstand'}, {'frequency': 'c', 'id': 733, 'synset': 'nightwear.n.01', 'synonyms': ['nightshirt', 'nightwear', 'sleepwear', 'nightclothes'], 'def': 'garments designed to be worn in bed', 'name': 'nightshirt'}, {'frequency': 'r', 'id': 734, 'synset': 'nosebag.n.01', 'synonyms': ['nosebag_(for_animals)', 'feedbag'], 'def': 'a canvas bag that is used to feed an animal (such as a horse); covers the muzzle and fastens at the top of the head', 'name': 'nosebag_(for_animals)'}, {'frequency': 'r', 'id': 735, 'synset': 'noseband.n.01', 'synonyms': ['noseband_(for_animals)', 'nosepiece_(for_animals)'], 'def': "a strap that is the part of a bridle that goes over the animal's nose", 'name': 'noseband_(for_animals)'}, {'frequency': 'f', 'id': 736, 'synset': 'notebook.n.01', 'synonyms': ['notebook'], 'def': 'a book with blank pages for recording notes or memoranda', 'name': 'notebook'}, {'frequency': 'c', 'id': 737, 'synset': 'notepad.n.01', 'synonyms': ['notepad'], 'def': 'a pad of paper for keeping notes', 'name': 'notepad'}, {'frequency': 'c', 'id': 738, 'synset': 'nut.n.03', 'synonyms': ['nut'], 'def': 'a small metal block (usually square or hexagonal) with internal screw thread to be fitted onto a bolt', 'name': 'nut'}, {'frequency': 'r', 'id': 739, 'synset': 'nutcracker.n.01', 'synonyms': ['nutcracker'], 'def': 'a hand tool used to crack nuts open', 'name': 'nutcracker'}, {'frequency': 'c', 'id': 740, 'synset': 'oar.n.01', 'synonyms': ['oar'], 'def': 'an implement used to propel or steer a boat', 'name': 'oar'}, {'frequency': 'r', 'id': 741, 'synset': 'octopus.n.01', 'synonyms': ['octopus_(food)'], 'def': 'tentacles of octopus prepared as food', 'name': 'octopus_(food)'}, {'frequency': 'r', 'id': 742, 'synset': 'octopus.n.02', 'synonyms': ['octopus_(animal)'], 'def': 'bottom-living cephalopod having a soft oval body with eight long tentacles', 'name': 'octopus_(animal)'}, {'frequency': 'c', 'id': 743, 'synset': 'oil_lamp.n.01', 'synonyms': ['oil_lamp', 'kerosene_lamp', 'kerosine_lamp'], 'def': 'a lamp that burns oil (as kerosine) for light', 'name': 'oil_lamp'}, {'frequency': 'c', 'id': 744, 'synset': 'olive_oil.n.01', 'synonyms': ['olive_oil'], 'def': 'oil from olives', 'name': 'olive_oil'}, {'frequency': 'r', 'id': 745, 'synset': 'omelet.n.01', 'synonyms': ['omelet', 'omelette'], 'def': 'beaten eggs cooked until just set; may be folded around e.g. ham or cheese or jelly', 'name': 'omelet'}, {'frequency': 'f', 'id': 746, 'synset': 'onion.n.01', 'synonyms': ['onion'], 'def': 'the bulb of an onion plant', 'name': 'onion'}, {'frequency': 'f', 'id': 747, 'synset': 'orange.n.01', 'synonyms': ['orange_(fruit)'], 'def': 'orange (FRUIT of an orange tree)', 'name': 'orange_(fruit)'}, {'frequency': 'c', 'id': 748, 'synset': 'orange_juice.n.01', 'synonyms': ['orange_juice'], 'def': 'bottled or freshly squeezed juice of oranges', 'name': 'orange_juice'}, {'frequency': 'r', 'id': 749, 'synset': 'oregano.n.01', 'synonyms': ['oregano', 'marjoram'], 'def': 'aromatic Eurasian perennial herb used in cooking and baking', 'name': 'oregano'}, {'frequency': 'c', 'id': 750, 'synset': 'ostrich.n.02', 'synonyms': ['ostrich'], 'def': 'fast-running African flightless bird with two-toed feet; largest living bird', 'name': 'ostrich'}, {'frequency': 'c', 'id': 751, 'synset': 'ottoman.n.03', 'synonyms': ['ottoman', 'pouf', 'pouffe', 'hassock'], 'def': 'thick cushion used as a seat', 'name': 'ottoman'}, {'frequency': 'c', 'id': 752, 'synset': 'overall.n.01', 'synonyms': ['overalls_(clothing)'], 'def': 'work clothing consisting of denim trousers usually with a bib and shoulder straps', 'name': 'overalls_(clothing)'}, {'frequency': 'c', 'id': 753, 'synset': 'owl.n.01', 'synonyms': ['owl'], 'def': 'nocturnal bird of prey with hawk-like beak and claws and large head with front-facing eyes', 'name': 'owl'}, {'frequency': 'c', 'id': 754, 'synset': 'packet.n.03', 'synonyms': ['packet'], 'def': 'a small package or bundle', 'name': 'packet'}, {'frequency': 'r', 'id': 755, 'synset': 'pad.n.03', 'synonyms': ['inkpad', 'inking_pad', 'stamp_pad'], 'def': 'absorbent material saturated with ink used to transfer ink evenly to a rubber stamp', 'name': 'inkpad'}, {'frequency': 'c', 'id': 756, 'synset': 'pad.n.04', 'synonyms': ['pad'], 'def': 'a flat mass of soft material used for protection, stuffing, or comfort', 'name': 'pad'}, {'frequency': 'c', 'id': 757, 'synset': 'paddle.n.04', 'synonyms': ['paddle', 'boat_paddle'], 'def': 'a short light oar used without an oarlock to propel a canoe or small boat', 'name': 'paddle'}, {'frequency': 'c', 'id': 758, 'synset': 'padlock.n.01', 'synonyms': ['padlock'], 'def': 'a detachable, portable lock', 'name': 'padlock'}, {'frequency': 'r', 'id': 759, 'synset': 'paintbox.n.01', 'synonyms': ['paintbox'], 'def': "a box containing a collection of cubes or tubes of artists' paint", 'name': 'paintbox'}, {'frequency': 'c', 'id': 760, 'synset': 'paintbrush.n.01', 'synonyms': ['paintbrush'], 'def': 'a brush used as an applicator to apply paint', 'name': 'paintbrush'}, {'frequency': 'f', 'id': 761, 'synset': 'painting.n.01', 'synonyms': ['painting'], 'def': 'graphic art consisting of an artistic composition made by applying paints to a surface', 'name': 'painting'}, {'frequency': 'c', 'id': 762, 'synset': 'pajama.n.02', 'synonyms': ['pajamas', 'pyjamas'], 'def': 'loose-fitting nightclothes worn for sleeping or lounging', 'name': 'pajamas'}, {'frequency': 'c', 'id': 763, 'synset': 'palette.n.02', 'synonyms': ['palette', 'pallet'], 'def': 'board that provides a flat surface on which artists mix paints and the range of colors used', 'name': 'palette'}, {'frequency': 'f', 'id': 764, 'synset': 'pan.n.01', 'synonyms': ['pan_(for_cooking)', 'cooking_pan'], 'def': 'cooking utensil consisting of a wide metal vessel', 'name': 'pan_(for_cooking)'}, {'frequency': 'r', 'id': 765, 'synset': 'pan.n.03', 'synonyms': ['pan_(metal_container)'], 'def': 'shallow container made of metal', 'name': 'pan_(metal_container)'}, {'frequency': 'c', 'id': 766, 'synset': 'pancake.n.01', 'synonyms': ['pancake'], 'def': 'a flat cake of thin batter fried on both sides on a griddle', 'name': 'pancake'}, {'frequency': 'r', 'id': 767, 'synset': 'pantyhose.n.01', 'synonyms': ['pantyhose'], 'def': "a woman's tights consisting of underpants and stockings", 'name': 'pantyhose'}, {'frequency': 'r', 'id': 768, 'synset': 'papaya.n.02', 'synonyms': ['papaya'], 'def': 'large oval melon-like tropical fruit with yellowish flesh', 'name': 'papaya'}, {'frequency': 'r', 'id': 769, 'synset': 'paper_clip.n.01', 'synonyms': ['paperclip'], 'def': 'a wire or plastic clip for holding sheets of paper together', 'name': 'paperclip'}, {'frequency': 'f', 'id': 770, 'synset': 'paper_plate.n.01', 'synonyms': ['paper_plate'], 'def': 'a disposable plate made of cardboard', 'name': 'paper_plate'}, {'frequency': 'f', 'id': 771, 'synset': 'paper_towel.n.01', 'synonyms': ['paper_towel'], 'def': 'a disposable towel made of absorbent paper', 'name': 'paper_towel'}, {'frequency': 'r', 'id': 772, 'synset': 'paperback_book.n.01', 'synonyms': ['paperback_book', 'paper-back_book', 'softback_book', 'soft-cover_book'], 'def': 'a book with paper covers', 'name': 'paperback_book'}, {'frequency': 'r', 'id': 773, 'synset': 'paperweight.n.01', 'synonyms': ['paperweight'], 'def': 'a weight used to hold down a stack of papers', 'name': 'paperweight'}, {'frequency': 'c', 'id': 774, 'synset': 'parachute.n.01', 'synonyms': ['parachute'], 'def': 'rescue equipment consisting of a device that fills with air and retards your fall', 'name': 'parachute'}, {'frequency': 'r', 'id': 775, 'synset': 'parakeet.n.01', 'synonyms': ['parakeet', 'parrakeet', 'parroket', 'paraquet', 'paroquet', 'parroquet'], 'def': 'any of numerous small slender long-tailed parrots', 'name': 'parakeet'}, {'frequency': 'c', 'id': 776, 'synset': 'parasail.n.01', 'synonyms': ['parasail_(sports)'], 'def': 'parachute that will lift a person up into the air when it is towed by a motorboat or a car', 'name': 'parasail_(sports)'}, {'frequency': 'r', 'id': 777, 'synset': 'parchment.n.01', 'synonyms': ['parchment'], 'def': 'a superior paper resembling sheepskin', 'name': 'parchment'}, {'frequency': 'r', 'id': 778, 'synset': 'parka.n.01', 'synonyms': ['parka', 'anorak'], 'def': "a kind of heavy jacket (`windcheater' is a British term)", 'name': 'parka'}, {'frequency': 'f', 'id': 779, 'synset': 'parking_meter.n.01', 'synonyms': ['parking_meter'], 'def': 'a coin-operated timer located next to a parking space', 'name': 'parking_meter'}, {'frequency': 'c', 'id': 780, 'synset': 'parrot.n.01', 'synonyms': ['parrot'], 'def': 'usually brightly colored tropical birds with short hooked beaks and the ability to mimic sounds', 'name': 'parrot'}, {'frequency': 'c', 'id': 781, 'synset': 'passenger_car.n.01', 'synonyms': ['passenger_car_(part_of_a_train)', 'coach_(part_of_a_train)'], 'def': 'a railcar where passengers ride', 'name': 'passenger_car_(part_of_a_train)'}, {'frequency': 'r', 'id': 782, 'synset': 'passenger_ship.n.01', 'synonyms': ['passenger_ship'], 'def': 'a ship built to carry passengers', 'name': 'passenger_ship'}, {'frequency': 'r', 'id': 783, 'synset': 'passport.n.02', 'synonyms': ['passport'], 'def': 'a document issued by a country to a citizen allowing that person to travel abroad and re-enter the home country', 'name': 'passport'}, {'frequency': 'f', 'id': 784, 'synset': 'pastry.n.02', 'synonyms': ['pastry'], 'def': 'any of various baked foods made of dough or batter', 'name': 'pastry'}, {'frequency': 'r', 'id': 785, 'synset': 'patty.n.01', 'synonyms': ['patty_(food)'], 'def': 'small flat mass of chopped food', 'name': 'patty_(food)'}, {'frequency': 'c', 'id': 786, 'synset': 'pea.n.01', 'synonyms': ['pea_(food)'], 'def': 'seed of a pea plant used for food', 'name': 'pea_(food)'}, {'frequency': 'c', 'id': 787, 'synset': 'peach.n.03', 'synonyms': ['peach'], 'def': 'downy juicy fruit with sweet yellowish or whitish flesh', 'name': 'peach'}, {'frequency': 'c', 'id': 788, 'synset': 'peanut_butter.n.01', 'synonyms': ['peanut_butter'], 'def': 'a spread made from ground peanuts', 'name': 'peanut_butter'}, {'frequency': 'c', 'id': 789, 'synset': 'pear.n.01', 'synonyms': ['pear'], 'def': 'sweet juicy gritty-textured fruit available in many varieties', 'name': 'pear'}, {'frequency': 'r', 'id': 790, 'synset': 'peeler.n.03', 'synonyms': ['peeler_(tool_for_fruit_and_vegetables)'], 'def': 'a device for peeling vegetables or fruits', 'name': 'peeler_(tool_for_fruit_and_vegetables)'}, {'frequency': 'r', 'id': 791, 'synset': 'pegboard.n.01', 'synonyms': ['pegboard'], 'def': 'a board perforated with regularly spaced holes into which pegs can be fitted', 'name': 'pegboard'}, {'frequency': 'c', 'id': 792, 'synset': 'pelican.n.01', 'synonyms': ['pelican'], 'def': 'large long-winged warm-water seabird having a large bill with a distensible pouch for fish', 'name': 'pelican'}, {'frequency': 'f', 'id': 793, 'synset': 'pen.n.01', 'synonyms': ['pen'], 'def': 'a writing implement with a point from which ink flows', 'name': 'pen'}, {'frequency': 'c', 'id': 794, 'synset': 'pencil.n.01', 'synonyms': ['pencil'], 'def': 'a thin cylindrical pointed writing implement made of wood and graphite', 'name': 'pencil'}, {'frequency': 'r', 'id': 795, 'synset': 'pencil_box.n.01', 'synonyms': ['pencil_box', 'pencil_case'], 'def': 'a box for holding pencils', 'name': 'pencil_box'}, {'frequency': 'r', 'id': 796, 'synset': 'pencil_sharpener.n.01', 'synonyms': ['pencil_sharpener'], 'def': 'a rotary implement for sharpening the point on pencils', 'name': 'pencil_sharpener'}, {'frequency': 'r', 'id': 797, 'synset': 'pendulum.n.01', 'synonyms': ['pendulum'], 'def': 'an apparatus consisting of an object mounted so that it swings freely under the influence of gravity', 'name': 'pendulum'}, {'frequency': 'c', 'id': 798, 'synset': 'penguin.n.01', 'synonyms': ['penguin'], 'def': 'short-legged flightless birds of cold southern regions having webbed feet and wings modified as flippers', 'name': 'penguin'}, {'frequency': 'r', 'id': 799, 'synset': 'pennant.n.02', 'synonyms': ['pennant'], 'def': 'a flag longer than it is wide (and often tapering)', 'name': 'pennant'}, {'frequency': 'r', 'id': 800, 'synset': 'penny.n.02', 'synonyms': ['penny_(coin)'], 'def': 'a coin worth one-hundredth of the value of the basic unit', 'name': 'penny_(coin)'}, {'frequency': 'c', 'id': 801, 'synset': 'pepper.n.03', 'synonyms': ['pepper', 'peppercorn'], 'def': 'pungent seasoning from the berry of the common pepper plant; whole or ground', 'name': 'pepper'}, {'frequency': 'c', 'id': 802, 'synset': 'pepper_mill.n.01', 'synonyms': ['pepper_mill', 'pepper_grinder'], 'def': 'a mill for grinding pepper', 'name': 'pepper_mill'}, {'frequency': 'c', 'id': 803, 'synset': 'perfume.n.02', 'synonyms': ['perfume'], 'def': 'a toiletry that emits and diffuses a fragrant odor', 'name': 'perfume'}, {'frequency': 'r', 'id': 804, 'synset': 'persimmon.n.02', 'synonyms': ['persimmon'], 'def': 'orange fruit resembling a plum; edible when fully ripe', 'name': 'persimmon'}, {'frequency': 'f', 'id': 805, 'synset': 'person.n.01', 'synonyms': ['baby', 'child', 'boy', 'girl', 'man', 'woman', 'person', 'human'], 'def': 'a human being', 'name': 'baby'}, {'frequency': 'r', 'id': 806, 'synset': 'pet.n.01', 'synonyms': ['pet'], 'def': 'a domesticated animal kept for companionship or amusement', 'name': 'pet'}, {'frequency': 'r', 'id': 807, 'synset': 'petfood.n.01', 'synonyms': ['petfood', 'pet-food'], 'def': 'food prepared for animal pets', 'name': 'petfood'}, {'frequency': 'r', 'id': 808, 'synset': 'pew.n.01', 'synonyms': ['pew_(church_bench)', 'church_bench'], 'def': 'long bench with backs; used in church by the congregation', 'name': 'pew_(church_bench)'}, {'frequency': 'r', 'id': 809, 'synset': 'phonebook.n.01', 'synonyms': ['phonebook', 'telephone_book', 'telephone_directory'], 'def': 'a directory containing an alphabetical list of telephone subscribers and their telephone numbers', 'name': 'phonebook'}, {'frequency': 'c', 'id': 810, 'synset': 'phonograph_record.n.01', 'synonyms': ['phonograph_record', 'phonograph_recording', 'record_(phonograph_recording)'], 'def': 'sound recording consisting of a typically black disk with a continuous groove', 'name': 'phonograph_record'}, {'frequency': 'c', 'id': 811, 'synset': 'piano.n.01', 'synonyms': ['piano'], 'def': 'a keyboard instrument that is played by depressing keys that cause hammers to strike tuned strings and produce sounds', 'name': 'piano'}, {'frequency': 'f', 'id': 812, 'synset': 'pickle.n.01', 'synonyms': ['pickle'], 'def': 'vegetables (especially cucumbers) preserved in brine or vinegar', 'name': 'pickle'}, {'frequency': 'f', 'id': 813, 'synset': 'pickup.n.01', 'synonyms': ['pickup_truck'], 'def': 'a light truck with an open body and low sides and a tailboard', 'name': 'pickup_truck'}, {'frequency': 'c', 'id': 814, 'synset': 'pie.n.01', 'synonyms': ['pie'], 'def': 'dish baked in pastry-lined pan often with a pastry top', 'name': 'pie'}, {'frequency': 'c', 'id': 815, 'synset': 'pigeon.n.01', 'synonyms': ['pigeon'], 'def': 'wild and domesticated birds having a heavy body and short legs', 'name': 'pigeon'}, {'frequency': 'r', 'id': 816, 'synset': 'piggy_bank.n.01', 'synonyms': ['piggy_bank', 'penny_bank'], 'def': "a child's coin bank (often shaped like a pig)", 'name': 'piggy_bank'}, {'frequency': 'f', 'id': 817, 'synset': 'pillow.n.01', 'synonyms': ['pillow'], 'def': 'a cushion to support the head of a sleeping person', 'name': 'pillow'}, {'frequency': 'r', 'id': 818, 'synset': 'pin.n.09', 'synonyms': ['pin_(non_jewelry)'], 'def': 'a small slender (often pointed) piece of wood or metal used to support or fasten or attach things', 'name': 'pin_(non_jewelry)'}, {'frequency': 'f', 'id': 819, 'synset': 'pineapple.n.02', 'synonyms': ['pineapple'], 'def': 'large sweet fleshy tropical fruit with a tuft of stiff leaves', 'name': 'pineapple'}, {'frequency': 'c', 'id': 820, 'synset': 'pinecone.n.01', 'synonyms': ['pinecone'], 'def': 'the seed-producing cone of a pine tree', 'name': 'pinecone'}, {'frequency': 'r', 'id': 821, 'synset': 'ping-pong_ball.n.01', 'synonyms': ['ping-pong_ball'], 'def': 'light hollow ball used in playing table tennis', 'name': 'ping-pong_ball'}, {'frequency': 'r', 'id': 822, 'synset': 'pinwheel.n.03', 'synonyms': ['pinwheel'], 'def': 'a toy consisting of vanes of colored paper or plastic that is pinned to a stick and spins when it is pointed into the wind', 'name': 'pinwheel'}, {'frequency': 'r', 'id': 823, 'synset': 'pipe.n.01', 'synonyms': ['tobacco_pipe'], 'def': 'a tube with a small bowl at one end; used for smoking tobacco', 'name': 'tobacco_pipe'}, {'frequency': 'f', 'id': 824, 'synset': 'pipe.n.02', 'synonyms': ['pipe', 'piping'], 'def': 'a long tube made of metal or plastic that is used to carry water or oil or gas etc.', 'name': 'pipe'}, {'frequency': 'r', 'id': 825, 'synset': 'pistol.n.01', 'synonyms': ['pistol', 'handgun'], 'def': 'a firearm that is held and fired with one hand', 'name': 'pistol'}, {'frequency': 'r', 'id': 826, 'synset': 'pita.n.01', 'synonyms': ['pita_(bread)', 'pocket_bread'], 'def': 'usually small round bread that can open into a pocket for filling', 'name': 'pita_(bread)'}, {'frequency': 'f', 'id': 827, 'synset': 'pitcher.n.02', 'synonyms': ['pitcher_(vessel_for_liquid)', 'ewer'], 'def': 'an open vessel with a handle and a spout for pouring', 'name': 'pitcher_(vessel_for_liquid)'}, {'frequency': 'r', 'id': 828, 'synset': 'pitchfork.n.01', 'synonyms': ['pitchfork'], 'def': 'a long-handled hand tool with sharp widely spaced prongs for lifting and pitching hay', 'name': 'pitchfork'}, {'frequency': 'f', 'id': 829, 'synset': 'pizza.n.01', 'synonyms': ['pizza'], 'def': 'Italian open pie made of thin bread dough spread with a spiced mixture of e.g. tomato sauce and cheese', 'name': 'pizza'}, {'frequency': 'f', 'id': 830, 'synset': 'place_mat.n.01', 'synonyms': ['place_mat'], 'def': 'a mat placed on a table for an individual place setting', 'name': 'place_mat'}, {'frequency': 'f', 'id': 831, 'synset': 'plate.n.04', 'synonyms': ['plate'], 'def': 'dish on which food is served or from which food is eaten', 'name': 'plate'}, {'frequency': 'c', 'id': 832, 'synset': 'platter.n.01', 'synonyms': ['platter'], 'def': 'a large shallow dish used for serving food', 'name': 'platter'}, {'frequency': 'r', 'id': 833, 'synset': 'playing_card.n.01', 'synonyms': ['playing_card'], 'def': 'one of a pack of cards that are used to play card games', 'name': 'playing_card'}, {'frequency': 'r', 'id': 834, 'synset': 'playpen.n.01', 'synonyms': ['playpen'], 'def': 'a portable enclosure in which babies may be left to play', 'name': 'playpen'}, {'frequency': 'c', 'id': 835, 'synset': 'pliers.n.01', 'synonyms': ['pliers', 'plyers'], 'def': 'a gripping hand tool with two hinged arms and (usually) serrated jaws', 'name': 'pliers'}, {'frequency': 'r', 'id': 836, 'synset': 'plow.n.01', 'synonyms': ['plow_(farm_equipment)', 'plough_(farm_equipment)'], 'def': 'a farm tool having one or more heavy blades to break the soil and cut a furrow prior to sowing', 'name': 'plow_(farm_equipment)'}, {'frequency': 'r', 'id': 837, 'synset': 'pocket_watch.n.01', 'synonyms': ['pocket_watch'], 'def': 'a watch that is carried in a small watch pocket', 'name': 'pocket_watch'}, {'frequency': 'c', 'id': 838, 'synset': 'pocketknife.n.01', 'synonyms': ['pocketknife'], 'def': 'a knife with a blade that folds into the handle; suitable for carrying in the pocket', 'name': 'pocketknife'}, {'frequency': 'c', 'id': 839, 'synset': 'poker.n.01', 'synonyms': ['poker_(fire_stirring_tool)', 'stove_poker', 'fire_hook'], 'def': 'fire iron consisting of a metal rod with a handle; used to stir a fire', 'name': 'poker_(fire_stirring_tool)'}, {'frequency': 'f', 'id': 840, 'synset': 'pole.n.01', 'synonyms': ['pole', 'post'], 'def': 'a long (usually round) rod of wood or metal or plastic', 'name': 'pole'}, {'frequency': 'r', 'id': 841, 'synset': 'police_van.n.01', 'synonyms': ['police_van', 'police_wagon', 'paddy_wagon', 'patrol_wagon'], 'def': 'van used by police to transport prisoners', 'name': 'police_van'}, {'frequency': 'f', 'id': 842, 'synset': 'polo_shirt.n.01', 'synonyms': ['polo_shirt', 'sport_shirt'], 'def': 'a shirt with short sleeves designed for comfort and casual wear', 'name': 'polo_shirt'}, {'frequency': 'r', 'id': 843, 'synset': 'poncho.n.01', 'synonyms': ['poncho'], 'def': 'a blanket-like cloak with a hole in the center for the head', 'name': 'poncho'}, {'frequency': 'c', 'id': 844, 'synset': 'pony.n.05', 'synonyms': ['pony'], 'def': 'any of various breeds of small gentle horses usually less than five feet high at the shoulder', 'name': 'pony'}, {'frequency': 'r', 'id': 845, 'synset': 'pool_table.n.01', 'synonyms': ['pool_table', 'billiard_table', 'snooker_table'], 'def': 'game equipment consisting of a heavy table on which pool is played', 'name': 'pool_table'}, {'frequency': 'f', 'id': 846, 'synset': 'pop.n.02', 'synonyms': ['pop_(soda)', 'soda_(pop)', 'tonic', 'soft_drink'], 'def': 'a sweet drink containing carbonated water and flavoring', 'name': 'pop_(soda)'}, {'frequency': 'r', 'id': 847, 'synset': 'portrait.n.02', 'synonyms': ['portrait', 'portrayal'], 'def': 'any likeness of a person, in any medium', 'name': 'portrait'}, {'frequency': 'c', 'id': 848, 'synset': 'postbox.n.01', 'synonyms': ['postbox_(public)', 'mailbox_(public)'], 'def': 'public box for deposit of mail', 'name': 'postbox_(public)'}, {'frequency': 'c', 'id': 849, 'synset': 'postcard.n.01', 'synonyms': ['postcard', 'postal_card', 'mailing-card'], 'def': 'a card for sending messages by post without an envelope', 'name': 'postcard'}, {'frequency': 'f', 'id': 850, 'synset': 'poster.n.01', 'synonyms': ['poster', 'placard'], 'def': 'a sign posted in a public place as an advertisement', 'name': 'poster'}, {'frequency': 'f', 'id': 851, 'synset': 'pot.n.01', 'synonyms': ['pot'], 'def': 'metal or earthenware cooking vessel that is usually round and deep; often has a handle and lid', 'name': 'pot'}, {'frequency': 'f', 'id': 852, 'synset': 'pot.n.04', 'synonyms': ['flowerpot'], 'def': 'a container in which plants are cultivated', 'name': 'flowerpot'}, {'frequency': 'f', 'id': 853, 'synset': 'potato.n.01', 'synonyms': ['potato'], 'def': 'an edible tuber native to South America', 'name': 'potato'}, {'frequency': 'c', 'id': 854, 'synset': 'potholder.n.01', 'synonyms': ['potholder'], 'def': 'an insulated pad for holding hot pots', 'name': 'potholder'}, {'frequency': 'c', 'id': 855, 'synset': 'pottery.n.01', 'synonyms': ['pottery', 'clayware'], 'def': 'ceramic ware made from clay and baked in a kiln', 'name': 'pottery'}, {'frequency': 'c', 'id': 856, 'synset': 'pouch.n.01', 'synonyms': ['pouch'], 'def': 'a small or medium size container for holding or carrying things', 'name': 'pouch'}, {'frequency': 'r', 'id': 857, 'synset': 'power_shovel.n.01', 'synonyms': ['power_shovel', 'excavator', 'digger'], 'def': 'a machine for excavating', 'name': 'power_shovel'}, {'frequency': 'c', 'id': 858, 'synset': 'prawn.n.01', 'synonyms': ['prawn', 'shrimp'], 'def': 'any of various edible decapod crustaceans', 'name': 'prawn'}, {'frequency': 'f', 'id': 859, 'synset': 'printer.n.03', 'synonyms': ['printer', 'printing_machine'], 'def': 'a machine that prints', 'name': 'printer'}, {'frequency': 'c', 'id': 860, 'synset': 'projectile.n.01', 'synonyms': ['projectile_(weapon)', 'missile'], 'def': 'a weapon that is forcibly thrown or projected at a targets', 'name': 'projectile_(weapon)'}, {'frequency': 'c', 'id': 861, 'synset': 'projector.n.02', 'synonyms': ['projector'], 'def': 'an optical instrument that projects an enlarged image onto a screen', 'name': 'projector'}, {'frequency': 'f', 'id': 862, 'synset': 'propeller.n.01', 'synonyms': ['propeller', 'propellor'], 'def': 'a mechanical device that rotates to push against air or water', 'name': 'propeller'}, {'frequency': 'r', 'id': 863, 'synset': 'prune.n.01', 'synonyms': ['prune'], 'def': 'dried plum', 'name': 'prune'}, {'frequency': 'r', 'id': 864, 'synset': 'pudding.n.01', 'synonyms': ['pudding'], 'def': 'any of various soft thick unsweetened baked dishes', 'name': 'pudding'}, {'frequency': 'r', 'id': 865, 'synset': 'puffer.n.02', 'synonyms': ['puffer_(fish)', 'pufferfish', 'blowfish', 'globefish'], 'def': 'fishes whose elongated spiny body can inflate itself with water or air to form a globe', 'name': 'puffer_(fish)'}, {'frequency': 'r', 'id': 866, 'synset': 'puffin.n.01', 'synonyms': ['puffin'], 'def': 'seabirds having short necks and brightly colored compressed bills', 'name': 'puffin'}, {'frequency': 'r', 'id': 867, 'synset': 'pug.n.01', 'synonyms': ['pug-dog'], 'def': 'small compact smooth-coated breed of Asiatic origin having a tightly curled tail and broad flat wrinkled muzzle', 'name': 'pug-dog'}, {'frequency': 'c', 'id': 868, 'synset': 'pumpkin.n.02', 'synonyms': ['pumpkin'], 'def': 'usually large pulpy deep-yellow round fruit of the squash family maturing in late summer or early autumn', 'name': 'pumpkin'}, {'frequency': 'r', 'id': 869, 'synset': 'punch.n.03', 'synonyms': ['puncher'], 'def': 'a tool for making holes or indentations', 'name': 'puncher'}, {'frequency': 'r', 'id': 870, 'synset': 'puppet.n.01', 'synonyms': ['puppet', 'marionette'], 'def': 'a small figure of a person operated from above with strings by a puppeteer', 'name': 'puppet'}, {'frequency': 'r', 'id': 871, 'synset': 'puppy.n.01', 'synonyms': ['puppy'], 'def': 'a young dog', 'name': 'puppy'}, {'frequency': 'r', 'id': 872, 'synset': 'quesadilla.n.01', 'synonyms': ['quesadilla'], 'def': 'a tortilla that is filled with cheese and heated', 'name': 'quesadilla'}, {'frequency': 'r', 'id': 873, 'synset': 'quiche.n.02', 'synonyms': ['quiche'], 'def': 'a tart filled with rich unsweetened custard; often contains other ingredients (as cheese or ham or seafood or vegetables)', 'name': 'quiche'}, {'frequency': 'f', 'id': 874, 'synset': 'quilt.n.01', 'synonyms': ['quilt', 'comforter'], 'def': 'bedding made of two layers of cloth filled with stuffing and stitched together', 'name': 'quilt'}, {'frequency': 'c', 'id': 875, 'synset': 'rabbit.n.01', 'synonyms': ['rabbit'], 'def': 'any of various burrowing animals of the family Leporidae having long ears and short tails', 'name': 'rabbit'}, {'frequency': 'r', 'id': 876, 'synset': 'racer.n.02', 'synonyms': ['race_car', 'racing_car'], 'def': 'a fast car that competes in races', 'name': 'race_car'}, {'frequency': 'c', 'id': 877, 'synset': 'racket.n.04', 'synonyms': ['racket', 'racquet'], 'def': 'a sports implement used to strike a ball in various games', 'name': 'racket'}, {'frequency': 'r', 'id': 878, 'synset': 'radar.n.01', 'synonyms': ['radar'], 'def': 'measuring instrument in which the echo of a pulse of microwave radiation is used to detect and locate distant objects', 'name': 'radar'}, {'frequency': 'c', 'id': 879, 'synset': 'radiator.n.03', 'synonyms': ['radiator'], 'def': 'a mechanism consisting of a metal honeycomb through which hot fluids circulate', 'name': 'radiator'}, {'frequency': 'c', 'id': 880, 'synset': 'radio_receiver.n.01', 'synonyms': ['radio_receiver', 'radio_set', 'radio', 'tuner_(radio)'], 'def': 'an electronic receiver that detects and demodulates and amplifies transmitted radio signals', 'name': 'radio_receiver'}, {'frequency': 'c', 'id': 881, 'synset': 'radish.n.03', 'synonyms': ['radish', 'daikon'], 'def': 'pungent edible root of any of various cultivated radish plants', 'name': 'radish'}, {'frequency': 'c', 'id': 882, 'synset': 'raft.n.01', 'synonyms': ['raft'], 'def': 'a flat float (usually made of logs or planks) that can be used for transport or as a platform for swimmers', 'name': 'raft'}, {'frequency': 'r', 'id': 883, 'synset': 'rag_doll.n.01', 'synonyms': ['rag_doll'], 'def': 'a cloth doll that is stuffed and (usually) painted', 'name': 'rag_doll'}, {'frequency': 'c', 'id': 884, 'synset': 'raincoat.n.01', 'synonyms': ['raincoat', 'waterproof_jacket'], 'def': 'a water-resistant coat', 'name': 'raincoat'}, {'frequency': 'c', 'id': 885, 'synset': 'ram.n.05', 'synonyms': ['ram_(animal)'], 'def': 'uncastrated adult male sheep', 'name': 'ram_(animal)'}, {'frequency': 'c', 'id': 886, 'synset': 'raspberry.n.02', 'synonyms': ['raspberry'], 'def': 'red or black edible aggregate berries usually smaller than the related blackberries', 'name': 'raspberry'}, {'frequency': 'r', 'id': 887, 'synset': 'rat.n.01', 'synonyms': ['rat'], 'def': 'any of various long-tailed rodents similar to but larger than a mouse', 'name': 'rat'}, {'frequency': 'c', 'id': 888, 'synset': 'razorblade.n.01', 'synonyms': ['razorblade'], 'def': 'a blade that has very sharp edge', 'name': 'razorblade'}, {'frequency': 'c', 'id': 889, 'synset': 'reamer.n.01', 'synonyms': ['reamer_(juicer)', 'juicer', 'juice_reamer'], 'def': 'a squeezer with a conical ridged center that is used for squeezing juice from citrus fruit', 'name': 'reamer_(juicer)'}, {'frequency': 'f', 'id': 890, 'synset': 'rearview_mirror.n.01', 'synonyms': ['rearview_mirror'], 'def': 'car mirror that reflects the view out of the rear window', 'name': 'rearview_mirror'}, {'frequency': 'c', 'id': 891, 'synset': 'receipt.n.02', 'synonyms': ['receipt'], 'def': 'an acknowledgment (usually tangible) that payment has been made', 'name': 'receipt'}, {'frequency': 'c', 'id': 892, 'synset': 'recliner.n.01', 'synonyms': ['recliner', 'reclining_chair', 'lounger_(chair)'], 'def': 'an armchair whose back can be lowered and foot can be raised to allow the sitter to recline in it', 'name': 'recliner'}, {'frequency': 'r', 'id': 893, 'synset': 'record_player.n.01', 'synonyms': ['record_player', 'phonograph_(record_player)', 'turntable'], 'def': 'machine in which rotating records cause a stylus to vibrate and the vibrations are amplified acoustically or electronically', 'name': 'record_player'}, {'frequency': 'r', 'id': 894, 'synset': 'red_cabbage.n.02', 'synonyms': ['red_cabbage'], 'def': 'compact head of purplish-red leaves', 'name': 'red_cabbage'}, {'frequency': 'f', 'id': 895, 'synset': 'reflector.n.01', 'synonyms': ['reflector'], 'def': 'device that reflects light, radiation, etc.', 'name': 'reflector'}, {'frequency': 'f', 'id': 896, 'synset': 'remote_control.n.01', 'synonyms': ['remote_control'], 'def': 'a device that can be used to control a machine or apparatus from a distance', 'name': 'remote_control'}, {'frequency': 'c', 'id': 897, 'synset': 'rhinoceros.n.01', 'synonyms': ['rhinoceros'], 'def': 'massive powerful herbivorous odd-toed ungulate of southeast Asia and Africa having very thick skin and one or two horns on the snout', 'name': 'rhinoceros'}, {'frequency': 'r', 'id': 898, 'synset': 'rib.n.03', 'synonyms': ['rib_(food)'], 'def': 'cut of meat including one or more ribs', 'name': 'rib_(food)'}, {'frequency': 'r', 'id': 899, 'synset': 'rifle.n.01', 'synonyms': ['rifle'], 'def': 'a shoulder firearm with a long barrel', 'name': 'rifle'}, {'frequency': 'f', 'id': 900, 'synset': 'ring.n.08', 'synonyms': ['ring'], 'def': 'jewelry consisting of a circlet of precious metal (often set with jewels) worn on the finger', 'name': 'ring'}, {'frequency': 'r', 'id': 901, 'synset': 'river_boat.n.01', 'synonyms': ['river_boat'], 'def': 'a boat used on rivers or to ply a river', 'name': 'river_boat'}, {'frequency': 'r', 'id': 902, 'synset': 'road_map.n.02', 'synonyms': ['road_map'], 'def': '(NOT A ROAD) a MAP showing roads (for automobile travel)', 'name': 'road_map'}, {'frequency': 'c', 'id': 903, 'synset': 'robe.n.01', 'synonyms': ['robe'], 'def': 'any loose flowing garment', 'name': 'robe'}, {'frequency': 'c', 'id': 904, 'synset': 'rocking_chair.n.01', 'synonyms': ['rocking_chair'], 'def': 'a chair mounted on rockers', 'name': 'rocking_chair'}, {'frequency': 'r', 'id': 905, 'synset': 'roller_skate.n.01', 'synonyms': ['roller_skate'], 'def': 'a shoe with pairs of rollers (small hard wheels) fixed to the sole', 'name': 'roller_skate'}, {'frequency': 'r', 'id': 906, 'synset': 'rollerblade.n.01', 'synonyms': ['Rollerblade'], 'def': 'an in-line variant of a roller skate', 'name': 'Rollerblade'}, {'frequency': 'c', 'id': 907, 'synset': 'rolling_pin.n.01', 'synonyms': ['rolling_pin'], 'def': 'utensil consisting of a cylinder (usually of wood) with a handle at each end; used to roll out dough', 'name': 'rolling_pin'}, {'frequency': 'r', 'id': 908, 'synset': 'root_beer.n.01', 'synonyms': ['root_beer'], 'def': 'carbonated drink containing extracts of roots and herbs', 'name': 'root_beer'}, {'frequency': 'c', 'id': 909, 'synset': 'router.n.02', 'synonyms': ['router_(computer_equipment)'], 'def': 'a device that forwards data packets between computer networks', 'name': 'router_(computer_equipment)'}, {'frequency': 'f', 'id': 910, 'synset': 'rubber_band.n.01', 'synonyms': ['rubber_band', 'elastic_band'], 'def': 'a narrow band of elastic rubber used to hold things (such as papers) together', 'name': 'rubber_band'}, {'frequency': 'c', 'id': 911, 'synset': 'runner.n.08', 'synonyms': ['runner_(carpet)'], 'def': 'a long narrow carpet', 'name': 'runner_(carpet)'}, {'frequency': 'f', 'id': 912, 'synset': 'sack.n.01', 'synonyms': ['plastic_bag', 'paper_bag'], 'def': "a bag made of paper or plastic for holding customer's purchases", 'name': 'plastic_bag'}, {'frequency': 'f', 'id': 913, 'synset': 'saddle.n.01', 'synonyms': ['saddle_(on_an_animal)'], 'def': 'a seat for the rider of a horse or camel', 'name': 'saddle_(on_an_animal)'}, {'frequency': 'f', 'id': 914, 'synset': 'saddle_blanket.n.01', 'synonyms': ['saddle_blanket', 'saddlecloth', 'horse_blanket'], 'def': 'stable gear consisting of a blanket placed under the saddle', 'name': 'saddle_blanket'}, {'frequency': 'c', 'id': 915, 'synset': 'saddlebag.n.01', 'synonyms': ['saddlebag'], 'def': 'a large bag (or pair of bags) hung over a saddle', 'name': 'saddlebag'}, {'frequency': 'r', 'id': 916, 'synset': 'safety_pin.n.01', 'synonyms': ['safety_pin'], 'def': 'a pin in the form of a clasp; has a guard so the point of the pin will not stick the user', 'name': 'safety_pin'}, {'frequency': 'c', 'id': 917, 'synset': 'sail.n.01', 'synonyms': ['sail'], 'def': 'a large piece of fabric by means of which wind is used to propel a sailing vessel', 'name': 'sail'}, {'frequency': 'c', 'id': 918, 'synset': 'salad.n.01', 'synonyms': ['salad'], 'def': 'food mixtures either arranged on a plate or tossed and served with a moist dressing; usually consisting of or including greens', 'name': 'salad'}, {'frequency': 'r', 'id': 919, 'synset': 'salad_plate.n.01', 'synonyms': ['salad_plate', 'salad_bowl'], 'def': 'a plate or bowl for individual servings of salad', 'name': 'salad_plate'}, {'frequency': 'r', 'id': 920, 'synset': 'salami.n.01', 'synonyms': ['salami'], 'def': 'highly seasoned fatty sausage of pork and beef usually dried', 'name': 'salami'}, {'frequency': 'r', 'id': 921, 'synset': 'salmon.n.01', 'synonyms': ['salmon_(fish)'], 'def': 'any of various large food and game fishes of northern waters', 'name': 'salmon_(fish)'}, {'frequency': 'r', 'id': 922, 'synset': 'salmon.n.03', 'synonyms': ['salmon_(food)'], 'def': 'flesh of any of various marine or freshwater fish of the family Salmonidae', 'name': 'salmon_(food)'}, {'frequency': 'r', 'id': 923, 'synset': 'salsa.n.01', 'synonyms': ['salsa'], 'def': 'spicy sauce of tomatoes and onions and chili peppers to accompany Mexican foods', 'name': 'salsa'}, {'frequency': 'f', 'id': 924, 'synset': 'saltshaker.n.01', 'synonyms': ['saltshaker'], 'def': 'a shaker with a perforated top for sprinkling salt', 'name': 'saltshaker'}, {'frequency': 'f', 'id': 925, 'synset': 'sandal.n.01', 'synonyms': ['sandal_(type_of_shoe)'], 'def': 'a shoe consisting of a sole fastened by straps to the foot', 'name': 'sandal_(type_of_shoe)'}, {'frequency': 'f', 'id': 926, 'synset': 'sandwich.n.01', 'synonyms': ['sandwich'], 'def': 'two (or more) slices of bread with a filling between them', 'name': 'sandwich'}, {'frequency': 'r', 'id': 927, 'synset': 'satchel.n.01', 'synonyms': ['satchel'], 'def': 'luggage consisting of a small case with a flat bottom and (usually) a shoulder strap', 'name': 'satchel'}, {'frequency': 'r', 'id': 928, 'synset': 'saucepan.n.01', 'synonyms': ['saucepan'], 'def': 'a deep pan with a handle; used for stewing or boiling', 'name': 'saucepan'}, {'frequency': 'f', 'id': 929, 'synset': 'saucer.n.02', 'synonyms': ['saucer'], 'def': 'a small shallow dish for holding a cup at the table', 'name': 'saucer'}, {'frequency': 'f', 'id': 930, 'synset': 'sausage.n.01', 'synonyms': ['sausage'], 'def': 'highly seasoned minced meat stuffed in casings', 'name': 'sausage'}, {'frequency': 'r', 'id': 931, 'synset': 'sawhorse.n.01', 'synonyms': ['sawhorse', 'sawbuck'], 'def': 'a framework for holding wood that is being sawed', 'name': 'sawhorse'}, {'frequency': 'r', 'id': 932, 'synset': 'sax.n.02', 'synonyms': ['saxophone'], 'def': "a wind instrument with a `J'-shaped form typically made of brass", 'name': 'saxophone'}, {'frequency': 'f', 'id': 933, 'synset': 'scale.n.07', 'synonyms': ['scale_(measuring_instrument)'], 'def': 'a measuring instrument for weighing; shows amount of mass', 'name': 'scale_(measuring_instrument)'}, {'frequency': 'r', 'id': 934, 'synset': 'scarecrow.n.01', 'synonyms': ['scarecrow', 'strawman'], 'def': 'an effigy in the shape of a man to frighten birds away from seeds', 'name': 'scarecrow'}, {'frequency': 'f', 'id': 935, 'synset': 'scarf.n.01', 'synonyms': ['scarf'], 'def': 'a garment worn around the head or neck or shoulders for warmth or decoration', 'name': 'scarf'}, {'frequency': 'c', 'id': 936, 'synset': 'school_bus.n.01', 'synonyms': ['school_bus'], 'def': 'a bus used to transport children to or from school', 'name': 'school_bus'}, {'frequency': 'f', 'id': 937, 'synset': 'scissors.n.01', 'synonyms': ['scissors'], 'def': 'a tool having two crossed pivoting blades with looped handles', 'name': 'scissors'}, {'frequency': 'c', 'id': 938, 'synset': 'scoreboard.n.01', 'synonyms': ['scoreboard'], 'def': 'a large board for displaying the score of a contest (and some other information)', 'name': 'scoreboard'}, {'frequency': 'c', 'id': 939, 'synset': 'scrambled_eggs.n.01', 'synonyms': ['scrambled_eggs'], 'def': 'eggs beaten and cooked to a soft firm consistency while stirring', 'name': 'scrambled_eggs'}, {'frequency': 'r', 'id': 940, 'synset': 'scraper.n.01', 'synonyms': ['scraper'], 'def': 'any of various hand tools for scraping', 'name': 'scraper'}, {'frequency': 'r', 'id': 941, 'synset': 'scratcher.n.03', 'synonyms': ['scratcher'], 'def': 'a device used for scratching', 'name': 'scratcher'}, {'frequency': 'c', 'id': 942, 'synset': 'screwdriver.n.01', 'synonyms': ['screwdriver'], 'def': 'a hand tool for driving screws; has a tip that fits into the head of a screw', 'name': 'screwdriver'}, {'frequency': 'c', 'id': 943, 'synset': 'scrub_brush.n.01', 'synonyms': ['scrubbing_brush'], 'def': 'a brush with short stiff bristles for heavy cleaning', 'name': 'scrubbing_brush'}, {'frequency': 'c', 'id': 944, 'synset': 'sculpture.n.01', 'synonyms': ['sculpture'], 'def': 'a three-dimensional work of art', 'name': 'sculpture'}, {'frequency': 'r', 'id': 945, 'synset': 'seabird.n.01', 'synonyms': ['seabird', 'seafowl'], 'def': 'a bird that frequents coastal waters and the open ocean: gulls; pelicans; gannets; cormorants; albatrosses; petrels; etc.', 'name': 'seabird'}, {'frequency': 'r', 'id': 946, 'synset': 'seahorse.n.02', 'synonyms': ['seahorse'], 'def': 'small fish with horse-like heads bent sharply downward and curled tails', 'name': 'seahorse'}, {'frequency': 'r', 'id': 947, 'synset': 'seaplane.n.01', 'synonyms': ['seaplane', 'hydroplane'], 'def': 'an airplane that can land on or take off from water', 'name': 'seaplane'}, {'frequency': 'c', 'id': 948, 'synset': 'seashell.n.01', 'synonyms': ['seashell'], 'def': 'the shell of a marine organism', 'name': 'seashell'}, {'frequency': 'r', 'id': 949, 'synset': 'seedling.n.01', 'synonyms': ['seedling'], 'def': 'young plant or tree grown from a seed', 'name': 'seedling'}, {'frequency': 'c', 'id': 950, 'synset': 'serving_dish.n.01', 'synonyms': ['serving_dish'], 'def': 'a dish used for serving food', 'name': 'serving_dish'}, {'frequency': 'r', 'id': 951, 'synset': 'sewing_machine.n.01', 'synonyms': ['sewing_machine'], 'def': 'a textile machine used as a home appliance for sewing', 'name': 'sewing_machine'}, {'frequency': 'r', 'id': 952, 'synset': 'shaker.n.03', 'synonyms': ['shaker'], 'def': 'a container in which something can be shaken', 'name': 'shaker'}, {'frequency': 'c', 'id': 953, 'synset': 'shampoo.n.01', 'synonyms': ['shampoo'], 'def': 'cleansing agent consisting of soaps or detergents used for washing the hair', 'name': 'shampoo'}, {'frequency': 'r', 'id': 954, 'synset': 'shark.n.01', 'synonyms': ['shark'], 'def': 'typically large carnivorous fishes with sharpe teeth', 'name': 'shark'}, {'frequency': 'r', 'id': 955, 'synset': 'sharpener.n.01', 'synonyms': ['sharpener'], 'def': 'any implement that is used to make something (an edge or a point) sharper', 'name': 'sharpener'}, {'frequency': 'r', 'id': 956, 'synset': 'sharpie.n.03', 'synonyms': ['Sharpie'], 'def': 'a pen with indelible ink that will write on any surface', 'name': 'Sharpie'}, {'frequency': 'r', 'id': 957, 'synset': 'shaver.n.03', 'synonyms': ['shaver_(electric)', 'electric_shaver', 'electric_razor'], 'def': 'a razor powered by an electric motor', 'name': 'shaver_(electric)'}, {'frequency': 'c', 'id': 958, 'synset': 'shaving_cream.n.01', 'synonyms': ['shaving_cream', 'shaving_soap'], 'def': 'toiletry consisting that forms a rich lather for softening the beard before shaving', 'name': 'shaving_cream'}, {'frequency': 'r', 'id': 959, 'synset': 'shawl.n.01', 'synonyms': ['shawl'], 'def': 'cloak consisting of an oblong piece of cloth used to cover the head and shoulders', 'name': 'shawl'}, {'frequency': 'r', 'id': 960, 'synset': 'shears.n.01', 'synonyms': ['shears'], 'def': 'large scissors with strong blades', 'name': 'shears'}, {'frequency': 'f', 'id': 961, 'synset': 'sheep.n.01', 'synonyms': ['sheep'], 'def': 'woolly usually horned ruminant mammal related to the goat', 'name': 'sheep'}, {'frequency': 'r', 'id': 962, 'synset': 'shepherd_dog.n.01', 'synonyms': ['shepherd_dog', 'sheepdog'], 'def': 'any of various usually long-haired breeds of dog reared to herd and guard sheep', 'name': 'shepherd_dog'}, {'frequency': 'r', 'id': 963, 'synset': 'sherbert.n.01', 'synonyms': ['sherbert', 'sherbet'], 'def': 'a frozen dessert made primarily of fruit juice and sugar', 'name': 'sherbert'}, {'frequency': 'r', 'id': 964, 'synset': 'shield.n.02', 'synonyms': ['shield'], 'def': 'armor carried on the arm to intercept blows', 'name': 'shield'}, {'frequency': 'f', 'id': 965, 'synset': 'shirt.n.01', 'synonyms': ['shirt'], 'def': 'a garment worn on the upper half of the body', 'name': 'shirt'}, {'frequency': 'f', 'id': 966, 'synset': 'shoe.n.01', 'synonyms': ['shoe', 'sneaker_(type_of_shoe)', 'tennis_shoe'], 'def': 'common footwear covering the foot', 'name': 'shoe'}, {'frequency': 'c', 'id': 967, 'synset': 'shopping_bag.n.01', 'synonyms': ['shopping_bag'], 'def': 'a bag made of plastic or strong paper (often with handles); used to transport goods after shopping', 'name': 'shopping_bag'}, {'frequency': 'c', 'id': 968, 'synset': 'shopping_cart.n.01', 'synonyms': ['shopping_cart'], 'def': 'a handcart that holds groceries or other goods while shopping', 'name': 'shopping_cart'}, {'frequency': 'f', 'id': 969, 'synset': 'short_pants.n.01', 'synonyms': ['short_pants', 'shorts_(clothing)', 'trunks_(clothing)'], 'def': 'trousers that end at or above the knee', 'name': 'short_pants'}, {'frequency': 'r', 'id': 970, 'synset': 'shot_glass.n.01', 'synonyms': ['shot_glass'], 'def': 'a small glass adequate to hold a single swallow of whiskey', 'name': 'shot_glass'}, {'frequency': 'c', 'id': 971, 'synset': 'shoulder_bag.n.01', 'synonyms': ['shoulder_bag'], 'def': 'a large handbag that can be carried by a strap looped over the shoulder', 'name': 'shoulder_bag'}, {'frequency': 'c', 'id': 972, 'synset': 'shovel.n.01', 'synonyms': ['shovel'], 'def': 'a hand tool for lifting loose material such as snow, dirt, etc.', 'name': 'shovel'}, {'frequency': 'f', 'id': 973, 'synset': 'shower.n.01', 'synonyms': ['shower_head'], 'def': 'a plumbing fixture that sprays water over you', 'name': 'shower_head'}, {'frequency': 'f', 'id': 974, 'synset': 'shower_curtain.n.01', 'synonyms': ['shower_curtain'], 'def': 'a curtain that keeps water from splashing out of the shower area', 'name': 'shower_curtain'}, {'frequency': 'r', 'id': 975, 'synset': 'shredder.n.01', 'synonyms': ['shredder_(for_paper)'], 'def': 'a device that shreds documents', 'name': 'shredder_(for_paper)'}, {'frequency': 'r', 'id': 976, 'synset': 'sieve.n.01', 'synonyms': ['sieve', 'screen_(sieve)'], 'def': 'a strainer for separating lumps from powdered material or grading particles', 'name': 'sieve'}, {'frequency': 'f', 'id': 977, 'synset': 'signboard.n.01', 'synonyms': ['signboard'], 'def': 'structure displaying a board on which advertisements can be posted', 'name': 'signboard'}, {'frequency': 'c', 'id': 978, 'synset': 'silo.n.01', 'synonyms': ['silo'], 'def': 'a cylindrical tower used for storing goods', 'name': 'silo'}, {'frequency': 'f', 'id': 979, 'synset': 'sink.n.01', 'synonyms': ['sink'], 'def': 'plumbing fixture consisting of a water basin fixed to a wall or floor and having a drainpipe', 'name': 'sink'}, {'frequency': 'f', 'id': 980, 'synset': 'skateboard.n.01', 'synonyms': ['skateboard'], 'def': 'a board with wheels that is ridden in a standing or crouching position and propelled by foot', 'name': 'skateboard'}, {'frequency': 'c', 'id': 981, 'synset': 'skewer.n.01', 'synonyms': ['skewer'], 'def': 'a long pin for holding meat in position while it is being roasted', 'name': 'skewer'}, {'frequency': 'f', 'id': 982, 'synset': 'ski.n.01', 'synonyms': ['ski'], 'def': 'sports equipment for skiing on snow', 'name': 'ski'}, {'frequency': 'f', 'id': 983, 'synset': 'ski_boot.n.01', 'synonyms': ['ski_boot'], 'def': 'a stiff boot that is fastened to a ski with a ski binding', 'name': 'ski_boot'}, {'frequency': 'f', 'id': 984, 'synset': 'ski_parka.n.01', 'synonyms': ['ski_parka', 'ski_jacket'], 'def': 'a parka to be worn while skiing', 'name': 'ski_parka'}, {'frequency': 'f', 'id': 985, 'synset': 'ski_pole.n.01', 'synonyms': ['ski_pole'], 'def': 'a pole with metal points used as an aid in skiing', 'name': 'ski_pole'}, {'frequency': 'f', 'id': 986, 'synset': 'skirt.n.02', 'synonyms': ['skirt'], 'def': 'a garment hanging from the waist; worn mainly by girls and women', 'name': 'skirt'}, {'frequency': 'c', 'id': 987, 'synset': 'sled.n.01', 'synonyms': ['sled', 'sledge', 'sleigh'], 'def': 'a vehicle or flat object for transportation over snow by sliding or pulled by dogs, etc.', 'name': 'sled'}, {'frequency': 'c', 'id': 988, 'synset': 'sleeping_bag.n.01', 'synonyms': ['sleeping_bag'], 'def': 'large padded bag designed to be slept in outdoors', 'name': 'sleeping_bag'}, {'frequency': 'r', 'id': 989, 'synset': 'sling.n.05', 'synonyms': ['sling_(bandage)', 'triangular_bandage'], 'def': 'bandage to support an injured forearm; slung over the shoulder or neck', 'name': 'sling_(bandage)'}, {'frequency': 'c', 'id': 990, 'synset': 'slipper.n.01', 'synonyms': ['slipper_(footwear)', 'carpet_slipper_(footwear)'], 'def': 'low footwear that can be slipped on and off easily; usually worn indoors', 'name': 'slipper_(footwear)'}, {'frequency': 'r', 'id': 991, 'synset': 'smoothie.n.02', 'synonyms': ['smoothie'], 'def': 'a thick smooth drink consisting of fresh fruit pureed with ice cream or yoghurt or milk', 'name': 'smoothie'}, {'frequency': 'r', 'id': 992, 'synset': 'snake.n.01', 'synonyms': ['snake', 'serpent'], 'def': 'limbless scaly elongate reptile; some are venomous', 'name': 'snake'}, {'frequency': 'f', 'id': 993, 'synset': 'snowboard.n.01', 'synonyms': ['snowboard'], 'def': 'a board that resembles a broad ski or a small surfboard; used in a standing position to slide down snow-covered slopes', 'name': 'snowboard'}, {'frequency': 'c', 'id': 994, 'synset': 'snowman.n.01', 'synonyms': ['snowman'], 'def': 'a figure of a person made of packed snow', 'name': 'snowman'}, {'frequency': 'c', 'id': 995, 'synset': 'snowmobile.n.01', 'synonyms': ['snowmobile'], 'def': 'tracked vehicle for travel on snow having skis in front', 'name': 'snowmobile'}, {'frequency': 'f', 'id': 996, 'synset': 'soap.n.01', 'synonyms': ['soap'], 'def': 'a cleansing agent made from the salts of vegetable or animal fats', 'name': 'soap'}, {'frequency': 'f', 'id': 997, 'synset': 'soccer_ball.n.01', 'synonyms': ['soccer_ball'], 'def': "an inflated ball used in playing soccer (called `football' outside of the United States)", 'name': 'soccer_ball'}, {'frequency': 'f', 'id': 998, 'synset': 'sock.n.01', 'synonyms': ['sock'], 'def': 'cloth covering for the foot; worn inside the shoe; reaches to between the ankle and the knee', 'name': 'sock'}, {'frequency': 'r', 'id': 999, 'synset': 'soda_fountain.n.02', 'synonyms': ['soda_fountain'], 'def': 'an apparatus for dispensing soda water', 'name': 'soda_fountain'}, {'frequency': 'r', 'id': 1000, 'synset': 'soda_water.n.01', 'synonyms': ['carbonated_water', 'club_soda', 'seltzer', 'sparkling_water'], 'def': 'effervescent beverage artificially charged with carbon dioxide', 'name': 'carbonated_water'}, {'frequency': 'f', 'id': 1001, 'synset': 'sofa.n.01', 'synonyms': ['sofa', 'couch', 'lounge'], 'def': 'an upholstered seat for more than one person', 'name': 'sofa'}, {'frequency': 'r', 'id': 1002, 'synset': 'softball.n.01', 'synonyms': ['softball'], 'def': 'ball used in playing softball', 'name': 'softball'}, {'frequency': 'c', 'id': 1003, 'synset': 'solar_array.n.01', 'synonyms': ['solar_array', 'solar_battery', 'solar_panel'], 'def': 'electrical device consisting of a large array of connected solar cells', 'name': 'solar_array'}, {'frequency': 'r', 'id': 1004, 'synset': 'sombrero.n.02', 'synonyms': ['sombrero'], 'def': 'a straw hat with a tall crown and broad brim; worn in American southwest and in Mexico', 'name': 'sombrero'}, {'frequency': 'c', 'id': 1005, 'synset': 'soup.n.01', 'synonyms': ['soup'], 'def': 'liquid food especially of meat or fish or vegetable stock often containing pieces of solid food', 'name': 'soup'}, {'frequency': 'r', 'id': 1006, 'synset': 'soup_bowl.n.01', 'synonyms': ['soup_bowl'], 'def': 'a bowl for serving soup', 'name': 'soup_bowl'}, {'frequency': 'c', 'id': 1007, 'synset': 'soupspoon.n.01', 'synonyms': ['soupspoon'], 'def': 'a spoon with a rounded bowl for eating soup', 'name': 'soupspoon'}, {'frequency': 'c', 'id': 1008, 'synset': 'sour_cream.n.01', 'synonyms': ['sour_cream', 'soured_cream'], 'def': 'soured light cream', 'name': 'sour_cream'}, {'frequency': 'r', 'id': 1009, 'synset': 'soya_milk.n.01', 'synonyms': ['soya_milk', 'soybean_milk', 'soymilk'], 'def': 'a milk substitute containing soybean flour and water; used in some infant formulas and in making tofu', 'name': 'soya_milk'}, {'frequency': 'r', 'id': 1010, 'synset': 'space_shuttle.n.01', 'synonyms': ['space_shuttle'], 'def': "a reusable spacecraft with wings for a controlled descent through the Earth's atmosphere", 'name': 'space_shuttle'}, {'frequency': 'r', 'id': 1011, 'synset': 'sparkler.n.02', 'synonyms': ['sparkler_(fireworks)'], 'def': 'a firework that burns slowly and throws out a shower of sparks', 'name': 'sparkler_(fireworks)'}, {'frequency': 'f', 'id': 1012, 'synset': 'spatula.n.02', 'synonyms': ['spatula'], 'def': 'a hand tool with a thin flexible blade used to mix or spread soft substances', 'name': 'spatula'}, {'frequency': 'r', 'id': 1013, 'synset': 'spear.n.01', 'synonyms': ['spear', 'lance'], 'def': 'a long pointed rod used as a tool or weapon', 'name': 'spear'}, {'frequency': 'f', 'id': 1014, 'synset': 'spectacles.n.01', 'synonyms': ['spectacles', 'specs', 'eyeglasses', 'glasses'], 'def': 'optical instrument consisting of a frame that holds a pair of lenses for correcting defective vision', 'name': 'spectacles'}, {'frequency': 'c', 'id': 1015, 'synset': 'spice_rack.n.01', 'synonyms': ['spice_rack'], 'def': 'a rack for displaying containers filled with spices', 'name': 'spice_rack'}, {'frequency': 'r', 'id': 1016, 'synset': 'spider.n.01', 'synonyms': ['spider'], 'def': 'predatory arachnid with eight legs, two poison fangs, two feelers, and usually two silk-spinning organs at the back end of the body', 'name': 'spider'}, {'frequency': 'c', 'id': 1017, 'synset': 'sponge.n.01', 'synonyms': ['sponge'], 'def': 'a porous mass usable to absorb water typically used for cleaning', 'name': 'sponge'}, {'frequency': 'f', 'id': 1018, 'synset': 'spoon.n.01', 'synonyms': ['spoon'], 'def': 'a piece of cutlery with a shallow bowl-shaped container and a handle', 'name': 'spoon'}, {'frequency': 'c', 'id': 1019, 'synset': 'sportswear.n.01', 'synonyms': ['sportswear', 'athletic_wear', 'activewear'], 'def': 'attire worn for sport or for casual wear', 'name': 'sportswear'}, {'frequency': 'c', 'id': 1020, 'synset': 'spotlight.n.02', 'synonyms': ['spotlight'], 'def': 'a lamp that produces a strong beam of light to illuminate a restricted area; used to focus attention of a stage performer', 'name': 'spotlight'}, {'frequency': 'r', 'id': 1021, 'synset': 'squirrel.n.01', 'synonyms': ['squirrel'], 'def': 'a kind of arboreal rodent having a long bushy tail', 'name': 'squirrel'}, {'frequency': 'c', 'id': 1022, 'synset': 'stapler.n.01', 'synonyms': ['stapler_(stapling_machine)'], 'def': 'a machine that inserts staples into sheets of paper in order to fasten them together', 'name': 'stapler_(stapling_machine)'}, {'frequency': 'r', 'id': 1023, 'synset': 'starfish.n.01', 'synonyms': ['starfish', 'sea_star'], 'def': 'echinoderms characterized by five arms extending from a central disk', 'name': 'starfish'}, {'frequency': 'f', 'id': 1024, 'synset': 'statue.n.01', 'synonyms': ['statue_(sculpture)'], 'def': 'a sculpture representing a human or animal', 'name': 'statue_(sculpture)'}, {'frequency': 'c', 'id': 1025, 'synset': 'steak.n.01', 'synonyms': ['steak_(food)'], 'def': 'a slice of meat cut from the fleshy part of an animal or large fish', 'name': 'steak_(food)'}, {'frequency': 'r', 'id': 1026, 'synset': 'steak_knife.n.01', 'synonyms': ['steak_knife'], 'def': 'a sharp table knife used in eating steak', 'name': 'steak_knife'}, {'frequency': 'r', 'id': 1027, 'synset': 'steamer.n.02', 'synonyms': ['steamer_(kitchen_appliance)'], 'def': 'a cooking utensil that can be used to cook food by steaming it', 'name': 'steamer_(kitchen_appliance)'}, {'frequency': 'f', 'id': 1028, 'synset': 'steering_wheel.n.01', 'synonyms': ['steering_wheel'], 'def': 'a handwheel that is used for steering', 'name': 'steering_wheel'}, {'frequency': 'r', 'id': 1029, 'synset': 'stencil.n.01', 'synonyms': ['stencil'], 'def': 'a sheet of material (metal, plastic, etc.) that has been perforated with a pattern; ink or paint can pass through the perforations to create the printed pattern on the surface below', 'name': 'stencil'}, {'frequency': 'r', 'id': 1030, 'synset': 'step_ladder.n.01', 'synonyms': ['stepladder'], 'def': 'a folding portable ladder hinged at the top', 'name': 'stepladder'}, {'frequency': 'c', 'id': 1031, 'synset': 'step_stool.n.01', 'synonyms': ['step_stool'], 'def': 'a stool that has one or two steps that fold under the seat', 'name': 'step_stool'}, {'frequency': 'c', 'id': 1032, 'synset': 'stereo.n.01', 'synonyms': ['stereo_(sound_system)'], 'def': 'electronic device for playing audio', 'name': 'stereo_(sound_system)'}, {'frequency': 'r', 'id': 1033, 'synset': 'stew.n.02', 'synonyms': ['stew'], 'def': 'food prepared by stewing especially meat or fish with vegetables', 'name': 'stew'}, {'frequency': 'r', 'id': 1034, 'synset': 'stirrer.n.02', 'synonyms': ['stirrer'], 'def': 'an implement used for stirring', 'name': 'stirrer'}, {'frequency': 'f', 'id': 1035, 'synset': 'stirrup.n.01', 'synonyms': ['stirrup'], 'def': "support consisting of metal loops into which rider's feet go", 'name': 'stirrup'}, {'frequency': 'c', 'id': 1036, 'synset': 'stocking.n.01', 'synonyms': ['stockings_(leg_wear)'], 'def': 'close-fitting hosiery to cover the foot and leg; come in matched pairs', 'name': 'stockings_(leg_wear)'}, {'frequency': 'f', 'id': 1037, 'synset': 'stool.n.01', 'synonyms': ['stool'], 'def': 'a simple seat without a back or arms', 'name': 'stool'}, {'frequency': 'f', 'id': 1038, 'synset': 'stop_sign.n.01', 'synonyms': ['stop_sign'], 'def': 'a traffic sign to notify drivers that they must come to a complete stop', 'name': 'stop_sign'}, {'frequency': 'f', 'id': 1039, 'synset': 'stoplight.n.01', 'synonyms': ['brake_light'], 'def': 'a red light on the rear of a motor vehicle that signals when the brakes are applied', 'name': 'brake_light'}, {'frequency': 'f', 'id': 1040, 'synset': 'stove.n.01', 'synonyms': ['stove', 'kitchen_stove', 'range_(kitchen_appliance)', 'kitchen_range', 'cooking_stove'], 'def': 'a kitchen appliance used for cooking food', 'name': 'stove'}, {'frequency': 'c', 'id': 1041, 'synset': 'strainer.n.01', 'synonyms': ['strainer'], 'def': 'a filter to retain larger pieces while smaller pieces and liquids pass through', 'name': 'strainer'}, {'frequency': 'f', 'id': 1042, 'synset': 'strap.n.01', 'synonyms': ['strap'], 'def': 'an elongated strip of material for binding things together or holding', 'name': 'strap'}, {'frequency': 'f', 'id': 1043, 'synset': 'straw.n.04', 'synonyms': ['straw_(for_drinking)', 'drinking_straw'], 'def': 'a thin paper or plastic tube used to suck liquids into the mouth', 'name': 'straw_(for_drinking)'}, {'frequency': 'f', 'id': 1044, 'synset': 'strawberry.n.01', 'synonyms': ['strawberry'], 'def': 'sweet fleshy red fruit', 'name': 'strawberry'}, {'frequency': 'f', 'id': 1045, 'synset': 'street_sign.n.01', 'synonyms': ['street_sign'], 'def': 'a sign visible from the street', 'name': 'street_sign'}, {'frequency': 'f', 'id': 1046, 'synset': 'streetlight.n.01', 'synonyms': ['streetlight', 'street_lamp'], 'def': 'a lamp supported on a lamppost; for illuminating a street', 'name': 'streetlight'}, {'frequency': 'r', 'id': 1047, 'synset': 'string_cheese.n.01', 'synonyms': ['string_cheese'], 'def': 'cheese formed in long strings twisted together', 'name': 'string_cheese'}, {'frequency': 'r', 'id': 1048, 'synset': 'stylus.n.02', 'synonyms': ['stylus'], 'def': 'a pointed tool for writing or drawing or engraving', 'name': 'stylus'}, {'frequency': 'r', 'id': 1049, 'synset': 'subwoofer.n.01', 'synonyms': ['subwoofer'], 'def': 'a loudspeaker that is designed to reproduce very low bass frequencies', 'name': 'subwoofer'}, {'frequency': 'r', 'id': 1050, 'synset': 'sugar_bowl.n.01', 'synonyms': ['sugar_bowl'], 'def': 'a dish in which sugar is served', 'name': 'sugar_bowl'}, {'frequency': 'r', 'id': 1051, 'synset': 'sugarcane.n.01', 'synonyms': ['sugarcane_(plant)'], 'def': 'juicy canes whose sap is a source of molasses and commercial sugar; fresh canes are sometimes chewed for the juice', 'name': 'sugarcane_(plant)'}, {'frequency': 'c', 'id': 1052, 'synset': 'suit.n.01', 'synonyms': ['suit_(clothing)'], 'def': 'a set of garments (usually including a jacket and trousers or skirt) for outerwear all of the same fabric and color', 'name': 'suit_(clothing)'}, {'frequency': 'c', 'id': 1053, 'synset': 'sunflower.n.01', 'synonyms': ['sunflower'], 'def': 'any plant of the genus Helianthus having large flower heads with dark disk florets and showy yellow rays', 'name': 'sunflower'}, {'frequency': 'f', 'id': 1054, 'synset': 'sunglasses.n.01', 'synonyms': ['sunglasses'], 'def': 'spectacles that are darkened or polarized to protect the eyes from the glare of the sun', 'name': 'sunglasses'}, {'frequency': 'c', 'id': 1055, 'synset': 'sunhat.n.01', 'synonyms': ['sunhat'], 'def': 'a hat with a broad brim that protects the face from direct exposure to the sun', 'name': 'sunhat'}, {'frequency': 'r', 'id': 1056, 'synset': 'sunscreen.n.01', 'synonyms': ['sunscreen', 'sunblock'], 'def': 'a cream spread on the skin; contains a chemical to filter out ultraviolet light and so protect from sunburn', 'name': 'sunscreen'}, {'frequency': 'f', 'id': 1057, 'synset': 'surfboard.n.01', 'synonyms': ['surfboard'], 'def': 'a narrow buoyant board for riding surf', 'name': 'surfboard'}, {'frequency': 'c', 'id': 1058, 'synset': 'sushi.n.01', 'synonyms': ['sushi'], 'def': 'rice (with raw fish) wrapped in seaweed', 'name': 'sushi'}, {'frequency': 'c', 'id': 1059, 'synset': 'swab.n.02', 'synonyms': ['mop'], 'def': 'cleaning implement consisting of absorbent material fastened to a handle; for cleaning floors', 'name': 'mop'}, {'frequency': 'c', 'id': 1060, 'synset': 'sweat_pants.n.01', 'synonyms': ['sweat_pants'], 'def': 'loose-fitting trousers with elastic cuffs; worn by athletes', 'name': 'sweat_pants'}, {'frequency': 'c', 'id': 1061, 'synset': 'sweatband.n.02', 'synonyms': ['sweatband'], 'def': 'a band of material tied around the forehead or wrist to absorb sweat', 'name': 'sweatband'}, {'frequency': 'f', 'id': 1062, 'synset': 'sweater.n.01', 'synonyms': ['sweater'], 'def': 'a crocheted or knitted garment covering the upper part of the body', 'name': 'sweater'}, {'frequency': 'f', 'id': 1063, 'synset': 'sweatshirt.n.01', 'synonyms': ['sweatshirt'], 'def': 'cotton knit pullover with long sleeves worn during athletic activity', 'name': 'sweatshirt'}, {'frequency': 'c', 'id': 1064, 'synset': 'sweet_potato.n.02', 'synonyms': ['sweet_potato'], 'def': 'the edible tuberous root of the sweet potato vine', 'name': 'sweet_potato'}, {'frequency': 'f', 'id': 1065, 'synset': 'swimsuit.n.01', 'synonyms': ['swimsuit', 'swimwear', 'bathing_suit', 'swimming_costume', 'bathing_costume', 'swimming_trunks', 'bathing_trunks'], 'def': 'garment worn for swimming', 'name': 'swimsuit'}, {'frequency': 'c', 'id': 1066, 'synset': 'sword.n.01', 'synonyms': ['sword'], 'def': 'a cutting or thrusting weapon that has a long metal blade', 'name': 'sword'}, {'frequency': 'r', 'id': 1067, 'synset': 'syringe.n.01', 'synonyms': ['syringe'], 'def': 'a medical instrument used to inject or withdraw fluids', 'name': 'syringe'}, {'frequency': 'r', 'id': 1068, 'synset': 'tabasco.n.02', 'synonyms': ['Tabasco_sauce'], 'def': 'very spicy sauce (trade name Tabasco) made from fully-aged red peppers', 'name': 'Tabasco_sauce'}, {'frequency': 'r', 'id': 1069, 'synset': 'table-tennis_table.n.01', 'synonyms': ['table-tennis_table', 'ping-pong_table'], 'def': 'a table used for playing table tennis', 'name': 'table-tennis_table'}, {'frequency': 'f', 'id': 1070, 'synset': 'table.n.02', 'synonyms': ['table'], 'def': 'a piece of furniture having a smooth flat top that is usually supported by one or more vertical legs', 'name': 'table'}, {'frequency': 'c', 'id': 1071, 'synset': 'table_lamp.n.01', 'synonyms': ['table_lamp'], 'def': 'a lamp that sits on a table', 'name': 'table_lamp'}, {'frequency': 'f', 'id': 1072, 'synset': 'tablecloth.n.01', 'synonyms': ['tablecloth'], 'def': 'a covering spread over a dining table', 'name': 'tablecloth'}, {'frequency': 'r', 'id': 1073, 'synset': 'tachometer.n.01', 'synonyms': ['tachometer'], 'def': 'measuring instrument for indicating speed of rotation', 'name': 'tachometer'}, {'frequency': 'r', 'id': 1074, 'synset': 'taco.n.02', 'synonyms': ['taco'], 'def': 'a small tortilla cupped around a filling', 'name': 'taco'}, {'frequency': 'f', 'id': 1075, 'synset': 'tag.n.02', 'synonyms': ['tag'], 'def': 'a label associated with something for the purpose of identification or information', 'name': 'tag'}, {'frequency': 'f', 'id': 1076, 'synset': 'taillight.n.01', 'synonyms': ['taillight', 'rear_light'], 'def': 'lamp (usually red) mounted at the rear of a motor vehicle', 'name': 'taillight'}, {'frequency': 'r', 'id': 1077, 'synset': 'tambourine.n.01', 'synonyms': ['tambourine'], 'def': 'a shallow drum with a single drumhead and with metallic disks in the sides', 'name': 'tambourine'}, {'frequency': 'r', 'id': 1078, 'synset': 'tank.n.01', 'synonyms': ['army_tank', 'armored_combat_vehicle', 'armoured_combat_vehicle'], 'def': 'an enclosed armored military vehicle; has a cannon and moves on caterpillar treads', 'name': 'army_tank'}, {'frequency': 'c', 'id': 1079, 'synset': 'tank.n.02', 'synonyms': ['tank_(storage_vessel)', 'storage_tank'], 'def': 'a large (usually metallic) vessel for holding gases or liquids', 'name': 'tank_(storage_vessel)'}, {'frequency': 'f', 'id': 1080, 'synset': 'tank_top.n.01', 'synonyms': ['tank_top_(clothing)'], 'def': 'a tight-fitting sleeveless shirt with wide shoulder straps and low neck and no front opening', 'name': 'tank_top_(clothing)'}, {'frequency': 'c', 'id': 1081, 'synset': 'tape.n.01', 'synonyms': ['tape_(sticky_cloth_or_paper)'], 'def': 'a long thin piece of cloth or paper as used for binding or fastening', 'name': 'tape_(sticky_cloth_or_paper)'}, {'frequency': 'c', 'id': 1082, 'synset': 'tape.n.04', 'synonyms': ['tape_measure', 'measuring_tape'], 'def': 'measuring instrument consisting of a narrow strip (cloth or metal) marked in inches or centimeters and used for measuring lengths', 'name': 'tape_measure'}, {'frequency': 'c', 'id': 1083, 'synset': 'tapestry.n.02', 'synonyms': ['tapestry'], 'def': 'a heavy textile with a woven design; used for curtains and upholstery', 'name': 'tapestry'}, {'frequency': 'f', 'id': 1084, 'synset': 'tarpaulin.n.01', 'synonyms': ['tarp'], 'def': 'waterproofed canvas', 'name': 'tarp'}, {'frequency': 'c', 'id': 1085, 'synset': 'tartan.n.01', 'synonyms': ['tartan', 'plaid'], 'def': 'a cloth having a crisscross design', 'name': 'tartan'}, {'frequency': 'c', 'id': 1086, 'synset': 'tassel.n.01', 'synonyms': ['tassel'], 'def': 'adornment consisting of a bunch of cords fastened at one end', 'name': 'tassel'}, {'frequency': 'r', 'id': 1087, 'synset': 'tea_bag.n.01', 'synonyms': ['tea_bag'], 'def': 'a measured amount of tea in a bag for an individual serving of tea', 'name': 'tea_bag'}, {'frequency': 'c', 'id': 1088, 'synset': 'teacup.n.02', 'synonyms': ['teacup'], 'def': 'a cup from which tea is drunk', 'name': 'teacup'}, {'frequency': 'c', 'id': 1089, 'synset': 'teakettle.n.01', 'synonyms': ['teakettle'], 'def': 'kettle for boiling water to make tea', 'name': 'teakettle'}, {'frequency': 'c', 'id': 1090, 'synset': 'teapot.n.01', 'synonyms': ['teapot'], 'def': 'pot for brewing tea; usually has a spout and handle', 'name': 'teapot'}, {'frequency': 'f', 'id': 1091, 'synset': 'teddy.n.01', 'synonyms': ['teddy_bear'], 'def': "plaything consisting of a child's toy bear (usually plush and stuffed with soft materials)", 'name': 'teddy_bear'}, {'frequency': 'f', 'id': 1092, 'synset': 'telephone.n.01', 'synonyms': ['telephone', 'phone', 'telephone_set'], 'def': 'electronic device for communicating by voice over long distances', 'name': 'telephone'}, {'frequency': 'c', 'id': 1093, 'synset': 'telephone_booth.n.01', 'synonyms': ['telephone_booth', 'phone_booth', 'call_box', 'telephone_box', 'telephone_kiosk'], 'def': 'booth for using a telephone', 'name': 'telephone_booth'}, {'frequency': 'f', 'id': 1094, 'synset': 'telephone_pole.n.01', 'synonyms': ['telephone_pole', 'telegraph_pole', 'telegraph_post'], 'def': 'tall pole supporting telephone wires', 'name': 'telephone_pole'}, {'frequency': 'r', 'id': 1095, 'synset': 'telephoto_lens.n.01', 'synonyms': ['telephoto_lens', 'zoom_lens'], 'def': 'a camera lens that magnifies the image', 'name': 'telephoto_lens'}, {'frequency': 'c', 'id': 1096, 'synset': 'television_camera.n.01', 'synonyms': ['television_camera', 'tv_camera'], 'def': 'television equipment for capturing and recording video', 'name': 'television_camera'}, {'frequency': 'f', 'id': 1097, 'synset': 'television_receiver.n.01', 'synonyms': ['television_set', 'tv', 'tv_set'], 'def': 'an electronic device that receives television signals and displays them on a screen', 'name': 'television_set'}, {'frequency': 'f', 'id': 1098, 'synset': 'tennis_ball.n.01', 'synonyms': ['tennis_ball'], 'def': 'ball about the size of a fist used in playing tennis', 'name': 'tennis_ball'}, {'frequency': 'f', 'id': 1099, 'synset': 'tennis_racket.n.01', 'synonyms': ['tennis_racket'], 'def': 'a racket used to play tennis', 'name': 'tennis_racket'}, {'frequency': 'r', 'id': 1100, 'synset': 'tequila.n.01', 'synonyms': ['tequila'], 'def': 'Mexican liquor made from fermented juices of an agave plant', 'name': 'tequila'}, {'frequency': 'c', 'id': 1101, 'synset': 'thermometer.n.01', 'synonyms': ['thermometer'], 'def': 'measuring instrument for measuring temperature', 'name': 'thermometer'}, {'frequency': 'c', 'id': 1102, 'synset': 'thermos.n.01', 'synonyms': ['thermos_bottle'], 'def': 'vacuum flask that preserves temperature of hot or cold drinks', 'name': 'thermos_bottle'}, {'frequency': 'c', 'id': 1103, 'synset': 'thermostat.n.01', 'synonyms': ['thermostat'], 'def': 'a regulator for automatically regulating temperature by starting or stopping the supply of heat', 'name': 'thermostat'}, {'frequency': 'r', 'id': 1104, 'synset': 'thimble.n.02', 'synonyms': ['thimble'], 'def': 'a small metal cap to protect the finger while sewing; can be used as a small container', 'name': 'thimble'}, {'frequency': 'c', 'id': 1105, 'synset': 'thread.n.01', 'synonyms': ['thread', 'yarn'], 'def': 'a fine cord of twisted fibers (of cotton or silk or wool or nylon etc.) used in sewing and weaving', 'name': 'thread'}, {'frequency': 'c', 'id': 1106, 'synset': 'thumbtack.n.01', 'synonyms': ['thumbtack', 'drawing_pin', 'pushpin'], 'def': 'a tack for attaching papers to a bulletin board or drawing board', 'name': 'thumbtack'}, {'frequency': 'c', 'id': 1107, 'synset': 'tiara.n.01', 'synonyms': ['tiara'], 'def': 'a jeweled headdress worn by women on formal occasions', 'name': 'tiara'}, {'frequency': 'c', 'id': 1108, 'synset': 'tiger.n.02', 'synonyms': ['tiger'], 'def': 'large feline of forests in most of Asia having a tawny coat with black stripes', 'name': 'tiger'}, {'frequency': 'c', 'id': 1109, 'synset': 'tights.n.01', 'synonyms': ['tights_(clothing)', 'leotards'], 'def': 'skintight knit hose covering the body from the waist to the feet worn by acrobats and dancers and as stockings by women and girls', 'name': 'tights_(clothing)'}, {'frequency': 'c', 'id': 1110, 'synset': 'timer.n.01', 'synonyms': ['timer', 'stopwatch'], 'def': 'a timepiece that measures a time interval and signals its end', 'name': 'timer'}, {'frequency': 'f', 'id': 1111, 'synset': 'tinfoil.n.01', 'synonyms': ['tinfoil'], 'def': 'foil made of tin or an alloy of tin and lead', 'name': 'tinfoil'}, {'frequency': 'r', 'id': 1112, 'synset': 'tinsel.n.01', 'synonyms': ['tinsel'], 'def': 'a showy decoration that is basically valueless', 'name': 'tinsel'}, {'frequency': 'f', 'id': 1113, 'synset': 'tissue.n.02', 'synonyms': ['tissue_paper'], 'def': 'a soft thin (usually translucent) paper', 'name': 'tissue_paper'}, {'frequency': 'c', 'id': 1114, 'synset': 'toast.n.01', 'synonyms': ['toast_(food)'], 'def': 'slice of bread that has been toasted', 'name': 'toast_(food)'}, {'frequency': 'f', 'id': 1115, 'synset': 'toaster.n.02', 'synonyms': ['toaster'], 'def': 'a kitchen appliance (usually electric) for toasting bread', 'name': 'toaster'}, {'frequency': 'c', 'id': 1116, 'synset': 'toaster_oven.n.01', 'synonyms': ['toaster_oven'], 'def': 'kitchen appliance consisting of a small electric oven for toasting or warming food', 'name': 'toaster_oven'}, {'frequency': 'f', 'id': 1117, 'synset': 'toilet.n.02', 'synonyms': ['toilet'], 'def': 'a plumbing fixture for defecation and urination', 'name': 'toilet'}, {'frequency': 'f', 'id': 1118, 'synset': 'toilet_tissue.n.01', 'synonyms': ['toilet_tissue', 'toilet_paper', 'bathroom_tissue'], 'def': 'a soft thin absorbent paper for use in toilets', 'name': 'toilet_tissue'}, {'frequency': 'f', 'id': 1119, 'synset': 'tomato.n.01', 'synonyms': ['tomato'], 'def': 'mildly acid red or yellow pulpy fruit eaten as a vegetable', 'name': 'tomato'}, {'frequency': 'c', 'id': 1120, 'synset': 'tongs.n.01', 'synonyms': ['tongs'], 'def': 'any of various devices for taking hold of objects; usually have two hinged legs with handles above and pointed hooks below', 'name': 'tongs'}, {'frequency': 'c', 'id': 1121, 'synset': 'toolbox.n.01', 'synonyms': ['toolbox'], 'def': 'a box or chest or cabinet for holding hand tools', 'name': 'toolbox'}, {'frequency': 'f', 'id': 1122, 'synset': 'toothbrush.n.01', 'synonyms': ['toothbrush'], 'def': 'small brush; has long handle; used to clean teeth', 'name': 'toothbrush'}, {'frequency': 'f', 'id': 1123, 'synset': 'toothpaste.n.01', 'synonyms': ['toothpaste'], 'def': 'a dentifrice in the form of a paste', 'name': 'toothpaste'}, {'frequency': 'c', 'id': 1124, 'synset': 'toothpick.n.01', 'synonyms': ['toothpick'], 'def': 'pick consisting of a small strip of wood or plastic; used to pick food from between the teeth', 'name': 'toothpick'}, {'frequency': 'c', 'id': 1125, 'synset': 'top.n.09', 'synonyms': ['cover'], 'def': 'covering for a hole (especially a hole in the top of a container)', 'name': 'cover'}, {'frequency': 'c', 'id': 1126, 'synset': 'tortilla.n.01', 'synonyms': ['tortilla'], 'def': 'thin unleavened pancake made from cornmeal or wheat flour', 'name': 'tortilla'}, {'frequency': 'c', 'id': 1127, 'synset': 'tow_truck.n.01', 'synonyms': ['tow_truck'], 'def': 'a truck equipped to hoist and pull wrecked cars (or to remove cars from no-parking zones)', 'name': 'tow_truck'}, {'frequency': 'f', 'id': 1128, 'synset': 'towel.n.01', 'synonyms': ['towel'], 'def': 'a rectangular piece of absorbent cloth (or paper) for drying or wiping', 'name': 'towel'}, {'frequency': 'f', 'id': 1129, 'synset': 'towel_rack.n.01', 'synonyms': ['towel_rack', 'towel_rail', 'towel_bar'], 'def': 'a rack consisting of one or more bars on which towels can be hung', 'name': 'towel_rack'}, {'frequency': 'f', 'id': 1130, 'synset': 'toy.n.03', 'synonyms': ['toy'], 'def': 'a device regarded as providing amusement', 'name': 'toy'}, {'frequency': 'c', 'id': 1131, 'synset': 'tractor.n.01', 'synonyms': ['tractor_(farm_equipment)'], 'def': 'a wheeled vehicle with large wheels; used in farming and other applications', 'name': 'tractor_(farm_equipment)'}, {'frequency': 'f', 'id': 1132, 'synset': 'traffic_light.n.01', 'synonyms': ['traffic_light'], 'def': 'a device to control vehicle traffic often consisting of three or more lights', 'name': 'traffic_light'}, {'frequency': 'r', 'id': 1133, 'synset': 'trail_bike.n.01', 'synonyms': ['dirt_bike'], 'def': 'a lightweight motorcycle equipped with rugged tires and suspension for off-road use', 'name': 'dirt_bike'}, {'frequency': 'c', 'id': 1134, 'synset': 'trailer_truck.n.01', 'synonyms': ['trailer_truck', 'tractor_trailer', 'trucking_rig', 'articulated_lorry', 'semi_truck'], 'def': 'a truck consisting of a tractor and trailer together', 'name': 'trailer_truck'}, {'frequency': 'f', 'id': 1135, 'synset': 'train.n.01', 'synonyms': ['train_(railroad_vehicle)', 'railroad_train'], 'def': 'public or private transport provided by a line of railway cars coupled together and drawn by a locomotive', 'name': 'train_(railroad_vehicle)'}, {'frequency': 'r', 'id': 1136, 'synset': 'trampoline.n.01', 'synonyms': ['trampoline'], 'def': 'gymnastic apparatus consisting of a strong canvas sheet attached with springs to a metal frame', 'name': 'trampoline'}, {'frequency': 'f', 'id': 1137, 'synset': 'tray.n.01', 'synonyms': ['tray'], 'def': 'an open receptacle for holding or displaying or serving articles or food', 'name': 'tray'}, {'frequency': 'r', 'id': 1138, 'synset': 'tree_house.n.01', 'synonyms': ['tree_house'], 'def': '(NOT A TREE) a PLAYHOUSE built in the branches of a tree', 'name': 'tree_house'}, {'frequency': 'r', 'id': 1139, 'synset': 'trench_coat.n.01', 'synonyms': ['trench_coat'], 'def': 'a military style raincoat; belted with deep pockets', 'name': 'trench_coat'}, {'frequency': 'r', 'id': 1140, 'synset': 'triangle.n.05', 'synonyms': ['triangle_(musical_instrument)'], 'def': 'a percussion instrument consisting of a metal bar bent in the shape of an open triangle', 'name': 'triangle_(musical_instrument)'}, {'frequency': 'r', 'id': 1141, 'synset': 'tricycle.n.01', 'synonyms': ['tricycle'], 'def': 'a vehicle with three wheels that is moved by foot pedals', 'name': 'tricycle'}, {'frequency': 'c', 'id': 1142, 'synset': 'tripod.n.01', 'synonyms': ['tripod'], 'def': 'a three-legged rack used for support', 'name': 'tripod'}, {'frequency': 'f', 'id': 1143, 'synset': 'trouser.n.01', 'synonyms': ['trousers', 'pants_(clothing)'], 'def': 'a garment extending from the waist to the knee or ankle, covering each leg separately', 'name': 'trousers'}, {'frequency': 'f', 'id': 1144, 'synset': 'truck.n.01', 'synonyms': ['truck'], 'def': 'an automotive vehicle suitable for hauling', 'name': 'truck'}, {'frequency': 'r', 'id': 1145, 'synset': 'truffle.n.03', 'synonyms': ['truffle_(chocolate)', 'chocolate_truffle'], 'def': 'creamy chocolate candy', 'name': 'truffle_(chocolate)'}, {'frequency': 'c', 'id': 1146, 'synset': 'trunk.n.02', 'synonyms': ['trunk'], 'def': 'luggage consisting of a large strong case used when traveling or for storage', 'name': 'trunk'}, {'frequency': 'r', 'id': 1147, 'synset': 'tub.n.02', 'synonyms': ['vat'], 'def': 'a large open vessel for holding or storing liquids', 'name': 'vat'}, {'frequency': 'c', 'id': 1148, 'synset': 'turban.n.01', 'synonyms': ['turban'], 'def': 'a traditional headdress consisting of a long scarf wrapped around the head', 'name': 'turban'}, {'frequency': 'r', 'id': 1149, 'synset': 'turkey.n.01', 'synonyms': ['turkey_(bird)'], 'def': 'large gallinaceous bird with fan-shaped tail; widely domesticated for food', 'name': 'turkey_(bird)'}, {'frequency': 'c', 'id': 1150, 'synset': 'turkey.n.04', 'synonyms': ['turkey_(food)'], 'def': 'flesh of large domesticated fowl usually roasted', 'name': 'turkey_(food)'}, {'frequency': 'r', 'id': 1151, 'synset': 'turnip.n.01', 'synonyms': ['turnip'], 'def': 'widely cultivated plant having a large fleshy edible white or yellow root', 'name': 'turnip'}, {'frequency': 'c', 'id': 1152, 'synset': 'turtle.n.02', 'synonyms': ['turtle'], 'def': 'any of various aquatic and land reptiles having a bony shell and flipper-like limbs for swimming', 'name': 'turtle'}, {'frequency': 'r', 'id': 1153, 'synset': 'turtleneck.n.01', 'synonyms': ['turtleneck_(clothing)', 'polo-neck'], 'def': 'a sweater or jersey with a high close-fitting collar', 'name': 'turtleneck_(clothing)'}, {'frequency': 'r', 'id': 1154, 'synset': 'typewriter.n.01', 'synonyms': ['typewriter'], 'def': 'hand-operated character printer for printing written messages one character at a time', 'name': 'typewriter'}, {'frequency': 'f', 'id': 1155, 'synset': 'umbrella.n.01', 'synonyms': ['umbrella'], 'def': 'a lightweight handheld collapsible canopy', 'name': 'umbrella'}, {'frequency': 'c', 'id': 1156, 'synset': 'underwear.n.01', 'synonyms': ['underwear', 'underclothes', 'underclothing', 'underpants'], 'def': 'undergarment worn next to the skin and under the outer garments', 'name': 'underwear'}, {'frequency': 'r', 'id': 1157, 'synset': 'unicycle.n.01', 'synonyms': ['unicycle'], 'def': 'a vehicle with a single wheel that is driven by pedals', 'name': 'unicycle'}, {'frequency': 'c', 'id': 1158, 'synset': 'urinal.n.01', 'synonyms': ['urinal'], 'def': 'a plumbing fixture (usually attached to the wall) used by men to urinate', 'name': 'urinal'}, {'frequency': 'r', 'id': 1159, 'synset': 'urn.n.01', 'synonyms': ['urn'], 'def': 'a large vase that usually has a pedestal or feet', 'name': 'urn'}, {'frequency': 'c', 'id': 1160, 'synset': 'vacuum.n.04', 'synonyms': ['vacuum_cleaner'], 'def': 'an electrical home appliance that cleans by suction', 'name': 'vacuum_cleaner'}, {'frequency': 'c', 'id': 1161, 'synset': 'valve.n.03', 'synonyms': ['valve'], 'def': 'control consisting of a mechanical device for controlling the flow of a fluid', 'name': 'valve'}, {'frequency': 'f', 'id': 1162, 'synset': 'vase.n.01', 'synonyms': ['vase'], 'def': 'an open jar of glass or porcelain used as an ornament or to hold flowers', 'name': 'vase'}, {'frequency': 'c', 'id': 1163, 'synset': 'vending_machine.n.01', 'synonyms': ['vending_machine'], 'def': 'a slot machine for selling goods', 'name': 'vending_machine'}, {'frequency': 'f', 'id': 1164, 'synset': 'vent.n.01', 'synonyms': ['vent', 'blowhole', 'air_vent'], 'def': 'a hole for the escape of gas or air', 'name': 'vent'}, {'frequency': 'c', 'id': 1165, 'synset': 'videotape.n.01', 'synonyms': ['videotape'], 'def': 'a video recording made on magnetic tape', 'name': 'videotape'}, {'frequency': 'r', 'id': 1166, 'synset': 'vinegar.n.01', 'synonyms': ['vinegar'], 'def': 'sour-tasting liquid produced usually by oxidation of the alcohol in wine or cider and used as a condiment or food preservative', 'name': 'vinegar'}, {'frequency': 'r', 'id': 1167, 'synset': 'violin.n.01', 'synonyms': ['violin', 'fiddle'], 'def': 'bowed stringed instrument that is the highest member of the violin family', 'name': 'violin'}, {'frequency': 'r', 'id': 1168, 'synset': 'vodka.n.01', 'synonyms': ['vodka'], 'def': 'unaged colorless liquor originating in Russia', 'name': 'vodka'}, {'frequency': 'r', 'id': 1169, 'synset': 'volleyball.n.02', 'synonyms': ['volleyball'], 'def': 'an inflated ball used in playing volleyball', 'name': 'volleyball'}, {'frequency': 'r', 'id': 1170, 'synset': 'vulture.n.01', 'synonyms': ['vulture'], 'def': 'any of various large birds of prey having naked heads and weak claws and feeding chiefly on carrion', 'name': 'vulture'}, {'frequency': 'c', 'id': 1171, 'synset': 'waffle.n.01', 'synonyms': ['waffle'], 'def': 'pancake batter baked in a waffle iron', 'name': 'waffle'}, {'frequency': 'r', 'id': 1172, 'synset': 'waffle_iron.n.01', 'synonyms': ['waffle_iron'], 'def': 'a kitchen appliance for baking waffles', 'name': 'waffle_iron'}, {'frequency': 'c', 'id': 1173, 'synset': 'wagon.n.01', 'synonyms': ['wagon'], 'def': 'any of various kinds of wheeled vehicles drawn by an animal or a tractor', 'name': 'wagon'}, {'frequency': 'c', 'id': 1174, 'synset': 'wagon_wheel.n.01', 'synonyms': ['wagon_wheel'], 'def': 'a wheel of a wagon', 'name': 'wagon_wheel'}, {'frequency': 'c', 'id': 1175, 'synset': 'walking_stick.n.01', 'synonyms': ['walking_stick'], 'def': 'a stick carried in the hand for support in walking', 'name': 'walking_stick'}, {'frequency': 'c', 'id': 1176, 'synset': 'wall_clock.n.01', 'synonyms': ['wall_clock'], 'def': 'a clock mounted on a wall', 'name': 'wall_clock'}, {'frequency': 'f', 'id': 1177, 'synset': 'wall_socket.n.01', 'synonyms': ['wall_socket', 'wall_plug', 'electric_outlet', 'electrical_outlet', 'outlet', 'electric_receptacle'], 'def': 'receptacle providing a place in a wiring system where current can be taken to run electrical devices', 'name': 'wall_socket'}, {'frequency': 'c', 'id': 1178, 'synset': 'wallet.n.01', 'synonyms': ['wallet', 'billfold'], 'def': 'a pocket-size case for holding papers and paper money', 'name': 'wallet'}, {'frequency': 'r', 'id': 1179, 'synset': 'walrus.n.01', 'synonyms': ['walrus'], 'def': 'either of two large northern marine mammals having ivory tusks and tough hide over thick blubber', 'name': 'walrus'}, {'frequency': 'r', 'id': 1180, 'synset': 'wardrobe.n.01', 'synonyms': ['wardrobe'], 'def': 'a tall piece of furniture that provides storage space for clothes; has a door and rails or hooks for hanging clothes', 'name': 'wardrobe'}, {'frequency': 'r', 'id': 1181, 'synset': 'wasabi.n.02', 'synonyms': ['wasabi'], 'def': 'the thick green root of the wasabi plant that the Japanese use in cooking and that tastes like strong horseradish', 'name': 'wasabi'}, {'frequency': 'c', 'id': 1182, 'synset': 'washer.n.03', 'synonyms': ['automatic_washer', 'washing_machine'], 'def': 'a home appliance for washing clothes and linens automatically', 'name': 'automatic_washer'}, {'frequency': 'f', 'id': 1183, 'synset': 'watch.n.01', 'synonyms': ['watch', 'wristwatch'], 'def': 'a small, portable timepiece', 'name': 'watch'}, {'frequency': 'f', 'id': 1184, 'synset': 'water_bottle.n.01', 'synonyms': ['water_bottle'], 'def': 'a bottle for holding water', 'name': 'water_bottle'}, {'frequency': 'c', 'id': 1185, 'synset': 'water_cooler.n.01', 'synonyms': ['water_cooler'], 'def': 'a device for cooling and dispensing drinking water', 'name': 'water_cooler'}, {'frequency': 'c', 'id': 1186, 'synset': 'water_faucet.n.01', 'synonyms': ['water_faucet', 'water_tap', 'tap_(water_faucet)'], 'def': 'a faucet for drawing water from a pipe or cask', 'name': 'water_faucet'}, {'frequency': 'r', 'id': 1187, 'synset': 'water_filter.n.01', 'synonyms': ['water_filter'], 'def': 'a filter to remove impurities from the water supply', 'name': 'water_filter'}, {'frequency': 'r', 'id': 1188, 'synset': 'water_heater.n.01', 'synonyms': ['water_heater', 'hot-water_heater'], 'def': 'a heater and storage tank to supply heated water', 'name': 'water_heater'}, {'frequency': 'r', 'id': 1189, 'synset': 'water_jug.n.01', 'synonyms': ['water_jug'], 'def': 'a jug that holds water', 'name': 'water_jug'}, {'frequency': 'r', 'id': 1190, 'synset': 'water_pistol.n.01', 'synonyms': ['water_gun', 'squirt_gun'], 'def': 'plaything consisting of a toy pistol that squirts water', 'name': 'water_gun'}, {'frequency': 'c', 'id': 1191, 'synset': 'water_scooter.n.01', 'synonyms': ['water_scooter', 'sea_scooter', 'jet_ski'], 'def': 'a motorboat resembling a motor scooter (NOT A SURFBOARD OR WATER SKI)', 'name': 'water_scooter'}, {'frequency': 'c', 'id': 1192, 'synset': 'water_ski.n.01', 'synonyms': ['water_ski'], 'def': 'broad ski for skimming over water towed by a speedboat (DO NOT MARK WATER)', 'name': 'water_ski'}, {'frequency': 'c', 'id': 1193, 'synset': 'water_tower.n.01', 'synonyms': ['water_tower'], 'def': 'a large reservoir for water', 'name': 'water_tower'}, {'frequency': 'c', 'id': 1194, 'synset': 'watering_can.n.01', 'synonyms': ['watering_can'], 'def': 'a container with a handle and a spout with a perforated nozzle; used to sprinkle water over plants', 'name': 'watering_can'}, {'frequency': 'c', 'id': 1195, 'synset': 'watermelon.n.02', 'synonyms': ['watermelon'], 'def': 'large oblong or roundish melon with a hard green rind and sweet watery red or occasionally yellowish pulp', 'name': 'watermelon'}, {'frequency': 'f', 'id': 1196, 'synset': 'weathervane.n.01', 'synonyms': ['weathervane', 'vane_(weathervane)', 'wind_vane'], 'def': 'mechanical device attached to an elevated structure; rotates freely to show the direction of the wind', 'name': 'weathervane'}, {'frequency': 'c', 'id': 1197, 'synset': 'webcam.n.01', 'synonyms': ['webcam'], 'def': 'a digital camera designed to take digital photographs and transmit them over the internet', 'name': 'webcam'}, {'frequency': 'c', 'id': 1198, 'synset': 'wedding_cake.n.01', 'synonyms': ['wedding_cake', 'bridecake'], 'def': 'a rich cake with two or more tiers and covered with frosting and decorations; served at a wedding reception', 'name': 'wedding_cake'}, {'frequency': 'c', 'id': 1199, 'synset': 'wedding_ring.n.01', 'synonyms': ['wedding_ring', 'wedding_band'], 'def': 'a ring given to the bride and/or groom at the wedding', 'name': 'wedding_ring'}, {'frequency': 'f', 'id': 1200, 'synset': 'wet_suit.n.01', 'synonyms': ['wet_suit'], 'def': 'a close-fitting garment made of a permeable material; worn in cold water to retain body heat', 'name': 'wet_suit'}, {'frequency': 'f', 'id': 1201, 'synset': 'wheel.n.01', 'synonyms': ['wheel'], 'def': 'a circular frame with spokes (or a solid disc) that can rotate on a shaft or axle', 'name': 'wheel'}, {'frequency': 'c', 'id': 1202, 'synset': 'wheelchair.n.01', 'synonyms': ['wheelchair'], 'def': 'a movable chair mounted on large wheels', 'name': 'wheelchair'}, {'frequency': 'c', 'id': 1203, 'synset': 'whipped_cream.n.01', 'synonyms': ['whipped_cream'], 'def': 'cream that has been beaten until light and fluffy', 'name': 'whipped_cream'}, {'frequency': 'r', 'id': 1204, 'synset': 'whiskey.n.01', 'synonyms': ['whiskey'], 'def': 'a liquor made from fermented mash of grain', 'name': 'whiskey'}, {'frequency': 'r', 'id': 1205, 'synset': 'whistle.n.03', 'synonyms': ['whistle'], 'def': 'a small wind instrument that produces a whistling sound by blowing into it', 'name': 'whistle'}, {'frequency': 'r', 'id': 1206, 'synset': 'wick.n.02', 'synonyms': ['wick'], 'def': 'a loosely woven cord in a candle or oil lamp that is lit on fire', 'name': 'wick'}, {'frequency': 'c', 'id': 1207, 'synset': 'wig.n.01', 'synonyms': ['wig'], 'def': 'hairpiece covering the head and made of real or synthetic hair', 'name': 'wig'}, {'frequency': 'c', 'id': 1208, 'synset': 'wind_chime.n.01', 'synonyms': ['wind_chime'], 'def': 'a decorative arrangement of pieces of metal or glass or pottery that hang together loosely so the wind can cause them to tinkle', 'name': 'wind_chime'}, {'frequency': 'c', 'id': 1209, 'synset': 'windmill.n.01', 'synonyms': ['windmill'], 'def': 'a mill that is powered by the wind', 'name': 'windmill'}, {'frequency': 'c', 'id': 1210, 'synset': 'window_box.n.01', 'synonyms': ['window_box_(for_plants)'], 'def': 'a container for growing plants on a windowsill', 'name': 'window_box_(for_plants)'}, {'frequency': 'f', 'id': 1211, 'synset': 'windshield_wiper.n.01', 'synonyms': ['windshield_wiper', 'windscreen_wiper', 'wiper_(for_windshield/screen)'], 'def': 'a mechanical device that cleans the windshield', 'name': 'windshield_wiper'}, {'frequency': 'c', 'id': 1212, 'synset': 'windsock.n.01', 'synonyms': ['windsock', 'air_sock', 'air-sleeve', 'wind_sleeve', 'wind_cone'], 'def': 'a truncated cloth cone mounted on a mast/pole; shows wind direction', 'name': 'windsock'}, {'frequency': 'f', 'id': 1213, 'synset': 'wine_bottle.n.01', 'synonyms': ['wine_bottle'], 'def': 'a bottle for holding wine', 'name': 'wine_bottle'}, {'frequency': 'r', 'id': 1214, 'synset': 'wine_bucket.n.01', 'synonyms': ['wine_bucket', 'wine_cooler'], 'def': 'a bucket of ice used to chill a bottle of wine', 'name': 'wine_bucket'}, {'frequency': 'f', 'id': 1215, 'synset': 'wineglass.n.01', 'synonyms': ['wineglass'], 'def': 'a glass that has a stem and in which wine is served', 'name': 'wineglass'}, {'frequency': 'r', 'id': 1216, 'synset': 'wing_chair.n.01', 'synonyms': ['wing_chair'], 'def': 'easy chair having wings on each side of a high back', 'name': 'wing_chair'}, {'frequency': 'c', 'id': 1217, 'synset': 'winker.n.02', 'synonyms': ['blinder_(for_horses)'], 'def': 'blinds that prevent a horse from seeing something on either side', 'name': 'blinder_(for_horses)'}, {'frequency': 'c', 'id': 1218, 'synset': 'wok.n.01', 'synonyms': ['wok'], 'def': 'pan with a convex bottom; used for frying in Chinese cooking', 'name': 'wok'}, {'frequency': 'r', 'id': 1219, 'synset': 'wolf.n.01', 'synonyms': ['wolf'], 'def': 'a wild carnivorous mammal of the dog family, living and hunting in packs', 'name': 'wolf'}, {'frequency': 'c', 'id': 1220, 'synset': 'wooden_spoon.n.02', 'synonyms': ['wooden_spoon'], 'def': 'a spoon made of wood', 'name': 'wooden_spoon'}, {'frequency': 'c', 'id': 1221, 'synset': 'wreath.n.01', 'synonyms': ['wreath'], 'def': 'an arrangement of flowers, leaves, or stems fastened in a ring', 'name': 'wreath'}, {'frequency': 'c', 'id': 1222, 'synset': 'wrench.n.03', 'synonyms': ['wrench', 'spanner'], 'def': 'a hand tool that is used to hold or twist a nut or bolt', 'name': 'wrench'}, {'frequency': 'c', 'id': 1223, 'synset': 'wristband.n.01', 'synonyms': ['wristband'], 'def': 'band consisting of a part of a sleeve that covers the wrist', 'name': 'wristband'}, {'frequency': 'f', 'id': 1224, 'synset': 'wristlet.n.01', 'synonyms': ['wristlet', 'wrist_band'], 'def': 'a band or bracelet worn around the wrist', 'name': 'wristlet'}, {'frequency': 'r', 'id': 1225, 'synset': 'yacht.n.01', 'synonyms': ['yacht'], 'def': 'an expensive vessel propelled by sail or power and used for cruising or racing', 'name': 'yacht'}, {'frequency': 'r', 'id': 1226, 'synset': 'yak.n.02', 'synonyms': ['yak'], 'def': 'large long-haired wild ox of Tibet often domesticated', 'name': 'yak'}, {'frequency': 'c', 'id': 1227, 'synset': 'yogurt.n.01', 'synonyms': ['yogurt', 'yoghurt', 'yoghourt'], 'def': 'a custard-like food made from curdled milk', 'name': 'yogurt'}, {'frequency': 'r', 'id': 1228, 'synset': 'yoke.n.07', 'synonyms': ['yoke_(animal_equipment)'], 'def': 'gear joining two animals at the neck; NOT egg yolk', 'name': 'yoke_(animal_equipment)'}, {'frequency': 'f', 'id': 1229, 'synset': 'zebra.n.01', 'synonyms': ['zebra'], 'def': 'any of several fleet black-and-white striped African equines', 'name': 'zebra'}, {'frequency': 'c', 'id': 1230, 'synset': 'zucchini.n.02', 'synonyms': ['zucchini', 'courgette'], 'def': 'small cucumber-shaped vegetable marrow; typically dark green', 'name': 'zucchini'}] # noqa
-# fmt: on
diff --git a/spaces/Cecil8352/vits-models/monotonic_align/__init__.py b/spaces/Cecil8352/vits-models/monotonic_align/__init__.py
deleted file mode 100644
index e97eecc595dd3bd97d0104ec62799e2e5efea57c..0000000000000000000000000000000000000000
--- a/spaces/Cecil8352/vits-models/monotonic_align/__init__.py
+++ /dev/null
@@ -1,20 +0,0 @@
-from numpy import zeros, int32, float32
-from torch import from_numpy
-
-from .core import maximum_path_jit
-
-
-def maximum_path(neg_cent, mask):
- """ numba optimized version.
- neg_cent: [b, t_t, t_s]
- mask: [b, t_t, t_s]
- """
- device = neg_cent.device
- dtype = neg_cent.dtype
- neg_cent = neg_cent.data.cpu().numpy().astype(float32)
- path = zeros(neg_cent.shape, dtype=int32)
-
- t_t_max = mask.sum(1)[:, 0].data.cpu().numpy().astype(int32)
- t_s_max = mask.sum(2)[:, 0].data.cpu().numpy().astype(int32)
- maximum_path_jit(path, neg_cent, t_t_max, t_s_max)
- return from_numpy(path).to(device=device, dtype=dtype)
diff --git a/spaces/ChandraMohanNayal/AutoGPT/autogpt/memory/base.py b/spaces/ChandraMohanNayal/AutoGPT/autogpt/memory/base.py
deleted file mode 100644
index 691e2299c4caa5c2e9af5b2436727834f3cc6c67..0000000000000000000000000000000000000000
--- a/spaces/ChandraMohanNayal/AutoGPT/autogpt/memory/base.py
+++ /dev/null
@@ -1,43 +0,0 @@
-"""Base class for memory providers."""
-import abc
-
-import openai
-
-from autogpt.config import AbstractSingleton, Config
-
-cfg = Config()
-
-
-def get_ada_embedding(text):
- text = text.replace("\n", " ")
- if cfg.use_azure:
- return openai.Embedding.create(
- input=[text],
- engine=cfg.get_azure_deployment_id_for_model("text-embedding-ada-002"),
- )["data"][0]["embedding"]
- else:
- return openai.Embedding.create(input=[text], model="text-embedding-ada-002")[
- "data"
- ][0]["embedding"]
-
-
-class MemoryProviderSingleton(AbstractSingleton):
- @abc.abstractmethod
- def add(self, data):
- pass
-
- @abc.abstractmethod
- def get(self, data):
- pass
-
- @abc.abstractmethod
- def clear(self):
- pass
-
- @abc.abstractmethod
- def get_relevant(self, data, num_relevant=5):
- pass
-
- @abc.abstractmethod
- def get_stats(self):
- pass
diff --git a/spaces/CikeyQI/meme-api/meme_generator/memes/always_like/__init__.py b/spaces/CikeyQI/meme-api/meme_generator/memes/always_like/__init__.py
deleted file mode 100644
index 55edf0349806ff39c085d517087ff5544d907615..0000000000000000000000000000000000000000
--- a/spaces/CikeyQI/meme-api/meme_generator/memes/always_like/__init__.py
+++ /dev/null
@@ -1,94 +0,0 @@
-import random
-from pathlib import Path
-from typing import List
-
-from pil_utils import BuildImage, Text2Image
-
-from meme_generator import MemeArgsModel, add_meme
-from meme_generator.exception import TextOrNameNotEnough, TextOverLength
-
-img_dir = Path(__file__).parent / "images"
-
-
-def always_like(images: List[BuildImage], texts: List[str], args: MemeArgsModel):
- names = [info.name for info in args.user_infos]
-
- if len(images) > len(texts) + len(names):
- raise TextOrNameNotEnough("always_like")
- texts = texts + names
-
- img = images[0].convert("RGBA")
- name = texts[0]
- text = "我永远喜欢" + name
-
- frame = BuildImage.open(img_dir / "0.png")
- frame.paste(
- img.resize((350, 400), keep_ratio=True, inside=True), (25, 35), alpha=True
- )
- try:
- frame.draw_text(
- (20, 470, frame.width - 20, 570),
- text,
- max_fontsize=70,
- min_fontsize=30,
- weight="bold",
- )
- except ValueError:
- raise TextOverLength(text)
-
- def random_color():
- return random.choice(
- ["red", "darkorange", "gold", "darkgreen", "blue", "cyan", "purple"]
- )
-
- if len(images) > 1:
- text_w = Text2Image.from_text(text, 70).width
- ratio = min((frame.width - 40) / text_w, 1)
- text_w *= ratio
- name_w = Text2Image.from_text(name, 70).width * ratio
- start_w = text_w - name_w + (frame.width - text_w) // 2
- frame.draw_line(
- (start_w, 525, start_w + name_w, 525), fill=random_color(), width=10
- )
-
- current_h = 400
- for i, (image, name) in enumerate(zip(images[1:], texts[1:]), start=1):
- img = image.convert("RGBA")
- frame.paste(
- img.resize((350, 400), keep_ratio=True, inside=True),
- (10 + random.randint(0, 50), 20 + random.randint(0, 70)),
- alpha=True,
- )
- try:
- frame.draw_text(
- (400, current_h, frame.width - 20, current_h + 80),
- name,
- max_fontsize=70,
- min_fontsize=30,
- weight="bold",
- )
- except ValueError:
- raise TextOverLength(text)
-
- if len(images) > i + 1:
- name_w = min(Text2Image.from_text(name, 70).width, 380)
- start_w = 400 + (410 - name_w) // 2
- line_h = current_h + 40
- frame.draw_line(
- (start_w, line_h, start_w + name_w, line_h),
- fill=random_color(),
- width=10,
- )
- current_h -= 70
- return frame.save_jpg()
-
-
-add_meme(
- "always_like",
- always_like,
- min_images=1,
- max_images=6,
- min_texts=0,
- max_texts=6,
- keywords=["我永远喜欢"],
-)
diff --git a/spaces/CikeyQI/meme-api/meme_generator/memes/maimai_awaken/__init__.py b/spaces/CikeyQI/meme-api/meme_generator/memes/maimai_awaken/__init__.py
deleted file mode 100644
index ec62ba20f89ca9a3c853f9fa97b97c030d58c891..0000000000000000000000000000000000000000
--- a/spaces/CikeyQI/meme-api/meme_generator/memes/maimai_awaken/__init__.py
+++ /dev/null
@@ -1,24 +0,0 @@
-from pathlib import Path
-from typing import List
-
-from pil_utils import BuildImage
-
-from meme_generator import add_meme
-from meme_generator.utils import make_jpg_or_gif
-
-img_dir = Path(__file__).parent / "images"
-
-
-def maimai_awaken(images: List[BuildImage], texts, args):
- frame = BuildImage.open(img_dir / "0.png")
-
- def make(img: BuildImage) -> BuildImage:
- img = img.convert("RGBA").square().resize((250, 250)).rotate(-25, expand=True)
- return frame.copy().paste(img, (134, 134), alpha=True, below=True)
-
- return make_jpg_or_gif(images[0], make)
-
-
-add_meme(
- "maimai_awaken", maimai_awaken, min_images=1, max_images=1, keywords=["旅行伙伴觉醒"]
-)
diff --git a/spaces/CofAI/chat/g4f/Provider/Providers/Mishalsgpt.py b/spaces/CofAI/chat/g4f/Provider/Providers/Mishalsgpt.py
deleted file mode 100644
index 63080c674900a181f66380bcfe6c185b7469cebd..0000000000000000000000000000000000000000
--- a/spaces/CofAI/chat/g4f/Provider/Providers/Mishalsgpt.py
+++ /dev/null
@@ -1,23 +0,0 @@
-import os, requests, uuid
-from ...typing import sha256, Dict, get_type_hints
-
-url = 'https://mishalsgpt.vercel.app'
-model = ['gpt-3.5-turbo-16k-0613', 'gpt-3.5-turbo']
-supports_stream = True
-needs_auth = False
-
-def _create_completion(model: str, messages: list, stream: bool, **kwargs):
- headers = {
- 'Content-Type': 'application/json',
- }
- data = {
- 'model': model,
- 'temperature': 0.7,
- 'messages': messages
- }
- response = requests.post(url + '/api/openai/v1/chat/completions',
- headers=headers, json=data, stream=True)
- yield response.json()['choices'][0]['message']['content']
-
-params = f'g4f.Providers.{os.path.basename(__file__)[:-3]} supports: ' + \
- '(%s)' % ', '.join([f"{name}: {get_type_hints(_create_completion)[name].__name__}" for name in _create_completion.__code__.co_varnames[:_create_completion.__code__.co_argcount]])
diff --git a/spaces/Cpp4App/Cpp4App/SEM/text_preprocessing.py b/spaces/Cpp4App/Cpp4App/SEM/text_preprocessing.py
deleted file mode 100644
index 0ab20f1410d61e0e89c746bbc7e82390ebb10e88..0000000000000000000000000000000000000000
--- a/spaces/Cpp4App/Cpp4App/SEM/text_preprocessing.py
+++ /dev/null
@@ -1,194 +0,0 @@
-import re
-import nltk
-from nltk.corpus import stopwords
-from nltk import word_tokenize,pos_tag
-from nltk.stem import WordNetLemmatizer
-from nltk.corpus import wordnet
-nltk.download('stopwords')
-nltk.download('punkt')
-nltk.download('averaged_perceptron_tagger')
-nltk.download('wordnet')
-nltk.download('omw-1.4')
-
-def tokenize(sentence):
-
- sentence = re.sub(r'\s+', ' ', sentence)
- token_words = word_tokenize(sentence)
- token_words = pos_tag(token_words)
- return token_words
-
-
-wordnet_lematizer = WordNetLemmatizer()
-def stem(token_words):
-
- words_lematizer = []
- for word, tag in token_words:
- if tag.startswith('NN'):
- word_lematizer = wordnet_lematizer.lemmatize(word, pos='n')
- elif tag.startswith('VB'):
- word_lematizer = wordnet_lematizer.lemmatize(word, pos='v')
- elif tag.startswith('JJ'):
- word_lematizer = wordnet_lematizer.lemmatize(word, pos='a')
- elif tag.startswith('R'):
- word_lematizer = wordnet_lematizer.lemmatize(word, pos='r')
- else:
- word_lematizer = wordnet_lematizer.lemmatize(word)
- words_lematizer.append(word_lematizer)
- return words_lematizer
-
-def delete_invalid_word(token_words):
- valid_word = []
- for word in token_words:
- if len(wordnet.synsets(word)) > 0:
- valid_word.append(word)
- return valid_word
-
-sr = stopwords.words('english')
-sr.append("limited")
-sr.append("additionnaly")
-sr.append("e.g")
-sr.remove("other")
-sr.remove("than")
-sr.remove("not")
-sr.remove("you")
-sr.remove("and")
-sr2 = stopwords.words('english')
-def delete_stopwords(token_words):
-
- cleaned_words = [word for word in token_words if word not in sr]
- return cleaned_words
-
-def delete_stopwords2(token_words):
-
- cleaned_words = [word for word in token_words if word not in sr2]
- return cleaned_words
-
-def delete_adjwords(token_words):
-
- cleaned_words = [word for word in token_words if word not in sr]
- return cleaned_words
-
-
-def is_number(s):
-
- try:
- float(s)
- return True
- except ValueError:
- pass
-
- try:
- import unicodedata
- unicodedata.numeric(s)
- return True
- except (TypeError, ValueError):
- pass
-
- return False
-characters_title = [' ','.',',','|' , ':', ';', '?', '(', ')', '[', ']', '&', '!', '*', '@', '#', '$', '%','-','...','^','{','}']
-characters = [' ','|' , ':', ';', '?', '(', ')', '[', ']', '&', '!', '*', '@', '#', '$', '%','-','...','^','{','}']
-characters_proposal = [' ','|' , '?', '(', ')', '[', ']', '&', '!', '*', '@', '#', '$', '%','-','...','^','{','}']
-def delete_characters(token_words):
-
- words_list = [word for word in token_words if word not in characters]
- return words_list
-def delete_characters_proposal(token_words):
-
- words_list = [word for word in token_words if word not in characters_proposal and not is_number(word)]
- return words_list
-
-def delete_characters_title(token_words):
-
- words_list = [word for word in token_words if word not in characters and not is_number(word)]
- return words_list
-
-
-def to_lower(token_words):
-
- words_lists = [x.lower() for x in token_words]
- return words_lists
-
-def pre_process_title(text):
-
- token_words = tokenize(text)
-
- token_words = stem(token_words)
-
- token_words = delete_invalid_word(token_words)
-
- token_words = delete_characters_title(token_words)
-
- token_words = to_lower(token_words)
-
- return ' '.join(token_words)
-
-def pre_process(text):
-
- token_words = tokenize(text)
-
- token_words = stem(token_words)
-
- token_words = delete_stopwords(token_words)
-
- token_words = delete_characters(token_words)
-
- token_words = to_lower(token_words)
-
- return ' '.join(token_words)
-
-def pre_process_type(text):
-
- token_words = tokenize(text)
-
- token_words = stem(token_words)
-
- token_words = delete_stopwords2(token_words)
-
- token_words = delete_characters(token_words)
-
- token_words = to_lower(token_words)
-
- return ' '.join(token_words)
-
-
-def pre_process_proposal(text):
-
- token_words = tokenize(text)
-
- token_words = stem(token_words)
-
- token_words = delete_stopwords(token_words)
-
- token_words = delete_characters_proposal(token_words)
-
- token_words = to_lower(token_words)
-
- return ' '.join(token_words)
-
-def pre_process_list(text):
-
- token_words = tokenize(text)
-
- token_words = stem(token_words)
-
- token_words = delete_stopwords(token_words)
-
- token_words = delete_characters(token_words)
-
- token_words = to_lower(token_words)
-
- return token_words
-
-def pre_process_stop(text):
-
- token_words = tokenize(text)
-
- token_words = stem(token_words)
-
- token_words = delete_characters(token_words)
-
- token_words = to_lower(token_words)
-
- text = ' '.join(token_words)
- final_text = text.split(".")
- return final_text
diff --git a/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/PIL/SpiderImagePlugin.py b/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/PIL/SpiderImagePlugin.py
deleted file mode 100644
index 5614957c176685c24f0c4cfebb4661d7c856b053..0000000000000000000000000000000000000000
--- a/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/PIL/SpiderImagePlugin.py
+++ /dev/null
@@ -1,318 +0,0 @@
-#
-# The Python Imaging Library.
-#
-# SPIDER image file handling
-#
-# History:
-# 2004-08-02 Created BB
-# 2006-03-02 added save method
-# 2006-03-13 added support for stack images
-#
-# Copyright (c) 2004 by Health Research Inc. (HRI) RENSSELAER, NY 12144.
-# Copyright (c) 2004 by William Baxter.
-# Copyright (c) 2004 by Secret Labs AB.
-# Copyright (c) 2004 by Fredrik Lundh.
-#
-
-##
-# Image plugin for the Spider image format. This format is used
-# by the SPIDER software, in processing image data from electron
-# microscopy and tomography.
-##
-
-#
-# SpiderImagePlugin.py
-#
-# The Spider image format is used by SPIDER software, in processing
-# image data from electron microscopy and tomography.
-#
-# Spider home page:
-# https://spider.wadsworth.org/spider_doc/spider/docs/spider.html
-#
-# Details about the Spider image format:
-# https://spider.wadsworth.org/spider_doc/spider/docs/image_doc.html
-#
-import os
-import struct
-import sys
-
-from . import Image, ImageFile
-
-
-def isInt(f):
- try:
- i = int(f)
- if f - i == 0:
- return 1
- else:
- return 0
- except (ValueError, OverflowError):
- return 0
-
-
-iforms = [1, 3, -11, -12, -21, -22]
-
-
-# There is no magic number to identify Spider files, so just check a
-# series of header locations to see if they have reasonable values.
-# Returns no. of bytes in the header, if it is a valid Spider header,
-# otherwise returns 0
-
-
-def isSpiderHeader(t):
- h = (99,) + t # add 1 value so can use spider header index start=1
- # header values 1,2,5,12,13,22,23 should be integers
- for i in [1, 2, 5, 12, 13, 22, 23]:
- if not isInt(h[i]):
- return 0
- # check iform
- iform = int(h[5])
- if iform not in iforms:
- return 0
- # check other header values
- labrec = int(h[13]) # no. records in file header
- labbyt = int(h[22]) # total no. of bytes in header
- lenbyt = int(h[23]) # record length in bytes
- if labbyt != (labrec * lenbyt):
- return 0
- # looks like a valid header
- return labbyt
-
-
-def isSpiderImage(filename):
- with open(filename, "rb") as fp:
- f = fp.read(92) # read 23 * 4 bytes
- t = struct.unpack(">23f", f) # try big-endian first
- hdrlen = isSpiderHeader(t)
- if hdrlen == 0:
- t = struct.unpack("<23f", f) # little-endian
- hdrlen = isSpiderHeader(t)
- return hdrlen
-
-
-class SpiderImageFile(ImageFile.ImageFile):
- format = "SPIDER"
- format_description = "Spider 2D image"
- _close_exclusive_fp_after_loading = False
-
- def _open(self):
- # check header
- n = 27 * 4 # read 27 float values
- f = self.fp.read(n)
-
- try:
- self.bigendian = 1
- t = struct.unpack(">27f", f) # try big-endian first
- hdrlen = isSpiderHeader(t)
- if hdrlen == 0:
- self.bigendian = 0
- t = struct.unpack("<27f", f) # little-endian
- hdrlen = isSpiderHeader(t)
- if hdrlen == 0:
- msg = "not a valid Spider file"
- raise SyntaxError(msg)
- except struct.error as e:
- msg = "not a valid Spider file"
- raise SyntaxError(msg) from e
-
- h = (99,) + t # add 1 value : spider header index starts at 1
- iform = int(h[5])
- if iform != 1:
- msg = "not a Spider 2D image"
- raise SyntaxError(msg)
-
- self._size = int(h[12]), int(h[2]) # size in pixels (width, height)
- self.istack = int(h[24])
- self.imgnumber = int(h[27])
-
- if self.istack == 0 and self.imgnumber == 0:
- # stk=0, img=0: a regular 2D image
- offset = hdrlen
- self._nimages = 1
- elif self.istack > 0 and self.imgnumber == 0:
- # stk>0, img=0: Opening the stack for the first time
- self.imgbytes = int(h[12]) * int(h[2]) * 4
- self.hdrlen = hdrlen
- self._nimages = int(h[26])
- # Point to the first image in the stack
- offset = hdrlen * 2
- self.imgnumber = 1
- elif self.istack == 0 and self.imgnumber > 0:
- # stk=0, img>0: an image within the stack
- offset = hdrlen + self.stkoffset
- self.istack = 2 # So Image knows it's still a stack
- else:
- msg = "inconsistent stack header values"
- raise SyntaxError(msg)
-
- if self.bigendian:
- self.rawmode = "F;32BF"
- else:
- self.rawmode = "F;32F"
- self.mode = "F"
-
- self.tile = [("raw", (0, 0) + self.size, offset, (self.rawmode, 0, 1))]
- self._fp = self.fp # FIXME: hack
-
- @property
- def n_frames(self):
- return self._nimages
-
- @property
- def is_animated(self):
- return self._nimages > 1
-
- # 1st image index is zero (although SPIDER imgnumber starts at 1)
- def tell(self):
- if self.imgnumber < 1:
- return 0
- else:
- return self.imgnumber - 1
-
- def seek(self, frame):
- if self.istack == 0:
- msg = "attempt to seek in a non-stack file"
- raise EOFError(msg)
- if not self._seek_check(frame):
- return
- self.stkoffset = self.hdrlen + frame * (self.hdrlen + self.imgbytes)
- self.fp = self._fp
- self.fp.seek(self.stkoffset)
- self._open()
-
- # returns a byte image after rescaling to 0..255
- def convert2byte(self, depth=255):
- (minimum, maximum) = self.getextrema()
- m = 1
- if maximum != minimum:
- m = depth / (maximum - minimum)
- b = -m * minimum
- return self.point(lambda i, m=m, b=b: i * m + b).convert("L")
-
- # returns a ImageTk.PhotoImage object, after rescaling to 0..255
- def tkPhotoImage(self):
- from . import ImageTk
-
- return ImageTk.PhotoImage(self.convert2byte(), palette=256)
-
-
-# --------------------------------------------------------------------
-# Image series
-
-
-# given a list of filenames, return a list of images
-def loadImageSeries(filelist=None):
- """create a list of :py:class:`~PIL.Image.Image` objects for use in a montage"""
- if filelist is None or len(filelist) < 1:
- return
-
- imglist = []
- for img in filelist:
- if not os.path.exists(img):
- print(f"unable to find {img}")
- continue
- try:
- with Image.open(img) as im:
- im = im.convert2byte()
- except Exception:
- if not isSpiderImage(img):
- print(img + " is not a Spider image file")
- continue
- im.info["filename"] = img
- imglist.append(im)
- return imglist
-
-
-# --------------------------------------------------------------------
-# For saving images in Spider format
-
-
-def makeSpiderHeader(im):
- nsam, nrow = im.size
- lenbyt = nsam * 4 # There are labrec records in the header
- labrec = int(1024 / lenbyt)
- if 1024 % lenbyt != 0:
- labrec += 1
- labbyt = labrec * lenbyt
- nvalues = int(labbyt / 4)
- if nvalues < 23:
- return []
-
- hdr = []
- for i in range(nvalues):
- hdr.append(0.0)
-
- # NB these are Fortran indices
- hdr[1] = 1.0 # nslice (=1 for an image)
- hdr[2] = float(nrow) # number of rows per slice
- hdr[3] = float(nrow) # number of records in the image
- hdr[5] = 1.0 # iform for 2D image
- hdr[12] = float(nsam) # number of pixels per line
- hdr[13] = float(labrec) # number of records in file header
- hdr[22] = float(labbyt) # total number of bytes in header
- hdr[23] = float(lenbyt) # record length in bytes
-
- # adjust for Fortran indexing
- hdr = hdr[1:]
- hdr.append(0.0)
- # pack binary data into a string
- return [struct.pack("f", v) for v in hdr]
-
-
-def _save(im, fp, filename):
- if im.mode[0] != "F":
- im = im.convert("F")
-
- hdr = makeSpiderHeader(im)
- if len(hdr) < 256:
- msg = "Error creating Spider header"
- raise OSError(msg)
-
- # write the SPIDER header
- fp.writelines(hdr)
-
- rawmode = "F;32NF" # 32-bit native floating point
- ImageFile._save(im, fp, [("raw", (0, 0) + im.size, 0, (rawmode, 0, 1))])
-
-
-def _save_spider(im, fp, filename):
- # get the filename extension and register it with Image
- ext = os.path.splitext(filename)[1]
- Image.register_extension(SpiderImageFile.format, ext)
- _save(im, fp, filename)
-
-
-# --------------------------------------------------------------------
-
-
-Image.register_open(SpiderImageFile.format, SpiderImageFile)
-Image.register_save(SpiderImageFile.format, _save_spider)
-
-if __name__ == "__main__":
- if len(sys.argv) < 2:
- print("Syntax: python3 SpiderImagePlugin.py [infile] [outfile]")
- sys.exit()
-
- filename = sys.argv[1]
- if not isSpiderImage(filename):
- print("input image must be in Spider format")
- sys.exit()
-
- with Image.open(filename) as im:
- print("image: " + str(im))
- print("format: " + str(im.format))
- print("size: " + str(im.size))
- print("mode: " + str(im.mode))
- print("max, min: ", end=" ")
- print(im.getextrema())
-
- if len(sys.argv) > 2:
- outfile = sys.argv[2]
-
- # perform some image operation
- im = im.transpose(Image.Transpose.FLIP_LEFT_RIGHT)
- print(
- f"saving a flipped version of {os.path.basename(filename)} "
- f"as {outfile} "
- )
- im.save(outfile, SpiderImageFile.format)
diff --git a/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/fastapi/security/open_id_connect_url.py b/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/fastapi/security/open_id_connect_url.py
deleted file mode 100644
index 4e65f1f6c486fa579554c61b9d137c7fda1f1b17..0000000000000000000000000000000000000000
--- a/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/fastapi/security/open_id_connect_url.py
+++ /dev/null
@@ -1,34 +0,0 @@
-from typing import Optional
-
-from fastapi.openapi.models import OpenIdConnect as OpenIdConnectModel
-from fastapi.security.base import SecurityBase
-from starlette.exceptions import HTTPException
-from starlette.requests import Request
-from starlette.status import HTTP_403_FORBIDDEN
-
-
-class OpenIdConnect(SecurityBase):
- def __init__(
- self,
- *,
- openIdConnectUrl: str,
- scheme_name: Optional[str] = None,
- description: Optional[str] = None,
- auto_error: bool = True,
- ):
- self.model = OpenIdConnectModel(
- openIdConnectUrl=openIdConnectUrl, description=description
- )
- self.scheme_name = scheme_name or self.__class__.__name__
- self.auto_error = auto_error
-
- async def __call__(self, request: Request) -> Optional[str]:
- authorization = request.headers.get("Authorization")
- if not authorization:
- if self.auto_error:
- raise HTTPException(
- status_code=HTTP_403_FORBIDDEN, detail="Not authenticated"
- )
- else:
- return None
- return authorization
diff --git a/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/fontTools/ttLib/tables/_m_a_x_p.py b/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/fontTools/ttLib/tables/_m_a_x_p.py
deleted file mode 100644
index 2934149773c6909cbab65861168524c10c9e7865..0000000000000000000000000000000000000000
--- a/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/fontTools/ttLib/tables/_m_a_x_p.py
+++ /dev/null
@@ -1,140 +0,0 @@
-from fontTools.misc import sstruct
-from fontTools.misc.textTools import safeEval
-from . import DefaultTable
-
-maxpFormat_0_5 = """
- > # big endian
- tableVersion: i
- numGlyphs: H
-"""
-
-maxpFormat_1_0_add = """
- > # big endian
- maxPoints: H
- maxContours: H
- maxCompositePoints: H
- maxCompositeContours: H
- maxZones: H
- maxTwilightPoints: H
- maxStorage: H
- maxFunctionDefs: H
- maxInstructionDefs: H
- maxStackElements: H
- maxSizeOfInstructions: H
- maxComponentElements: H
- maxComponentDepth: H
-"""
-
-
-class table__m_a_x_p(DefaultTable.DefaultTable):
-
- dependencies = ["glyf"]
-
- def decompile(self, data, ttFont):
- dummy, data = sstruct.unpack2(maxpFormat_0_5, data, self)
- self.numGlyphs = int(self.numGlyphs)
- if self.tableVersion != 0x00005000:
- dummy, data = sstruct.unpack2(maxpFormat_1_0_add, data, self)
- assert len(data) == 0
-
- def compile(self, ttFont):
- if "glyf" in ttFont:
- if ttFont.isLoaded("glyf") and ttFont.recalcBBoxes:
- self.recalc(ttFont)
- else:
- pass # CFF
- self.numGlyphs = len(ttFont.getGlyphOrder())
- if self.tableVersion != 0x00005000:
- self.tableVersion = 0x00010000
- data = sstruct.pack(maxpFormat_0_5, self)
- if self.tableVersion == 0x00010000:
- data = data + sstruct.pack(maxpFormat_1_0_add, self)
- return data
-
- def recalc(self, ttFont):
- """Recalculate the font bounding box, and most other maxp values except
- for the TT instructions values. Also recalculate the value of bit 1
- of the flags field and the font bounding box of the 'head' table.
- """
- glyfTable = ttFont["glyf"]
- hmtxTable = ttFont["hmtx"]
- headTable = ttFont["head"]
- self.numGlyphs = len(glyfTable)
- INFINITY = 100000
- xMin = +INFINITY
- yMin = +INFINITY
- xMax = -INFINITY
- yMax = -INFINITY
- maxPoints = 0
- maxContours = 0
- maxCompositePoints = 0
- maxCompositeContours = 0
- maxComponentElements = 0
- maxComponentDepth = 0
- allXMinIsLsb = 1
- for glyphName in ttFont.getGlyphOrder():
- g = glyfTable[glyphName]
- if g.numberOfContours:
- if hmtxTable[glyphName][1] != g.xMin:
- allXMinIsLsb = 0
- xMin = min(xMin, g.xMin)
- yMin = min(yMin, g.yMin)
- xMax = max(xMax, g.xMax)
- yMax = max(yMax, g.yMax)
- if g.numberOfContours > 0:
- nPoints, nContours = g.getMaxpValues()
- maxPoints = max(maxPoints, nPoints)
- maxContours = max(maxContours, nContours)
- elif g.isComposite():
- nPoints, nContours, componentDepth = g.getCompositeMaxpValues(
- glyfTable
- )
- maxCompositePoints = max(maxCompositePoints, nPoints)
- maxCompositeContours = max(maxCompositeContours, nContours)
- maxComponentElements = max(maxComponentElements, len(g.components))
- maxComponentDepth = max(maxComponentDepth, componentDepth)
- if xMin == +INFINITY:
- headTable.xMin = 0
- headTable.yMin = 0
- headTable.xMax = 0
- headTable.yMax = 0
- else:
- headTable.xMin = xMin
- headTable.yMin = yMin
- headTable.xMax = xMax
- headTable.yMax = yMax
- self.maxPoints = maxPoints
- self.maxContours = maxContours
- self.maxCompositePoints = maxCompositePoints
- self.maxCompositeContours = maxCompositeContours
- self.maxComponentElements = maxComponentElements
- self.maxComponentDepth = maxComponentDepth
- if allXMinIsLsb:
- headTable.flags = headTable.flags | 0x2
- else:
- headTable.flags = headTable.flags & ~0x2
-
- def testrepr(self):
- items = sorted(self.__dict__.items())
- print(". . . . . . . . .")
- for combo in items:
- print(" %s: %s" % combo)
- print(". . . . . . . . .")
-
- def toXML(self, writer, ttFont):
- if self.tableVersion != 0x00005000:
- writer.comment("Most of this table will be recalculated by the compiler")
- writer.newline()
- formatstring, names, fixes = sstruct.getformat(maxpFormat_0_5)
- if self.tableVersion != 0x00005000:
- formatstring, names_1_0, fixes = sstruct.getformat(maxpFormat_1_0_add)
- names = names + names_1_0
- for name in names:
- value = getattr(self, name)
- if name == "tableVersion":
- value = hex(value)
- writer.simpletag(name, value=value)
- writer.newline()
-
- def fromXML(self, name, attrs, content, ttFont):
- setattr(self, name, safeEval(attrs["value"]))
diff --git a/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/fontTools/varLib/builder.py b/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/fontTools/varLib/builder.py
deleted file mode 100644
index 94cc5bf063b1dc67ff58bdb7f2bd3d642bee4ce4..0000000000000000000000000000000000000000
--- a/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/fontTools/varLib/builder.py
+++ /dev/null
@@ -1,157 +0,0 @@
-from fontTools import ttLib
-from fontTools.ttLib.tables import otTables as ot
-
-# VariationStore
-
-
-def buildVarRegionAxis(axisSupport):
- self = ot.VarRegionAxis()
- self.StartCoord, self.PeakCoord, self.EndCoord = [float(v) for v in axisSupport]
- return self
-
-
-def buildVarRegion(support, axisTags):
- assert all(tag in axisTags for tag in support.keys()), (
- "Unknown axis tag found.",
- support,
- axisTags,
- )
- self = ot.VarRegion()
- self.VarRegionAxis = []
- for tag in axisTags:
- self.VarRegionAxis.append(buildVarRegionAxis(support.get(tag, (0, 0, 0))))
- return self
-
-
-def buildVarRegionList(supports, axisTags):
- self = ot.VarRegionList()
- self.RegionAxisCount = len(axisTags)
- self.Region = []
- for support in supports:
- self.Region.append(buildVarRegion(support, axisTags))
- self.RegionCount = len(self.Region)
- return self
-
-
-def _reorderItem(lst, mapping):
- return [lst[i] for i in mapping]
-
-
-def VarData_calculateNumShorts(self, optimize=False):
- count = self.VarRegionCount
- items = self.Item
- bit_lengths = [0] * count
- for item in items:
- # The "+ (i < -1)" magic is to handle two's-compliment.
- # That is, we want to get back 7 for -128, whereas
- # bit_length() returns 8. Similarly for -65536.
- # The reason "i < -1" is used instead of "i < 0" is that
- # the latter would make it return 0 for "-1" instead of 1.
- bl = [(i + (i < -1)).bit_length() for i in item]
- bit_lengths = [max(*pair) for pair in zip(bl, bit_lengths)]
- # The addition of 8, instead of seven, is to account for the sign bit.
- # This "((b + 8) >> 3) if b else 0" when combined with the above
- # "(i + (i < -1)).bit_length()" is a faster way to compute byte-lengths
- # conforming to:
- #
- # byte_length = (0 if i == 0 else
- # 1 if -128 <= i < 128 else
- # 2 if -65536 <= i < 65536 else
- # ...)
- byte_lengths = [((b + 8) >> 3) if b else 0 for b in bit_lengths]
-
- # https://github.com/fonttools/fonttools/issues/2279
- longWords = any(b > 2 for b in byte_lengths)
-
- if optimize:
- # Reorder columns such that wider columns come before narrower columns
- mapping = []
- mapping.extend(i for i, b in enumerate(byte_lengths) if b > 2)
- mapping.extend(i for i, b in enumerate(byte_lengths) if b == 2)
- mapping.extend(i for i, b in enumerate(byte_lengths) if b == 1)
-
- byte_lengths = _reorderItem(byte_lengths, mapping)
- self.VarRegionIndex = _reorderItem(self.VarRegionIndex, mapping)
- self.VarRegionCount = len(self.VarRegionIndex)
- for i in range(len(items)):
- items[i] = _reorderItem(items[i], mapping)
-
- if longWords:
- self.NumShorts = (
- max((i for i, b in enumerate(byte_lengths) if b > 2), default=-1) + 1
- )
- self.NumShorts |= 0x8000
- else:
- self.NumShorts = (
- max((i for i, b in enumerate(byte_lengths) if b > 1), default=-1) + 1
- )
-
- self.VarRegionCount = len(self.VarRegionIndex)
- return self
-
-
-ot.VarData.calculateNumShorts = VarData_calculateNumShorts
-
-
-def VarData_CalculateNumShorts(self, optimize=True):
- """Deprecated name for VarData_calculateNumShorts() which
- defaults to optimize=True. Use varData.calculateNumShorts()
- or varData.optimize()."""
- return VarData_calculateNumShorts(self, optimize=optimize)
-
-
-def VarData_optimize(self):
- return VarData_calculateNumShorts(self, optimize=True)
-
-
-ot.VarData.optimize = VarData_optimize
-
-
-def buildVarData(varRegionIndices, items, optimize=True):
- self = ot.VarData()
- self.VarRegionIndex = list(varRegionIndices)
- regionCount = self.VarRegionCount = len(self.VarRegionIndex)
- records = self.Item = []
- if items:
- for item in items:
- assert len(item) == regionCount
- records.append(list(item))
- self.ItemCount = len(self.Item)
- self.calculateNumShorts(optimize=optimize)
- return self
-
-
-def buildVarStore(varRegionList, varDataList):
- self = ot.VarStore()
- self.Format = 1
- self.VarRegionList = varRegionList
- self.VarData = list(varDataList)
- self.VarDataCount = len(self.VarData)
- return self
-
-
-# Variation helpers
-
-
-def buildVarIdxMap(varIdxes, glyphOrder):
- self = ot.VarIdxMap()
- self.mapping = {g: v for g, v in zip(glyphOrder, varIdxes)}
- return self
-
-
-def buildDeltaSetIndexMap(varIdxes):
- mapping = list(varIdxes)
- if all(i == v for i, v in enumerate(mapping)):
- return None
- self = ot.DeltaSetIndexMap()
- self.mapping = mapping
- self.Format = 1 if len(mapping) > 0xFFFF else 0
- return self
-
-
-def buildVarDevTable(varIdx):
- self = ot.Device()
- self.DeltaFormat = 0x8000
- self.StartSize = varIdx >> 16
- self.EndSize = varIdx & 0xFFFF
- return self
diff --git a/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/fsspec/implementations/webhdfs.py b/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/fsspec/implementations/webhdfs.py
deleted file mode 100644
index cc595934f9a0161be24d3e300260fb73d4fd9784..0000000000000000000000000000000000000000
--- a/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/fsspec/implementations/webhdfs.py
+++ /dev/null
@@ -1,447 +0,0 @@
-# https://hadoop.apache.org/docs/r1.0.4/webhdfs.html
-
-import logging
-import os
-import secrets
-import shutil
-import tempfile
-import uuid
-from contextlib import suppress
-from urllib.parse import quote
-
-import requests
-
-from ..spec import AbstractBufferedFile, AbstractFileSystem
-from ..utils import infer_storage_options, tokenize
-
-logger = logging.getLogger("webhdfs")
-
-
-class WebHDFS(AbstractFileSystem):
- """
- Interface to HDFS over HTTP using the WebHDFS API. Supports also HttpFS gateways.
-
- Three auth mechanisms are supported:
-
- insecure: no auth is done, and the user is assumed to be whoever they
- say they are (parameter ``user``), or a predefined value such as
- "dr.who" if not given
- spnego: when kerberos authentication is enabled, auth is negotiated by
- requests_kerberos https://github.com/requests/requests-kerberos .
- This establishes a session based on existing kinit login and/or
- specified principal/password; parameters are passed with ``kerb_kwargs``
- token: uses an existing Hadoop delegation token from another secured
- service. Indeed, this client can also generate such tokens when
- not insecure. Note that tokens expire, but can be renewed (by a
- previously specified user) and may allow for proxying.
-
- """
-
- tempdir = str(tempfile.gettempdir())
- protocol = "webhdfs", "webHDFS"
-
- def __init__(
- self,
- host,
- port=50070,
- kerberos=False,
- token=None,
- user=None,
- proxy_to=None,
- kerb_kwargs=None,
- data_proxy=None,
- use_https=False,
- **kwargs,
- ):
- """
- Parameters
- ----------
- host: str
- Name-node address
- port: int
- Port for webHDFS
- kerberos: bool
- Whether to authenticate with kerberos for this connection
- token: str or None
- If given, use this token on every call to authenticate. A user
- and user-proxy may be encoded in the token and should not be also
- given
- user: str or None
- If given, assert the user name to connect with
- proxy_to: str or None
- If given, the user has the authority to proxy, and this value is
- the user in who's name actions are taken
- kerb_kwargs: dict
- Any extra arguments for HTTPKerberosAuth, see
- ``_
- data_proxy: dict, callable or None
- If given, map data-node addresses. This can be necessary if the
- HDFS cluster is behind a proxy, running on Docker or otherwise has
- a mismatch between the host-names given by the name-node and the
- address by which to refer to them from the client. If a dict,
- maps host names ``host->data_proxy[host]``; if a callable, full
- URLs are passed, and function must conform to
- ``url->data_proxy(url)``.
- use_https: bool
- Whether to connect to the Name-node using HTTPS instead of HTTP
- kwargs
- """
- if self._cached:
- return
- super().__init__(**kwargs)
- self.url = "{protocol}://{host}:{port}/webhdfs/v1".format(
- protocol="https" if use_https else "http", host=host, port=port
- )
- self.kerb = kerberos
- self.kerb_kwargs = kerb_kwargs or {}
- self.pars = {}
- self.proxy = data_proxy or {}
- if token is not None:
- if user is not None or proxy_to is not None:
- raise ValueError(
- "If passing a delegation token, must not set "
- "user or proxy_to, as these are encoded in the"
- " token"
- )
- self.pars["delegation"] = token
- if user is not None:
- self.pars["user.name"] = user
- if proxy_to is not None:
- self.pars["doas"] = proxy_to
- if kerberos and user is not None:
- raise ValueError(
- "If using Kerberos auth, do not specify the "
- "user, this is handled by kinit."
- )
- self._connect()
-
- self._fsid = "webhdfs_" + tokenize(host, port)
-
- @property
- def fsid(self):
- return self._fsid
-
- def _connect(self):
- self.session = requests.Session()
- if self.kerb:
- from requests_kerberos import HTTPKerberosAuth
-
- self.session.auth = HTTPKerberosAuth(**self.kerb_kwargs)
-
- def _call(self, op, method="get", path=None, data=None, redirect=True, **kwargs):
- url = self.url + quote(path or "")
- args = kwargs.copy()
- args.update(self.pars)
- args["op"] = op.upper()
- logger.debug("sending %s with %s", url, method)
- out = self.session.request(
- method=method.upper(),
- url=url,
- params=args,
- data=data,
- allow_redirects=redirect,
- )
- if out.status_code in [400, 401, 403, 404, 500]:
- try:
- err = out.json()
- msg = err["RemoteException"]["message"]
- exp = err["RemoteException"]["exception"]
- except (ValueError, KeyError):
- pass
- else:
- if exp in ["IllegalArgumentException", "UnsupportedOperationException"]:
- raise ValueError(msg)
- elif exp in ["SecurityException", "AccessControlException"]:
- raise PermissionError(msg)
- elif exp in ["FileNotFoundException"]:
- raise FileNotFoundError(msg)
- else:
- raise RuntimeError(msg)
- out.raise_for_status()
- return out
-
- def _open(
- self,
- path,
- mode="rb",
- block_size=None,
- autocommit=True,
- replication=None,
- permissions=None,
- **kwargs,
- ):
- """
-
- Parameters
- ----------
- path: str
- File location
- mode: str
- 'rb', 'wb', etc.
- block_size: int
- Client buffer size for read-ahead or write buffer
- autocommit: bool
- If False, writes to temporary file that only gets put in final
- location upon commit
- replication: int
- Number of copies of file on the cluster, write mode only
- permissions: str or int
- posix permissions, write mode only
- kwargs
-
- Returns
- -------
- WebHDFile instance
- """
- block_size = block_size or self.blocksize
- return WebHDFile(
- self,
- path,
- mode=mode,
- block_size=block_size,
- tempdir=self.tempdir,
- autocommit=autocommit,
- replication=replication,
- permissions=permissions,
- )
-
- @staticmethod
- def _process_info(info):
- info["type"] = info["type"].lower()
- info["size"] = info["length"]
- return info
-
- @classmethod
- def _strip_protocol(cls, path):
- return infer_storage_options(path)["path"]
-
- @staticmethod
- def _get_kwargs_from_urls(urlpath):
- out = infer_storage_options(urlpath)
- out.pop("path", None)
- out.pop("protocol", None)
- if "username" in out:
- out["user"] = out.pop("username")
- return out
-
- def info(self, path):
- out = self._call("GETFILESTATUS", path=path)
- info = out.json()["FileStatus"]
- info["name"] = path
- return self._process_info(info)
-
- def ls(self, path, detail=False):
- out = self._call("LISTSTATUS", path=path)
- infos = out.json()["FileStatuses"]["FileStatus"]
- for info in infos:
- self._process_info(info)
- info["name"] = path.rstrip("/") + "/" + info["pathSuffix"]
- if detail:
- return sorted(infos, key=lambda i: i["name"])
- else:
- return sorted(info["name"] for info in infos)
-
- def content_summary(self, path):
- """Total numbers of files, directories and bytes under path"""
- out = self._call("GETCONTENTSUMMARY", path=path)
- return out.json()["ContentSummary"]
-
- def ukey(self, path):
- """Checksum info of file, giving method and result"""
- out = self._call("GETFILECHECKSUM", path=path, redirect=False)
- if "Location" in out.headers:
- location = self._apply_proxy(out.headers["Location"])
- out2 = self.session.get(location)
- out2.raise_for_status()
- return out2.json()["FileChecksum"]
- else:
- out.raise_for_status()
- return out.json()["FileChecksum"]
-
- def home_directory(self):
- """Get user's home directory"""
- out = self._call("GETHOMEDIRECTORY")
- return out.json()["Path"]
-
- def get_delegation_token(self, renewer=None):
- """Retrieve token which can give the same authority to other uses
-
- Parameters
- ----------
- renewer: str or None
- User who may use this token; if None, will be current user
- """
- if renewer:
- out = self._call("GETDELEGATIONTOKEN", renewer=renewer)
- else:
- out = self._call("GETDELEGATIONTOKEN")
- t = out.json()["Token"]
- if t is None:
- raise ValueError("No token available for this user/security context")
- return t["urlString"]
-
- def renew_delegation_token(self, token):
- """Make token live longer. Returns new expiry time"""
- out = self._call("RENEWDELEGATIONTOKEN", method="put", token=token)
- return out.json()["long"]
-
- def cancel_delegation_token(self, token):
- """Stop the token from being useful"""
- self._call("CANCELDELEGATIONTOKEN", method="put", token=token)
-
- def chmod(self, path, mod):
- """Set the permission at path
-
- Parameters
- ----------
- path: str
- location to set (file or directory)
- mod: str or int
- posix epresentation or permission, give as oct string, e.g, '777'
- or 0o777
- """
- self._call("SETPERMISSION", method="put", path=path, permission=mod)
-
- def chown(self, path, owner=None, group=None):
- """Change owning user and/or group"""
- kwargs = {}
- if owner is not None:
- kwargs["owner"] = owner
- if group is not None:
- kwargs["group"] = group
- self._call("SETOWNER", method="put", path=path, **kwargs)
-
- def set_replication(self, path, replication):
- """
- Set file replication factor
-
- Parameters
- ----------
- path: str
- File location (not for directories)
- replication: int
- Number of copies of file on the cluster. Should be smaller than
- number of data nodes; normally 3 on most systems.
- """
- self._call("SETREPLICATION", path=path, method="put", replication=replication)
-
- def mkdir(self, path, **kwargs):
- self._call("MKDIRS", method="put", path=path)
-
- def makedirs(self, path, exist_ok=False):
- if exist_ok is False and self.exists(path):
- raise FileExistsError(path)
- self.mkdir(path)
-
- def mv(self, path1, path2, **kwargs):
- self._call("RENAME", method="put", path=path1, destination=path2)
-
- def rm(self, path, recursive=False, **kwargs):
- self._call(
- "DELETE",
- method="delete",
- path=path,
- recursive="true" if recursive else "false",
- )
-
- def rm_file(self, path, **kwargs):
- self.rm(path)
-
- def cp_file(self, lpath, rpath, **kwargs):
- with self.open(lpath) as lstream:
- tmp_fname = "/".join([self._parent(rpath), f".tmp.{secrets.token_hex(16)}"])
- # Perform an atomic copy (stream to a temporary file and
- # move it to the actual destination).
- try:
- with self.open(tmp_fname, "wb") as rstream:
- shutil.copyfileobj(lstream, rstream)
- self.mv(tmp_fname, rpath)
- except BaseException: # noqa
- with suppress(FileNotFoundError):
- self.rm(tmp_fname)
- raise
-
- def _apply_proxy(self, location):
- if self.proxy and callable(self.proxy):
- location = self.proxy(location)
- elif self.proxy:
- # as a dict
- for k, v in self.proxy.items():
- location = location.replace(k, v, 1)
- return location
-
-
-class WebHDFile(AbstractBufferedFile):
- """A file living in HDFS over webHDFS"""
-
- def __init__(self, fs, path, **kwargs):
- super().__init__(fs, path, **kwargs)
- kwargs = kwargs.copy()
- if kwargs.get("permissions", None) is None:
- kwargs.pop("permissions", None)
- if kwargs.get("replication", None) is None:
- kwargs.pop("replication", None)
- self.permissions = kwargs.pop("permissions", 511)
- tempdir = kwargs.pop("tempdir")
- if kwargs.pop("autocommit", False) is False:
- self.target = self.path
- self.path = os.path.join(tempdir, str(uuid.uuid4()))
-
- def _upload_chunk(self, final=False):
- """Write one part of a multi-block file upload
-
- Parameters
- ==========
- final: bool
- This is the last block, so should complete file, if
- self.autocommit is True.
- """
- out = self.fs.session.post(
- self.location,
- data=self.buffer.getvalue(),
- headers={"content-type": "application/octet-stream"},
- )
- out.raise_for_status()
- return True
-
- def _initiate_upload(self):
- """Create remote file/upload"""
- kwargs = self.kwargs.copy()
- if "a" in self.mode:
- op, method = "APPEND", "POST"
- else:
- op, method = "CREATE", "PUT"
- kwargs["overwrite"] = "true"
- out = self.fs._call(op, method, self.path, redirect=False, **kwargs)
- location = self.fs._apply_proxy(out.headers["Location"])
- if "w" in self.mode:
- # create empty file to append to
- out2 = self.fs.session.put(
- location, headers={"content-type": "application/octet-stream"}
- )
- out2.raise_for_status()
- # after creating empty file, change location to append to
- out2 = self.fs._call("APPEND", "POST", self.path, redirect=False, **kwargs)
- self.location = self.fs._apply_proxy(out2.headers["Location"])
-
- def _fetch_range(self, start, end):
- start = max(start, 0)
- end = min(self.size, end)
- if start >= end or start >= self.size:
- return b""
- out = self.fs._call(
- "OPEN", path=self.path, offset=start, length=end - start, redirect=False
- )
- out.raise_for_status()
- if "Location" in out.headers:
- location = out.headers["Location"]
- out2 = self.fs.session.get(self.fs._apply_proxy(location))
- return out2.content
- else:
- return out.content
-
- def commit(self):
- self.fs.mv(self.path, self.target)
-
- def discard(self):
- self.fs.rm(self.path)
diff --git a/spaces/Daniil-plotnikov/Daniil-plotnikov-russian-vision-v4/README.md b/spaces/Daniil-plotnikov/Daniil-plotnikov-russian-vision-v4/README.md
deleted file mode 100644
index 1c9425bb54a51af364f74d1d4d023f1e2234c4cd..0000000000000000000000000000000000000000
--- a/spaces/Daniil-plotnikov/Daniil-plotnikov-russian-vision-v4/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Daniil Plotnikov Russian Vision V4
-emoji: 🌖
-colorFrom: gray
-colorTo: blue
-sdk: gradio
-sdk_version: 3.36.1
-app_file: app.py
-pinned: false
-license: openrail
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/Dauzy/whisper-webui/src/prompts/abstractPromptStrategy.py b/spaces/Dauzy/whisper-webui/src/prompts/abstractPromptStrategy.py
deleted file mode 100644
index 41e8cba49fdbcc294ea216fffcafee89b07ed4df..0000000000000000000000000000000000000000
--- a/spaces/Dauzy/whisper-webui/src/prompts/abstractPromptStrategy.py
+++ /dev/null
@@ -1,73 +0,0 @@
-import abc
-
-
-class AbstractPromptStrategy:
- """
- Represents a strategy for generating prompts for a given audio segment.
-
- Note that the strategy must be picklable, as it will be serialized and sent to the workers.
- """
-
- @abc.abstractmethod
- def get_segment_prompt(self, segment_index: int, whisper_prompt: str, detected_language: str) -> str:
- """
- Retrieves the prompt for a given segment.
-
- Parameters
- ----------
- segment_index: int
- The index of the segment.
- whisper_prompt: str
- The prompt for the segment generated by Whisper. This is typically concatenated with the initial prompt.
- detected_language: str
- The language detected for the segment.
- """
- pass
-
- @abc.abstractmethod
- def on_segment_finished(self, segment_index: int, whisper_prompt: str, detected_language: str, result: dict):
- """
- Called when a segment has finished processing.
-
- Parameters
- ----------
- segment_index: int
- The index of the segment.
- whisper_prompt: str
- The prompt for the segment generated by Whisper. This is typically concatenated with the initial prompt.
- detected_language: str
- The language detected for the segment.
- result: dict
- The result of the segment. It has the following format:
- {
- "text": str,
- "segments": [
- {
- "text": str,
- "start": float,
- "end": float,
- "words": [words],
- }
- ],
- "language": str,
- }
- """
- pass
-
- def _concat_prompt(self, prompt1, prompt2):
- """
- Concatenates two prompts.
-
- Parameters
- ----------
- prompt1: str
- The first prompt.
- prompt2: str
- The second prompt.
- """
- if (prompt1 is None):
- return prompt2
- elif (prompt2 is None):
- return prompt1
- else:
- return prompt1 + " " + prompt2
\ No newline at end of file
diff --git a/spaces/Detomo/detect_greeting_app/README.md b/spaces/Detomo/detect_greeting_app/README.md
deleted file mode 100644
index 3994a01c0dfebce5a47725711f3a43d18e4ad3ac..0000000000000000000000000000000000000000
--- a/spaces/Detomo/detect_greeting_app/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Detect Greeting
-emoji: 📚
-colorFrom: gray
-colorTo: indigo
-sdk: gradio
-sdk_version: 3.21.0
-app_file: app.py
-pinned: false
-license: creativeml-openrail-m
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/Dragonnnext/scylla-proxy/README.md b/spaces/Dragonnnext/scylla-proxy/README.md
deleted file mode 100644
index e8692664aa94cb9a310c2cdfede4940b0892f1b4..0000000000000000000000000000000000000000
--- a/spaces/Dragonnnext/scylla-proxy/README.md
+++ /dev/null
@@ -1,9 +0,0 @@
----
-title: Scylla OAI Proxy
-emoji: 🐙
-colorFrom: purple
-colorTo: gray
-sdk: docker
-pinned: false
----
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/ECCV2022/bytetrack/yolox/exp/base_exp.py b/spaces/ECCV2022/bytetrack/yolox/exp/base_exp.py
deleted file mode 100644
index c4aed89f55ad742cf32d1ba6c7bd7363609a222e..0000000000000000000000000000000000000000
--- a/spaces/ECCV2022/bytetrack/yolox/exp/base_exp.py
+++ /dev/null
@@ -1,75 +0,0 @@
-#!/usr/bin/env python3
-# -*- coding:utf-8 -*-
-# Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
-
-import torch
-from torch.nn import Module
-
-from yolox.utils import LRScheduler
-
-import ast
-import pprint
-from abc import ABCMeta, abstractmethod
-from tabulate import tabulate
-from typing import Dict
-
-
-class BaseExp(metaclass=ABCMeta):
- """Basic class for any experiment."""
-
- def __init__(self):
- self.seed = None
- self.output_dir = "./YOLOX_outputs"
- self.print_interval = 100
- self.eval_interval = 10
-
- @abstractmethod
- def get_model(self) -> Module:
- pass
-
- @abstractmethod
- def get_data_loader(
- self, batch_size: int, is_distributed: bool
- ) -> Dict[str, torch.utils.data.DataLoader]:
- pass
-
- @abstractmethod
- def get_optimizer(self, batch_size: int) -> torch.optim.Optimizer:
- pass
-
- @abstractmethod
- def get_lr_scheduler(
- self, lr: float, iters_per_epoch: int, **kwargs
- ) -> LRScheduler:
- pass
-
- @abstractmethod
- def get_evaluator(self):
- pass
-
- @abstractmethod
- def eval(self, model, evaluator, weights):
- pass
-
- def __repr__(self):
- table_header = ["keys", "values"]
- exp_table = [
- (str(k), pprint.pformat(v))
- for k, v in vars(self).items()
- if not k.startswith("_")
- ]
- return tabulate(exp_table, headers=table_header, tablefmt="fancy_grid")
-
- def merge(self, cfg_list):
- assert len(cfg_list) % 2 == 0
- for k, v in zip(cfg_list[0::2], cfg_list[1::2]):
- # only update value with same key
- if hasattr(self, k):
- src_value = getattr(self, k)
- src_type = type(src_value)
- if src_value is not None and src_type != type(v):
- try:
- v = src_type(v)
- except Exception:
- v = ast.literal_eval(v)
- setattr(self, k, v)
diff --git a/spaces/EronSamez/RVC_HFmeu/infer/lib/uvr5_pack/lib_v5/nets_537227KB.py b/spaces/EronSamez/RVC_HFmeu/infer/lib/uvr5_pack/lib_v5/nets_537227KB.py
deleted file mode 100644
index 823b44fb64898e8dcbb12180ba45d1718f9b03f7..0000000000000000000000000000000000000000
--- a/spaces/EronSamez/RVC_HFmeu/infer/lib/uvr5_pack/lib_v5/nets_537227KB.py
+++ /dev/null
@@ -1,123 +0,0 @@
-import numpy as np
-import torch
-import torch.nn.functional as F
-from torch import nn
-
-from . import layers_537238KB as layers
-
-
-class BaseASPPNet(nn.Module):
- def __init__(self, nin, ch, dilations=(4, 8, 16)):
- super(BaseASPPNet, self).__init__()
- self.enc1 = layers.Encoder(nin, ch, 3, 2, 1)
- self.enc2 = layers.Encoder(ch, ch * 2, 3, 2, 1)
- self.enc3 = layers.Encoder(ch * 2, ch * 4, 3, 2, 1)
- self.enc4 = layers.Encoder(ch * 4, ch * 8, 3, 2, 1)
-
- self.aspp = layers.ASPPModule(ch * 8, ch * 16, dilations)
-
- self.dec4 = layers.Decoder(ch * (8 + 16), ch * 8, 3, 1, 1)
- self.dec3 = layers.Decoder(ch * (4 + 8), ch * 4, 3, 1, 1)
- self.dec2 = layers.Decoder(ch * (2 + 4), ch * 2, 3, 1, 1)
- self.dec1 = layers.Decoder(ch * (1 + 2), ch, 3, 1, 1)
-
- def __call__(self, x):
- h, e1 = self.enc1(x)
- h, e2 = self.enc2(h)
- h, e3 = self.enc3(h)
- h, e4 = self.enc4(h)
-
- h = self.aspp(h)
-
- h = self.dec4(h, e4)
- h = self.dec3(h, e3)
- h = self.dec2(h, e2)
- h = self.dec1(h, e1)
-
- return h
-
-
-class CascadedASPPNet(nn.Module):
- def __init__(self, n_fft):
- super(CascadedASPPNet, self).__init__()
- self.stg1_low_band_net = BaseASPPNet(2, 64)
- self.stg1_high_band_net = BaseASPPNet(2, 64)
-
- self.stg2_bridge = layers.Conv2DBNActiv(66, 32, 1, 1, 0)
- self.stg2_full_band_net = BaseASPPNet(32, 64)
-
- self.stg3_bridge = layers.Conv2DBNActiv(130, 64, 1, 1, 0)
- self.stg3_full_band_net = BaseASPPNet(64, 128)
-
- self.out = nn.Conv2d(128, 2, 1, bias=False)
- self.aux1_out = nn.Conv2d(64, 2, 1, bias=False)
- self.aux2_out = nn.Conv2d(64, 2, 1, bias=False)
-
- self.max_bin = n_fft // 2
- self.output_bin = n_fft // 2 + 1
-
- self.offset = 128
-
- def forward(self, x, aggressiveness=None):
- mix = x.detach()
- x = x.clone()
-
- x = x[:, :, : self.max_bin]
-
- bandw = x.size()[2] // 2
- aux1 = torch.cat(
- [
- self.stg1_low_band_net(x[:, :, :bandw]),
- self.stg1_high_band_net(x[:, :, bandw:]),
- ],
- dim=2,
- )
-
- h = torch.cat([x, aux1], dim=1)
- aux2 = self.stg2_full_band_net(self.stg2_bridge(h))
-
- h = torch.cat([x, aux1, aux2], dim=1)
- h = self.stg3_full_band_net(self.stg3_bridge(h))
-
- mask = torch.sigmoid(self.out(h))
- mask = F.pad(
- input=mask,
- pad=(0, 0, 0, self.output_bin - mask.size()[2]),
- mode="replicate",
- )
-
- if self.training:
- aux1 = torch.sigmoid(self.aux1_out(aux1))
- aux1 = F.pad(
- input=aux1,
- pad=(0, 0, 0, self.output_bin - aux1.size()[2]),
- mode="replicate",
- )
- aux2 = torch.sigmoid(self.aux2_out(aux2))
- aux2 = F.pad(
- input=aux2,
- pad=(0, 0, 0, self.output_bin - aux2.size()[2]),
- mode="replicate",
- )
- return mask * mix, aux1 * mix, aux2 * mix
- else:
- if aggressiveness:
- mask[:, :, : aggressiveness["split_bin"]] = torch.pow(
- mask[:, :, : aggressiveness["split_bin"]],
- 1 + aggressiveness["value"] / 3,
- )
- mask[:, :, aggressiveness["split_bin"] :] = torch.pow(
- mask[:, :, aggressiveness["split_bin"] :],
- 1 + aggressiveness["value"],
- )
-
- return mask * mix
-
- def predict(self, x_mag, aggressiveness=None):
- h = self.forward(x_mag, aggressiveness)
-
- if self.offset > 0:
- h = h[:, :, :, self.offset : -self.offset]
- assert h.size()[3] > 0
-
- return h
diff --git a/spaces/EsoCode/text-generation-webui/modules/html_generator.py b/spaces/EsoCode/text-generation-webui/modules/html_generator.py
deleted file mode 100644
index 509fe70b7e64b354e9549f475a0e5e956528ef8e..0000000000000000000000000000000000000000
--- a/spaces/EsoCode/text-generation-webui/modules/html_generator.py
+++ /dev/null
@@ -1,273 +0,0 @@
-import os
-import re
-import time
-from pathlib import Path
-
-import markdown
-from PIL import Image, ImageOps
-
-from modules.utils import get_available_chat_styles
-
-# This is to store the paths to the thumbnails of the profile pictures
-image_cache = {}
-
-with open(Path(__file__).resolve().parent / '../css/html_readable_style.css', 'r') as f:
- readable_css = f.read()
-with open(Path(__file__).resolve().parent / '../css/html_4chan_style.css', 'r') as css_f:
- _4chan_css = css_f.read()
-with open(Path(__file__).resolve().parent / '../css/html_instruct_style.css', 'r') as f:
- instruct_css = f.read()
-
-# Custom chat styles
-chat_styles = {}
-for k in get_available_chat_styles():
- chat_styles[k] = open(Path(f'css/chat_style-{k}.css'), 'r').read()
-
-
-def fix_newlines(string):
- string = string.replace('\n', '\n\n')
- string = re.sub(r"\n{3,}", "\n\n", string)
- string = string.strip()
- return string
-
-
-def replace_blockquote(m):
- return m.group().replace('\n', '\n> ').replace('\\begin{blockquote}', '').replace('\\end{blockquote}', '')
-
-
-def convert_to_markdown(string):
-
- # Blockquote
- pattern = re.compile(r'\\begin{blockquote}(.*?)\\end{blockquote}', re.DOTALL)
- string = pattern.sub(replace_blockquote, string)
-
- # Code
- string = string.replace('\\begin{code}', '```')
- string = string.replace('\\end{code}', '```')
- string = re.sub(r"(.)```", r"\1\n```", string)
-
- result = ''
- is_code = False
- for line in string.split('\n'):
- if line.lstrip(' ').startswith('```'):
- is_code = not is_code
-
- result += line
- if is_code or line.startswith('|'): # Don't add an extra \n for tables or code
- result += '\n'
- else:
- result += '\n\n'
-
- if is_code:
- result = result + '```' # Unfinished code block
-
- string = result.strip()
- return markdown.markdown(string, extensions=['fenced_code', 'tables'])
-
-
-def generate_basic_html(string):
- string = convert_to_markdown(string)
- string = f'
{src}\n'
- src = f'Anonymous No.{number}\n{src}'
- return src
-
-
-def generate_4chan_html(f):
- posts = []
- post = ''
- c = -2
- for line in f.splitlines():
- line += "\n"
- if line == '-----\n':
- continue
- elif line.startswith('--- '):
- c += 1
- if post != '':
- src = process_post(post, c)
- posts.append(src)
- post = line
- else:
- post += line
- if post != '':
- src = process_post(post, c)
- posts.append(src)
-
- for i in range(len(posts)):
- if i == 0:
- posts[i] = f'
{posts[i]}
\n'
- else:
- posts[i] = f'
{posts[i]}
\n'
-
- output = ''
- output += f'
'
- for post in posts:
- output += post
- output += '
'
- output = output.split('\n')
- for i in range(len(output)):
- output[i] = re.sub(r'^(>(.*?)( |))', r'\1', output[i])
- output[i] = re.sub(r'^
'
-
- # We use ?name2 and ?time.time() to force the browser to reset caches
- img_bot = f'' if Path("cache/pfp_character.png").exists() else ''
- img_me = f'' if Path("cache/pfp_me.png").exists() else ''
-
- for i, _row in enumerate(history[::-1]):
- row = [convert_to_markdown(entry) for entry in _row]
-
- output += f"""
-
-
-The steps are the following:
-
-- Paste a read-access token from hf.co/settings/tokens. Read access is enough given that we will open a PR against the source repo.
-- Input a model id from the Hub
-- Input the filename from the root dir of the repo that you would like to convert, e.g. 'xl-pruned.safetensors'
-- Click "Submit"
-- That's it! You'll get feedback if it works or not, and if it worked, you'll get the URL of the opened PR 🔥
-
-⚠️ If you encounter weird error messages, please have a look into the Logs and feel free to open a PR to correct the error messages.
-
-
-
-"""
- for key, text in items.items():
- info += f"""
-
-{str(key)}:[{str(text)}]
-
-""".strip()+"\n"
-
- if len(info) == 0:
- message = "Nothing found in the image."
- info = f"
{message}
"
-
- return (info,a,res)
-
-
-def main():
- args = parse_args()
- model = load_model()
- labels = load_labels()
-
- func = functools.partial(predict, model=model, labels=labels)
- func = functools.update_wrapper(func, predict)
-
- gr.Interface(
- func,
- [
- gr.inputs.Image(type='pil', label='Input'),
- gr.inputs.Slider(0,
- 1,
- step=args.score_slider_step,
- default=args.score_threshold,
- label='Score Threshold'),
- ],
- [
- gr.outputs.HTML(),
- gr.outputs.Textbox(label='DeepDanbooru Output (string)'),
- gr.outputs.Label(label='DeepDanbooru Output (label)')
- ],
- examples=[
- ['eula.png',0.5],
- ['keqing.png',0.5]
- ],
- title=TITLE,
- description='''
-Just play for fun...
- ''',
- theme=args.theme,
- allow_flagging=args.allow_flagging,
- ).launch(
- enable_queue=True,
- share=args.share,
- )
-
-
-if __name__ == '__main__':
- main()
diff --git a/spaces/Pattr/DrumClassification/lilypond-2.24.2/lib/lilypond/2.24.2/ccache/lily/skyline.go b/spaces/Pattr/DrumClassification/lilypond-2.24.2/lib/lilypond/2.24.2/ccache/lily/skyline.go
deleted file mode 100644
index 4c0ecc5d03a2366aec32d5c5b2395d32ebf06268..0000000000000000000000000000000000000000
Binary files a/spaces/Pattr/DrumClassification/lilypond-2.24.2/lib/lilypond/2.24.2/ccache/lily/skyline.go and /dev/null differ
diff --git a/spaces/Pattr/DrumClassification/lilypond-2.24.2/lib/lilypond/2.24.2/ccache/lily/song-util.go b/spaces/Pattr/DrumClassification/lilypond-2.24.2/lib/lilypond/2.24.2/ccache/lily/song-util.go
deleted file mode 100644
index bbc98b125caf392b4397516fdd02b486cda73484..0000000000000000000000000000000000000000
Binary files a/spaces/Pattr/DrumClassification/lilypond-2.24.2/lib/lilypond/2.24.2/ccache/lily/song-util.go and /dev/null differ
diff --git a/spaces/Pie31415/control-animation/annotator/midas/utils.py b/spaces/Pie31415/control-animation/annotator/midas/utils.py
deleted file mode 100644
index 9a9d3b5b66370fa98da9e067ba53ead848ea9a59..0000000000000000000000000000000000000000
--- a/spaces/Pie31415/control-animation/annotator/midas/utils.py
+++ /dev/null
@@ -1,189 +0,0 @@
-"""Utils for monoDepth."""
-import sys
-import re
-import numpy as np
-import cv2
-import torch
-
-
-def read_pfm(path):
- """Read pfm file.
-
- Args:
- path (str): path to file
-
- Returns:
- tuple: (data, scale)
- """
- with open(path, "rb") as file:
-
- color = None
- width = None
- height = None
- scale = None
- endian = None
-
- header = file.readline().rstrip()
- if header.decode("ascii") == "PF":
- color = True
- elif header.decode("ascii") == "Pf":
- color = False
- else:
- raise Exception("Not a PFM file: " + path)
-
- dim_match = re.match(r"^(\d+)\s(\d+)\s$", file.readline().decode("ascii"))
- if dim_match:
- width, height = list(map(int, dim_match.groups()))
- else:
- raise Exception("Malformed PFM header.")
-
- scale = float(file.readline().decode("ascii").rstrip())
- if scale < 0:
- # little-endian
- endian = "<"
- scale = -scale
- else:
- # big-endian
- endian = ">"
-
- data = np.fromfile(file, endian + "f")
- shape = (height, width, 3) if color else (height, width)
-
- data = np.reshape(data, shape)
- data = np.flipud(data)
-
- return data, scale
-
-
-def write_pfm(path, image, scale=1):
- """Write pfm file.
-
- Args:
- path (str): pathto file
- image (array): data
- scale (int, optional): Scale. Defaults to 1.
- """
-
- with open(path, "wb") as file:
- color = None
-
- if image.dtype.name != "float32":
- raise Exception("Image dtype must be float32.")
-
- image = np.flipud(image)
-
- if len(image.shape) == 3 and image.shape[2] == 3: # color image
- color = True
- elif (
- len(image.shape) == 2 or len(image.shape) == 3 and image.shape[2] == 1
- ): # greyscale
- color = False
- else:
- raise Exception("Image must have H x W x 3, H x W x 1 or H x W dimensions.")
-
- file.write("PF\n" if color else "Pf\n".encode())
- file.write("%d %d\n".encode() % (image.shape[1], image.shape[0]))
-
- endian = image.dtype.byteorder
-
- if endian == "<" or endian == "=" and sys.byteorder == "little":
- scale = -scale
-
- file.write("%f\n".encode() % scale)
-
- image.tofile(file)
-
-
-def read_image(path):
- """Read image and output RGB image (0-1).
-
- Args:
- path (str): path to file
-
- Returns:
- array: RGB image (0-1)
- """
- img = cv2.imread(path)
-
- if img.ndim == 2:
- img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
-
- img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) / 255.0
-
- return img
-
-
-def resize_image(img):
- """Resize image and make it fit for network.
-
- Args:
- img (array): image
-
- Returns:
- tensor: data ready for network
- """
- height_orig = img.shape[0]
- width_orig = img.shape[1]
-
- if width_orig > height_orig:
- scale = width_orig / 384
- else:
- scale = height_orig / 384
-
- height = (np.ceil(height_orig / scale / 32) * 32).astype(int)
- width = (np.ceil(width_orig / scale / 32) * 32).astype(int)
-
- img_resized = cv2.resize(img, (width, height), interpolation=cv2.INTER_AREA)
-
- img_resized = (
- torch.from_numpy(np.transpose(img_resized, (2, 0, 1))).contiguous().float()
- )
- img_resized = img_resized.unsqueeze(0)
-
- return img_resized
-
-
-def resize_depth(depth, width, height):
- """Resize depth map and bring to CPU (numpy).
-
- Args:
- depth (tensor): depth
- width (int): image width
- height (int): image height
-
- Returns:
- array: processed depth
- """
- depth = torch.squeeze(depth[0, :, :, :]).to("cpu")
-
- depth_resized = cv2.resize(
- depth.numpy(), (width, height), interpolation=cv2.INTER_CUBIC
- )
-
- return depth_resized
-
-def write_depth(path, depth, bits=1):
- """Write depth map to pfm and png file.
-
- Args:
- path (str): filepath without extension
- depth (array): depth
- """
- write_pfm(path + ".pfm", depth.astype(np.float32))
-
- depth_min = depth.min()
- depth_max = depth.max()
-
- max_val = (2**(8*bits))-1
-
- if depth_max - depth_min > np.finfo("float").eps:
- out = max_val * (depth - depth_min) / (depth_max - depth_min)
- else:
- out = np.zeros(depth.shape, dtype=depth.type)
-
- if bits == 1:
- cv2.imwrite(path + ".png", out.astype("uint8"))
- elif bits == 2:
- cv2.imwrite(path + ".png", out.astype("uint16"))
-
- return
diff --git a/spaces/PineSearch/generatorImage/generate.py b/spaces/PineSearch/generatorImage/generate.py
deleted file mode 100644
index 0d1e041b399533fa76ccf0a47b9482009647c274..0000000000000000000000000000000000000000
--- a/spaces/PineSearch/generatorImage/generate.py
+++ /dev/null
@@ -1,125 +0,0 @@
-import gradio as gr
-from gradio.inputs import Textbox
-
-import torch
-from diffusers import StableDiffusionPipeline
-import boto3
-from io import BytesIO
-import os
-import botocore
-from time import sleep
-
-AWS_ACCESS_KEY_ID = os.getenv("AWS_ACCESS_KEY_ID")
-AWS_SECRET_ACCESS_KEY = os.getenv("AWS_SECRET_ACCESS_KEY")
-S3_BUCKET_NAME = 'pineblogs101145-dev'
-
-model_id = "CompVis/stable-diffusion-v1-4"
-device = "cuda" if torch.cuda.is_available() else "cpu"
-
-pipe = StableDiffusionPipeline.from_pretrained(
- model_id, torch_dtype=torch.float32)
-
-pipe = pipe.to(device)
-
-s3 = boto3.resource('s3',
- aws_access_key_id=AWS_ACCESS_KEY_ID,
- aws_secret_access_key=AWS_SECRET_ACCESS_KEY)
-
-s3_client = boto3.client('s3',
- aws_access_key_id=AWS_ACCESS_KEY_ID,
- aws_secret_access_key=AWS_SECRET_ACCESS_KEY)
-
-bucket_name = 'pineblogs101145-dev'
-folder = 'public/mdx/'
-
-
-def text_to_image(prompt, save_as, key_id):
-
- if AWS_ACCESS_KEY_ID != key_id:
- return "not permition"
-
- # Create an instance of the S3 client
- s3 = boto3.client('s3',
- aws_access_key_id=AWS_ACCESS_KEY_ID,
- aws_secret_access_key=AWS_SECRET_ACCESS_KEY)
-
- image_name = '-'.join(save_as.split()) + ".webp"
-
- def save_image_to_s3(image):
- # Create a BytesIO object to store the image.
- image_buffer = BytesIO()
- image.save(image_buffer, format='WEBP')
- image_buffer.seek(0)
-
- # Full path of the file in the bucket
- s3_key = "public/" + image_name
- print('Saving image to s3')
-
- # Upload the image to the S3 bucket
- s3.upload_fileobj(image_buffer, S3_BUCKET_NAME, s3_key)
- print('Image saved to s3')
-
- def generator_image(prompt):
- prompt = prompt
- print('Starting to generate the image ...')
- try:
- image = pipe(prompt).images[0]
- except Exception as e:
- print('Error: ', e)
-
- print('Image generation completed')
-
- # Save the image in S3
- save_image_to_s3(image)
-
- generator_image(prompt)
- return image_name
-
-
-def check_if_exist(bucket_name, key):
-
- try:
- s3.Object(bucket_name, key).load()
- except botocore.exceptions.ClientError as e:
- if e.response['Error']['Code'] == "404":
- # The object does not exist.
- return False
- else:
- # Something else has gone wrong.
- raise
- else:
- return True
-
-
-def list_s3_files(bucket_name, folder):
-
- my_bucket = s3.Bucket(bucket_name)
-
- for objects in my_bucket.objects.filter(Prefix=folder):
- print(objects.key)
-
- filename_ext = '%s' % os.path.basename(objects.key)
- filename = os.path.splitext(filename_ext)[0]
- s3image = 'public/%s.webp' % filename
-
- if check_if_exist(bucket_name, s3image):
- print('Image %s already exists!' % s3image)
- else:
- response = s3_client.head_object(Bucket=bucket_name, Key=objects.key)
- metadata = response['Metadata']
- print(metadata)
- if 'resumen' in metadata:
- print('Has resume, ready to create image!')
- print('Start creating image.. %s ' % s3image)
- resumen = metadata['resumen']
- else:
- print('There is NOT resume, skipping..')
-
- sleep(500/1000)
- text_to_image(resumen, filename, AWS_ACCESS_KEY_ID)
-
-
-list_s3_files(bucket_name, folder)
-
-iface = gr.Interface(fn=list_s3_files, inputs=[Textbox(label="bucket_name"), Textbox(label="folder")], outputs="text")
-iface.launch()
diff --git a/spaces/Prof-Reza/Audiocraft_Music-Audio_Generation/audiocraft/modules/__init__.py b/spaces/Prof-Reza/Audiocraft_Music-Audio_Generation/audiocraft/modules/__init__.py
deleted file mode 100644
index 61418616ef18f0ecca56a007c43af4a731d98b9b..0000000000000000000000000000000000000000
--- a/spaces/Prof-Reza/Audiocraft_Music-Audio_Generation/audiocraft/modules/__init__.py
+++ /dev/null
@@ -1,22 +0,0 @@
-# Copyright (c) Meta Platforms, Inc. and affiliates.
-# All rights reserved.
-#
-# This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
-"""Modules used for building the models."""
-
-# flake8: noqa
-from .conv import (
- NormConv1d,
- NormConv2d,
- NormConvTranspose1d,
- NormConvTranspose2d,
- StreamableConv1d,
- StreamableConvTranspose1d,
- pad_for_conv1d,
- pad1d,
- unpad1d,
-)
-from .lstm import StreamableLSTM
-from .seanet import SEANetEncoder, SEANetDecoder
-from .transformer import StreamingTransformer
\ No newline at end of file
diff --git a/spaces/Prof-Reza/Audiocraft_Music-Audio_Generation/scripts/templates/index.html b/spaces/Prof-Reza/Audiocraft_Music-Audio_Generation/scripts/templates/index.html
deleted file mode 100644
index 7bd3afe9d933271bb922c1a0a534dd6b86fe67bc..0000000000000000000000000000000000000000
--- a/spaces/Prof-Reza/Audiocraft_Music-Audio_Generation/scripts/templates/index.html
+++ /dev/null
@@ -1,28 +0,0 @@
-{% extends "base.html" %}
-{% block content %}
-
-
- Welcome {{session['user']}} to the internal MOS assistant for AudioCraft.
- You can create custom surveys between your models, that you can
- evaluate yourself, or with the help of your teammates, by simply
- sharing a link!
-
-
-- """, - - # Backrgound-color Font-size Font-color Name Content - "SYSTEM": """ -
-
-
-
- - - -## Sponsor - -🐯 If you find this project helpful, feel free to buy me a coke or a cup of coffee~ - -
- -
diff --git a/spaces/Alichuan/VITS-Umamusume-voice-synthesizer/ONNXVITS_to_onnx.py b/spaces/Alichuan/VITS-Umamusume-voice-synthesizer/ONNXVITS_to_onnx.py
deleted file mode 100644
index 846e39849535ed08accb10d7001f2431a851d372..0000000000000000000000000000000000000000
--- a/spaces/Alichuan/VITS-Umamusume-voice-synthesizer/ONNXVITS_to_onnx.py
+++ /dev/null
@@ -1,31 +0,0 @@
-import ONNXVITS_models
-import utils
-from text import text_to_sequence
-import torch
-import commons
-
-def get_text(text, hps):
- text_norm = text_to_sequence(text, hps.symbols, hps.data.text_cleaners)
- if hps.data.add_blank:
- text_norm = commons.intersperse(text_norm, 0)
- text_norm = torch.LongTensor(text_norm)
- return text_norm
-
-hps = utils.get_hparams_from_file("../vits/pretrained_models/uma87.json")
-symbols = hps.symbols
-net_g = ONNXVITS_models.SynthesizerTrn(
- len(symbols),
- hps.data.filter_length // 2 + 1,
- hps.train.segment_size // hps.data.hop_length,
- n_speakers=hps.data.n_speakers,
- **hps.model)
-_ = net_g.eval()
-_ = utils.load_checkpoint("../vits/pretrained_models/uma_1153000.pth", net_g)
-
-text1 = get_text("ありがとうございます。", hps)
-stn_tst = text1
-with torch.no_grad():
- x_tst = stn_tst.unsqueeze(0)
- x_tst_lengths = torch.LongTensor([stn_tst.size(0)])
- sid = torch.tensor([0])
- o = net_g(x_tst, x_tst_lengths, sid=sid, noise_scale=.667, noise_scale_w=0.8, length_scale=1)
\ No newline at end of file
diff --git a/spaces/Ameaou/academic-chatgpt3.1/toolbox.py b/spaces/Ameaou/academic-chatgpt3.1/toolbox.py
deleted file mode 100644
index 038d7be858f3b7fbc6ff62f5031dcacdebe4d70c..0000000000000000000000000000000000000000
--- a/spaces/Ameaou/academic-chatgpt3.1/toolbox.py
+++ /dev/null
@@ -1,507 +0,0 @@
-import markdown
-import importlib
-import traceback
-import inspect
-import re
-from latex2mathml.converter import convert as tex2mathml
-from functools import wraps, lru_cache
-############################### 插件输入输出接驳区 #######################################
-class ChatBotWithCookies(list):
- def __init__(self, cookie):
- self._cookies = cookie
-
- def write_list(self, list):
- for t in list:
- self.append(t)
-
- def get_list(self):
- return [t for t in self]
-
- def get_cookies(self):
- return self._cookies
-
-def ArgsGeneralWrapper(f):
- """
- 装饰器函数，用于重组输入参数，改变输入参数的顺序与结构。
- """
- def decorated(cookies, max_length, llm_model, txt, txt2, top_p, temperature, chatbot, history, system_prompt, *args):
- txt_passon = txt
- if txt == "" and txt2 != "": txt_passon = txt2
- # 引入一个有cookie的chatbot
- cookies.update({
- 'top_p':top_p,
- 'temperature':temperature,
- })
- llm_kwargs = {
- 'api_key': cookies['api_key'],
- 'llm_model': llm_model,
- 'top_p':top_p,
- 'max_length': max_length,
- 'temperature':temperature,
- }
- plugin_kwargs = {
- # 目前还没有
- }
- chatbot_with_cookie = ChatBotWithCookies(cookies)
- chatbot_with_cookie.write_list(chatbot)
- yield from f(txt_passon, llm_kwargs, plugin_kwargs, chatbot_with_cookie, history, system_prompt, *args)
- return decorated
-
-def update_ui(chatbot, history, msg='正常', **kwargs): # 刷新界面
- """
- 刷新用户界面
- """
- assert isinstance(chatbot, ChatBotWithCookies), "在传递chatbot的过程中不要将其丢弃。必要时，可用clear将其清空，然后用for+append循环重新赋值。"
- yield chatbot.get_cookies(), chatbot, history, msg
-
-def CatchException(f):
- """
- 装饰器函数，捕捉函数f中的异常并封装到一个生成器中返回，并显示到聊天当中。
- """
- @wraps(f)
- def decorated(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
- try:
- yield from f(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT)
- except Exception as e:
- from check_proxy import check_proxy
- from toolbox import get_conf
- proxies, = get_conf('proxies')
- tb_str = '```\n' + traceback.format_exc() + '```'
- if chatbot is None or len(chatbot) == 0:
- chatbot = [["插件调度异常", "异常原因"]]
- chatbot[-1] = (chatbot[-1][0],
- f"[Local Message] 实验性函数调用出错: \n\n{tb_str} \n\n当前代理可用性: \n\n{check_proxy(proxies)}")
- yield from update_ui(chatbot=chatbot, history=history, msg=f'异常 {e}') # 刷新界面
- return decorated
-
-
-def HotReload(f):
- """
- HotReload的装饰器函数，用于实现Python函数插件的热更新。
- 函数热更新是指在不停止程序运行的情况下，更新函数代码，从而达到实时更新功能。
- 在装饰器内部，使用wraps(f)来保留函数的元信息，并定义了一个名为decorated的内部函数。
- 内部函数通过使用importlib模块的reload函数和inspect模块的getmodule函数来重新加载并获取函数模块，
- 然后通过getattr函数获取函数名，并在新模块中重新加载函数。
- 最后，使用yield from语句返回重新加载过的函数，并在被装饰的函数上执行。
- 最终，装饰器函数返回内部函数。这个内部函数可以将函数的原始定义更新为最新版本，并执行函数的新版本。
- """
- @wraps(f)
- def decorated(*args, **kwargs):
- fn_name = f.__name__
- f_hot_reload = getattr(importlib.reload(inspect.getmodule(f)), fn_name)
- yield from f_hot_reload(*args, **kwargs)
- return decorated
-
-
-####################################### 其他小工具 #####################################
-
-def get_reduce_token_percent(text):
- """
- * 此函数未来将被弃用
- """
- try:
- # text = "maximum context length is 4097 tokens. However, your messages resulted in 4870 tokens"
- pattern = r"(\d+)\s+tokens\b"
- match = re.findall(pattern, text)
- EXCEED_ALLO = 500 # 稍微留一点余地，否则在回复时会因余量太少出问题
- max_limit = float(match[0]) - EXCEED_ALLO
- current_tokens = float(match[1])
- ratio = max_limit/current_tokens
- assert ratio > 0 and ratio < 1
- return ratio, str(int(current_tokens-max_limit))
- except:
- return 0.5, '不详'
-
-
-
-def write_results_to_file(history, file_name=None):
- """
- 将对话记录history以Markdown格式写入文件中。如果没有指定文件名，则使用当前时间生成文件名。
- """
- import os
- import time
- if file_name is None:
- # file_name = time.strftime("chatGPT分析报告%Y-%m-%d-%H-%M-%S", time.localtime()) + '.md'
- file_name = 'chatGPT分析报告' + \
- time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime()) + '.md'
- os.makedirs('./gpt_log/', exist_ok=True)
- with open(f'./gpt_log/{file_name}', 'w', encoding='utf8') as f:
- f.write('# chatGPT 分析报告\n')
- for i, content in enumerate(history):
- try: # 这个bug没找到触发条件，暂时先这样顶一下
- if type(content) != str:
- content = str(content)
- except:
- continue
- if i % 2 == 0:
- f.write('## ')
- f.write(content)
- f.write('\n\n')
- res = '以上材料已经被写入' + os.path.abspath(f'./gpt_log/{file_name}')
- print(res)
- return res
-
-
-def regular_txt_to_markdown(text):
- """
- 将普通文本转换为Markdown格式的文本。
- """
- text = text.replace('\n', '\n\n')
- text = text.replace('\n\n\n', '\n\n')
- text = text.replace('\n\n\n', '\n\n')
- return text
-
-
-
-
-def report_execption(chatbot, history, a, b):
- """
- 向chatbot中添加错误信息
- """
- chatbot.append((a, b))
- history.append(a)
- history.append(b)
-
-
-def text_divide_paragraph(text):
- """
- 将文本按照段落分隔符分割开，生成带有段落标签的HTML代码。
- """
- if '```' in text:
- # careful input
- return text
- else:
- # wtf input
- lines = text.split("\n")
- for i, line in enumerate(lines):
- lines[i] = lines[i].replace(" ", " ")
- text = "".join(lines)
- return text
-
-
-def markdown_convertion(txt):
- """
- 将Markdown格式的文本转换为HTML格式。如果包含数学公式，则先将公式转换为HTML格式。
- """
- pre = '' - suf = '' - markdown_extension_configs = { - 'mdx_math': { - 'enable_dollar_delimiter': True, - 'use_gitlab_delimiters': False, - }, - } - find_equation_pattern = r'\n', '') - return content - - - if ('$' in txt) and ('```' not in txt): # 有$标识的公式符号，且没有代码段```的标识 - # convert everything to html format - split = markdown.markdown(text='---') - convert_stage_1 = markdown.markdown(text=txt, extensions=['mdx_math', 'fenced_code', 'tables', 'sane_lists'], extension_configs=markdown_extension_configs) - convert_stage_1 = markdown_bug_hunt(convert_stage_1) - # re.DOTALL: Make the '.' special character match any character at all, including a newline; without this flag, '.' will match anything except a newline. Corresponds to the inline flag (?s). - # 1. convert to easy-to-copy tex (do not render math) - convert_stage_2_1, n = re.subn(find_equation_pattern, replace_math_no_render, convert_stage_1, flags=re.DOTALL) - # 2. convert to rendered equation - convert_stage_2_2, n = re.subn(find_equation_pattern, replace_math_render, convert_stage_1, flags=re.DOTALL) - # cat them together - return pre + convert_stage_2_1 + f'{split}' + convert_stage_2_2 + suf - else: - return pre + markdown.markdown(txt, extensions=['fenced_code', 'codehilite', 'tables', 'sane_lists']) + suf - - -def close_up_code_segment_during_stream(gpt_reply): - """ - 在gpt输出代码的中途（输出了前面的```，但还没输出完后面的```），补上后面的``` - - Args: - gpt_reply (str): GPT模型返回的回复字符串。 - - Returns: - str: 返回一个新的字符串，将输出代码片段的“后面的```”补上。 - - """ - if '```' not in gpt_reply: - return gpt_reply - if gpt_reply.endswith('```'): - return gpt_reply - - # 排除了以上两个情况，我们 - segments = gpt_reply.split('```') - n_mark = len(segments) - 1 - if n_mark % 2 == 1: - # print('输出代码片段中！') - return gpt_reply+'\n```' - else: - return gpt_reply - - -def format_io(self, y): - """ - 将输入和输出解析为HTML格式。将y中最后一项的输入部分段落化，并将输出部分的Markdown和数学公式转换为HTML格式。 - """ - if y is None or y == []: - return [] - i_ask, gpt_reply = y[-1] - i_ask = text_divide_paragraph(i_ask) # 输入部分太自由，预处理一波 - gpt_reply = close_up_code_segment_during_stream(gpt_reply) # 当代码输出半截的时候，试着补上后个``` - y[-1] = ( - None if i_ask is None else markdown.markdown(i_ask, extensions=['fenced_code', 'tables']), - None if gpt_reply is None else markdown_convertion(gpt_reply) - ) - return y - - -def find_free_port(): - """ - 返回当前系统中可用的未使用端口。 - """ - import socket - from contextlib import closing - with closing(socket.socket(socket.AF_INET, socket.SOCK_STREAM)) as s: - s.bind(('', 0)) - s.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1) - return s.getsockname()[1] - - -def extract_archive(file_path, dest_dir): - import zipfile - import tarfile - import os - # Get the file extension of the input file - file_extension = os.path.splitext(file_path)[1] - - # Extract the archive based on its extension - if file_extension == '.zip': - with zipfile.ZipFile(file_path, 'r') as zipobj: - zipobj.extractall(path=dest_dir) - print("Successfully extracted zip archive to {}".format(dest_dir)) - - elif file_extension in ['.tar', '.gz', '.bz2']: - with tarfile.open(file_path, 'r:*') as tarobj: - tarobj.extractall(path=dest_dir) - print("Successfully extracted tar archive to {}".format(dest_dir)) - - # 第三方库，需要预先pip install rarfile - # 此外，Windows上还需要安装winrar软件，配置其Path环境变量，如"C:\Program Files\WinRAR"才可以 - elif file_extension == '.rar': - try: - import rarfile - with rarfile.RarFile(file_path) as rf: - rf.extractall(path=dest_dir) - print("Successfully extracted rar archive to {}".format(dest_dir)) - except: - print("Rar format requires additional dependencies to install") - return '\n\n需要安装pip install rarfile来解压rar文件' - - # 第三方库，需要预先pip install py7zr - elif file_extension == '.7z': - try: - import py7zr - with py7zr.SevenZipFile(file_path, mode='r') as f: - f.extractall(path=dest_dir) - print("Successfully extracted 7z archive to {}".format(dest_dir)) - except: - print("7z format requires additional dependencies to install") - return '\n\n需要安装pip install py7zr来解压7z文件' - else: - return '' - return '' - - -def find_recent_files(directory): - """ - me: find files that is created with in one minutes under a directory with python, write a function - gpt: here it is! - """ - import os - import time - current_time = time.time() - one_minute_ago = current_time - 60 - recent_files = [] - - for filename in os.listdir(directory): - file_path = os.path.join(directory, filename) - if file_path.endswith('.log'): - continue - created_time = os.path.getmtime(file_path) - if created_time >= one_minute_ago: - if os.path.isdir(file_path): - continue - recent_files.append(file_path) - - return recent_files - - -def on_file_uploaded(files, chatbot, txt, txt2, checkboxes): - if len(files) == 0: - return chatbot, txt - import shutil - import os - import time - import glob - from toolbox import extract_archive - try: - shutil.rmtree('./private_upload/') - except: - pass - time_tag = time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime()) - os.makedirs(f'private_upload/{time_tag}', exist_ok=True) - err_msg = '' - for file in files: - file_origin_name = os.path.basename(file.orig_name) - shutil.copy(file.name, f'private_upload/{time_tag}/{file_origin_name}') - err_msg += extract_archive(f'private_upload/{time_tag}/{file_origin_name}', - dest_dir=f'private_upload/{time_tag}/{file_origin_name}.extract') - moved_files = [fp for fp in glob.glob( - 'private_upload/**/*', recursive=True)] - if "底部输入区" in checkboxes: - txt = "" - txt2 = f'private_upload/{time_tag}' - else: - txt = f'private_upload/{time_tag}' - txt2 = "" - moved_files_str = '\t\n\n'.join(moved_files) - chatbot.append(['我上传了文件，请查收', - f'[Local Message] 收到以下文件: \n\n{moved_files_str}' + - f'\n\n调用路径参数已自动修正到: \n\n{txt}' + - f'\n\n现在您点击任意“红颜色”标识的函数插件时，以上文件将被作为输入参数'+err_msg]) - return chatbot, txt, txt2 - - -def on_report_generated(files, chatbot): - from toolbox import find_recent_files - report_files = find_recent_files('gpt_log') - if len(report_files) == 0: - return None, chatbot - # files.extend(report_files) - chatbot.append(['汇总报告如何远程获取？', '汇总报告已经添加到右侧“文件上传区”（可能处于折叠状态），请查收。']) - return report_files, chatbot - -def is_openai_api_key(key): - API_MATCH = re.match(r"sk-[a-zA-Z0-9]{48}$", key) - return bool(API_MATCH) - -def is_api2d_key(key): - if key.startswith('fk') and len(key) == 41: - return True - else: - return False - -def is_any_api_key(key): - if ',' in key: - keys = key.split(',') - for k in keys: - if is_any_api_key(k): return True - return False - else: - return is_openai_api_key(key) or is_api2d_key(key) - - -def select_api_key(keys, llm_model): - import random - avail_key_list = [] - key_list = keys.split(',') - - if llm_model.startswith('gpt-'): - for k in key_list: - if is_openai_api_key(k): avail_key_list.append(k) - - if llm_model.startswith('api2d-'): - for k in key_list: - if is_api2d_key(k): avail_key_list.append(k) - - if len(avail_key_list) == 0: - raise RuntimeError(f"您提供的api-key不满足要求，不包含任何可用于{llm_model}的api-key。") - - api_key = random.choice(avail_key_list) # 随机负载均衡 - return api_key - -@lru_cache(maxsize=128) -def read_single_conf_with_lru_cache(arg): - from colorful import print亮红, print亮绿 - try: - r = getattr(importlib.import_module('config_private'), arg) - except: - r = getattr(importlib.import_module('config'), arg) - # 在读取API_KEY时，检查一下是不是忘了改config - if arg == 'API_KEY': - if is_any_api_key(r): - print亮绿(f"[API_KEY] 您的 API_KEY 是: {r[:15]}*** API_KEY 导入成功") - else: - print亮红( "[API_KEY] 正确的 API_KEY 是'sk'开头的51位密钥（OpenAI），或者 'fk'开头的41位密钥，请在config文件中修改API密钥之后再运行。") - if arg == 'proxies': - if r is None: - print亮红('[PROXY] 网络代理状态：未配置。无代理状态下很可能无法访问OpenAI家族的模型。建议：检查USE_PROXY选项是否修改。') - else: - print亮绿('[PROXY] 网络代理状态：已配置。配置信息如下：', r) - assert isinstance(r, dict), 'proxies格式错误，请注意proxies选项的格式，不要遗漏括号。' - return r - - -def get_conf(*args): - # 建议您复制一个config_private.py放自己的秘密, 如API和代理网址, 避免不小心传github被别人看到 - res = [] - for arg in args: - r = read_single_conf_with_lru_cache(arg) - res.append(r) - return res - - -def clear_line_break(txt): - txt = txt.replace('\n', ' ') - txt = txt.replace(' ', ' ') - txt = txt.replace(' ', ' ') - return txt - - -class DummyWith(): - """ - 这段代码定义了一个名为DummyWith的空上下文管理器， - 它的作用是……额……没用，即在代码结构不变得情况下取代其他的上下文管理器。 - 上下文管理器是一种Python对象，用于与with语句一起使用， - 以确保一些资源在代码块执行期间得到正确的初始化和清理。 - 上下文管理器必须实现两个方法，分别为 __enter__()和 __exit__()。 - 在上下文执行开始的情况下，__enter__()方法会在代码块被执行前被调用， - 而在上下文执行结束时，__exit__()方法则会被调用。 - """ - def __enter__(self): - return self - - def __exit__(self, exc_type, exc_value, traceback): - return diff --git a/spaces/Amrrs/DragGan-Inversion/stylegan_human/dnnlib/tflib/ops/upfirdn_2d.py b/spaces/Amrrs/DragGan-Inversion/stylegan_human/dnnlib/tflib/ops/upfirdn_2d.py deleted file mode 100644 index 89413336877e0b6fcc5aff0a215cae3a7fe558cf..0000000000000000000000000000000000000000 --- a/spaces/Amrrs/DragGan-Inversion/stylegan_human/dnnlib/tflib/ops/upfirdn_2d.py +++ /dev/null @@ -1,391 +0,0 @@ -# Copyright (c) SenseTime Research. All rights reserved. - -# Copyright (c) 2019, NVIDIA Corporation. All rights reserved. -# -# This work is made available under the Nvidia Source Code License-NC. -# To view a copy of this license, visit -# https://nvlabs.github.io/stylegan2/license.html - -"""Custom TensorFlow ops for efficient resampling of 2D images.""" - -import os -import numpy as np -import tensorflow as tf -from .. import custom_ops - - -def _get_plugin(): - return custom_ops.get_plugin(os.path.splitext(__file__)[0] + '.cu') - -# ---------------------------------------------------------------------------- - - -def upfirdn_2d(x, k, upx=1, upy=1, downx=1, downy=1, padx0=0, padx1=0, pady0=0, pady1=0, impl='cuda'): - r"""Pad, upsample, FIR filter, and downsample a batch of 2D images. - - Accepts a batch of 2D images of the shape `[majorDim, inH, inW, minorDim]` - and performs the following operations for each image, batched across - `majorDim` and `minorDim`: - - 1. Pad the image with zeros by the specified number of pixels on each side - (`padx0`, `padx1`, `pady0`, `pady1`). Specifying a negative value - corresponds to cropping the image. - - 2. Upsample the image by inserting the zeros after each pixel (`upx`, `upy`). - - 3. Convolve the image with the specified 2D FIR filter (`k`), shrinking the - image so that the footprint of all output pixels lies within the input image. - - 4. Downsample the image by throwing away pixels (`downx`, `downy`). - - This sequence of operations bears close resemblance to scipy.signal.upfirdn(). - The fused op is considerably more efficient than performing the same calculation - using standard TensorFlow ops. It supports gradients of arbitrary order. - - Args: - x: Input tensor of the shape `[majorDim, inH, inW, minorDim]`. - k: 2D FIR filter of the shape `[firH, firW]`. - upx: Integer upsampling factor along the X-axis (default: 1). - upy: Integer upsampling factor along the Y-axis (default: 1). - downx: Integer downsampling factor along the X-axis (default: 1). - downy: Integer downsampling factor along the Y-axis (default: 1). - padx0: Number of pixels to pad on the left side (default: 0). - padx1: Number of pixels to pad on the right side (default: 0). - pady0: Number of pixels to pad on the top side (default: 0). - pady1: Number of pixels to pad on the bottom side (default: 0). - impl: Name of the implementation to use. Can be `"ref"` or `"cuda"` (default). - - Returns: - Tensor of the shape `[majorDim, outH, outW, minorDim]`, and same datatype as `x`. - """ - - impl_dict = { - 'ref': _upfirdn_2d_ref, - 'cuda': _upfirdn_2d_cuda, - } - return impl_dict[impl](x=x, k=k, upx=upx, upy=upy, downx=downx, downy=downy, padx0=padx0, padx1=padx1, pady0=pady0, pady1=pady1) - -# ---------------------------------------------------------------------------- - - -def _upfirdn_2d_ref(x, k, upx, upy, downx, downy, padx0, padx1, pady0, pady1): - """Slow reference implementation of `upfirdn_2d()` using standard TensorFlow ops.""" - - x = tf.convert_to_tensor(x) - k = np.asarray(k, dtype=np.float32) - assert x.shape.rank == 4 - inH = x.shape[1].value - inW = x.shape[2].value - minorDim = _shape(x, 3) - kernelH, kernelW = k.shape - assert inW >= 1 and inH >= 1 - assert kernelW >= 1 and kernelH >= 1 - assert isinstance(upx, int) and isinstance(upy, int) - assert isinstance(downx, int) and isinstance(downy, int) - assert isinstance(padx0, int) and isinstance(padx1, int) - assert isinstance(pady0, int) and isinstance(pady1, int) - - # Upsample (insert zeros). - x = tf.reshape(x, [-1, inH, 1, inW, 1, minorDim]) - x = tf.pad(x, [[0, 0], [0, 0], [0, upy - 1], [0, 0], [0, upx - 1], [0, 0]]) - x = tf.reshape(x, [-1, inH * upy, inW * upx, minorDim]) - - # Pad (crop if negative). - x = tf.pad(x, [[0, 0], [max(pady0, 0), max(pady1, 0)], - [max(padx0, 0), max(padx1, 0)], [0, 0]]) - x = x[:, max(-pady0, 0): x.shape[1].value - max(-pady1, 0), - max(-padx0, 0): x.shape[2].value - max(-padx1, 0), :] - - # Convolve with filter. - x = tf.transpose(x, [0, 3, 1, 2]) - x = tf.reshape(x, [-1, 1, inH * upy + pady0 + - pady1, inW * upx + padx0 + padx1]) - w = tf.constant(k[::-1, ::-1, np.newaxis, np.newaxis], dtype=x.dtype) - x = tf.nn.conv2d(x, w, strides=[1, 1, 1, 1], - padding='VALID', data_format='NCHW') - x = tf.reshape(x, [-1, minorDim, inH * upy + pady0 + pady1 - - kernelH + 1, inW * upx + padx0 + padx1 - kernelW + 1]) - x = tf.transpose(x, [0, 2, 3, 1]) - - # Downsample (throw away pixels). - return x[:, ::downy, ::downx, :] - -# ---------------------------------------------------------------------------- - - -def _upfirdn_2d_cuda(x, k, upx, upy, downx, downy, padx0, padx1, pady0, pady1): - """Fast CUDA implementation of `upfirdn_2d()` using custom ops.""" - - x = tf.convert_to_tensor(x) - k = np.asarray(k, dtype=np.float32) - majorDim, inH, inW, minorDim = x.shape.as_list() - kernelH, kernelW = k.shape - assert inW >= 1 and inH >= 1 - assert kernelW >= 1 and kernelH >= 1 - assert isinstance(upx, int) and isinstance(upy, int) - assert isinstance(downx, int) and isinstance(downy, int) - assert isinstance(padx0, int) and isinstance(padx1, int) - assert isinstance(pady0, int) and isinstance(pady1, int) - - outW = (inW * upx + padx0 + padx1 - kernelW) // downx + 1 - outH = (inH * upy + pady0 + pady1 - kernelH) // downy + 1 - assert outW >= 1 and outH >= 1 - - kc = tf.constant(k, dtype=x.dtype) - gkc = tf.constant(k[::-1, ::-1], dtype=x.dtype) - gpadx0 = kernelW - padx0 - 1 - gpady0 = kernelH - pady0 - 1 - gpadx1 = inW * upx - outW * downx + padx0 - upx + 1 - gpady1 = inH * upy - outH * downy + pady0 - upy + 1 - - @tf.custom_gradient - def func(x): - y = _get_plugin().up_fir_dn2d(x=x, k=kc, upx=upx, upy=upy, downx=downx, - downy=downy, padx0=padx0, padx1=padx1, pady0=pady0, pady1=pady1) - y.set_shape([majorDim, outH, outW, minorDim]) - - @tf.custom_gradient - def grad(dy): - dx = _get_plugin().up_fir_dn2d(x=dy, k=gkc, upx=downx, upy=downy, downx=upx, - downy=upy, padx0=gpadx0, padx1=gpadx1, pady0=gpady0, pady1=gpady1) - dx.set_shape([majorDim, inH, inW, minorDim]) - return dx, func - return y, grad - return func(x) - -# ---------------------------------------------------------------------------- - - -def filter_2d(x, k, gain=1, data_format='NCHW', impl='cuda'): - r"""Filter a batch of 2D images with the given FIR filter. - - Accepts a batch of 2D images of the shape `[N, C, H, W]` or `[N, H, W, C]` - and filters each image with the given filter. The filter is normalized so that - if the input pixels are constant, they will be scaled by the specified `gain`. - Pixels outside the image are assumed to be zero. - - Args: - x: Input tensor of the shape `[N, C, H, W]` or `[N, H, W, C]`. - k: FIR filter of the shape `[firH, firW]` or `[firN]` (separable). - gain: Scaling factor for signal magnitude (default: 1.0). - data_format: `'NCHW'` or `'NHWC'` (default: `'NCHW'`). - impl: Name of the implementation to use. Can be `"ref"` or `"cuda"` (default). - - Returns: - Tensor of the same shape and datatype as `x`. - """ - - k = _setup_kernel(k) * gain - p = k.shape[0] - 1 - return _simple_upfirdn_2d(x, k, pad0=(p+1)//2, pad1=p//2, data_format=data_format, impl=impl) - -# ---------------------------------------------------------------------------- - - -def upsample_2d(x, k=None, factor=2, gain=1, data_format='NCHW', impl='cuda'): - r"""Upsample a batch of 2D images with the given filter. - - Accepts a batch of 2D images of the shape `[N, C, H, W]` or `[N, H, W, C]` - and upsamples each image with the given filter. The filter is normalized so that - if the input pixels are constant, they will be scaled by the specified `gain`. - Pixels outside the image are assumed to be zero, and the filter is padded with - zeros so that its shape is a multiple of the upsampling factor. - - Args: - x: Input tensor of the shape `[N, C, H, W]` or `[N, H, W, C]`. - k: FIR filter of the shape `[firH, firW]` or `[firN]` (separable). - The default is `[1] * factor`, which corresponds to nearest-neighbor - upsampling. - factor: Integer upsampling factor (default: 2). - gain: Scaling factor for signal magnitude (default: 1.0). - data_format: `'NCHW'` or `'NHWC'` (default: `'NCHW'`). - impl: Name of the implementation to use. Can be `"ref"` or `"cuda"` (default). - - Returns: - Tensor of the shape `[N, C, H * factor, W * factor]` or - `[N, H * factor, W * factor, C]`, and same datatype as `x`. - """ - - assert isinstance(factor, int) and factor >= 1 - if k is None: - k = [1] * factor - k = _setup_kernel(k) * (gain * (factor ** 2)) - p = k.shape[0] - factor - return _simple_upfirdn_2d(x, k, up=factor, pad0=(p+1)//2+factor-1, pad1=p//2, data_format=data_format, impl=impl) - -# ---------------------------------------------------------------------------- - - -def downsample_2d(x, k=None, factor=2, gain=1, data_format='NCHW', impl='cuda'): - r"""Downsample a batch of 2D images with the given filter. - - Accepts a batch of 2D images of the shape `[N, C, H, W]` or `[N, H, W, C]` - and downsamples each image with the given filter. The filter is normalized so that - if the input pixels are constant, they will be scaled by the specified `gain`. - Pixels outside the image are assumed to be zero, and the filter is padded with - zeros so that its shape is a multiple of the downsampling factor. - - Args: - x: Input tensor of the shape `[N, C, H, W]` or `[N, H, W, C]`. - k: FIR filter of the shape `[firH, firW]` or `[firN]` (separable). - The default is `[1] * factor`, which corresponds to average pooling. - factor: Integer downsampling factor (default: 2). - gain: Scaling factor for signal magnitude (default: 1.0). - data_format: `'NCHW'` or `'NHWC'` (default: `'NCHW'`). - impl: Name of the implementation to use. Can be `"ref"` or `"cuda"` (default). - - Returns: - Tensor of the shape `[N, C, H // factor, W // factor]` or - `[N, H // factor, W // factor, C]`, and same datatype as `x`. - """ - - assert isinstance(factor, int) and factor >= 1 - if k is None: - k = [1] * factor - k = _setup_kernel(k) * gain - p = k.shape[0] - factor - return _simple_upfirdn_2d(x, k, down=factor, pad0=(p+1)//2, pad1=p//2, data_format=data_format, impl=impl) - -# ---------------------------------------------------------------------------- - - -def upsample_conv_2d(x, w, k=None, factor=2, gain=1, data_format='NCHW', impl='cuda'): - r"""Fused `upsample_2d()` followed by `tf.nn.conv2d()`. - - Padding is performed only once at the beginning, not between the operations. - The fused op is considerably more efficient than performing the same calculation - using standard TensorFlow ops. It supports gradients of arbitrary order. - - Args: - x: Input tensor of the shape `[N, C, H, W]` or `[N, H, W, C]`. - w: Weight tensor of the shape `[filterH, filterW, inChannels, outChannels]`. - Grouped convolution can be performed by `inChannels = x.shape[0] // numGroups`. - k: FIR filter of the shape `[firH, firW]` or `[firN]` (separable). - The default is `[1] * factor`, which corresponds to nearest-neighbor - upsampling. - factor: Integer upsampling factor (default: 2). - gain: Scaling factor for signal magnitude (default: 1.0). - data_format: `'NCHW'` or `'NHWC'` (default: `'NCHW'`). - impl: Name of the implementation to use. Can be `"ref"` or `"cuda"` (default). - - Returns: - Tensor of the shape `[N, C, H * factor, W * factor]` or - `[N, H * factor, W * factor, C]`, and same datatype as `x`. - """ - - assert isinstance(factor, int) and factor >= 1 - - # Check weight shape. - w = tf.convert_to_tensor(w) - assert w.shape.rank == 4 - convH = w.shape[0].value - convW = w.shape[1].value - inC = _shape(w, 2) - outC = _shape(w, 3) - assert convW == convH - - # Setup filter kernel. - if k is None: - k = [1] * factor - k = _setup_kernel(k) * (gain * (factor ** 2)) - p = (k.shape[0] - factor) - (convW - 1) - - # Determine data dimensions. - if data_format == 'NCHW': - stride = [1, 1, factor, factor] - output_shape = [_shape(x, 0), outC, (_shape( - x, 2) - 1) * factor + convH, (_shape(x, 3) - 1) * factor + convW] - num_groups = _shape(x, 1) // inC - else: - stride = [1, factor, factor, 1] - output_shape = [_shape(x, 0), (_shape( - x, 1) - 1) * factor + convH, (_shape(x, 2) - 1) * factor + convW, outC] - num_groups = _shape(x, 3) // inC - - # Transpose weights. - w = tf.reshape(w, [convH, convW, inC, num_groups, -1]) - w = tf.transpose(w[::-1, ::-1], [0, 1, 4, 3, 2]) - w = tf.reshape(w, [convH, convW, -1, num_groups * inC]) - - # Execute. - x = tf.nn.conv2d_transpose(x, w, output_shape=output_shape, - strides=stride, padding='VALID', data_format=data_format) - return _simple_upfirdn_2d(x, k, pad0=(p+1)//2+factor-1, pad1=p//2+1, data_format=data_format, impl=impl) - -# ---------------------------------------------------------------------------- - - -def conv_downsample_2d(x, w, k=None, factor=2, gain=1, data_format='NCHW', impl='cuda'): - r"""Fused `tf.nn.conv2d()` followed by `downsample_2d()`. - - Padding is performed only once at the beginning, not between the operations. - The fused op is considerably more efficient than performing the same calculation - using standard TensorFlow ops. It supports gradients of arbitrary order. - - Args: - x: Input tensor of the shape `[N, C, H, W]` or `[N, H, W, C]`. - w: Weight tensor of the shape `[filterH, filterW, inChannels, outChannels]`. - Grouped convolution can be performed by `inChannels = x.shape[0] // numGroups`. - k: FIR filter of the shape `[firH, firW]` or `[firN]` (separable). - The default is `[1] * factor`, which corresponds to average pooling. - factor: Integer downsampling factor (default: 2). - gain: Scaling factor for signal magnitude (default: 1.0). - data_format: `'NCHW'` or `'NHWC'` (default: `'NCHW'`). - impl: Name of the implementation to use. Can be `"ref"` or `"cuda"` (default). - - Returns: - Tensor of the shape `[N, C, H // factor, W // factor]` or - `[N, H // factor, W // factor, C]`, and same datatype as `x`. - """ - - assert isinstance(factor, int) and factor >= 1 - w = tf.convert_to_tensor(w) - convH, convW, _inC, _outC = w.shape.as_list() - assert convW == convH - if k is None: - k = [1] * factor - k = _setup_kernel(k) * gain - p = (k.shape[0] - factor) + (convW - 1) - if data_format == 'NCHW': - s = [1, 1, factor, factor] - else: - s = [1, factor, factor, 1] - x = _simple_upfirdn_2d(x, k, pad0=(p+1)//2, pad1=p // - 2, data_format=data_format, impl=impl) - return tf.nn.conv2d(x, w, strides=s, padding='VALID', data_format=data_format) - -# ---------------------------------------------------------------------------- -# Internal helper funcs. - - -def _shape(tf_expr, dim_idx): - if tf_expr.shape.rank is not None: - dim = tf_expr.shape[dim_idx].value - if dim is not None: - return dim - return tf.shape(tf_expr)[dim_idx] - - -def _setup_kernel(k): - k = np.asarray(k, dtype=np.float32) - if k.ndim == 1: - k = np.outer(k, k) - k /= np.sum(k) - assert k.ndim == 2 - assert k.shape[0] == k.shape[1] - return k - - -def _simple_upfirdn_2d(x, k, up=1, down=1, pad0=0, pad1=0, data_format='NCHW', impl='cuda'): - assert data_format in ['NCHW', 'NHWC'] - assert x.shape.rank == 4 - y = x - if data_format == 'NCHW': - y = tf.reshape(y, [-1, _shape(y, 2), _shape(y, 3), 1]) - y = upfirdn_2d(y, k, upx=up, upy=up, downx=down, downy=down, - padx0=pad0, padx1=pad1, pady0=pad0, pady1=pad1, impl=impl) - if data_format == 'NCHW': - y = tf.reshape(y, [-1, _shape(x, 1), _shape(y, 1), _shape(y, 2)]) - return y - -# ---------------------------------------------------------------------------- diff --git a/spaces/Andy1621/uniformer_image_detection/configs/mask_rcnn/mask_rcnn_x101_64x4d_fpn_2x_coco.py b/spaces/Andy1621/uniformer_image_detection/configs/mask_rcnn/mask_rcnn_x101_64x4d_fpn_2x_coco.py deleted file mode 100644 index 9ba92c5b0b6dcaf10746aeacf7a868348133ff80..0000000000000000000000000000000000000000 --- a/spaces/Andy1621/uniformer_image_detection/configs/mask_rcnn/mask_rcnn_x101_64x4d_fpn_2x_coco.py +++ /dev/null @@ -1,13 +0,0 @@ -_base_ = './mask_rcnn_x101_32x4d_fpn_2x_coco.py' -model = dict( - pretrained='open-mmlab://resnext101_64x4d', - backbone=dict( - type='ResNeXt', - depth=101, - groups=64, - base_width=4, - num_stages=4, - out_indices=(0, 1, 2, 3), - frozen_stages=1, - norm_cfg=dict(type='BN', requires_grad=True), - style='pytorch')) diff --git a/spaces/Andy1621/uniformer_image_detection/configs/tridentnet/tridentnet_r50_caffe_mstrain_3x_coco.py b/spaces/Andy1621/uniformer_image_detection/configs/tridentnet/tridentnet_r50_caffe_mstrain_3x_coco.py deleted file mode 100644 index 0f402826d3a22714078d8c50ed6bd8959018e4e7..0000000000000000000000000000000000000000 --- a/spaces/Andy1621/uniformer_image_detection/configs/tridentnet/tridentnet_r50_caffe_mstrain_3x_coco.py +++ /dev/null @@ -1,4 +0,0 @@ -_base_ = 'tridentnet_r50_caffe_mstrain_1x_coco.py' - -lr_config = dict(step=[28, 34]) -runner = dict(type='EpochBasedRunner', max_epochs=36) diff --git a/spaces/Andy1621/uniformer_image_detection/mmdet/core/bbox/assigners/grid_assigner.py b/spaces/Andy1621/uniformer_image_detection/mmdet/core/bbox/assigners/grid_assigner.py deleted file mode 100644 index 7390ea6370639c939d578c6ebf0f9268499161bc..0000000000000000000000000000000000000000 --- a/spaces/Andy1621/uniformer_image_detection/mmdet/core/bbox/assigners/grid_assigner.py +++ /dev/null @@ -1,155 +0,0 @@ -import torch - -from ..builder import BBOX_ASSIGNERS -from ..iou_calculators import build_iou_calculator -from .assign_result import AssignResult -from .base_assigner import BaseAssigner - - -@BBOX_ASSIGNERS.register_module() -class GridAssigner(BaseAssigner): - """Assign a corresponding gt bbox or background to each bbox. - - Each proposals will be assigned with `-1`, `0`, or a positive integer - indicating the ground truth index. - - - -1: don't care - - 0: negative sample, no assigned gt - - positive integer: positive sample, index (1-based) of assigned gt - - Args: - pos_iou_thr (float): IoU threshold for positive bboxes. - neg_iou_thr (float or tuple): IoU threshold for negative bboxes. - min_pos_iou (float): Minimum iou for a bbox to be considered as a - positive bbox. Positive samples can have smaller IoU than - pos_iou_thr due to the 4th step (assign max IoU sample to each gt). - gt_max_assign_all (bool): Whether to assign all bboxes with the same - highest overlap with some gt to that gt. - """ - - def __init__(self, - pos_iou_thr, - neg_iou_thr, - min_pos_iou=.0, - gt_max_assign_all=True, - iou_calculator=dict(type='BboxOverlaps2D')): - self.pos_iou_thr = pos_iou_thr - self.neg_iou_thr = neg_iou_thr - self.min_pos_iou = min_pos_iou - self.gt_max_assign_all = gt_max_assign_all - self.iou_calculator = build_iou_calculator(iou_calculator) - - def assign(self, bboxes, box_responsible_flags, gt_bboxes, gt_labels=None): - """Assign gt to bboxes. The process is very much like the max iou - assigner, except that positive samples are constrained within the cell - that the gt boxes fell in. - - This method assign a gt bbox to every bbox (proposal/anchor), each bbox - will be assigned with -1, 0, or a positive number. -1 means don't care, - 0 means negative sample, positive number is the index (1-based) of - assigned gt. - The assignment is done in following steps, the order matters. - - 1. assign every bbox to -1 - 2. assign proposals whose iou with all gts <= neg_iou_thr to 0 - 3. for each bbox within a cell, if the iou with its nearest gt > - pos_iou_thr and the center of that gt falls inside the cell, - assign it to that bbox - 4. for each gt bbox, assign its nearest proposals within the cell the - gt bbox falls in to itself. - - Args: - bboxes (Tensor): Bounding boxes to be assigned, shape(n, 4). - box_responsible_flags (Tensor): flag to indicate whether box is - responsible for prediction, shape(n, ) - gt_bboxes (Tensor): Groundtruth boxes, shape (k, 4). - gt_labels (Tensor, optional): Label of gt_bboxes, shape (k, ). - - Returns: - :obj:`AssignResult`: The assign result. - """ - num_gts, num_bboxes = gt_bboxes.size(0), bboxes.size(0) - - # compute iou between all gt and bboxes - overlaps = self.iou_calculator(gt_bboxes, bboxes) - - # 1. assign -1 by default - assigned_gt_inds = overlaps.new_full((num_bboxes, ), - -1, - dtype=torch.long) - - if num_gts == 0 or num_bboxes == 0: - # No ground truth or boxes, return empty assignment - max_overlaps = overlaps.new_zeros((num_bboxes, )) - if num_gts == 0: - # No truth, assign everything to background - assigned_gt_inds[:] = 0 - if gt_labels is None: - assigned_labels = None - else: - assigned_labels = overlaps.new_full((num_bboxes, ), - -1, - dtype=torch.long) - return AssignResult( - num_gts, - assigned_gt_inds, - max_overlaps, - labels=assigned_labels) - - # 2. assign negative: below - # for each anchor, which gt best overlaps with it - # for each anchor, the max iou of all gts - # shape of max_overlaps == argmax_overlaps == num_bboxes - max_overlaps, argmax_overlaps = overlaps.max(dim=0) - - if isinstance(self.neg_iou_thr, float): - assigned_gt_inds[(max_overlaps >= 0) - & (max_overlaps <= self.neg_iou_thr)] = 0 - elif isinstance(self.neg_iou_thr, (tuple, list)): - assert len(self.neg_iou_thr) == 2 - assigned_gt_inds[(max_overlaps > self.neg_iou_thr[0]) - & (max_overlaps <= self.neg_iou_thr[1])] = 0 - - # 3. assign positive: falls into responsible cell and above - # positive IOU threshold, the order matters. - # the prior condition of comparision is to filter out all - # unrelated anchors, i.e. not box_responsible_flags - overlaps[:, ~box_responsible_flags.type(torch.bool)] = -1. - - # calculate max_overlaps again, but this time we only consider IOUs - # for anchors responsible for prediction - max_overlaps, argmax_overlaps = overlaps.max(dim=0) - - # for each gt, which anchor best overlaps with it - # for each gt, the max iou of all proposals - # shape of gt_max_overlaps == gt_argmax_overlaps == num_gts - gt_max_overlaps, gt_argmax_overlaps = overlaps.max(dim=1) - - pos_inds = (max_overlaps > - self.pos_iou_thr) & box_responsible_flags.type(torch.bool) - assigned_gt_inds[pos_inds] = argmax_overlaps[pos_inds] + 1 - - # 4. assign positive to max overlapped anchors within responsible cell - for i in range(num_gts): - if gt_max_overlaps[i] > self.min_pos_iou: - if self.gt_max_assign_all: - max_iou_inds = (overlaps[i, :] == gt_max_overlaps[i]) & \ - box_responsible_flags.type(torch.bool) - assigned_gt_inds[max_iou_inds] = i + 1 - elif box_responsible_flags[gt_argmax_overlaps[i]]: - assigned_gt_inds[gt_argmax_overlaps[i]] = i + 1 - - # assign labels of positive anchors - if gt_labels is not None: - assigned_labels = assigned_gt_inds.new_full((num_bboxes, ), -1) - pos_inds = torch.nonzero( - assigned_gt_inds > 0, as_tuple=False).squeeze() - if pos_inds.numel() > 0: - assigned_labels[pos_inds] = gt_labels[ - assigned_gt_inds[pos_inds] - 1] - - else: - assigned_labels = None - - return AssignResult( - num_gts, assigned_gt_inds, max_overlaps, labels=assigned_labels) diff --git a/spaces/Andy1621/uniformer_image_detection/mmdet/models/detectors/__init__.py b/spaces/Andy1621/uniformer_image_detection/mmdet/models/detectors/__init__.py deleted file mode 100644 index 04011130435cf9fdfadeb821919046b1bddab7d4..0000000000000000000000000000000000000000 --- a/spaces/Andy1621/uniformer_image_detection/mmdet/models/detectors/__init__.py +++ /dev/null @@ -1,40 +0,0 @@ -from .atss import ATSS -from .base import BaseDetector -from .cascade_rcnn import CascadeRCNN -from .cornernet import CornerNet -from .detr import DETR -from .fast_rcnn import FastRCNN -from .faster_rcnn import FasterRCNN -from .fcos import FCOS -from .fovea import FOVEA -from .fsaf import FSAF -from .gfl import GFL -from .grid_rcnn import GridRCNN -from .htc import HybridTaskCascade -from .kd_one_stage import KnowledgeDistillationSingleStageDetector -from .mask_rcnn import MaskRCNN -from .mask_scoring_rcnn import MaskScoringRCNN -from .nasfcos import NASFCOS -from .paa import PAA -from .point_rend import PointRend -from .reppoints_detector import RepPointsDetector -from .retinanet import RetinaNet -from .rpn import RPN -from .scnet import SCNet -from .single_stage import SingleStageDetector -from .sparse_rcnn import SparseRCNN -from .trident_faster_rcnn import TridentFasterRCNN -from .two_stage import TwoStageDetector -from .vfnet import VFNet -from .yolact import YOLACT -from .yolo import YOLOV3 - -__all__ = [ - 'ATSS', 'BaseDetector', 'SingleStageDetector', - 'KnowledgeDistillationSingleStageDetector', 'TwoStageDetector', 'RPN', - 'FastRCNN', 'FasterRCNN', 'MaskRCNN', 'CascadeRCNN', 'HybridTaskCascade', - 'RetinaNet', 'FCOS', 'GridRCNN', 'MaskScoringRCNN', 'RepPointsDetector', - 'FOVEA', 'FSAF', 'NASFCOS', 'PointRend', 'GFL', 'CornerNet', 'PAA', - 'YOLOV3', 'YOLACT', 'VFNet', 'DETR', 'TridentFasterRCNN', 'SparseRCNN', - 'SCNet' -] diff --git a/spaces/Andy1621/uniformer_image_segmentation/configs/_base_/datasets/cityscapes.py b/spaces/Andy1621/uniformer_image_segmentation/configs/_base_/datasets/cityscapes.py deleted file mode 100644 index f21867c63e1835f6fceb61f066e802fd8fd2a735..0000000000000000000000000000000000000000 --- a/spaces/Andy1621/uniformer_image_segmentation/configs/_base_/datasets/cityscapes.py +++ /dev/null @@ -1,54 +0,0 @@ -# dataset settings -dataset_type = 'CityscapesDataset' -data_root = 'data/cityscapes/' -img_norm_cfg = dict( - mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True) -crop_size = (512, 1024) -train_pipeline = [ - dict(type='LoadImageFromFile'), - dict(type='LoadAnnotations'), - dict(type='Resize', img_scale=(2048, 1024), ratio_range=(0.5, 2.0)), - dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75), - dict(type='RandomFlip', prob=0.5), - dict(type='PhotoMetricDistortion'), - dict(type='Normalize', **img_norm_cfg), - dict(type='Pad', size=crop_size, pad_val=0, seg_pad_val=255), - dict(type='DefaultFormatBundle'), - dict(type='Collect', keys=['img', 'gt_semantic_seg']), -] -test_pipeline = [ - dict(type='LoadImageFromFile'), - dict( - type='MultiScaleFlipAug', - img_scale=(2048, 1024), - # img_ratios=[0.5, 0.75, 1.0, 1.25, 1.5, 1.75], - flip=False, - transforms=[ - dict(type='Resize', keep_ratio=True), - dict(type='RandomFlip'), - dict(type='Normalize', **img_norm_cfg), - dict(type='ImageToTensor', keys=['img']), - dict(type='Collect', keys=['img']), - ]) -] -data = dict( - samples_per_gpu=2, - workers_per_gpu=2, - train=dict( - type=dataset_type, - data_root=data_root, - img_dir='leftImg8bit/train', - ann_dir='gtFine/train', - pipeline=train_pipeline), - val=dict( - type=dataset_type, - data_root=data_root, - img_dir='leftImg8bit/val', - ann_dir='gtFine/val', - pipeline=test_pipeline), - test=dict( - type=dataset_type, - data_root=data_root, - img_dir='leftImg8bit/val', - ann_dir='gtFine/val', - pipeline=test_pipeline)) diff --git a/spaces/Andy1621/uniformer_image_segmentation/configs/_base_/default_runtime.py b/spaces/Andy1621/uniformer_image_segmentation/configs/_base_/default_runtime.py deleted file mode 100644 index b564cc4e7e7d9a67dacaaddecb100e4d8f5c005b..0000000000000000000000000000000000000000 --- a/spaces/Andy1621/uniformer_image_segmentation/configs/_base_/default_runtime.py +++ /dev/null @@ -1,14 +0,0 @@ -# yapf:disable -log_config = dict( - interval=50, - hooks=[ - dict(type='TextLoggerHook', by_epoch=False), - # dict(type='TensorboardLoggerHook') - ]) -# yapf:enable -dist_params = dict(backend='nccl') -log_level = 'INFO' -load_from = None -resume_from = None -workflow = [('train', 1)] -cudnn_benchmark = True diff --git a/spaces/Andy1621/uniformer_image_segmentation/configs/ccnet/ccnet_r101-d8_769x769_80k_cityscapes.py b/spaces/Andy1621/uniformer_image_segmentation/configs/ccnet/ccnet_r101-d8_769x769_80k_cityscapes.py deleted file mode 100644 index 654f377b6f6152c9bd98d33824a39a41d7510c3f..0000000000000000000000000000000000000000 --- a/spaces/Andy1621/uniformer_image_segmentation/configs/ccnet/ccnet_r101-d8_769x769_80k_cityscapes.py +++ /dev/null @@ -1,2 +0,0 @@ -_base_ = './ccnet_r50-d8_769x769_80k_cityscapes.py' -model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) diff --git a/spaces/Andy1621/uniformer_image_segmentation/configs/mobilenet_v2/pspnet_m-v2-d8_512x512_160k_ade20k.py b/spaces/Andy1621/uniformer_image_segmentation/configs/mobilenet_v2/pspnet_m-v2-d8_512x512_160k_ade20k.py deleted file mode 100644 index 5b72ac830be29b865ed52adaf41f2fe800f252cc..0000000000000000000000000000000000000000 --- a/spaces/Andy1621/uniformer_image_segmentation/configs/mobilenet_v2/pspnet_m-v2-d8_512x512_160k_ade20k.py +++ /dev/null @@ -1,12 +0,0 @@ -_base_ = '../pspnet/pspnet_r101-d8_512x512_160k_ade20k.py' -model = dict( - pretrained='mmcls://mobilenet_v2', - backbone=dict( - _delete_=True, - type='MobileNetV2', - widen_factor=1., - strides=(1, 2, 2, 1, 1, 1, 1), - dilations=(1, 1, 1, 2, 2, 4, 4), - out_indices=(1, 2, 4, 6)), - decode_head=dict(in_channels=320), - auxiliary_head=dict(in_channels=96)) diff --git a/spaces/AppleQAQ/anime-remove-background/README.md b/spaces/AppleQAQ/anime-remove-background/README.md deleted file mode 100644 index 1ba3cb5ea0e994e246d57b7d62b8aa5a6331901c..0000000000000000000000000000000000000000 --- a/spaces/AppleQAQ/anime-remove-background/README.md +++ /dev/null @@ -1,14 +0,0 @@ ---- -title: Anime Remove Background -emoji: 🪄🖼️ -colorFrom: indigo -colorTo: pink -sdk: gradio -sdk_version: 3.1.4 -app_file: app.py -pinned: false -license: apache-2.0 -duplicated_from: skytnt/anime-remove-background ---- - -Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference diff --git a/spaces/Ataturk-Chatbot/HuggingFaceChat/venv/lib/python3.11/site-packages/pip/_vendor/idna/__init__.py b/spaces/Ataturk-Chatbot/HuggingFaceChat/venv/lib/python3.11/site-packages/pip/_vendor/idna/__init__.py deleted file mode 100644 index a40eeafcc914108ca79c5d83d6e81da1b29c6e80..0000000000000000000000000000000000000000 --- a/spaces/Ataturk-Chatbot/HuggingFaceChat/venv/lib/python3.11/site-packages/pip/_vendor/idna/__init__.py +++ /dev/null @@ -1,44 +0,0 @@ -from .package_data import __version__ -from .core import ( - IDNABidiError, - IDNAError, - InvalidCodepoint, - InvalidCodepointContext, - alabel, - check_bidi, - check_hyphen_ok, - check_initial_combiner, - check_label, - check_nfc, - decode, - encode, - ulabel, - uts46_remap, - valid_contextj, - valid_contexto, - valid_label_length, - valid_string_length, -) -from .intranges import intranges_contain - -__all__ = [ - "IDNABidiError", - "IDNAError", - "InvalidCodepoint", - "InvalidCodepointContext", - "alabel", - "check_bidi", - "check_hyphen_ok", - "check_initial_combiner", - "check_label", - "check_nfc", - "decode", - "encode", - "intranges_contain", - "ulabel", - "uts46_remap", - "valid_contextj", - "valid_contexto", - "valid_label_length", - "valid_string_length", -] diff --git a/spaces/Ataturk-Chatbot/HuggingFaceChat/venv/lib/python3.11/site-packages/pkg_resources/_vendor/importlib_resources/_common.py b/spaces/Ataturk-Chatbot/HuggingFaceChat/venv/lib/python3.11/site-packages/pkg_resources/_vendor/importlib_resources/_common.py deleted file mode 100644 index a12e2c75d132c73b556702159d535d15ed9abfd2..0000000000000000000000000000000000000000 --- a/spaces/Ataturk-Chatbot/HuggingFaceChat/venv/lib/python3.11/site-packages/pkg_resources/_vendor/importlib_resources/_common.py +++ /dev/null @@ -1,104 +0,0 @@ -import os -import pathlib -import tempfile -import functools -import contextlib -import types -import importlib - -from typing import Union, Optional -from .abc import ResourceReader, Traversable - -from ._compat import wrap_spec - -Package = Union[types.ModuleType, str] - - -def files(package): - # type: (Package) -> Traversable - """ - Get a Traversable resource from a package - """ - return from_package(get_package(package)) - - -def get_resource_reader(package): - # type: (types.ModuleType) -> Optional[ResourceReader] - """ - Return the package's loader if it's a ResourceReader. - """ - # We can't use - # a issubclass() check here because apparently abc.'s __subclasscheck__() - # hook wants to create a weak reference to the object, but - # zipimport.zipimporter does not support weak references, resulting in a - # TypeError. That seems terrible. - spec = package.__spec__ - reader = getattr(spec.loader, 'get_resource_reader', None) # type: ignore - if reader is None: - return None - return reader(spec.name) # type: ignore - - -def resolve(cand): - # type: (Package) -> types.ModuleType - return cand if isinstance(cand, types.ModuleType) else importlib.import_module(cand) - - -def get_package(package): - # type: (Package) -> types.ModuleType - """Take a package name or module object and return the module. - - Raise an exception if the resolved module is not a package. - """ - resolved = resolve(package) - if wrap_spec(resolved).submodule_search_locations is None: - raise TypeError(f'{package!r} is not a package') - return resolved - - -def from_package(package): - """ - Return a Traversable object for the given package. - - """ - spec = wrap_spec(package) - reader = spec.loader.get_resource_reader(spec.name) - return reader.files() - - -@contextlib.contextmanager -def _tempfile(reader, suffix=''): - # Not using tempfile.NamedTemporaryFile as it leads to deeper 'try' - # blocks due to the need to close the temporary file to work on Windows - # properly. - fd, raw_path = tempfile.mkstemp(suffix=suffix) - try: - try: - os.write(fd, reader()) - finally: - os.close(fd) - del reader - yield pathlib.Path(raw_path) - finally: - try: - os.remove(raw_path) - except FileNotFoundError: - pass - - -@functools.singledispatch -def as_file(path): - """ - Given a Traversable object, return that object as a - path on the local file system in a context manager. - """ - return _tempfile(path.read_bytes, suffix=path.name) - - -@as_file.register(pathlib.Path) -@contextlib.contextmanager -def _(path): - """ - Degenerate behavior for pathlib.Path objects. - """ - yield path diff --git a/spaces/Awiny/Image2Paragraph/models/grit_src/third_party/CenterNet2/configs/new_baselines/mask_rcnn_regnety_4gf_dds_FPN_200ep_LSJ.py b/spaces/Awiny/Image2Paragraph/models/grit_src/third_party/CenterNet2/configs/new_baselines/mask_rcnn_regnety_4gf_dds_FPN_200ep_LSJ.py deleted file mode 100644 index b867cc865e5ac4d7b70221da141894efd7cbd75c..0000000000000000000000000000000000000000 --- a/spaces/Awiny/Image2Paragraph/models/grit_src/third_party/CenterNet2/configs/new_baselines/mask_rcnn_regnety_4gf_dds_FPN_200ep_LSJ.py +++ /dev/null @@ -1,14 +0,0 @@ -from .mask_rcnn_regnety_4gf_dds_FPN_100ep_LSJ import ( - dataloader, - lr_multiplier, - model, - optimizer, - train, -) - -train.max_iter *= 2 # 100ep -> 200ep - -lr_multiplier.scheduler.milestones = [ - milestone * 2 for milestone in lr_multiplier.scheduler.milestones -] -lr_multiplier.scheduler.num_updates = train.max_iter diff --git a/spaces/Awiny/Image2Paragraph/models/grit_src/third_party/CenterNet2/tests/modeling/test_fast_rcnn.py b/spaces/Awiny/Image2Paragraph/models/grit_src/third_party/CenterNet2/tests/modeling/test_fast_rcnn.py deleted file mode 100644 index e29b944bffca1ccbf5b02be59a753f3188d90a4f..0000000000000000000000000000000000000000 --- a/spaces/Awiny/Image2Paragraph/models/grit_src/third_party/CenterNet2/tests/modeling/test_fast_rcnn.py +++ /dev/null @@ -1,171 +0,0 @@ -# Copyright (c) Facebook, Inc. and its affiliates. -import logging -import unittest -import torch - -from detectron2.layers import ShapeSpec -from detectron2.modeling.box_regression import Box2BoxTransform, Box2BoxTransformRotated -from detectron2.modeling.roi_heads.fast_rcnn import FastRCNNOutputLayers -from detectron2.modeling.roi_heads.rotated_fast_rcnn import RotatedFastRCNNOutputLayers -from detectron2.structures import Boxes, Instances, RotatedBoxes -from detectron2.utils.events import EventStorage - -logger = logging.getLogger(__name__) - - -class FastRCNNTest(unittest.TestCase): - def test_fast_rcnn(self): - torch.manual_seed(132) - - box_head_output_size = 8 - - box_predictor = FastRCNNOutputLayers( - ShapeSpec(channels=box_head_output_size), - box2box_transform=Box2BoxTransform(weights=(10, 10, 5, 5)), - num_classes=5, - ) - feature_pooled = torch.rand(2, box_head_output_size) - predictions = box_predictor(feature_pooled) - - proposal_boxes = torch.tensor([[0.8, 1.1, 3.2, 2.8], [2.3, 2.5, 7, 8]], dtype=torch.float32) - gt_boxes = torch.tensor([[1, 1, 3, 3], [2, 2, 6, 6]], dtype=torch.float32) - proposal = Instances((10, 10)) - proposal.proposal_boxes = Boxes(proposal_boxes) - proposal.gt_boxes = Boxes(gt_boxes) - proposal.gt_classes = torch.tensor([1, 2]) - - with EventStorage(): # capture events in a new storage to discard them - losses = box_predictor.losses(predictions, [proposal]) - - expected_losses = { - "loss_cls": torch.tensor(1.7951188087), - "loss_box_reg": torch.tensor(4.0357131958), - } - for name in expected_losses.keys(): - assert torch.allclose(losses[name], expected_losses[name]) - - def test_fast_rcnn_empty_batch(self, device="cpu"): - box_predictor = FastRCNNOutputLayers( - ShapeSpec(channels=10), - box2box_transform=Box2BoxTransform(weights=(10, 10, 5, 5)), - num_classes=8, - ).to(device=device) - - logits = torch.randn(0, 100, requires_grad=True, device=device) - deltas = torch.randn(0, 4, requires_grad=True, device=device) - losses = box_predictor.losses([logits, deltas], []) - for value in losses.values(): - self.assertTrue(torch.allclose(value, torch.zeros_like(value))) - sum(losses.values()).backward() - self.assertTrue(logits.grad is not None) - self.assertTrue(deltas.grad is not None) - - predictions, _ = box_predictor.inference([logits, deltas], []) - self.assertEqual(len(predictions), 0) - - @unittest.skipIf(not torch.cuda.is_available(), "CUDA not available") - def test_fast_rcnn_empty_batch_cuda(self): - self.test_fast_rcnn_empty_batch(device=torch.device("cuda")) - - def test_fast_rcnn_rotated(self): - torch.manual_seed(132) - box_head_output_size = 8 - - box_predictor = RotatedFastRCNNOutputLayers( - ShapeSpec(channels=box_head_output_size), - box2box_transform=Box2BoxTransformRotated(weights=(10, 10, 5, 5, 1)), - num_classes=5, - ) - feature_pooled = torch.rand(2, box_head_output_size) - predictions = box_predictor(feature_pooled) - proposal_boxes = torch.tensor( - [[2, 1.95, 2.4, 1.7, 0], [4.65, 5.25, 4.7, 5.5, 0]], dtype=torch.float32 - ) - gt_boxes = torch.tensor([[2, 2, 2, 2, 0], [4, 4, 4, 4, 0]], dtype=torch.float32) - proposal = Instances((10, 10)) - proposal.proposal_boxes = RotatedBoxes(proposal_boxes) - proposal.gt_boxes = RotatedBoxes(gt_boxes) - proposal.gt_classes = torch.tensor([1, 2]) - - with EventStorage(): # capture events in a new storage to discard them - losses = box_predictor.losses(predictions, [proposal]) - - # Note: the expected losses are slightly different even if - # the boxes are essentially the same as in the FastRCNNOutput test, because - # bbox_pred in FastRCNNOutputLayers have different Linear layers/initialization - # between the two cases. - expected_losses = { - "loss_cls": torch.tensor(1.7920907736), - "loss_box_reg": torch.tensor(4.0410838127), - } - for name in expected_losses.keys(): - assert torch.allclose(losses[name], expected_losses[name]) - - def test_predict_boxes_tracing(self): - class Model(torch.nn.Module): - def __init__(self, output_layer): - super(Model, self).__init__() - self._output_layer = output_layer - - def forward(self, proposal_deltas, proposal_boxes): - instances = Instances((10, 10)) - instances.proposal_boxes = Boxes(proposal_boxes) - return self._output_layer.predict_boxes((None, proposal_deltas), [instances]) - - box_head_output_size = 8 - - box_predictor = FastRCNNOutputLayers( - ShapeSpec(channels=box_head_output_size), - box2box_transform=Box2BoxTransform(weights=(10, 10, 5, 5)), - num_classes=5, - ) - - model = Model(box_predictor) - - from detectron2.export.torchscript_patch import patch_builtin_len - - with torch.no_grad(), patch_builtin_len(): - func = torch.jit.trace(model, (torch.randn(10, 20), torch.randn(10, 4))) - - o = func(torch.randn(10, 20), torch.randn(10, 4)) - self.assertEqual(o[0].shape, (10, 20)) - o = func(torch.randn(5, 20), torch.randn(5, 4)) - self.assertEqual(o[0].shape, (5, 20)) - o = func(torch.randn(20, 20), torch.randn(20, 4)) - self.assertEqual(o[0].shape, (20, 20)) - - def test_predict_probs_tracing(self): - class Model(torch.nn.Module): - def __init__(self, output_layer): - super(Model, self).__init__() - self._output_layer = output_layer - - def forward(self, scores, proposal_boxes): - instances = Instances((10, 10)) - instances.proposal_boxes = Boxes(proposal_boxes) - return self._output_layer.predict_probs((scores, None), [instances]) - - box_head_output_size = 8 - - box_predictor = FastRCNNOutputLayers( - ShapeSpec(channels=box_head_output_size), - box2box_transform=Box2BoxTransform(weights=(10, 10, 5, 5)), - num_classes=5, - ) - - model = Model(box_predictor) - - from detectron2.export.torchscript_patch import patch_builtin_len - - with torch.no_grad(), patch_builtin_len(): - func = torch.jit.trace(model, (torch.randn(10, 6), torch.rand(10, 4))) - o = func(torch.randn(10, 6), torch.randn(10, 4)) - self.assertEqual(o[0].shape, (10, 6)) - o = func(torch.randn(5, 6), torch.randn(5, 4)) - self.assertEqual(o[0].shape, (5, 6)) - o = func(torch.randn(20, 6), torch.randn(20, 4)) - self.assertEqual(o[0].shape, (20, 6)) - - -if __name__ == "__main__": - unittest.main() diff --git a/spaces/BL00DY-257/dolle-mini-lol/index.html b/spaces/BL00DY-257/dolle-mini-lol/index.html deleted file mode 100644 index f548beb27dd81f9f12ab66b56c8cc102f5e1fc3b..0000000000000000000000000000000000000000 --- a/spaces/BL00DY-257/dolle-mini-lol/index.html +++ /dev/null @@ -1,295 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - diff --git a/spaces/BatuhanYilmaz/Youtube-Transcriber/app.py b/spaces/BatuhanYilmaz/Youtube-Transcriber/app.py deleted file mode 100644 index ce86dfd889cb8322e0958d30b4576af548306c0c..0000000000000000000000000000000000000000 --- a/spaces/BatuhanYilmaz/Youtube-Transcriber/app.py +++ /dev/null @@ -1,168 +0,0 @@ -import whisper -from pytube import YouTube -import requests, io -from urllib.request import urlopen -from PIL import Image -import time -import streamlit as st -from streamlit_lottie import st_lottie -import numpy as np -import os -from typing import Iterator -from io import StringIO -from utils import write_vtt, write_srt - -st.set_page_config(page_title="YouTube Transcriber", page_icon="🗣", layout="wide") - -# Define a function that we can use to load lottie files from a link. -@st.cache(allow_output_mutation=True) -def load_lottieurl(url: str): - r = requests.get(url) - if r.status_code != 200: - return None - return r.json() - -col1, col2 = st.columns([1, 3]) -with col1: - lottie = load_lottieurl("https://assets9.lottiefiles.com/private_files/lf30_bntlaz7t.json") - st_lottie(lottie, speed=1, height=200, width=200) - -with col2: - st.write(""" - ## Youtube Transcriber - ##### This is an app that transcribes YouTube videos into text.""") - - -#def load_model(size): - #default_size = size - #if size == default_size: - #return None - #else: - #loaded_model = whisper.load_model(size) - #return loaded_model - - -@st.cache(allow_output_mutation=True) -def populate_metadata(link): - yt = YouTube(link) - author = yt.author - title = yt.title - description = yt.description - thumbnail = yt.thumbnail_url - length = yt.length - views = yt.views - return author, title, description, thumbnail, length, views - -# Uncomment if you want to fetch the thumbnails as well. -#def fetch_thumbnail(thumbnail): - #tnail = urlopen(thumbnail) - #raw_data = tnail.read() - #image = Image.open(io.BytesIO(raw_data)) - #st.image(image, use_column_width=True) - - -def convert(seconds): - return time.strftime("%H:%M:%S", time.gmtime(seconds)) - - -loaded_model = whisper.load_model("base") -current_size = "None" -size = st.selectbox("Model Size", ["tiny", "base", "small", "medium", "large"], index=1) - - -def change_model(current_size, size): - if current_size != size: - loaded_model = whisper.load_model(size) - st.write(f"Model is {'multilingual' if loaded_model.is_multilingual else 'English-only'} " - f"and has {sum(np.prod(p.shape) for p in loaded_model.parameters()):,} parameters.") - return loaded_model - else: - return None - - -@st.cache(allow_output_mutation=True) -def inference(link): - yt = YouTube(link) - path = yt.streams.filter(only_audio=True)[0].download(filename="audio.mp4") - results = loaded_model.transcribe(path) - vtt = getSubs(results["segments"], "vtt", 80) - srt = getSubs(results["segments"], "srt", 80) - return results["text"], vtt, srt - -def getSubs(segments: Iterator[dict], format: str, maxLineWidth: int) -> str: - segmentStream = StringIO() - - if format == 'vtt': - write_vtt(segments, file=segmentStream, maxLineWidth=maxLineWidth) - elif format == 'srt': - write_srt(segments, file=segmentStream, maxLineWidth=maxLineWidth) - else: - raise Exception("Unknown format " + format) - - segmentStream.seek(0) - return segmentStream.read() - - -def main(): - change_model(current_size, size) - link = st.text_input("YouTube Link") - if st.button("Transcribe"): - author, title, description, thumbnail, length, views = populate_metadata(link) - results = inference(link) - - col3, col4 = st.columns(2) - with col3: - #fetch_thumbnail(thumbnail) - st.video(link) - st.markdown(f"**Channel**: {author}") - st.markdown(f"**Title**: {title}") - st.markdown(f"**Length**: {convert(length)}") - st.markdown(f"**Views**: {views:,}") - - with col4: - with st.expander("Video Description"): - st.write(description) - #st.markdown(f"**Video Description**: {description}") - with st.expander("Video Transcript"): - st.write(results[0]) - # Write the results to a .txt file and download it. - with open("transcript.txt", "w+") as f: - f.writelines(results[0]) - f.close() - with open(os.path.join(os.getcwd(), "transcript.txt"), "rb") as f: - datatxt = f.read() - - - with open("transcript.vtt", "w+") as f: - f.writelines(results[1]) - f.close() - with open(os.path.join(os.getcwd(), "transcript.vtt"), "rb") as f: - datavtt = f.read() - - with open("transcript.srt", "w+") as f: - f.writelines(results[2]) - f.close() - with open(os.path.join(os.getcwd(), "transcript.srt"), "rb") as f: - datasrt = f.read() - - if st.download_button(label="Download Transcript (.txt) ", - data=datatxt, - file_name=f"{title}.txt"): - st.success("Downloaded Successfully!") - - elif st.download_button(label="Download Transcript (.vtt)", - data=datavtt, - file_name=f"{title}.vtt"): - st.success("Downloaded Successfully!") - - elif st.download_button(label="Download Transcript (.srt)", - data=datasrt, - file_name=f"{title}.srt"): - st.success("Downloaded Successfully! ") - else: - st.success("You can download the transcript in .srt format and upload it to YouTube to create subtitles for your video.") - st.info("Streamlit refreshes after the download button is clicked. The data is cached so you can download the transcript again without having to transcribe the video again.") - - -if __name__ == "__main__": - main() \ No newline at end of file diff --git a/spaces/Benson/text-generation/Examples/Android_6_8_9_10.apk Download.md b/spaces/Benson/text-generation/Examples/Android_6_8_9_10.apk Download.md deleted file mode 100644 index e7cb61ad1edc9e06f5e8ddf68b894fab40091c54..0000000000000000000000000000000000000000 --- a/spaces/Benson/text-generation/Examples/Android_6_8_9_10.apk Download.md +++ /dev/null @@ -1,96 +0,0 @@ -
' if Path("cache/pfp_character.png").exists() else ''
- img_me = f' if reset_cache else )
' if Path("cache/pfp_me.png").exists() else ''
-
- for i, _row in enumerate(history[::-1]):
- row = [convert_to_markdown(entry) for entry in _row]
-
- output += f"""
-
- """
-
- if len(row[0]) == 0: # don't display empty user messages
- continue
-
- output += f"""
-
- """
-
- output += "' - - for i, _row in enumerate(history[::-1]): - row = [convert_to_markdown(entry) for entry in _row] - - output += f""" - - """ - - if len(row[0]) == 0: # don't display empty user messages - continue - - output += f""" - - """ - - output += "" - return output - - -def chat_html_wrapper(history, name1, name2, mode, style, reset_cache=False): - if mode == 'instruct': - return generate_instruct_html(history) - elif style == 'wpp': - return generate_chat_html(history, name1, name2) - else: - return generate_cai_chat_html(history, name1, name2, style, reset_cache) diff --git a/spaces/FFusion/FFXL-SDXL-Convert-diffusers/app.py b/spaces/FFusion/FFXL-SDXL-Convert-diffusers/app.py deleted file mode 100644 index da0a8d80975b7a3dda4997816b0afdfa3ea93af6..0000000000000000000000000000000000000000 --- a/spaces/FFusion/FFXL-SDXL-Convert-diffusers/app.py +++ /dev/null @@ -1,46 +0,0 @@ -import gradio as gr - -from convert import convert - -DESCRIPTION = """ --- -The steps are the following: - -- Paste a read-access token from hf.co/settings/tokens. Read access is enough given that we will open a PR against the source repo. -- Input a model id from the Hub -- Input the filename from the root dir of the repo that you would like to convert, e.g. 'xl-pruned.safetensors' -- Click "Submit" -- That's it! You'll get feedback if it works or not, and if it worked, you'll get the URL of the opened PR 🔥 - -⚠️ If you encounter weird error messages, please have a look into the Logs and feel free to open a PR to correct the error messages. - - --
-
-- -""" - -demo = gr.Interface( - title="Convert Stable Diffusion XL .safetensors to Diffusers and open a PR", - description=DESCRIPTION, - allow_flagging="never", - article="Check out the [Diffusers from FFXL on HuggingFace](https://huggingface.co/FFusion/FFusionXL-09-SDXL)", - inputs=[ - gr.Text(max_lines=1, label="your_hf_token"), - gr.Text(max_lines=1, label="model_id"), - gr.Text(max_lines=1, label="filename"), - ], - outputs=[gr.Markdown(label="output")], - fn=convert, -).queue(max_size=10, concurrency_count=1) - -demo.launch(show_api=True) diff --git a/spaces/Felix123456/bingo/src/components/chat-suggestions.tsx b/spaces/Felix123456/bingo/src/components/chat-suggestions.tsx deleted file mode 100644 index 00c2fee295c9e010946046eb71705a5e131f7a5a..0000000000000000000000000000000000000000 --- a/spaces/Felix123456/bingo/src/components/chat-suggestions.tsx +++ /dev/null @@ -1,45 +0,0 @@ -import React, { useMemo } from 'react' -import Image from 'next/image' -import HelpIcon from '@/assets/images/help.svg' -import { SuggestedResponse } from '@/lib/bots/bing/types' -import { useBing } from '@/lib/hooks/use-bing' -import { atom, useAtom } from 'jotai' - -type Suggestions = SuggestedResponse[] -const helpSuggestions = ['为什么不回应某些主题', '告诉我更多关于必应的资迅', '必应如何使用 AI?'].map((text) => ({ text })) -const suggestionsAtom = atom-
-
-
-
-- Code Interpreter: 代码解释器模式，模型可以在一个 Jupyter 环境中执行代码并获取结果，以完成复杂任务。
- 
-
-### 代码调用
-
-可以通过如下代码调用 ChatGLM 模型来生成对话：
-
-```python
->>> from transformers import AutoTokenizer, AutoModel
->>> tokenizer = AutoTokenizer.from_pretrained("THUDM/chatglm3-6b", trust_remote_code=True)
->>> model = AutoModel.from_pretrained("THUDM/chatglm3-6b", trust_remote_code=True, device='cuda')
->>> model = model.eval()
->>> response, history = model.chat(tokenizer, "你好", history=[])
->>> print(response)
-你好👋!我是人工智能助手 ChatGLM3-6B,很高兴见到你,欢迎问我任何问题。
->>> response, history = model.chat(tokenizer, "晚上睡不着应该怎么办", history=history)
->>> print(response)
-晚上睡不着可能会让你感到焦虑或不舒服,但以下是一些可以帮助你入睡的方法:
-
-1. 制定规律的睡眠时间表:保持规律的睡眠时间表可以帮助你建立健康的睡眠习惯,使你更容易入睡。尽量在每天的相同时间上床,并在同一时间起床。
-2. 创造一个舒适的睡眠环境:确保睡眠环境舒适,安静,黑暗且温度适宜。可以使用舒适的床上用品,并保持房间通风。
-3. 放松身心:在睡前做些放松的活动,例如泡个热水澡,听些轻柔的音乐,阅读一些有趣的书籍等,有助于缓解紧张和焦虑,使你更容易入睡。
-4. 避免饮用含有咖啡因的饮料:咖啡因是一种刺激性物质,会影响你的睡眠质量。尽量避免在睡前饮用含有咖啡因的饮料,例如咖啡,茶和可乐。
-5. 避免在床上做与睡眠无关的事情:在床上做些与睡眠无关的事情,例如看电影,玩游戏或工作等,可能会干扰你的睡眠。
-6. 尝试呼吸技巧:深呼吸是一种放松技巧,可以帮助你缓解紧张和焦虑,使你更容易入睡。试着慢慢吸气,保持几秒钟,然后缓慢呼气。
-
-如果这些方法无法帮助你入睡,你可以考虑咨询医生或睡眠专家,寻求进一步的建议。
-```
-
-#### 从本地加载模型
-以上代码会由 `transformers` 自动下载模型实现和参数。完整的模型实现在 [Hugging Face Hub](https://huggingface.co/THUDM/chatglm3-6b)。如果你的网络环境较差，下载模型参数可能会花费较长时间甚至失败。此时可以先将模型下载到本地，然后从本地加载。
-
-从 Hugging Face Hub 下载模型需要先[安装Git LFS](https://docs.github.com/zh/repositories/working-with-files/managing-large-files/installing-git-large-file-storage)，然后运行
-```Shell
-git clone https://huggingface.co/THUDM/chatglm3-6b
-```
-
-如果从你从 HuggingFace 下载比较慢，也可以从 [ModelScope](https://modelscope.cn/models/ZhipuAI/chatglm3-6b)
-中下载。
-
-### 网页版对话 Demo
-
-可以通过以下命令启动基于 Gradio 的网页版 demo：
-```shell
-python web_demo.py
-```
-
-
-
-可以通过以下命令启动基于 Streamlit 的网页版 demo：
-```shell
-streamlit run web_demo2.py
-```
-
-网页版 demo 会运行一个 Web Server，并输出地址。在浏览器中打开输出的地址即可使用。 经测试，基于 Streamlit 的网页版 Demo 会更流畅。
-
-### 命令行对话 Demo
-
-
-
-运行仓库中 [cli_demo.py](cli_demo.py)：
-
-```shell
-python cli_demo.py
-```
-
-程序会在命令行中进行交互式的对话，在命令行中输入指示并回车即可生成回复，输入 `clear` 可以清空对话历史，输入 `stop` 终止程序。
-
-### LangChain Demo
-请参考 [基于 LangChain 的工具调用 Demo](langchain_demo/README.md)。
-
-### 工具调用
-关于工具调用的方法请参考 [工具调用](tool_using/README.md)。
-
-### API 部署
-感谢 [@xusenlinzy](https://github.com/xusenlinzy) 实现了 OpenAI 格式的流式 API 部署，可以作为任意基于 ChatGPT 的应用的后端，比如 [ChatGPT-Next-Web](https://github.com/Yidadaa/ChatGPT-Next-Web)。可以通过运行仓库中的[openai_api.py](openai_api.py) 进行部署：
-```shell
-python openai_api.py
-```
-进行 API 调用的示例代码为
-```python
-import openai
-if __name__ == "__main__":
- openai.api_base = "http://localhost:8000/v1"
- openai.api_key = "none"
- for chunk in openai.ChatCompletion.create(
- model="chatglm3-6b",
- messages=[
- {"role": "user", "content": "你好"}
- ],
- stream=True
- ):
- if hasattr(chunk.choices[0].delta, "content"):
- print(chunk.choices[0].delta.content, end="", flush=True)
-```
-
-## 低成本部署
-
-### 模型量化
-
-默认情况下，模型以 FP16 精度加载，运行上述代码需要大概 13GB 显存。如果你的 GPU 显存有限，可以尝试以量化方式加载模型，使用方法如下：
-
-```python
-model = AutoModel.from_pretrained("THUDM/chatglm3-6b",trust_remote_code=True).quantize(4).cuda()
-```
-
-模型量化会带来一定的性能损失，经过测试，ChatGLM3-6B 在 4-bit 量化下仍然能够进行自然流畅的生成。
-
-### CPU 部署
-
-如果你没有 GPU 硬件的话，也可以在 CPU 上进行推理，但是推理速度会更慢。使用方法如下（需要大概 32GB 内存）
-```python
-model = AutoModel.from_pretrained("THUDM/chatglm3-6b", trust_remote_code=True).float()
-```
-
-### Mac 部署
-
-对于搭载了 Apple Silicon 或者 AMD GPU 的 Mac，可以使用 MPS 后端来在 GPU 上运行 ChatGLM3-6B。需要参考 Apple 的 [官方说明](https://developer.apple.com/metal/pytorch) 安装 PyTorch-Nightly（正确的版本号应该是2.x.x.dev2023xxxx，而不是 2.x.x）。
-
-目前在 MacOS 上只支持[从本地加载模型](README.md#从本地加载模型)。将代码中的模型加载改为从本地加载，并使用 mps 后端：
-```python
-model = AutoModel.from_pretrained("your local path", trust_remote_code=True).to('mps')
-```
-
-加载半精度的 ChatGLM3-6B 模型需要大概 13GB 内存。内存较小的机器（比如 16GB 内存的 MacBook Pro），在空余内存不足的情况下会使用硬盘上的虚拟内存，导致推理速度严重变慢。
-
-### 多卡部署
-如果你有多张 GPU，但是每张 GPU 的显存大小都不足以容纳完整的模型，那么可以将模型切分在多张GPU上。首先安装 accelerate: `pip install accelerate`，然后通过如下方法加载模型：
-```python
-from utils import load_model_on_gpus
-model = load_model_on_gpus("THUDM/chatglm3-6b", num_gpus=2)
-```
-即可将模型部署到两张 GPU 上进行推理。你可以将 `num_gpus` 改为你希望使用的 GPU 数。默认是均匀切分的，你也可以传入 `device_map` 参数来自己指定。
-
-## 引用
-
-如果你觉得我们的工作有帮助的话，请考虑引用下列论文。
-
-```
-@article{zeng2022glm,
- title={Glm-130b: An open bilingual pre-trained model},
- author={Zeng, Aohan and Liu, Xiao and Du, Zhengxiao and Wang, Zihan and Lai, Hanyu and Ding, Ming and Yang, Zhuoyi and Xu, Yifan and Zheng, Wendi and Xia, Xiao and others},
- journal={arXiv preprint arXiv:2210.02414},
- year={2022}
-}
-```
-```
-@inproceedings{du2022glm,
- title={GLM: General Language Model Pretraining with Autoregressive Blank Infilling},
- author={Du, Zhengxiao and Qian, Yujie and Liu, Xiao and Ding, Ming and Qiu, Jiezhong and Yang, Zhilin and Tang, Jie},
- booktitle={Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
- pages={320--335},
- year={2022}
-}
-```
diff --git a/spaces/PAIR/Text2Video-Zero/annotator/uniformer/configs/_base_/datasets/drive.py b/spaces/PAIR/Text2Video-Zero/annotator/uniformer/configs/_base_/datasets/drive.py
deleted file mode 100644
index 06e8ff606e0d2a4514ec8b7d2c6c436a32efcbf4..0000000000000000000000000000000000000000
--- a/spaces/PAIR/Text2Video-Zero/annotator/uniformer/configs/_base_/datasets/drive.py
+++ /dev/null
@@ -1,59 +0,0 @@
-# dataset settings
-dataset_type = 'DRIVEDataset'
-data_root = 'data/DRIVE'
-img_norm_cfg = dict(
- mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
-img_scale = (584, 565)
-crop_size = (64, 64)
-train_pipeline = [
- dict(type='LoadImageFromFile'),
- dict(type='LoadAnnotations'),
- dict(type='Resize', img_scale=img_scale, ratio_range=(0.5, 2.0)),
- dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75),
- dict(type='RandomFlip', prob=0.5),
- dict(type='PhotoMetricDistortion'),
- dict(type='Normalize', **img_norm_cfg),
- dict(type='Pad', size=crop_size, pad_val=0, seg_pad_val=255),
- dict(type='DefaultFormatBundle'),
- dict(type='Collect', keys=['img', 'gt_semantic_seg'])
-]
-test_pipeline = [
- dict(type='LoadImageFromFile'),
- dict(
- type='MultiScaleFlipAug',
- img_scale=img_scale,
- # img_ratios=[0.5, 0.75, 1.0, 1.25, 1.5, 1.75, 2.0],
- flip=False,
- transforms=[
- dict(type='Resize', keep_ratio=True),
- dict(type='RandomFlip'),
- dict(type='Normalize', **img_norm_cfg),
- dict(type='ImageToTensor', keys=['img']),
- dict(type='Collect', keys=['img'])
- ])
-]
-
-data = dict(
- samples_per_gpu=4,
- workers_per_gpu=4,
- train=dict(
- type='RepeatDataset',
- times=40000,
- dataset=dict(
- type=dataset_type,
- data_root=data_root,
- img_dir='images/training',
- ann_dir='annotations/training',
- pipeline=train_pipeline)),
- val=dict(
- type=dataset_type,
- data_root=data_root,
- img_dir='images/validation',
- ann_dir='annotations/validation',
- pipeline=test_pipeline),
- test=dict(
- type=dataset_type,
- data_root=data_root,
- img_dir='images/validation',
- ann_dir='annotations/validation',
- pipeline=test_pipeline))
diff --git a/spaces/PAIR/Text2Video-Zero/annotator/uniformer/configs/_base_/default_runtime.py b/spaces/PAIR/Text2Video-Zero/annotator/uniformer/configs/_base_/default_runtime.py
deleted file mode 100644
index b564cc4e7e7d9a67dacaaddecb100e4d8f5c005b..0000000000000000000000000000000000000000
--- a/spaces/PAIR/Text2Video-Zero/annotator/uniformer/configs/_base_/default_runtime.py
+++ /dev/null
@@ -1,14 +0,0 @@
-# yapf:disable
-log_config = dict(
- interval=50,
- hooks=[
- dict(type='TextLoggerHook', by_epoch=False),
- # dict(type='TensorboardLoggerHook')
- ])
-# yapf:enable
-dist_params = dict(backend='nccl')
-log_level = 'INFO'
-load_from = None
-resume_from = None
-workflow = [('train', 1)]
-cudnn_benchmark = True
diff --git a/spaces/PICOF/YusamiAlchemy/app.py b/spaces/PICOF/YusamiAlchemy/app.py
deleted file mode 100644
index d10dc0c19d36fd7a810f431c844f598c494a3590..0000000000000000000000000000000000000000
--- a/spaces/PICOF/YusamiAlchemy/app.py
+++ /dev/null
@@ -1,175 +0,0 @@
-#!/usr/bin/env python
-
-from __future__ import annotations
-
-import argparse
-import functools
-import os
-import html
-import pathlib
-import tarfile
-
-import deepdanbooru as dd
-import gradio as gr
-import huggingface_hub
-import numpy as np
-import PIL.Image
-import tensorflow as tf
-import piexif
-import piexif.helper
-
-TITLE = 'Alchemy'
-
-TOKEN = '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'
-MODEL_REPO = 'PICOF/deepdanbooru'
-MODEL_FILENAME = 'model-resnet_custom_v3.h5'
-LABEL_FILENAME = 'tags.txt'
-
-
-def parse_args() -> argparse.Namespace:
- parser = argparse.ArgumentParser()
- parser.add_argument('--score-slider-step', type=float, default=0.05)
- parser.add_argument('--score-threshold', type=float, default=0.5)
- parser.add_argument('--theme', type=str, default='dark-grass')
-# parser.add_argument('--live', action='store_true')
- parser.add_argument('--share', action='store_true')
-# parser.add_argument('--port', type=int)
-# parser.add_argument('--disable-queue',
-# dest='enable_queue',
-# action='store_false')
- parser.add_argument('--allow-flagging', type=str, default='never')
- return parser.parse_args()
-
-#def load_sample_image_paths() -> list[pathlib.Path]:
-# image_dir = pathlib.Path('images')
-# if not image_dir.exists():
-# dataset_repo = 'hysts/sample-images-TADNE'
-# path = huggingface_hub.hf_hub_download(dataset_repo,
-# 'images.tar.gz',
-# repo_type='dataset',
-# use_auth_token=TOKEN)
-# with tarfile.open(path) as f:
-# f.extractall()
-# return sorted(image_dir.glob('*'))
-
-
-def load_model() -> tf.keras.Model:
- path = huggingface_hub.hf_hub_download(MODEL_REPO,
- MODEL_FILENAME,
- use_auth_token=TOKEN)
- model = tf.keras.models.load_model(path)
- return model
-
-
-def load_labels() -> list[str]:
- path = huggingface_hub.hf_hub_download(MODEL_REPO,
- LABEL_FILENAME,
- use_auth_token=TOKEN)
- with open(path) as f:
- labels = [line.strip() for line in f.readlines()]
- return labels
-
-def plaintext_to_html(text):
- text = "
- 
- 
-