Datasets:

Weyaxi
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huggingface-spaces-codes

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-import gradio as gr
-import huggingface_hub
-import onnxruntime as rt
-import numpy as np
-import cv2
-def get_mask(img, s=1024):
-    img = (img / 255).astype(np.float32)
-    h, w = h0, w0 = img.shape[:-1]
-    h, w = (s, int(s * w / h)) if h > w else (int(s * h / w), s)
-    ph, pw = s - h, s - w
-    img_input = np.zeros([s, s, 3], dtype=np.float32)
-    img_input[ph // 2:ph // 2 + h, pw // 2:pw // 2 + w] = cv2.resize(img, (w, h))
-    img_input = np.transpose(img_input, (2, 0, 1))
-    img_input = img_input[np.newaxis, :]
-    mask = rmbg_model.run(None, {'img': img_input})[0][0]
-    mask = np.transpose(mask, (1, 2, 0))
-    mask = mask[ph // 2:ph // 2 + h, pw // 2:pw // 2 + w]
-    mask = cv2.resize(mask, (w0, h0))[:, :, np.newaxis]
-    return mask
-def rmbg_fn(img):
-    mask = get_mask(img)
-    img = (mask * img + 255 * (1 - mask)).astype(np.uint8)
-    mask = (mask * 255).astype(np.uint8)
-    img = np.concatenate([img, mask], axis=2, dtype=np.uint8)
-    mask = mask.repeat(3, axis=2)
-    return mask, img
-if __name__ == "__main__":
-    providers = ['CUDAExecutionProvider', 'CPUExecutionProvider']
-    model_path = huggingface_hub.hf_hub_download("skytnt/anime-seg", "isnetis.onnx")
-    rmbg_model = rt.InferenceSession(model_path, providers=providers)
-    app = gr.Blocks()
-    with app:
-        gr.Markdown("# Anime Remove Background\n\n"
-                    "![visitor badge](https://visitor-badge.glitch.me/badge?page_id=skytnt.animeseg)\n\n"
-                    "demo for [https://github.com/SkyTNT/anime-segmentation/](https://github.com/SkyTNT/anime-segmentation/)")
-        with gr.Row():
-            with gr.Column():
-                input_img = gr.Image(label="input image")
-                examples_data = [[f"examples/{x:02d}.jpg"] for x in range(1, 4)]
-                examples = gr.Dataset(components=[input_img], samples=examples_data)
-            run_btn = gr.Button(variant="primary")
-            output_mask = gr.Image(label="mask")
-            output_img = gr.Image(label="result", image_mode="RGBA")
-        examples.click(lambda x: x[0], [examples], [input_img])
-        run_btn.click(rmbg_fn, [input_img], [output_mask, output_img])
-    app.launch()

spaces/1acneusushi/gradio-2dmoleculeeditor/data/Astute Graphics Plugins Keygen Torrent Create Stunning Artwork in Illustrator with These Plug-ins.md DELETED Viewed

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-<h1>Astute Graphics Plugins Keygen Torrent: How to Download and Install the Best Plugins for Adobe Illustrator</h1>
- <p>If you are a graphic designer, illustrator, or vector artist, you probably use Adobe Illustrator as your main tool for creating stunning artworks. But did you know that you can enhance your workflow and creativity with Astute Graphics Plugins? These are a set of plugins that add new features and functions to Adobe Illustrator, making it easier, faster, and more fun to work with vectors. In this article, we will show you what Astute Graphics Plugins are, what they can do for you, and how to download and install them using a keygen torrent.</p>
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- <h2>What are Astute Graphics Plugins?</h2>
- <p>Astute Graphics Plugins are a collection of plugins that extend the capabilities of Adobe Illustrator. They are developed by Astute Graphics, a company that specializes in creating software solutions for vector design. Astute Graphics Plugins are designed to help you work smarter and faster with vectors, by adding new tools, effects, panels, and shortcuts to Adobe Illustrator. They also improve the performance and stability of Adobe Illustrator, by reducing memory usage and crashes.</p>
- <h3>The benefits of using Astute Graphics Plugins</h3>
- <p>By using Astute Graphics Plugins, you can enjoy many benefits such as:</p>
- <ul>
-<li>Save time and effort by automating tedious tasks and simplifying complex operations.</li>
-<li>Enhance your creativity by exploring new possibilities and styles with vectors.</li>
-<li>Increase your productivity by working more efficiently and accurately with vectors.</li>
-<li>Improve your quality by achieving more professional and consistent results with vectors.</li>
-</ul>
- <h3>The features of Astute Graphics Plugins</h3>
- <p>Astute Graphics Plugins offer a wide range of features that cover different aspects of vector design. Some of the most popular features include:</p>
- <ul>
-<li><b>VectorScribe</b>: This plugin allows you to edit and manipulate vectors with ease. You can use it to draw shapes, curves, paths, corners, points, segments, tangents, handles, measurements, guides, grids, alignment, snapping, symmetry, scaling, rotation, transformation, distortion, warping, blending, smoothing, simplifying, cleaning up, converting, expanding, joining, splitting, cutting, erasing, trimming, extending, offsetting, outlining, stroking, filling, coloring, shading, gradients, transparency...</li>
-<li><b>InkScribe</b>: This plugin allows you to draw vectors with precision and control. You can use it to create smooth curves, straight lines, perfect circles, ellipses, arcs, spirals, stars, polygons, and more. You can also adjust the width, pressure, profile, and variable width of your strokes.</li>
-<li><b>Phantasm</b>: This plugin allows you to apply color adjustments and effects to vectors. You can use it to change the hue, saturation, brightness, contrast, levels, curves, exposure, color balance, colorize, invert, grayscale, duotone, halftone, posterize, solarize, threshold, and more. You can also apply filters such as blur, sharpen, noise, glow, shadow, emboss, bevel...</li>
-<li><b>MirrorMe</b>: This plugin allows you to create symmetrical designs with vectors. You can use it to reflect rotate scale and copy your artwork along one or more axes. You can also create radial symmetry patterns with ease.</li>
-<li><b>Texturino</b>: This plugin allows you to add textures and opacity brushes to vectors. You can use it to create realistic effects such as wood grain metallic fabric paper leather watercolor and more. You can also customize your own textures and brushes from images or photos.</li>
-<li><b>ColliderScribe</b>: This plugin allows you to arrange and align objects with precision. You can use it to snap objects together distribute them evenly rotate them around a point place them along a path or create complex shapes from simple ones.</li>
-<li><b>Stylism</b>: This plugin allows you to apply and edit live effects on vectors. You can use it to add drop shadows inner glows outer glows feather gaussian blur offset path transform and more. You can also adjust the parameters of the effects directly on the artboard.</li>
-<li><b>DynamicSketch</b>: This plugin allows you to draw naturally with your mouse or tablet. You can use it to sketch freehand trace images or create smooth curves with variable width. You can also edit your sketches with smart gestures and intuitive tools.</li>
-<li><b>Autosaviour</b>: This plugin allows you to save your work automatically and securely. You can use it to backup your files create versions set reminders and recover lost data.</li>
-<li><b>Rasterino</b>: This plugin allows you to work with raster images in Adobe Illustrator. You can use it to crop trim resize rotate embed unembed and edit raster images without leaving Illustrator.</li>
-<li><b>DirectPrefs</b>: This plugin allows you to access and customize your Illustrator preferences easily. You can use it to change your keyboard shortcuts units guides grids snap options and more.</li>
-<li><b>InkQuest</b>: This plugin allows you to prepare your artwork for printing or exporting. You can use it to check your colors inks overprints traps bleeds marks and more.</li>
-<li><b>SubScribe</b>: This plugin allows you to draw geometric shapes and curves with accuracy. You can use it to create circles arcs lines tangents perpendiculars spirals and more.</li>
-<li><b>WidthScribe</b>: This plugin allows you to vary the width of your strokes along their length. You can use it to create tapered ends calligraphic effects or artistic variations.</li>
-</ul>
- <h2>What is a keygen torrent?</h2>
- <p>A keygen torrent is a type of file that contains a software program (keygen) that generates serial numbers or activation codes for another software program (in this case Astute Graphics Plugins). A keygen torrent also contains a torrent file that helps you download the keygen from other users who have already downloaded it.</p>
- <h3>The advantages and disadvantages of using a keygen torrent</h3>
- <p>Using a keygen torrent has some advantages and disadvantages that you should be aware of before downloading one:</p>
- <table>
-<tr>
-<th>Advantages</th>
-<th>Disadvantages</th>
-</tr>
-<tr>
-<td>You can get access to premium software for free or at a low cost.</td>
-<td>You may violate the intellectual property rights of the software developers or publishers.</td>
-</tr>
-<tr>
-<td>You can test the software before buying it or find an alternative if you cannot afford it.</td>
-<td>You may expose your computer or device to viruses malware spyware ransomware or other malicious programs that may harm your data or system.</td>
-</tr>
-<tr>
-<td>You can bypass the online activation or registration process that may require personal information or payment details.</td>
-<td>You may not receive updates bug fixes technical support or customer service from the software developers or publishers.</td>
-</tr>
-<tr>
-<td>You can share the software with other users who may benefit from it or appreciate it.</td>
-<td>You may face legal consequences such as fines lawsuits or criminal charges if you are caught using or distributing pirated software.</td>
-</tr>
-</table>
- <h3>The risks and precautions of using a keygen torrent</h3>
- <p>Using a keygen torrent involves some risks that you should be careful about when downloading one:</p>
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- <ul>
-<li>The keygen may not work properly or at all for the software that you want to activate. It may generate invalid serial numbers or expired codes that may not activate the software. It may also generate codes that have been used by other users and may be blacklisted by the software developers or publishers.</li>
-<li>The keygen may contain malware that can infect your computer or device. Some keygens are disguised as malware or bundled with malware that can steal your personal information, damage your files, encrypt your data, display unwanted ads, or hijack your browser.</li>
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-</ul>
- <p>To reduce the risks of using a keygen torrent, you should take some precautions such as:</p>
- <ul>
-<li>Download the keygen torrent from a reputable source that has positive feedback and comments from other users. Avoid sources that have negative feedback, comments, or warnings from other users.</li>
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-</ul>
- <h2>How to download and install Astute Graphics Plugins Keygen Torrent</h2>
- <p>Now that you know what Astute Graphics Plugins and keygen torrents are, you may wonder how to download and install them on your computer. Here are the steps to follow:</p>
- <h3>The steps to download and install Astute Graphics Plugins Keygen Torrent</h3>
- <ol>
-<li>Download a torrent client such as uTorrent, BitTorrent, qBittorrent, etc. Install and run the torrent client on your computer.</li>
-<li>Download the Astute Graphics Plugins Keygen Torrent file from a reputable source. You can use a search engine such as Google, Bing, Yahoo, etc. to find one. Make sure to check the feedback and comments of other users before downloading.</li>
-<li>Open the Astute Graphics Plugins Keygen Torrent file with your torrent client. Choose a location to save the downloaded files and start the download process.</li>
-<li>Wait for the download to finish. You should see a folder containing the Astute Graphics Plugins setup file and the keygen file.</li>
-<li>Run the Astute Graphics Plugins setup file and follow the instructions to install the plugins on your computer. Do not open the plugins yet.</li>
-<li>Run the keygen file and select the plugins that you want to activate from a drop-down menu. Click on \"Generate\" to create a serial number or an activation code for each plugin.</li>
-<li>Open Adobe Illustrator and go to \"Help\" > \"Astute Graphics\" > \"License Manager\". Enter the serial number or the activation code for each plugin that you generated with the keygen. Click on \"Activate\" to activate the plugins.</li>
-<li>Enjoy using Astute Graphics Plugins with Adobe Illustrator.</li>
-</ol>
- <h3>The tips and tricks to use Astute Graphics Plugins Keygen Torrent</h3>
- <p>To make the most out of Astute Graphics Plugins Keygen Torrent, you should also follow some tips and tricks such as:</p>
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-<li>Update Adobe Illustrator to the latest version before installing Astute Graphics Plugins. This can ensure compatibility and stability between Adobe Illustrator and Astute Graphics Plugins.</li>
-<li>Check for updates for Astute Graphics Plugins regularly. This can help you get new features, bug fixes, and improvements for Astute Graphics Plugins.</li>
-<li>Learn how to use Astute Graphics Plugins effectively. You can watch tutorials, read manuals, join forums, or take courses on how to use Astute Graphics Plugins with Adobe Illustrator.</li>
-<li>Create backups of your files before using Astute Graphics Plugins. This can help you recover your files in case something goes wrong while using Astute Graphics Plugins.</li>
-</ul>
- <h2>Conclusion</h2>
- <p>Astute Graphics Plugins are amazing tools that can enhance your workflow and creativity with Adobe Illustrator. However, they are not free and require a license to use them fully. If you want to try them out without paying for them, you can use a keygen torrent to generate serial numbers or activation codes for them. However, you should be aware of the drawbacks and risks of using a keygen torrent. You should also take some precautions to protect yourself and your computer from malware, legal issues, or other problems. However, if you like Astute Graphics Plugins and want to support the developers, you should consider buying a license from their official website. This way, you can enjoy the full features and benefits of Astute Graphics Plugins without any worries.</p>
- <h2>Conclusion</h2>
- <p>In this article, we have shown you what Astute Graphics Plugins are, what they can do for you, and how to download and install them using a keygen torrent. We have also discussed the advantages and disadvantages of using a keygen torrent, as well as the risks and precautions of using one. We hope that this article has been helpful and informative for you. However, we do not encourage or endorse piracy or illegal use of software. If you want to use Astute Graphics Plugins legally and ethically, you should buy a license from their official website. This way, you can support the developers and enjoy the best plugins for Adobe Illustrator.</p>
- <h3>FAQs</h3>
- <p>Here are some frequently asked questions about Astute Graphics Plugins Keygen Torrent:</p>
- <ol>
-<li><b>What are the system requirements for Astute Graphics Plugins?</b></li>
-<p>Astute Graphics Plugins require Adobe Illustrator CS6 or higher (including CC versions) and Windows 7 or higher or Mac OS X 10.10 or higher.</p>
-<li><b>How much does Astute Graphics Plugins cost?</b></li>
-<p>Astute Graphics Plugins offer different pricing plans depending on your needs. You can buy individual plugins for $39-$119 each, or buy bundles of plugins for $119-$399 each. You can also subscribe to Astute Graphics Plugins Elite Bundle for $119 per year, which gives you access to all plugins and updates.</p>
-<li><b>How can I get support for Astute Graphics Plugins?</b></li>
-<p>Astute Graphics Plugins offer various support options for their customers. You can contact their support team via email, phone, chat, or social media. You can also visit their website for tutorials, manuals, videos, blogs, forums, webinars, and FAQs.</p>
-<li><b>Are Astute Graphics Plugins compatible with other plugins or software?</b></li>
-<p>Astute Graphics Plugins are generally compatible with other plugins or software that work with Adobe Illustrator. However, some plugins or software may cause conflicts or issues with Astute Graphics Plugins. If you encounter any problems, you should contact the support team of both parties for assistance.</p>
-<li><b>Can I use Astute Graphics Plugins on multiple computers?</b></li>
-<p>Astute Graphics Plugins allow you to activate your license on up to two computers at a time. However, you cannot use them simultaneously on both computers. If you want to use them on more than two computers, you need to buy more licenses or deactivate your license on one computer before activating it on another.</p>
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-<p>AI home camera apk is a great app for home security, but it is not perfect. Here are some of the pros and cons of AI home camera apk that you should consider:</p>
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-<tr><td>- It supports cloud and local storage</td><td>- It may have some privacy or security issues</td></tr>
-<tr><td>- It allows sharing and collaboration</td><td>- It may have some compatibility or performance issues</td></tr>
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-<p>Thank you for reading this article. We hope you found it helpful and informative. If you have any feedback or suggestions, please let us know in the comments section below. We would love to hear from you!</p>
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spaces/1phancelerku/anime-remove-background/Android Oyun Clubta Durak Online 3D Para Hilesi Nasl Yaplr? te Admlar.md DELETED Viewed

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-<h1>Durak Online Para Hilesi Android Oyun Club: How to Play Durak Online and Win Money</h1>
-<p>If you are looking for a card game that is fun, challenging, and rewarding, then you should try <strong>Durak Online</strong>. Durak Online is a modern version of the famous card game that originated in Russia and is also popular in Turkey. In this article, we will tell you everything you need to know about Durak Online, how to play it, how to win money in it, and how to use <strong>Durak Online para hilesi android oyun club</strong>, a cheat tool that can generate unlimited coins and items for you.</p>
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-<h3>Durak Online is a popular card game in Russia and Turkey</h3>
-<p>Durak means "fool" in Russian, and the name of the game refers to the last player who is left with cards in their hand at the end of the game. Durak is a card game that involves skill, strategy, and luck. It can be played by 2 to 6 players, using a deck of 24, 36, or 52 cards. The game is also known as "Attack-Defence" or "Beat off" in English.</p>
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-<h3>Durak Online is available on Google Play for Android devices</h3>
-<p>Durak Online is a free app that you can download from Google Play for your Android device. The app has great 3D graphics, realistic sounds, smooth animations, and no intrusive ads. The app also has a user-friendly interface with landscape mode. You can link your account to your Google account and sync your progress across devices. You can also play offline against bots if you don't have an internet connection.</p>
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-<h3>The objective of Durak Online is to get rid of all your cards</h3>
-<p>The objective of Durak Online is to get rid of all your cards before your opponents do. The game starts with one player being the dealer, who shuffles the deck and deals six cards to each player. The dealer then reveals the bottom card of the remaining deck, which determines the trump suit for the game. The trump suit is the strongest suit in the game, and can beat any other suit. The player to the left of the dealer is the first attacker, and the player to their left is the first defender.</p>
-<h3>The rules of Durak Online are simple and easy to learn</h3>
-<p>The rules of Durak Online are similar to the rules of the original card game. The game consists of a series of attacks and defences, where each player tries to get rid of their cards by playing them on the table. The attacker plays one or more cards of the same rank, and the defender has to beat them with higher cards of the same suit or with trumps. If the defender succeeds, they can pass the attack to the next player, who becomes the new defender. If the defender fails, they have to take all the cards on the table and add them to their hand. The game ends when one player has no cards left in their hand or in the deck.</p>
-<h3>The tips and tricks of Durak Online are to use your trumps wisely and to throw-in more cards</h3>
-<p>The tips and tricks of Durak Online are to use your trumps wisely and to throw-in more cards. Trumps are very valuable in Durak Online, as they can beat any other suit. You should save your trumps for when you really need them, and avoid wasting them on low cards. You should also try to get rid of your non-trump cards as soon as possible, as they can become useless later in the game. Another tip is to throw-in more cards when you are not the attacker or the defender. Throwing-in means playing a card of the same rank as any card on the table, which adds more pressure on the defender and helps you get rid of your cards faster. However, you should be careful not to throw-in too many cards, as you might run out of options later.</p>
- <h2>How to win money in Durak Online?</h2>
-<h3>Durak Online has a championship mode where you can compete with other players for prizes</h3>
-<p>Durak Online has a championship mode where you can compete with other players for prizes. The championship mode is a tournament where you have to play a series of games against different opponents and accumulate points based on your performance. The more games you win, the more points you get. The top players at the end of the tournament will receive prizes such as coins, items, or even real money. You can enter the championship mode by paying an entry fee with coins or watching an ad.</p>
-<h3>Durak Online has a gift system where you can send and receive coins and items</h3>
-<p>Durak Online has a gift system where you can send and receive coins and items. Coins are the currency of Durak Online, which you can use to enter games, buy items, or exchange for real money. Items are special cards that have different effects on the game, such as changing the trump suit, skipping a turn, or revealing an opponent's card. You can send and receive coins and items with your friends or random players in Durak Online, as a way of showing your appreciation or friendship. You can also earn coins and items by completing daily tasks, watching ads, or inviting friends.</p>
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-<h3>Durak Online has a leaderboard where you can rank up and earn rewards</h3>
-<p>Durak Online has a leaderboard where you can rank up and earn rewards. The leaderboard is a list of players who have achieved the highest scores in Durak Online. You can see your own rank and score, as well as other players' ranks and scores. You can also see your statistics, such as your win rate, your average score, your best score, and your total games played. By playing more games and winning more points, you can improve your rank and score in Durak Online. You can also earn rewards such as coins, items, or badges based on your rank.</p>
- <h2>How to use Durak Online para hilesi android oyun club?</h2>
-<h3>Durak Online para hilesi android oyun club is a cheat tool that can generate unlimited coins and items for Durak Online</h3>
-<p>Durak Online para hilesi android oyun club is a cheat tool that can generate unlimited coins and items for Durak Online. Durak Online para hilesi android oyun club is a website that offers a hack for Durak Online that can give you access to unlimited resources in the game. By using this hack, you can get as many coins and items as you want without spending any real money. Durak Online para hilesi android oyun club is a great way to enhance your gaming experience and enjoy Durak Online more.</p>
-<h3>Durak Online para hilesi android oyun club is easy to use and does not require root or jailbreak</h3>
-<p>Durak Online para hilesi android oyun club is easy to use and does not require root or jailbreak. Durak Online para hilesi android oyun club is a web-based tool that works on any browser and device. You do not need to download or install anything on your device, or to modify your system settings. All you need to do is to visit the website, enter your username or email, select the amount of coins and items you want, and click on the generate button. The hack will then process your request and transfer the resources to your account in a few minutes.</p>
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-<p>Durak Online para hilesi android oyun club is safe and undetectable by the game developers. Durak Online para hilesi android oyun club uses advanced encryption and proxy servers to protect your account and data from any harm or detection. Durak Online para hilesi android oyun club also has a built-in anti-ban system that prevents your account from being banned or suspended by the game developers. Durak Online para hilesi android oyun club is tested and updated regularly to ensure its functionality and compatibility with the latest version of Durak Online.</p>
- <h2>Conclusion</h2>
-<h3>Durak Online is a fun and addictive card game that you can play online with real people</h3>
-<p>Durak Online is a fun and addictive card game that you can play online with real people. Durak Online is a modern version of the famous card game that originated in Russia and is also popular in Turkey. Durak Online has different modes and settings that you can choose from, such as flip-flop, transferable, or classic. Durak Online has great 3D graphics, realistic sounds, smooth animations, and no intrusive ads. Durak Online is a free app that you can download from Google Play for your Android device.</p>
-<h3>Durak Online can help you improve your skills, strategy, and luck in card games</h3>
-<p>Durak Online can help you improve your skills, strategy, and luck in card games. Durak Online is a card game that involves skill, strategy, and luck. The objective of Durak Online is to get rid of all your cards before your opponents do. The rules of Durak Online are simple and easy to learn, but the game is challenging and exciting. The tips and tricks of Durak Online are to use your trumps wisely, to throw-in more cards, and to be aware of your opponents' cards. By playing more games and winning more points, you can improve your rank and score in Durak Online.</p>
-<h3>Durak Online para hilesi android oyun club can help you get more coins and items to enhance your gaming experience</h3>
-<p>Durak Online para hilesi android oyun club can help you get more coins and items to enhance your gaming experience. Durak Online para hilesi android oyun club is a cheat tool that can generate unlimited coins and items for Durak Online. By using this hack, you can get as many coins and items as you want without spending any real money. You can use these coins and items to enter games, buy items, or exchange for real money. You can also use these coins and items to send and receive gifts with other players, or to compete in the championship mode for prizes.</p>
- <h2>FAQs</h2>
-<h4>Q: What is the best way to learn how to play Durak Online?</h4>
-<p>A: The best way to learn how to play Durak Online is to watch the tutorial videos in the app, or to play against bots in the offline mode. You can also read the rules of the game in the app, or ask other players for advice in the chat.</p>
-<h4>Q: How can I get more coins and items in Durak Online without using Durak Online para hilesi android oyun club?</h4>
-<p>A: You can get more coins and items in Durak Online without using Durak Online para hilesi android oyun club by completing daily tasks, watching ads, inviting friends, or winning games.</p>
-<h4>Q: Is Durak Online para hilesi android oyun club legal?</h4>
-<p>A: Durak Online para hilesi android oyun club is not legal, as it violates the terms of service of Durak Online. Using this hack may result in your account being banned or suspended by the game developers. We do not recommend using this hack, as it may ruin the fun and fairness of the game.</p>
-<h4>Q: How can I contact the support team of Durak Online if I have any issues or questions?</h4>
-<p>A: You can contact the support team of Durak Online by sending an email to [email protected], or by filling out the feedback form in the app. You can also visit the official website of Durak Online at www.durakonline.com, or follow their social media accounts on Facebook, Twitter, and Instagram.</p>
-<h4>Q: Can I play Durak Online on other devices besides Android?</h4>
-<p>A: Yes, you can play Durak Online on other devices besides Android. Durak Online is also available on iOS, Windows, and Mac devices. You can download the app from the App Store, the Microsoft Store, or the official website of Durak Online. You can also play Durak Online on your browser by visiting www.durakonline.com.</p> 401be4b1e0<br />
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spaces/1phancelerku/anime-remove-background/Como baixar e instalar bhop pro no seu computador com BlueStacks.md DELETED Viewed

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-<h1>How to Download and Play Bhop Pro on Your PC or Mobile Device</h1>
-<p>If you are a fan of Counter-Strike or other first-person shooter games, you might have heard of or tried the bunny hop technique. This is a skill that allows you to move faster and more unpredictably by jumping and strafing in the air. It can give you an edge over your opponents in competitive matches, or simply make you feel like a pro.</p>
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-<p>Bhop Pro is a game that can be played on both PC and mobile devices. Depending on your preference and convenience, you can enjoy different benefits of playing Bhop Pro on each platform. Some of these benefits are:</p>
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-<h1>Conflict of Nations World War 3 Mod Apk: What You Need to Know</h1>
-<p>If you are a fan of modern military-themed strategy games, you might have heard of Conflict of Nations World War 3, a real-time strategy game that lets you take control of the armed forces of your nation and compete with other players for global dominance. But did you know that there is a mod apk version of this game that can give you unlimited gold, resources, or other benefits? In this article, we will tell you what you need to know about Conflict of Nations World War 3 mod apk, how to download and install it, how to play it, and some tips and tricks to help you win the war.</p>
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-<h3>A real-time strategy game set in modern global conflicts</h3>
-<p>Conflict of Nations World War 3 is a game developed by Dorado Games and Bytro Labs that simulates modern global conflicts in a realistic and immersive way. You can choose from almost every nation in the world and lead its military expansion, technological research, and economic development. You can also join or create coalitions with other players and wage total war on the battlefields of World War 3.</p>
-<h3>A game that requires strategic planning, diplomacy, and resource management</h3>
-<p>Conflict of Nations World War 3 is not a game for the faint-hearted. It requires strategic planning, diplomacy, and resource management to succeed. You have to balance your military power with your economic efficiency, your technological superiority with your moral stability, and your offensive capabilities with your defensive measures. You also have to deal with other players who may be your allies or enemies, depending on the situation. You have to communicate, negotiate, trade, spy, sabotage, or attack them as you see fit.</p>
-<h3>A game that offers different military doctrines, nations, and scenarios</h3>
-<p>Conflict of Nations World War 3 offers a variety of options for customization and replayability. You can choose from three different military doctrines: Western, Eastern, or European. Each doctrine has its own advantages and disadvantages, as well as its own technology tree and iconic units. You can also choose from different nations, each with its own unique traits, map location, and map size. You can also join different scenarios, ranging from the cold war to modern global conflicts to terrorist insurgencies.</p>
-<h2>What is a mod apk?</h2>
-<h3>A modified version of an Android application</h3>
-<p>A mod apk is a modified version of an Android application that has been altered by someone other than the original developer. A mod apk can offer features or functions that are not available in the official version of the application. For example, a mod apk for Conflict of Nations World War 3 can give you unlimited gold, resources, or other advantages that can help you dominate the game.</p>
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-<p>One of the main reasons why some players look for a mod apk for Conflict of Nations World War 3 is to get unlimited gold, resources, or other advantages. Gold is the premium currency of the game that can be used to speed up research, construction, or recruitment. Resources are the basic materials that are needed to build and maintain your army and economy. Other advantages can include unlocking all units and technologies, increasing your morale and stability, or disabling ads and pop-ups.</p>
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-<p>However, a mod apk for Conflict of Nations World War 3 can also pose risks such as malware, bans, or legal issues. Malware is a malicious software that can harm your device or steal your personal information. Bans are the penalties that the game developers or moderators can impose on players who violate the game rules or terms of service. Legal issues are the potential lawsuits or fines that the game developers or owners can file against players who infringe their intellectual property rights or damage their reputation.</p>
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-<h3>Find a reliable source for the mod apk file</h3>
-<p>The first step to download and install Conflict of Nations World War 3 mod apk is to find a reliable source for the mod apk file. You can search online for websites or forums that offer mod apk files for various games. However, you have to be careful and cautious when choosing a source, as some of them may contain viruses, malware, or fake files. You can check the reviews, ratings, comments, or feedback from other users to verify the credibility and safety of the source.</p>
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-<p>The second step to download and install Conflict of Nations World War 3 mod apk is to enable unknown sources on your device settings. This is because most Android devices do not allow the installation of applications from sources other than the official Google Play Store. To enable unknown sources, you have to go to your device settings, then security, then unknown sources, and then toggle it on. You may also have to grant some permissions or accept some warnings before proceeding.</p>
-<h3>Download and install the mod apk file</h3>
-<p>The third step to download and install Conflict of Nations World War 3 mod apk is to download and install the mod apk file. You can do this by clicking on the download link or button from the source website or forum. You may have to wait for a few seconds or minutes for the download to complete. After that, you can open the downloaded file and follow the instructions to install it on your device. You may have to overwrite or uninstall the original version of the game before installing the mod apk version.</p>
-<h2>How to play Conflict of Nations World War 3 mod apk?</h2>
-<h3>Choose your nation and doctrine</h3>
-<p>The first step to play Conflict of Nations World War 3 mod apk is to choose your nation and doctrine. You can select from almost every nation in the world and lead its military expansion, technological research, and economic development. You can also choose from three different military doctrines: Western, Eastern, or European. Each doctrine has its own advantages and disadvantages, as well as its own technology tree and iconic units.</p>
-<h3>Build your army and economy</h3>
-<p>The second step to play Conflict of Nations World War 3 mod apk is to build your army and economy. You have to balance your military power with your economic efficiency, your technological superiority with your moral stability, and your offensive capabilities with your defensive measures. You have to produce and manage resources such as oil, food, metal, rare earths, components, money, manpower, and electricity. You also have to research and upgrade your units and technologies such as infantry, tanks, aircraft, ships, submarines, missiles, drones, satellites, nuclear weapons, and more.</p>
-<h3>Form alliances and wage war</h3>
-<p>The third step to play Conflict of Nations World War 3 mod apk is to form alliances and wage war. You can join or create coalitions with other players and cooperate or compete with them for global dominance. You can also communicate, negotiate, trade, spy, sabotage, or attack other players as you see fit. You have to use diplomacy and communication wisely, as your actions and words can have consequences. You also have to be prepared for the challenges and threats that may arise from the dynamic and unpredictable world of World War 3.</p>
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-<h3>Know your nation's strengths and weaknesses</h3>
-<p>One of the tips and tricks for Conflict of Nations World War 3 mod apk is to know your nation's strengths and weaknesses. Each nation has its own unique traits, map location, and map size that can affect its performance and strategy. For example, some nations have access to more resources, some have better geographical advantages, some have stronger military units, and some have faster research speed. You have to use your nation's strengths to your advantage and compensate for its weaknesses.</p>
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-<p>Another tip and trick for Conflict of Nations World War 3 mod apk is to research and upgrade your units and technologies. You have to invest in your technological development to gain an edge over your enemies. You have to research new units and technologies that can improve your military capabilities, such as stealth, precision, mobility, range, firepower, defense, or intelligence. You also have to upgrade your existing units and technologies to enhance their performance and efficiency.</p>
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-<p>A final tip and trick for Conflict of Nations World War 3 mod apk is to use diplomacy and communication wisely. You have to interact with other players in a smart and respectful way. You have to communicate your intentions, needs, and expectations clearly and honestly. You have to negotiate fair and beneficial deals with your allies or enemies. You have to spy on your rivals or enemies to gather information or disrupt their plans. You also have to avoid unnecessary conflicts or provocations that can damage your reputation or relationships.</p>
-<h2>Conclusion</h2>
-<p>Conflict of Nations World War 3 mod apk is a modified version of an Android application that can offer unlimited gold, resources, or other advantages for the game Conflict of Nations World War 3, a real-time strategy game that simulates modern global conflicts in a realistic and immersive way. However, it can also pose risks such as malware, bans, or legal issues. To download and install it, you have to find a reliable source for the mod apk file, enable unknown sources on your device settings, and download and install the mod apk file. To play it, you have to choose your nation and doctrine, build your army and economy, and form alliances and wage war. To win the war, you have to know your nation's strengths and weaknesses, research and upgrade your units and technologies, and use diplomacy and communication wisely.</p>
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-<li><b>What is the difference between Conflict of Nations World War 3 mod apk and the official version?</b></li>
-<p>The main difference between Conflict of Nations World War 3 mod apk and the official version is that the mod apk version can offer unlimited gold, resources, or other advantages that are not available in the official version.</p>
-<li><b>Is Conflict of Nations World War 3 mod apk safe to use?</b></li>
-<p>Conflict of Nations World War 3 mod apk is not completely safe to use. It can pose risks such as malware, bans, or legal issues. Therefore, you should use it at your own risk and discretion.</p>
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-<p>You can get more gold in Conflict of Nations World War 3 mod apk by using the unlimited gold feature that the mod apk version offers. Alternatively, you can also get more gold by completing missions, achievements, or participating in events in the game.</p>
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-<p>No, you cannot play Conflict of Nations World War 3 mod apk offline. The game requires an internet connection to run and sync with the servers and other players.</p>
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-<p>Yes, you can play Conflict of Nations World War 3 mod apk with your friends. You can join or create coalitions with your friends and cooperate or compete with them for global dominance. You can also chat, trade, or fight with them in the game.</p>
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-<p>Zack Tabudlo is a young and talented singer-songwriter from Manila, Philippines. He started his music career at the age of 11, when he joined a reality TV show called <em>Star Circle Quest</em>. Since then, he has released several songs, such as <em>Binibini</em>, <em>Hindi Ko Kaya</em>, <em>Lost</em>, and <em>Heart Can't Lose</em>. He is also known for his covers of popular songs, such as <em>Driver's License</em> by Olivia Rodrigo, <em>Blinding Lights</em> by The Weeknd, and <em>Dynamite</em> by BTS.</p>
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-<p>Tank Hero is a 2D side-scrolling tank game developed by UP STUDIO. The game has over 120 levels, 3 unique environments, 5 weapons, and 5 types of AI tanks to fight against. You can also play online with other players in multiplayer mode. The game is simple to control: just drag to move and release to fire. You can also choose from different firing options, such as single shot, double shot, triple shot, etc. The game is fun and addictive, as you have to use your strategy and skills to defeat the enemies and clear the levels.</p>
-<h2>download game tank hero mod apk</h2><br /><p><b><b>Download</b> &mdash;&mdash;&mdash; <a href="https://jinyurl.com/2uNSeV">https://jinyurl.com/2uNSeV</a></b></p><br /><br />
- <h2>Features of Tank Hero</h2>
-<p>Some of the features that make Tank Hero stand out are:</p>
-<ul>
-<li><b>Awesome graphics and sound effects:</b> The game has colorful and cartoonish graphics that suit the arcade style. The sound effects are also realistic and immersive, making you feel like you are in a real tank battle.</li>
-<li><b>Various tanks and weapons:</b> You can collect and upgrade different tanks and weapons in the game. Each tank has its own characteristics, such as speed, armor, fire rate, etc. Each weapon also has its own effects, such as fireball, laser, missile, etc. You can mix and match different tanks and weapons to suit your play style.</li>
-<li><b>Unique talents:</b> You can also unlock and use over 100 talents in the game. Talents are special abilities that can boost your firepower, defense, speed, or other aspects. You can choose from random talents or customize your own talent combination.</li>
-</ul>
- <h2>How to download and install Tank Hero mod apk</h2>
-<p>If you want to enjoy more features and benefits in Tank Hero, you can download the mod apk version of the game. The mod apk version will give you unlimited money, god mode, one hit kill, and other features that will make the game easier and more fun. Here are the steps to download and install Tank Hero mod apk:</p>
-<ol>
-<li>Go to [this link](^1^) or [this link](^2^) or [this link](^3^) to download the Tank Hero mod apk file.</li>
-<li>After downloading the file, go to your device settings and enable the installation of unknown sources.</li>
-<li>Locate the downloaded file in your file manager and tap on it to install it.</li>
-<li>Wait for the installation to finish and then launch the game.</li>
-<li>Enjoy playing Tank Hero with unlimited money, god mode, one hit kill, and other features.</li>
-</ol>
- <h2>Tips and tricks to master Tank Hero</h2>
-<p>If you want to become a tank hero yourself, here are some tips and tricks that will help you improve your skills and performance in the game:</p>
- <h3>Choose the right tank and weapon for each level</h3>
-<p>As mentioned earlier, each tank and weapon has its own advantages and disadvantages. You should choose the ones that suit the level's difficulty, terrain, enemies, and objectives. For example, if the level has many obstacles or narrow spaces, you might want to use a fast tank with a laser weapon that can penetrate through walls. If the level has many enemies or bosses, you might want to use a tank with a tank with high armor and a fireball weapon that can deal splash damage. You can also switch tanks and weapons during the level if you find a better option.</p>
- <h3>Upgrade your tank and skills regularly</h3>
-<p>As you progress in the game, you will earn money and experience that you can use to upgrade your tank and skills. Upgrading your tank will increase its stats, such as speed, armor, fire rate, etc. Upgrading your skills will unlock new talents or improve the existing ones. You should always upgrade your tank and skills whenever you can, as they will make a big difference in your performance and survival.</p>
- <h3>Use the terrain and obstacles to your advantage</h3>
-<p>The game has various terrains and obstacles that can affect the gameplay. For example, some terrains can slow you down or speed you up, some obstacles can block your shots or reflect them, some items can heal you or give you extra ammo, etc. You should always be aware of your surroundings and use them to your advantage. For example, you can hide behind walls or rocks to avoid enemy fire, you can bounce your shots off walls or mirrors to hit enemies from different angles, you can use speed boosts or ramps to escape or chase enemies, etc.</p>
- <h2>Conclusion</h2>
-<p>Tank Hero is a fun and addictive tank game that will keep you entertained for hours. You can download the mod apk version of Tank Hero and enjoy unlimited money, god mode, one hit kill, and other features that will make the game easier and more fun. You can also follow our tips and tricks to master the game and become a tank hero yourself. So what are you waiting for? Download Tank Hero mod apk now and start blasting your enemies!</p>
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-<p>Here are some frequently asked questions about Tank Hero mod apk:</p>
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-<li><b>Q: Is Tank Hero mod apk safe to download and install?</b></li>
-<li>A: Yes, Tank Hero mod apk is safe to download and install. It does not contain any viruses or malware that can harm your device. However, you should always download it from a trusted source and enable the installation of unknown sources in your device settings.</li>
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spaces/AHzizi/WaifuVoiceGen/app.py DELETED Viewed

@@ -1,264 +0,0 @@
-# coding=utf-8
-import os
-import re
-import argparse
-import utils
-import commons
-import json
-import torch
-import gradio as gr
-from models import SynthesizerTrn
-from text import text_to_sequence, _clean_text
-from torch import no_grad, LongTensor
-import gradio.processing_utils as gr_processing_utils
-import logging
-logging.getLogger('numba').setLevel(logging.WARNING)
-limitation = os.getenv("SYSTEM") == "spaces"  # limit text and audio length in huggingface spaces
-hps_ms = utils.get_hparams_from_file(r'config/config.json')
-audio_postprocess_ori = gr.Audio.postprocess
-def audio_postprocess(self, y):
-    data = audio_postprocess_ori(self, y)
-    if data is None:
-        return None
-    return gr_processing_utils.encode_url_or_file_to_base64(data["name"])
-gr.Audio.postprocess = audio_postprocess
-def get_text(text, hps, is_symbol):
-    text_norm, clean_text = text_to_sequence(text, hps.symbols, [] if is_symbol else hps.data.text_cleaners)
-    if hps.data.add_blank:
-        text_norm = commons.intersperse(text_norm, 0)
-    text_norm = LongTensor(text_norm)
-    return text_norm, clean_text
-def create_tts_fn(net_g_ms, speaker_id):
-    def tts_fn(text, language, noise_scale, noise_scale_w, length_scale, is_symbol):
-        text = text.replace('\n', ' ').replace('\r', '').replace(" ", "")
-        if limitation:
-            text_len = len(re.sub("\[([A-Z]{2})\]", "", text))
-            max_len = 100
-            if is_symbol:
-                max_len *= 3
-            if text_len > max_len:
-                return "Error: Text is too long", None
-        if not is_symbol:
-            if language == 0:
-                text = f"[ZH]{text}[ZH]"
-            elif language == 1:
-                text = f"[JA]{text}[JA]"
-            else:
-                text = f"{text}"
-        stn_tst, clean_text = get_text(text, hps_ms, is_symbol)
-        with no_grad():
-            x_tst = stn_tst.unsqueeze(0).to(device)
-            x_tst_lengths = LongTensor([stn_tst.size(0)]).to(device)
-            sid = LongTensor([speaker_id]).to(device)
-            audio = net_g_ms.infer(x_tst, x_tst_lengths, sid=sid, noise_scale=noise_scale, noise_scale_w=noise_scale_w,
-                                   length_scale=length_scale)[0][0, 0].data.cpu().float().numpy()
-        return "Success", (22050, audio)
-    return tts_fn
-def create_to_symbol_fn(hps):
-    def to_symbol_fn(is_symbol_input, input_text, temp_lang):
-        if temp_lang == 0:
-            clean_text = f'[ZH]{input_text}[ZH]'
-        elif temp_lang == 1:
-            clean_text = f'[JA]{input_text}[JA]'
-        else:
-            clean_text = input_text
-        return _clean_text(clean_text, hps.data.text_cleaners) if is_symbol_input else ''
-    return to_symbol_fn
-def change_lang(language):
-    if language == 0:
-        return 0.6, 0.668, 1.2
-    elif language == 1:
-        return 0.6, 0.668, 1
-    else:
-        return 0.6, 0.668, 1
-download_audio_js = """
-() =>{{
-    let root = document.querySelector("body > gradio-app");
-    if (root.shadowRoot != null)
-        root = root.shadowRoot;
-    let audio = root.querySelector("#tts-audio-{audio_id}").querySelector("audio");
-    let text = root.querySelector("#input-text-{audio_id}").querySelector("textarea");
-    if (audio == undefined)
-        return;
-    text = text.value;
-    if (text == undefined)
-        text = Math.floor(Math.random()*100000000);
-    audio = audio.src;
-    let oA = document.createElement("a");
-    oA.download = text.substr(0, 20)+'.wav';
-    oA.href = audio;
-    document.body.appendChild(oA);
-    oA.click();
-    oA.remove();
-}}
-"""
-if __name__ == '__main__':
-    parser = argparse.ArgumentParser()
-    parser.add_argument('--device', type=str, default='cpu')
-    parser.add_argument('--api', action="store_true", default=False)
-    parser.add_argument("--share", action="store_true", default=False, help="share gradio app")
-    args = parser.parse_args()
-    device = torch.device(args.device)
-    models = []
-    with open("pretrained_models/info.json", "r", encoding="utf-8") as f:
-        models_info = json.load(f)
-    for i, info in models_info.items():
-        if not info['enable']:
-            continue
-        sid = info['sid']
-        name_en = info['name_en']
-        name_zh = info['name_zh']
-        title = info['title']
-        cover = f"pretrained_models/{i}/{info['cover']}"
-        example = info['example']
-        language = info['language']
-        net_g_ms = SynthesizerTrn(
-            len(hps_ms.symbols),
-            hps_ms.data.filter_length // 2 + 1,
-            hps_ms.train.segment_size // hps_ms.data.hop_length,
-            n_speakers=hps_ms.data.n_speakers if info['type'] == "multi" else 0,
-            **hps_ms.model)
-        utils.load_checkpoint(f'pretrained_models/{i}/{i}.pth', net_g_ms, None)
-        _ = net_g_ms.eval().to(device)
-        models.append((sid, name_en, name_zh, title, cover, example, language, net_g_ms, create_tts_fn(net_g_ms, sid), create_to_symbol_fn(hps_ms)))
-    with gr.Blocks() as app:
-        gr.Markdown(
-            "# <center> vits-models\n"
-            "## <center> Please do not generate content that could infringe upon the rights or cause harm to individuals or organizations.\n"
-            "## <center> ·请不要生成会对个人以及组织造成侵害的内容\n"
-            "![visitor badge](https://visitor-badge.glitch.me/badge?page_id=sayashi.vits-models)\n\n"
-            "[Open In Colab]"
-            "(https://colab.research.google.com/drive/10QOk9NPgoKZUXkIhhuVaZ7SYra1MPMKH?usp=share_link)"
-            " without queue and length limitation.(无需等待队列，并且没有长度限制)\n\n"
-            "[Finetune your own model](https://github.com/SayaSS/vits-finetuning)"
-        )
-        with gr.Tabs():
-            with gr.TabItem("EN"):
-                for (sid, name_en, name_zh, title, cover, example, language, net_g_ms, tts_fn, to_symbol_fn) in models:
-                    with gr.TabItem(name_en):
-                        with gr.Row():
-                            gr.Markdown(
-                                '<div align="center">'
-                                f'<a><strong>{title}</strong></a>'
-                                f'<img style="width:auto;height:300px;" src="file/{cover}">' if cover else ""
-                                '</div>'
-                            )
-                        with gr.Row():
-                            with gr.Column():
-                                input_text = gr.Textbox(label="Text (100 words limitation)" if limitation else "Text", lines=5, value=example, elem_id=f"input-text-en-{name_en.replace(' ','')}")
-                                lang = gr.Dropdown(label="Language", choices=["Chinese", "Japanese", "Mix（wrap the Chinese text with [ZH][ZH], wrap the Japanese text with [JA][JA]）"],
-                                            type="index", value=language)
-                                with gr.Accordion(label="Advanced Options", open=False):
-                                    symbol_input = gr.Checkbox(value=False, label="Symbol input")
-                                    symbol_list = gr.Dataset(label="Symbol list", components=[input_text],
-                                                             samples=[[x] for x in hps_ms.symbols])
-                                    symbol_list_json = gr.Json(value=hps_ms.symbols, visible=False)
-                                btn = gr.Button(value="Generate", variant="primary")
-                                with gr.Row():
-                                    ns = gr.Slider(label="noise_scale", minimum=0.1, maximum=1.0, step=0.1, value=0.6, interactive=True)
-                                    nsw = gr.Slider(label="noise_scale_w", minimum=0.1, maximum=1.0, step=0.1, value=0.668, interactive=True)
-                                    ls = gr.Slider(label="length_scale", minimum=0.1, maximum=2.0, step=0.1, value=1.2 if language=="Chinese" else 1, interactive=True)
-                            with gr.Column():
-                                o1 = gr.Textbox(label="Output Message")
-                                o2 = gr.Audio(label="Output Audio", elem_id=f"tts-audio-en-{name_en.replace(' ','')}")
-                                download = gr.Button("Download Audio")
-                            btn.click(tts_fn, inputs=[input_text, lang,  ns, nsw, ls, symbol_input], outputs=[o1, o2], api_name=f"tts-{name_en}")
-                            download.click(None, [], [], _js=download_audio_js.format(audio_id=f"en-{name_en.replace(' ', '')}"))
-                            lang.change(change_lang, inputs=[lang], outputs=[ns, nsw, ls])
-                            symbol_input.change(
-                                to_symbol_fn,
-                                [symbol_input, input_text, lang],
-                                [input_text]
-                            )
-                            symbol_list.click(None, [symbol_list, symbol_list_json], [input_text],
-                                              _js=f"""
-                            (i,symbols) => {{
-                                let root = document.querySelector("body > gradio-app");
-                                if (root.shadowRoot != null)
-                                    root = root.shadowRoot;
-                                let text_input = root.querySelector("#input-text-en-{name_en.replace(' ', '')}").querySelector("textarea");
-                                let startPos = text_input.selectionStart;
-                                let endPos = text_input.selectionEnd;
-                                let oldTxt = text_input.value;
-                                let result = oldTxt.substring(0, startPos) + symbols[i] + oldTxt.substring(endPos);
-                                text_input.value = result;
-                                let x = window.scrollX, y = window.scrollY;
-                                text_input.focus();
-                                text_input.selectionStart = startPos + symbols[i].length;
-                                text_input.selectionEnd = startPos + symbols[i].length;
-                                text_input.blur();
-                                window.scrollTo(x, y);
-                                return text_input.value;
-                            }}""")
-            with gr.TabItem("中文"):
-                for (sid, name_en, name_zh, title, cover, example, language,  net_g_ms, tts_fn, to_symbol_fn) in models:
-                    with gr.TabItem(name_zh):
-                        with gr.Row():
-                            gr.Markdown(
-                                '<div align="center">'
-                                f'<a><strong>{title}</strong></a>'
-                                f'<img style="width:auto;height:300px;" src="file/{cover}">' if cover else ""
-                                '</div>'
-                            )
-                        with gr.Row():
-                            with gr.Column():
-                                input_text = gr.Textbox(label="文本 (100字上限)" if limitation else "文本", lines=5, value=example, elem_id=f"input-text-zh-{name_zh}")
-                                lang = gr.Dropdown(label="语言", choices=["中文", "日语", "中日混合（中文用[ZH][ZH]包裹起来，日文用[JA][JA]包裹起来）"],
-                                            type="index", value="中文"if language == "Chinese" else "日语")
-                                with gr.Accordion(label="高级选项", open=False):
-                                    symbol_input = gr.Checkbox(value=False, label="符号输入")
-                                    symbol_list = gr.Dataset(label="符号列表", components=[input_text],
-                                                             samples=[[x] for x in hps_ms.symbols])
-                                    symbol_list_json = gr.Json(value=hps_ms.symbols, visible=False)
-                                btn = gr.Button(value="生成", variant="primary")
-                                with gr.Row():
-                                    ns = gr.Slider(label="控制感情变化程度", minimum=0.1, maximum=1.0, step=0.1, value=0.6, interactive=True)
-                                    nsw = gr.Slider(label="控制音素发音长度", minimum=0.1, maximum=1.0, step=0.1, value=0.668, interactive=True)
-                                    ls = gr.Slider(label="控制整体语速", minimum=0.1, maximum=2.0, step=0.1, value=1.2 if language=="Chinese" else 1, interactive=True)
-                            with gr.Column():
-                                o1 = gr.Textbox(label="输出信息")
-                                o2 = gr.Audio(label="输出音频", elem_id=f"tts-audio-zh-{name_zh}")
-                                download = gr.Button("下载音频")
-                            btn.click(tts_fn, inputs=[input_text, lang,  ns, nsw, ls, symbol_input], outputs=[o1, o2])
-                            download.click(None, [], [], _js=download_audio_js.format(audio_id=f"zh-{name_zh}"))
-                            lang.change(change_lang, inputs=[lang], outputs=[ns, nsw, ls])
-                            symbol_input.change(
-                                to_symbol_fn,
-                                [symbol_input, input_text, lang],
-                                [input_text]
-                            )
-                            symbol_list.click(None, [symbol_list, symbol_list_json], [input_text],
-                                              _js=f"""
-                            (i,symbols) => {{
-                                let root = document.querySelector("body > gradio-app");
-                                if (root.shadowRoot != null)
-                                    root = root.shadowRoot;
-                                let text_input = root.querySelector("#input-text-zh-{name_zh}").querySelector("textarea");
-                                let startPos = text_input.selectionStart;
-                                let endPos = text_input.selectionEnd;
-                                let oldTxt = text_input.value;
-                                let result = oldTxt.substring(0, startPos) + symbols[i] + oldTxt.substring(endPos);
-                                text_input.value = result;
-                                let x = window.scrollX, y = window.scrollY;
-                                text_input.focus();
-                                text_input.selectionStart = startPos + symbols[i].length;
-                                text_input.selectionEnd = startPos + symbols[i].length;
-                                text_input.blur();
-                                window.scrollTo(x, y);
-                                return text_input.value;
-                            }}""")
-    app.queue(concurrency_count=1, api_open=args.api).launch(share=args.share)

spaces/AIConsultant/MusicGen/audiocraft/modules/conv.py DELETED Viewed

@@ -1,243 +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.
-import math
-import typing as tp
-import warnings
-import torch
-from torch import nn
-from torch.nn import functional as F
-from torch.nn.utils import spectral_norm, weight_norm
-CONV_NORMALIZATIONS = frozenset(['none', 'weight_norm', 'spectral_norm',
-                                 'time_group_norm'])
-def apply_parametrization_norm(module: nn.Module, norm: str = 'none'):
-    assert norm in CONV_NORMALIZATIONS
-    if norm == 'weight_norm':
-        return weight_norm(module)
-    elif norm == 'spectral_norm':
-        return spectral_norm(module)
-    else:
-        # We already check was in CONV_NORMALIZATION, so any other choice
-        # doesn't need reparametrization.
-        return module
-def get_norm_module(module: nn.Module, causal: bool = False, norm: str = 'none', **norm_kwargs):
-    """Return the proper normalization module. If causal is True, this will ensure the returned
-    module is causal, or return an error if the normalization doesn't support causal evaluation.
-    """
-    assert norm in CONV_NORMALIZATIONS
-    if norm == 'time_group_norm':
-        if causal:
-            raise ValueError("GroupNorm doesn't support causal evaluation.")
-        assert isinstance(module, nn.modules.conv._ConvNd)
-        return nn.GroupNorm(1, module.out_channels, **norm_kwargs)
-    else:
-        return nn.Identity()
-def get_extra_padding_for_conv1d(x: torch.Tensor, kernel_size: int, stride: int,
-                                 padding_total: int = 0) -> int:
-    """See `pad_for_conv1d`."""
-    length = x.shape[-1]
-    n_frames = (length - kernel_size + padding_total) / stride + 1
-    ideal_length = (math.ceil(n_frames) - 1) * stride + (kernel_size - padding_total)
-    return ideal_length - length
-def pad_for_conv1d(x: torch.Tensor, kernel_size: int, stride: int, padding_total: int = 0):
-    """Pad for a convolution to make sure that the last window is full.
-    Extra padding is added at the end. This is required to ensure that we can rebuild
-    an output of the same length, as otherwise, even with padding, some time steps
-    might get removed.
-    For instance, with total padding = 4, kernel size = 4, stride = 2:
-        0 0 1 2 3 4 5 0 0   # (0s are padding)
-        1   2   3           # (output frames of a convolution, last 0 is never used)
-        0 0 1 2 3 4 5 0     # (output of tr. conv., but pos. 5 is going to get removed as padding)
-            1 2 3 4         # once you removed padding, we are missing one time step !
-    """
-    extra_padding = get_extra_padding_for_conv1d(x, kernel_size, stride, padding_total)
-    return F.pad(x, (0, extra_padding))
-def pad1d(x: torch.Tensor, paddings: tp.Tuple[int, int], mode: str = 'constant', value: float = 0.):
-    """Tiny wrapper around F.pad, just to allow for reflect padding on small input.
-    If this is the case, we insert extra 0 padding to the right before the reflection happen.
-    """
-    length = x.shape[-1]
-    padding_left, padding_right = paddings
-    assert padding_left >= 0 and padding_right >= 0, (padding_left, padding_right)
-    if mode == 'reflect':
-        max_pad = max(padding_left, padding_right)
-        extra_pad = 0
-        if length <= max_pad:
-            extra_pad = max_pad - length + 1
-            x = F.pad(x, (0, extra_pad))
-        padded = F.pad(x, paddings, mode, value)
-        end = padded.shape[-1] - extra_pad
-        return padded[..., :end]
-    else:
-        return F.pad(x, paddings, mode, value)
-def unpad1d(x: torch.Tensor, paddings: tp.Tuple[int, int]):
-    """Remove padding from x, handling properly zero padding. Only for 1d!"""
-    padding_left, padding_right = paddings
-    assert padding_left >= 0 and padding_right >= 0, (padding_left, padding_right)
-    assert (padding_left + padding_right) <= x.shape[-1]
-    end = x.shape[-1] - padding_right
-    return x[..., padding_left: end]
-class NormConv1d(nn.Module):
-    """Wrapper around Conv1d and normalization applied to this conv
-    to provide a uniform interface across normalization approaches.
-    """
-    def __init__(self, *args, causal: bool = False, norm: str = 'none',
-                 norm_kwargs: tp.Dict[str, tp.Any] = {}, **kwargs):
-        super().__init__()
-        self.conv = apply_parametrization_norm(nn.Conv1d(*args, **kwargs), norm)
-        self.norm = get_norm_module(self.conv, causal, norm, **norm_kwargs)
-        self.norm_type = norm
-    def forward(self, x):
-        x = self.conv(x)
-        x = self.norm(x)
-        return x
-class NormConv2d(nn.Module):
-    """Wrapper around Conv2d and normalization applied to this conv
-    to provide a uniform interface across normalization approaches.
-    """
-    def __init__(self, *args, norm: str = 'none', norm_kwargs: tp.Dict[str, tp.Any] = {}, **kwargs):
-        super().__init__()
-        self.conv = apply_parametrization_norm(nn.Conv2d(*args, **kwargs), norm)
-        self.norm = get_norm_module(self.conv, causal=False, norm=norm, **norm_kwargs)
-        self.norm_type = norm
-    def forward(self, x):
-        x = self.conv(x)
-        x = self.norm(x)
-        return x
-class NormConvTranspose1d(nn.Module):
-    """Wrapper around ConvTranspose1d and normalization applied to this conv
-    to provide a uniform interface across normalization approaches.
-    """
-    def __init__(self, *args, causal: bool = False, norm: str = 'none',
-                 norm_kwargs: tp.Dict[str, tp.Any] = {}, **kwargs):
-        super().__init__()
-        self.convtr = apply_parametrization_norm(nn.ConvTranspose1d(*args, **kwargs), norm)
-        self.norm = get_norm_module(self.convtr, causal, norm, **norm_kwargs)
-        self.norm_type = norm
-    def forward(self, x):
-        x = self.convtr(x)
-        x = self.norm(x)
-        return x
-class NormConvTranspose2d(nn.Module):
-    """Wrapper around ConvTranspose2d and normalization applied to this conv
-    to provide a uniform interface across normalization approaches.
-    """
-    def __init__(self, *args, norm: str = 'none', norm_kwargs: tp.Dict[str, tp.Any] = {}, **kwargs):
-        super().__init__()
-        self.convtr = apply_parametrization_norm(nn.ConvTranspose2d(*args, **kwargs), norm)
-        self.norm = get_norm_module(self.convtr, causal=False, norm=norm, **norm_kwargs)
-    def forward(self, x):
-        x = self.convtr(x)
-        x = self.norm(x)
-        return x
-class StreamableConv1d(nn.Module):
-    """Conv1d with some builtin handling of asymmetric or causal padding
-    and normalization.
-    """
-    def __init__(self, in_channels: int, out_channels: int,
-                 kernel_size: int, stride: int = 1, dilation: int = 1,
-                 groups: int = 1, bias: bool = True, causal: bool = False,
-                 norm: str = 'none', norm_kwargs: tp.Dict[str, tp.Any] = {},
-                 pad_mode: str = 'reflect'):
-        super().__init__()
-        # warn user on unusual setup between dilation and stride
-        if stride > 1 and dilation > 1:
-            warnings.warn("StreamableConv1d has been initialized with stride > 1 and dilation > 1"
-                          f" (kernel_size={kernel_size} stride={stride}, dilation={dilation}).")
-        self.conv = NormConv1d(in_channels, out_channels, kernel_size, stride,
-                               dilation=dilation, groups=groups, bias=bias, causal=causal,
-                               norm=norm, norm_kwargs=norm_kwargs)
-        self.causal = causal
-        self.pad_mode = pad_mode
-    def forward(self, x):
-        B, C, T = x.shape
-        kernel_size = self.conv.conv.kernel_size[0]
-        stride = self.conv.conv.stride[0]
-        dilation = self.conv.conv.dilation[0]
-        kernel_size = (kernel_size - 1) * dilation + 1  # effective kernel size with dilations
-        padding_total = kernel_size - stride
-        extra_padding = get_extra_padding_for_conv1d(x, kernel_size, stride, padding_total)
-        if self.causal:
-            # Left padding for causal
-            x = pad1d(x, (padding_total, extra_padding), mode=self.pad_mode)
-        else:
-            # Asymmetric padding required for odd strides
-            padding_right = padding_total // 2
-            padding_left = padding_total - padding_right
-            x = pad1d(x, (padding_left, padding_right + extra_padding), mode=self.pad_mode)
-        return self.conv(x)
-class StreamableConvTranspose1d(nn.Module):
-    """ConvTranspose1d with some builtin handling of asymmetric or causal padding
-    and normalization.
-    """
-    def __init__(self, in_channels: int, out_channels: int,
-                 kernel_size: int, stride: int = 1, causal: bool = False,
-                 norm: str = 'none', trim_right_ratio: float = 1.,
-                 norm_kwargs: tp.Dict[str, tp.Any] = {}):
-        super().__init__()
-        self.convtr = NormConvTranspose1d(in_channels, out_channels, kernel_size, stride,
-                                          causal=causal, norm=norm, norm_kwargs=norm_kwargs)
-        self.causal = causal
-        self.trim_right_ratio = trim_right_ratio
-        assert self.causal or self.trim_right_ratio == 1., \
-            "`trim_right_ratio` != 1.0 only makes sense for causal convolutions"
-        assert self.trim_right_ratio >= 0. and self.trim_right_ratio <= 1.
-    def forward(self, x):
-        kernel_size = self.convtr.convtr.kernel_size[0]
-        stride = self.convtr.convtr.stride[0]
-        padding_total = kernel_size - stride
-        y = self.convtr(x)
-        # We will only trim fixed padding. Extra padding from `pad_for_conv1d` would be
-        # removed at the very end, when keeping only the right length for the output,
-        # as removing it here would require also passing the length at the matching layer
-        # in the encoder.
-        if self.causal:
-            # Trim the padding on the right according to the specified ratio
-            # if trim_right_ratio = 1.0, trim everything from right
-            padding_right = math.ceil(padding_total * self.trim_right_ratio)
-            padding_left = padding_total - padding_right
-            y = unpad1d(y, (padding_left, padding_right))
-        else:
-            # Asymmetric padding required for odd strides
-            padding_right = padding_total // 2
-            padding_left = padding_total - padding_right
-            y = unpad1d(y, (padding_left, padding_right))
-        return y

spaces/AIConsultant/MusicGen/audiocraft/utils/best_state.py DELETED Viewed

@@ -1,81 +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 collections import defaultdict
-import logging
-import typing as tp
-import flashy
-import torch
-from ..optim import ModuleDictEMA
-from .utils import copy_state
-logger = logging.getLogger(__name__)
-class BestStateDictManager(flashy.state.StateDictSource):
-    """BestStateDictManager maintains a copy of best state_dict() for registered sources.
-    BestStateDictManager has two main attributes:
-        states (dict): State dict of the registered StateDictSource.
-        param_ids (dict): Dict of parameter ids for registered states from ModuleDictEMA and other sources.
-    When registering new sources, the BestStateDictManager will ensure two conflicting sources between
-    ModuleDictEMA and original modules are not both registered as it would otherwise create ambiguity about
-    what to consider for best state.
-    Args:
-        device (torch.device or str): Device on which we keep the copy.
-        dtype (torch.dtype): Data type for the state parameters.
-    """
-    def __init__(self, device: tp.Union[torch.device, str] = 'cpu',
-                 dtype: tp.Optional[torch.dtype] = None):
-        self.device = device
-        self.states: dict = {}
-        self.param_ids: dict = defaultdict(dict)
-        self.dtype = dtype
-    def _get_parameter_ids(self, state_dict):
-        return {id(p): name for name, p in state_dict.items() if isinstance(p, torch.Tensor)}
-    def _validate_no_parameter_ids_overlap(self, name: str, param_ids: dict):
-        for registered_name, registered_param_ids in self.param_ids.items():
-            if registered_name != name:
-                overlap = set.intersection(registered_param_ids.keys(), param_ids.keys())
-                assert len(overlap) == 0, f"Found {len(overlap)} / {len(param_ids.keys())} overlapping parameters"
-                f" in {name} and already registered {registered_name}: {' '.join(overlap)}"
-    def update(self, name: str, source: flashy.state.StateDictSource):
-        if name not in self.states:
-            raise ValueError(f"{name} missing from registered states.")
-        self.states[name] = copy_state(source.state_dict(), device=self.device, dtype=self.dtype)
-    def register(self, name: str, source: flashy.state.StateDictSource):
-        if name in self.states:
-            raise ValueError(f"{name} already present in states.")
-        # Registering parameter ids for EMA and non-EMA states allows us to check that
-        # there is no overlap that would create ambiguity about how to handle the best state
-        param_ids = self._get_parameter_ids(source.state_dict())
-        if isinstance(source, ModuleDictEMA):
-            logger.debug(f"Registering to best state: ModuleDictEMA '{name}' with {len(param_ids)} params")
-            self._validate_no_parameter_ids_overlap(name, param_ids)
-            self.param_ids[name] = param_ids
-        else:
-            logger.debug(f"Registering to best state: StateDictSource '{name}' with {len(param_ids)} params")
-            self._validate_no_parameter_ids_overlap('base', param_ids)
-            self.param_ids['base'].update(param_ids)
-        # Register state
-        self.states[name] = copy_state(source.state_dict(), device=self.device, dtype=self.dtype)
-    def state_dict(self) -> flashy.state.StateDict:
-        return self.states
-    def load_state_dict(self, state: flashy.state.StateDict):
-        for name, sub_state in state.items():
-            for k, v in sub_state.items():
-                self.states[name][k].copy_(v)

spaces/AIGC-Audio/AudioGPT/text_to_speech/utils/nn/schedulers.py DELETED Viewed

@@ -1,105 +0,0 @@
-import numpy as np
-class NoneSchedule(object):
-    def __init__(self, optimizer, lr):
-        self.optimizer = optimizer
-        self.constant_lr = lr
-        self.step(0)
-    def step(self, num_updates):
-        self.lr = self.constant_lr
-        for param_group in self.optimizer.param_groups:
-            param_group['lr'] = self.lr
-        return self.lr
-    def get_lr(self):
-        return self.optimizer.param_groups[0]['lr']
-    def get_last_lr(self):
-        return self.get_lr()
-class RSQRTSchedule(NoneSchedule):
-    def __init__(self, optimizer, lr, warmup_updates, hidden_size):
-        self.optimizer = optimizer
-        self.constant_lr = lr
-        self.warmup_updates = warmup_updates
-        self.hidden_size = hidden_size
-        self.lr = lr
-        for param_group in optimizer.param_groups:
-            param_group['lr'] = self.lr
-        self.step(0)
-    def step(self, num_updates):
-        constant_lr = self.constant_lr
-        warmup = min(num_updates / self.warmup_updates, 1.0)
-        rsqrt_decay = max(self.warmup_updates, num_updates) ** -0.5
-        rsqrt_hidden = self.hidden_size ** -0.5
-        self.lr = max(constant_lr * warmup * rsqrt_decay * rsqrt_hidden, 1e-6)
-        for param_group in self.optimizer.param_groups:
-            param_group['lr'] = self.lr
-        return self.lr
-class WarmupSchedule(NoneSchedule):
-    def __init__(self, optimizer, lr, warmup_updates):
-        self.optimizer = optimizer
-        self.constant_lr = self.lr = lr
-        self.warmup_updates = warmup_updates
-        for param_group in optimizer.param_groups:
-            param_group['lr'] = self.lr
-        self.step(0)
-    def step(self, num_updates):
-        constant_lr = self.constant_lr
-        warmup = min(num_updates / self.warmup_updates, 1.0)
-        self.lr = max(constant_lr * warmup, 1e-7)
-        for param_group in self.optimizer.param_groups:
-            param_group['lr'] = self.lr
-        return self.lr
-class CosineSchedule(NoneSchedule):
-    def __init__(self, optimizer, lr, warmup_updates, total_updates):
-        self.optimizer = optimizer
-        self.constant_lr = lr
-        self.warmup_updates = warmup_updates
-        self.total_updates = total_updates
-        self.lr = lr
-        self.assign_learning_rate(self.optimizer, self.lr)
-        self.step(0)
-    def assign_learning_rate(self, optimizer, new_lr):
-        for param_group in optimizer.param_groups:
-            param_group["lr"] = new_lr
-    def _warmup_lr(self, base_lr, warmup_length, step):
-        return base_lr * (step + 1) / warmup_length
-    def step(self, num_updates):
-        if num_updates < self.warmup_updates:
-            lr = self._warmup_lr(self.lr, self.warmup_updates, num_updates)
-        else:
-            e = num_updates - self.warmup_updates
-            es = self.total_updates - self.warmup_updates
-            lr = 0.5 * (1 + np.cos(np.pi * e / es)) * self.lr
-        self.assign_learning_rate(self.optimizer, lr)
-        return lr
-if __name__ == '__main__':
-    import numpy as np
-    import matplotlib.pyplot as plt
-    import torch
-    def plot_scheduler(scheduler, label=None):
-        y = np.array([scheduler.step(x) for x in range(0,160000, 10)])
-        x = np.arange(0,160000, 10)
-        plt.plot(x, y, label=label)
-    dummy_model = torch.nn.Linear(10,10)
-    dummy_optimizer = torch.optim.Adam(dummy_model.parameters())
-    rsqrt = CosineSchedule(dummy_optimizer, lr=0.0005, warmup_updates=10000, total_updates=160000)
-    plot_scheduler(rsqrt, "8000")
-    plt.savefig("0.png")

spaces/AbelKidane/headdetector/README.md DELETED Viewed

@@ -1,13 +0,0 @@
----
-title: Headdetector
-emoji: 🏆
-colorFrom: blue
-colorTo: green
-sdk: streamlit
-sdk_version: 1.25.0
-app_file: app.py
-pinned: false
-license: mit
----
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

spaces/Adapter/T2I-Adapter/ldm/modules/extra_condition/midas/api.py DELETED Viewed

@@ -1,175 +0,0 @@
-# based on https://github.com/isl-org/MiDaS
-import os
-import cv2
-import torch
-import torch.nn as nn
-from torchvision.transforms import Compose
-from ldm.modules.extra_condition.midas.midas.dpt_depth import DPTDepthModel
-from ldm.modules.extra_condition.midas.midas.midas_net import MidasNet
-from ldm.modules.extra_condition.midas.midas.midas_net_custom import MidasNet_small
-from ldm.modules.extra_condition.midas.midas.transforms import Resize, NormalizeImage, PrepareForNet
-ISL_PATHS = {
-    "dpt_large": "models/dpt_large-midas-2f21e586.pt",
-    "dpt_hybrid": "models/dpt_hybrid-midas-501f0c75.pt",
-    "midas_v21": "",
-    "midas_v21_small": "",
-}
-remote_model_path = "https://github.com/intel-isl/DPT/releases/download/1_0/dpt_hybrid-midas-501f0c75.pt"
-def disabled_train(self, mode=True):
-    """Overwrite model.train with this function to make sure train/eval mode
-    does not change anymore."""
-    return self
-def load_midas_transform(model_type):
-    # https://github.com/isl-org/MiDaS/blob/master/run.py
-    # load transform only
-    if model_type == "dpt_large":  # DPT-Large
-        net_w, net_h = 384, 384
-        resize_mode = "minimal"
-        normalization = NormalizeImage(mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5])
-    elif model_type == "dpt_hybrid":  # DPT-Hybrid
-        net_w, net_h = 384, 384
-        resize_mode = "minimal"
-        normalization = NormalizeImage(mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5])
-    elif model_type == "midas_v21":
-        net_w, net_h = 384, 384
-        resize_mode = "upper_bound"
-        normalization = NormalizeImage(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
-    elif model_type == "midas_v21_small":
-        net_w, net_h = 256, 256
-        resize_mode = "upper_bound"
-        normalization = NormalizeImage(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
-    else:
-        assert False, f"model_type '{model_type}' not implemented, use: --model_type large"
-    transform = Compose(
-        [
-            Resize(
-                net_w,
-                net_h,
-                resize_target=None,
-                keep_aspect_ratio=True,
-                ensure_multiple_of=32,
-                resize_method=resize_mode,
-                image_interpolation_method=cv2.INTER_CUBIC,
-            ),
-            normalization,
-            PrepareForNet(),
-        ]
-    )
-    return transform
-def load_model(model_type):
-    # https://github.com/isl-org/MiDaS/blob/master/run.py
-    # load network
-    model_path = ISL_PATHS[model_type]
-    if model_type == "dpt_large":  # DPT-Large
-        model = DPTDepthModel(
-            path=model_path,
-            backbone="vitl16_384",
-            non_negative=True,
-        )
-        net_w, net_h = 384, 384
-        resize_mode = "minimal"
-        normalization = NormalizeImage(mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5])
-    elif model_type == "dpt_hybrid":  # DPT-Hybrid
-        if not os.path.exists(model_path):
-            from basicsr.utils.download_util import load_file_from_url
-            load_file_from_url(remote_model_path, model_dir='models')
-        model = DPTDepthModel(
-            path=model_path,
-            backbone="vitb_rn50_384",
-            non_negative=True,
-        )
-        net_w, net_h = 384, 384
-        resize_mode = "minimal"
-        normalization = NormalizeImage(mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5])
-    elif model_type == "midas_v21":
-        model = MidasNet(model_path, non_negative=True)
-        net_w, net_h = 384, 384
-        resize_mode = "upper_bound"
-        normalization = NormalizeImage(
-            mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]
-        )
-    elif model_type == "midas_v21_small":
-        model = MidasNet_small(model_path, features=64, backbone="efficientnet_lite3", exportable=True,
-                               non_negative=True, blocks={'expand': True})
-        net_w, net_h = 256, 256
-        resize_mode = "upper_bound"
-        normalization = NormalizeImage(
-            mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]
-        )
-    else:
-        print(f"model_type '{model_type}' not implemented, use: --model_type large")
-        assert False
-    transform = Compose(
-        [
-            Resize(
-                net_w,
-                net_h,
-                resize_target=None,
-                keep_aspect_ratio=True,
-                ensure_multiple_of=32,
-                resize_method=resize_mode,
-                image_interpolation_method=cv2.INTER_CUBIC,
-            ),
-            normalization,
-            PrepareForNet(),
-        ]
-    )
-    return model.eval(), transform
-class MiDaSInference(nn.Module):
-    MODEL_TYPES_TORCH_HUB = [
-        "DPT_Large",
-        "DPT_Hybrid",
-        "MiDaS_small"
-    ]
-    MODEL_TYPES_ISL = [
-        "dpt_large",
-        "dpt_hybrid",
-        "midas_v21",
-        "midas_v21_small",
-    ]
-    def __init__(self, model_type):
-        super().__init__()
-        assert (model_type in self.MODEL_TYPES_ISL)
-        model, _ = load_model(model_type)
-        self.model = model
-        self.model.train = disabled_train
-    def forward(self, x):
-        # x in 0..1 as produced by calling self.transform on a 0..1 float64 numpy array
-        # NOTE: we expect that the correct transform has been called during dataloading.
-        with torch.no_grad():
-            prediction = self.model(x)
-            prediction = torch.nn.functional.interpolate(
-                prediction.unsqueeze(1),
-                size=x.shape[2:],
-                mode="bicubic",
-                align_corners=False,
-            )
-        assert prediction.shape == (x.shape[0], 1, x.shape[2], x.shape[3])
-        return prediction

spaces/AgentVerse/agentVerse/ui/src/phaser3-rex-plugins/templates/ui/basesizer/PushIntoBounds.js DELETED Viewed

@@ -1,15 +0,0 @@
-import GetViewport from '../../../plugins/utils/system/GetViewport.js';
-var PushIntoBounds = function (bounds) {
-    if (bounds === undefined) {
-        bounds = GetViewport(this.scene);
-    }
-    this.left = Math.max(this.left, bounds.left);
-    this.right = Math.min(this.right, bounds.right);
-    this.top = Math.max(this.top, bounds.top);
-    this.bottom = Math.min(this.bottom, bounds.bottom);
-    return this;
-}
-export default PushIntoBounds;

spaces/AgentVerse/agentVerse/ui/src/phaser3-rex-plugins/templates/ui/overlapsizer/GetChildrenWidth.js DELETED Viewed

@@ -1,19 +0,0 @@
-var GetChildrenWidth = function () {
-    if (this.rexSizer.hidden) {
-        return 0;
-    }
-    var result = 0;
-    var children = this.sizerChildren;
-    var child, padding, childWidth;
-    for (var key in children) {
-        child = children[key];
-        padding = child.rexSizer.padding;
-        childWidth = this.getChildWidth(child) + padding.left + padding.right;
-        result = Math.max(childWidth, result);
-    }
-    return result + this.space.left + this.space.right;
-}
-export default GetChildrenWidth;

spaces/AgentVerse/agentVerse/ui/src/phaser3-rex-plugins/templates/ui/sizer/ExpandMethods.js DELETED Viewed

@@ -1,11 +0,0 @@
-export default {
-    getChildExpand(gameObject) {
-        return this.getSizerConfig(gameObject).expand;
-    },
-    setChildExpand(gameObject, expand) {
-        this.getSizerConfig(gameObject).expand = expand;
-        return this;
-    },
-}

spaces/Al-Chan/Vits_League_of_Legends_Yuumi_TTS/text/symbols.py DELETED Viewed

@@ -1,76 +0,0 @@
-'''
-Defines the set of symbols used in text input to the model.
-'''
-# japanese_cleaners
-# _pad        = '_'
-# _punctuation = ',.!?-'
-# _letters = 'AEINOQUabdefghijkmnoprstuvwyzʃʧ↓↑ '
-'''# japanese_cleaners2
-_pad        = '_'
-_punctuation = ',.!?-~…'
-_letters = 'AEINOQUabdefghijkmnoprstuvwyzʃʧʦ↓↑ '
-'''
-'''# korean_cleaners
-_pad        = '_'
-_punctuation = ',.!?…~'
-_letters = 'ㄱㄴㄷㄹㅁㅂㅅㅇㅈㅊㅋㅌㅍㅎㄲㄸㅃㅆㅉㅏㅓㅗㅜㅡㅣㅐㅔ '
-'''
-'''# chinese_cleaners
-_pad        = '_'
-_punctuation = '，。！？—…'
-_letters = 'ㄅㄆㄇㄈㄉㄊㄋㄌㄍㄎㄏㄐㄑㄒㄓㄔㄕㄖㄗㄘㄙㄚㄛㄜㄝㄞㄟㄠㄡㄢㄣㄤㄥㄦㄧㄨㄩˉˊˇˋ˙ '
-'''
-# # zh_ja_mixture_cleaners
-# _pad        = '_'
-# _punctuation = ',.!?-~…'
-# _letters = 'AEINOQUabdefghijklmnoprstuvwyzʃʧʦɯɹəɥ⁼ʰ`→↓↑ '
-'''# sanskrit_cleaners
-_pad        = '_'
-_punctuation = '।'
-_letters = 'ँंःअआइईउऊऋएऐओऔकखगघङचछजझञटठडढणतथदधनपफबभमयरलळवशषसहऽािीुूृॄेैोौ्ॠॢ '
-'''
-'''# cjks_cleaners
-_pad        = '_'
-_punctuation = ',.!?-~…'
-_letters = 'NQabdefghijklmnopstuvwxyzʃʧʥʦɯɹəɥçɸɾβŋɦː⁼ʰ`^#*=→↓↑ '
-'''
-'''# thai_cleaners
-_pad        = '_'
-_punctuation = '.!? '
-_letters = 'กขฃคฆงจฉชซฌญฎฏฐฑฒณดตถทธนบปผฝพฟภมยรฤลวศษสหฬอฮฯะัาำิีึืุูเแโใไๅๆ็่้๊๋์'
-'''
-# # cjke_cleaners2
-_pad        = '_'
-_punctuation = ',.!?-~…'
-_letters = 'NQabdefghijklmnopstuvwxyzɑæʃʑçɯɪɔɛɹðəɫɥɸʊɾʒθβŋɦ⁼ʰ`^#*=ˈˌ→↓↑ '
-'''# shanghainese_cleaners
-_pad        = '_'
-_punctuation = ',.!?…'
-_letters = 'abdfghiklmnopstuvyzøŋȵɑɔɕəɤɦɪɿʑʔʰ̩̃ᴀᴇ15678 '
-'''
-'''# chinese_dialect_cleaners
-_pad        = '_'
-_punctuation = ',.!?~…─'
-_letters = '#Nabdefghijklmnoprstuvwxyzæçøŋœȵɐɑɒɓɔɕɗɘəɚɛɜɣɤɦɪɭɯɵɷɸɻɾɿʂʅʊʋʌʏʑʔʦʮʰʷˀː˥˦˧˨˩̥̩̃̚ᴀᴇ↑↓∅ⱼ '
-'''
-# Export all symbols:
-symbols = [_pad] + list(_punctuation) + list(_letters)
-# Special symbol ids
-SPACE_ID = symbols.index(" ")

spaces/AlbertoFH98/CastenaApp/utils.py DELETED Viewed

@@ -1,291 +0,0 @@
-# -- Utils .py file
-# -- Libraries
-from   typing                      import Any, Dict, List, Mapping, Optional
-from   pydantic                    import Extra, Field, root_validator
-from   langchain.llms.base         import LLM
-from   langchain.utils             import get_from_dict_or_env
-from   langchain.vectorstores      import Chroma
-from   langchain.text_splitter     import RecursiveCharacterTextSplitter
-from   langchain.chains            import RetrievalQA
-from   langchain.document_loaders  import TextLoader
-from   langchain.embeddings        import HuggingFaceEmbeddings
-from   googletrans                 import Translator
-import streamlit as st
-import together
-import textwrap
-import spacy
-import os
-import re
-os.environ["TOGETHER_API_KEY"] = "6101599d6e33e3bda336b8d007ca22e35a64c72cfd52c2d8197f663389fc50c5"
-# -- LLM class
-class TogetherLLM(LLM):
-    """Together large language models."""
-    model: str = "togethercomputer/llama-2-70b-chat"
-    """model endpoint to use"""
-    together_api_key: str = os.environ["TOGETHER_API_KEY"]
-    """Together API key"""
-    temperature: float = 0.7
-    """What sampling temperature to use."""
-    max_tokens: int = 512
-    """The maximum number of tokens to generate in the completion."""
-    class Config:
-        extra = Extra.forbid
-    @root_validator()
-    def validate_environment(cls, values: Dict) -> Dict:
-        """Validate that the API key is set."""
-        api_key = get_from_dict_or_env(
-            values, "together_api_key", "TOGETHER_API_KEY"
-        )
-        values["together_api_key"] = api_key
-        return values
-    @property
-    def _llm_type(self) -> str:
-        """Return type of LLM."""
-        return "together"
-    def clean_duplicates(self, transcription: str) -> str:
-      lines = transcription.strip().split('\n')
-      new_transcription = []
-      for linea in lines:
-          if linea.replace('CONTEXT:/n/n ', '').replace('/n', '') not in new_transcription and linea != '':
-              new_transcription.append(linea.replace('CONTEXT:/n/n ', '').replace('/n', ''))
-      # Create new transcription without duplicates
-      new_transcription = '\n\n'.join(new_transcription).replace("""<</SYS>>
-      """, """<</SYS>>
-      CONTEXT: """)
-      return new_transcription
-    def _call(
-        self,
-        prompt: str,
-        **kwargs: Any,
-    ) -> str:
-        """Call to Together endpoint."""
-        together.api_key = self.together_api_key
-        output = together.Complete.create(prompt,
-                                          model=self.model,
-                                          max_tokens=self.max_tokens,
-                                          temperature=self.temperature,
-                                          )
-        text = output['output']['choices'][0]['text']
-        cleaned_text = self.clean_duplicates(text)
-        return cleaned_text
-# -- Python function to setup basic features: translator, SpaCy pipeline and LLM model
-@st.cache_resource
-def setup_app(transcription_path, emb_model, model, _logger):
-    # -- Setup enviroment and features
-    translator = Translator(service_urls=['translate.googleapis.com'])
-    nlp        = spacy.load('es_core_news_lg')
-    _logger.info('Setup environment and features...')
-    # -- Setup LLM
-    together.api_key = os.environ["TOGETHER_API_KEY"]
-    # List available models and descriptons
-    models = together.Models.list()
-    # Set llama2 7b LLM
-    together.Models.start(model)
-    _logger.info('Setup environment and features - FINISHED!')
-    # -- Read translated transcription
-    _logger.info('Loading transcription...')
-    loader = TextLoader(transcription_path)
-    documents = loader.load()
-    # Splitting the text into chunks
-    text_splitter = RecursiveCharacterTextSplitter(chunk_size=1500, chunk_overlap=100)
-    texts = text_splitter.split_documents(documents)
-    _logger.info('Loading transcription - FINISHED!')
-    # -- Load embedding
-    _logger.info('Loading embedding...')
-    encode_kwargs = {'normalize_embeddings': True} # set True to compute cosine similarity
-    model_norm = HuggingFaceEmbeddings(
-        model_name=emb_model,
-        model_kwargs={'device': 'cpu'},
-        encode_kwargs=encode_kwargs
-    )
-    _logger.info('Loading embedding - FINISHED!')
-    # -- Create document database
-    _logger.info('Creating document database...')
-    # Embed and store the texts
-    # Supplying a persist_directory will store the embeddings on disk
-    persist_directory = 'db'
-    ## Here is the nmew embeddings being used
-    embedding = model_norm
-    vectordb = Chroma.from_documents(documents=texts,
-                                     embedding=embedding,
-                                     persist_directory=persist_directory)
-    # -- Make a retreiver
-    retriever = vectordb.as_retriever(search_type="similarity_score_threshold",
-                                      search_kwargs={"k": 5, "score_threshold": 0.5})
-    _logger.info('Creating document database - FINISHED!')
-    _logger.info('Setup finished!')
-    return translator, nlp, retriever
-# -- Function to get prompt template
-def get_prompt(instruction, system_prompt, b_sys, e_sys, b_inst, e_inst, _logger):
-    new_system_prompt = b_sys + system_prompt + e_sys
-    prompt_template   =  b_inst + new_system_prompt + instruction + e_inst
-    _logger.info('Prompt template created: {}'.format(instruction))
-    return prompt_template
-# -- Function to create the chain to answer questions
-@st.cache_resource
-def create_llm_chain(model, _retriever, _chain_type_kwargs, _logger):
-    _logger.info('Creating LLM chain...')
-    llm = TogetherLLM(
-        model= model,
-        temperature = 0.0,
-        max_tokens = 1024
-    )
-    qa_chain = RetrievalQA.from_chain_type(llm=llm,
-                                           chain_type="stuff",
-                                           retriever=_retriever,
-                                           chain_type_kwargs=_chain_type_kwargs,
-                                           return_source_documents=True)
-    _logger.info('Creating LLM chain - FINISHED!')
-    return qa_chain
-# -------------------------------------------
-# -- Auxiliar functions
-def translate_text(text, nlp, target_lang='en'):
-    # Traducir el texto sin los nombres propios
-    translator = Translator()
-    # Tokenizar el texto y encontrar nombres propios
-    doc = nlp(text)
-    named_entities = [ent.text for ent in doc if ent.pos_ == 'PROPN' and ent.dep_ in ['NNP', 'NN']]
-    named_entities_list = []
-    # Reemplazar los nombres propios con marcadores temporales
-    for entity in named_entities:
-        text = text.replace(entity, f'__{entity}__')
-        named_entities_list.append(entity)
-    translated_text = translator.translate(text, dest=target_lang).text
-    final_translated_text = []
-    i = 0
-    for text in translated_text.split(' '):
-      if '__' in text and len(named_entities_list):
-        final_translated_text.append(named_entities_list[i])
-        i+=1
-      else:
-        final_translated_text.append(text)
-    return ' '.join(final_translated_text)
-def wrap_text_preserve_newlines(text, width=110):
-    # Split the input text into lines based on newline characters
-    lines = text.split('\n')
-    # Wrap each line individually
-    wrapped_lines = [textwrap.fill(line, width=width) for line in lines]
-    # Join the wrapped lines back together using newline characters
-    wrapped_text = '\n'.join(wrapped_lines)
-    return wrapped_text
-def process_llm_response(llm_response, nlp):
-  response = llm_response['result']
-  return wrap_text_preserve_newlines(translate_text(response, nlp, target_lang='es'))
-def time_to_seconds(time_str):
-    parts = time_str.split(':')
-    hours, minutes, seconds = map(float, parts)
-    return int((hours * 3600) + (minutes * 60) + seconds)
-def add_hyperlink_and_convert_to_seconds(text):
-    time_pattern = r'(\d{2}:\d{2}:\d{2}(.\d{6})?)'
-    def replace_with_hyperlink(match):
-        time_str = match.group(1)
-        seconds = time_to_seconds(time_str)
-        link = f'<button type="button" class="button" onclick="seek({seconds})">{time_str}</button>'
-        return link
-    modified_text = re.sub(time_pattern, replace_with_hyperlink, text)
-    return modified_text
-# -- Streamlit HTML template
-def typewrite(text, youtube_video_url):
-    js = """var player, seconds = 0;
-            function onYouTubeIframeAPIReady() {
-                console.log("player");
-                player = new YT.Player('player', {
-                    events: {
-                      'onReady': onPlayerReady
-                    }
-                  });
-            }
-            function onPlayerReady(event) {
-                event.target.playVideo();
-            }
-            function seek(sec){
-                if(player){
-                    player.seekTo(sec, true);
-                }
-            }
-        """
-    css = """
-    .button {
-      background-color: transparent;
-      font-family: "Tahoma sans-serif;", monospace;
-      color: red;
-      font-weight: bold;
-      border: none;
-      text-align: center;
-      text-decoration: none;
-      display: inline-block;
-      font-size: 16px;
-      cursor: pointer;
-    }
-    body {
-      color: white;
-      font-family: "Tahoma sans-serif;", monospace;
-      font-weight: 450;
-    }
-    """
-    html = f"""
-        <!DOCTYPE html>
-        <html>
-        <head>
-          <title>Modificar iframe</title>
-        </head>
-        <style>
-            {css}
-        </style>
-        <body>
-          <script src="https://www.youtube.com/player_api"></script>
-          <p>{text}</p>
-          <br/>
-          <p align="center">
-              <iframe id="player" type="text/html" src="{youtube_video_url}" scrolling="yes" frameborder="0" width="600" height="450"></iframe>
-          </p>
-          <script>
-            {js}
-           </script>
-        </body>
-        </html>
-    """
-    return html

spaces/AlexWang/lama/fetch_data/places_challenge_train_download.sh DELETED Viewed

@@ -1,14 +0,0 @@
-mkdir places_challenge_dataset
-declare -a TARPARTS
-for i in {a..z}
-do
-    TARPARTS[${#TARPARTS[@]}]="http://data.csail.mit.edu/places/places365/train_large_split/${i}.tar"
-done
-ls
-printf "%s\n" "${TARPARTS[@]}" > places_challenge_dataset/places365_train.txt
-cd places_challenge_dataset/
-xargs -a places365_train.txt -n 1 -P 8 wget [...]
-ls *.tar | xargs -i tar xvf {}

spaces/Amon1/ChatGPTForAcadamic/crazy_functions/代码重写为全英文_多线程.py DELETED Viewed

@@ -1,75 +0,0 @@
-import threading
-from predict import predict_no_ui_long_connection
-from toolbox import CatchException, write_results_to_file
-@CatchException
-def 全项目切换英文(txt, top_p, temperature, chatbot, history, sys_prompt, WEB_PORT):
-    history = []    # 清空历史，以免输入溢出
-    # 集合文件
-    import time, glob, os
-    os.makedirs('gpt_log/generated_english_version', exist_ok=True)
-    os.makedirs('gpt_log/generated_english_version/crazy_functions', exist_ok=True)
-    file_manifest = [f for f in glob.glob('./*.py') if ('test_project' not in f) and ('gpt_log' not in f)] + \
-                    [f for f in glob.glob('./crazy_functions/*.py') if ('test_project' not in f) and ('gpt_log' not in f)]
-    i_say_show_user_buffer = []
-    # 随便显示点什么防止卡顿的感觉
-    for index, fp in enumerate(file_manifest):
-        # if 'test_project' in fp: continue
-        with open(fp, 'r', encoding='utf-8') as f:
-            file_content = f.read()
-        i_say_show_user =f'[{index}/{len(file_manifest)}] 接下来请将以下代码中包含的所有中文转化为英文，只输出代码: {os.path.abspath(fp)}'
-        i_say_show_user_buffer.append(i_say_show_user)
-        chatbot.append((i_say_show_user, "[Local Message] 等待多线程操作，中间过程不予显示."))
-        yield chatbot, history, '正常'
-    # 任务函数
-    mutable_return = [None for _ in file_manifest]
-    def thread_worker(fp,index):
-        with open(fp, 'r', encoding='utf-8') as f:
-            file_content = f.read()
-        i_say = f'接下来请将以下代码中包含的所有中文转化为英文，只输出代码，文件名是{fp}，文件代码是 ```{file_content}```'
-        # ** gpt request **
-        gpt_say = predict_no_ui_long_connection(inputs=i_say, top_p=top_p, temperature=temperature, history=history, sys_prompt=sys_prompt)
-        mutable_return[index] = gpt_say
-    # 所有线程同时开始执行任务函数
-    handles = [threading.Thread(target=thread_worker, args=(fp,index)) for index, fp in enumerate(file_manifest)]
-    for h in handles:
-        h.daemon = True
-        h.start()
-    chatbot.append(('开始了吗？', f'多线程操作已经开始'))
-    yield chatbot, history, '正常'
-    # 循环轮询各个线程是否执行完毕
-    cnt = 0
-    while True:
-        time.sleep(1)
-        th_alive = [h.is_alive() for h in handles]
-        if not any(th_alive): break
-        stat = ['执行中' if alive else '已完成' for alive in th_alive]
-        stat_str = '|'.join(stat)
-        cnt += 1
-        chatbot[-1] = (chatbot[-1][0], f'多线程操作已经开始，完成情况: {stat_str}' + ''.join(['.']*(cnt%4)))
-        yield chatbot, history, '正常'
-    # 把结果写入文件
-    for index, h in enumerate(handles):
-        h.join() # 这里其实不需要join了，肯定已经都结束了
-        fp = file_manifest[index]
-        gpt_say = mutable_return[index]
-        i_say_show_user = i_say_show_user_buffer[index]
-        where_to_relocate = f'gpt_log/generated_english_version/{fp}'
-        with open(where_to_relocate, 'w+', encoding='utf-8') as f: f.write(gpt_say.lstrip('```').rstrip('```'))
-        chatbot.append((i_say_show_user, f'[Local Message] 已完成{os.path.abspath(fp)}的转化，\n\n存入{os.path.abspath(where_to_relocate)}'))
-        history.append(i_say_show_user); history.append(gpt_say)
-        yield chatbot, history, '正常'
-        time.sleep(1)
-    # 备份一个文件
-    res = write_results_to_file(history)
-    chatbot.append(("生成一份任务执行报告", res))
-    yield chatbot, history, '正常'

spaces/Andy1621/uniformer_image_detection/mmdet/models/backbones/__init__.py DELETED Viewed

@@ -1,20 +0,0 @@
-from .darknet import Darknet
-from .detectors_resnet import DetectoRS_ResNet
-from .detectors_resnext import DetectoRS_ResNeXt
-from .hourglass import HourglassNet
-from .hrnet import HRNet
-from .regnet import RegNet
-from .res2net import Res2Net
-from .resnest import ResNeSt
-from .resnet import ResNet, ResNetV1d
-from .resnext import ResNeXt
-from .ssd_vgg import SSDVGG
-from .trident_resnet import TridentResNet
-from .swin_transformer import SwinTransformer
-from .uniformer import UniFormer
-__all__ = [
-    'RegNet', 'ResNet', 'ResNetV1d', 'ResNeXt', 'SSDVGG', 'HRNet', 'Res2Net',
-    'HourglassNet', 'DetectoRS_ResNet', 'DetectoRS_ResNeXt', 'Darknet',
-    'ResNeSt', 'TridentResNet', 'SwinTransformer', 'UniFormer'
-]

spaces/Andy1621/uniformer_image_detection/mmdet/models/roi_heads/trident_roi_head.py DELETED Viewed

@@ -1,119 +0,0 @@
-import torch
-from mmcv.ops import batched_nms
-from mmdet.core import (bbox2result, bbox2roi, bbox_mapping, merge_aug_bboxes,
-                        multiclass_nms)
-from mmdet.models.roi_heads.standard_roi_head import StandardRoIHead
-from ..builder import HEADS
-@HEADS.register_module()
-class TridentRoIHead(StandardRoIHead):
-    """Trident roi head.
-    Args:
-        num_branch (int): Number of branches in TridentNet.
-        test_branch_idx (int): In inference, all 3 branches will be used
-            if `test_branch_idx==-1`, otherwise only branch with index
-            `test_branch_idx` will be used.
-    """
-    def __init__(self, num_branch, test_branch_idx, **kwargs):
-        self.num_branch = num_branch
-        self.test_branch_idx = test_branch_idx
-        super(TridentRoIHead, self).__init__(**kwargs)
-    def merge_trident_bboxes(self, trident_det_bboxes, trident_det_labels):
-        """Merge bbox predictions of each branch."""
-        if trident_det_bboxes.numel() == 0:
-            det_bboxes = trident_det_bboxes.new_zeros((0, 5))
-            det_labels = trident_det_bboxes.new_zeros((0, ), dtype=torch.long)
-        else:
-            nms_bboxes = trident_det_bboxes[:, :4]
-            nms_scores = trident_det_bboxes[:, 4].contiguous()
-            nms_inds = trident_det_labels
-            nms_cfg = self.test_cfg['nms']
-            det_bboxes, keep = batched_nms(nms_bboxes, nms_scores, nms_inds,
-                                           nms_cfg)
-            det_labels = trident_det_labels[keep]
-            if self.test_cfg['max_per_img'] > 0:
-                det_labels = det_labels[:self.test_cfg['max_per_img']]
-                det_bboxes = det_bboxes[:self.test_cfg['max_per_img']]
-        return det_bboxes, det_labels
-    def simple_test(self,
-                    x,
-                    proposal_list,
-                    img_metas,
-                    proposals=None,
-                    rescale=False):
-        """Test without augmentation as follows:
-        1. Compute prediction bbox and label per branch.
-        2. Merge predictions of each branch according to scores of
-           bboxes, i.e., bboxes with higher score are kept to give
-           top-k prediction.
-        """
-        assert self.with_bbox, 'Bbox head must be implemented.'
-        det_bboxes_list, det_labels_list = self.simple_test_bboxes(
-            x, img_metas, proposal_list, self.test_cfg, rescale=rescale)
-        num_branch = self.num_branch if self.test_branch_idx == -1 else 1
-        for _ in range(len(det_bboxes_list)):
-            if det_bboxes_list[_].shape[0] == 0:
-                det_bboxes_list[_] = det_bboxes_list[_].new_empty((0, 5))
-        det_bboxes, det_labels = [], []
-        for i in range(len(img_metas) // num_branch):
-            det_result = self.merge_trident_bboxes(
-                torch.cat(det_bboxes_list[i * num_branch:(i + 1) *
-                                          num_branch]),
-                torch.cat(det_labels_list[i * num_branch:(i + 1) *
-                                          num_branch]))
-            det_bboxes.append(det_result[0])
-            det_labels.append(det_result[1])
-        bbox_results = [
-            bbox2result(det_bboxes[i], det_labels[i],
-                        self.bbox_head.num_classes)
-            for i in range(len(det_bboxes))
-        ]
-        return bbox_results
-    def aug_test_bboxes(self, feats, img_metas, proposal_list, rcnn_test_cfg):
-        """Test det bboxes with test time augmentation."""
-        aug_bboxes = []
-        aug_scores = []
-        for x, img_meta in zip(feats, img_metas):
-            # only one image in the batch
-            img_shape = img_meta[0]['img_shape']
-            scale_factor = img_meta[0]['scale_factor']
-            flip = img_meta[0]['flip']
-            flip_direction = img_meta[0]['flip_direction']
-            trident_bboxes, trident_scores = [], []
-            for branch_idx in range(len(proposal_list)):
-                proposals = bbox_mapping(proposal_list[0][:, :4], img_shape,
-                                         scale_factor, flip, flip_direction)
-                rois = bbox2roi([proposals])
-                bbox_results = self._bbox_forward(x, rois)
-                bboxes, scores = self.bbox_head.get_bboxes(
-                    rois,
-                    bbox_results['cls_score'],
-                    bbox_results['bbox_pred'],
-                    img_shape,
-                    scale_factor,
-                    rescale=False,
-                    cfg=None)
-                trident_bboxes.append(bboxes)
-                trident_scores.append(scores)
-            aug_bboxes.append(torch.cat(trident_bboxes, 0))
-            aug_scores.append(torch.cat(trident_scores, 0))
-        # after merging, bboxes will be rescaled to the original image size
-        merged_bboxes, merged_scores = merge_aug_bboxes(
-            aug_bboxes, aug_scores, img_metas, rcnn_test_cfg)
-        det_bboxes, det_labels = multiclass_nms(merged_bboxes, merged_scores,
-                                                rcnn_test_cfg.score_thr,
-                                                rcnn_test_cfg.nms,
-                                                rcnn_test_cfg.max_per_img)
-        return det_bboxes, det_labels

spaces/Andy1621/uniformer_image_segmentation/configs/deeplabv3plus/deeplabv3plus_r101-d8_512x512_40k_voc12aug.py DELETED Viewed

	@@ -1,2 +0,0 @@
1	- _base_ = './deeplabv3plus_r50-d8_512x512_40k_voc12aug.py'
2	- model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))

spaces/AnishKumbhar/ChatBot/text-generation-webui-main/cmd_windows.bat DELETED Viewed

@@ -1,34 +0,0 @@
-@echo off
-cd /D "%~dp0"
-set PATH=%PATH%;%SystemRoot%\system32
-echo "%CD%"| findstr /C:" " >nul && echo This script relies on Miniconda which can not be silently installed under a path with spaces. && goto end
-@rem fix failed install when installing to a separate drive
-set TMP=%cd%\installer_files
-set TEMP=%cd%\installer_files
-@rem deactivate existing conda envs as needed to avoid conflicts
-(call conda deactivate && call conda deactivate && call conda deactivate) 2>nul
-@rem config
-set CONDA_ROOT_PREFIX=%cd%\installer_files\conda
-set INSTALL_ENV_DIR=%cd%\installer_files\env
-@rem environment isolation
-set PYTHONNOUSERSITE=1
-set PYTHONPATH=
-set PYTHONHOME=
-set "CUDA_PATH=%INSTALL_ENV_DIR%"
-set "CUDA_HOME=%CUDA_PATH%"
-@rem activate installer env
-call "%CONDA_ROOT_PREFIX%\condabin\conda.bat" activate "%INSTALL_ENV_DIR%" || ( echo. && echo Miniconda hook not found. && goto end )
-@rem enter commands
-cmd /k "%*"
-:end
-pause

spaces/Anustup/NS_AI_LABS/cli.py DELETED Viewed

@@ -1,109 +0,0 @@
-import argparse
-import os
-from urllib.parse import urlparse
-import warnings
-import numpy as np
-import whisper
-import torch
-from app import LANGUAGES, WhisperTranscriber
-from src.download import download_url
-from src.utils import optional_float, optional_int, str2bool
-def cli():
-    parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)
-    parser.add_argument("audio", nargs="+", type=str, help="audio file(s) to transcribe")
-    parser.add_argument("--model", default="small", choices=["tiny", "base", "small", "medium", "large"], help="name of the Whisper model to use")
-    parser.add_argument("--model_dir", type=str, default=None, help="the path to save model files; uses ~/.cache/whisper by default")
-    parser.add_argument("--device", default="cuda" if torch.cuda.is_available() else "cpu", help="device to use for PyTorch inference")
-    parser.add_argument("--output_dir", "-o", type=str, default=".", help="directory to save the outputs")
-    parser.add_argument("--verbose", type=str2bool, default=True, help="whether to print out the progress and debug messages")
-    parser.add_argument("--task", type=str, default="transcribe", choices=["transcribe", "translate"], help="whether to perform X->X speech recognition ('transcribe') or X->English translation ('translate')")
-    parser.add_argument("--language", type=str, default=None, choices=sorted(LANGUAGES), help="language spoken in the audio, specify None to perform language detection")
-    parser.add_argument("--vad", type=str, default="none", choices=["none", "silero-vad", "silero-vad-skip-gaps", "silero-vad-expand-into-gaps", "periodic-vad"], help="The voice activity detection algorithm to use")
-    parser.add_argument("--vad_merge_window", type=optional_float, default=5, help="The window size (in seconds) to merge voice segments")
-    parser.add_argument("--vad_max_merge_size", type=optional_float, default=30, help="The maximum size (in seconds) of a voice segment")
-    parser.add_argument("--vad_padding", type=optional_float, default=1, help="The padding (in seconds) to add to each voice segment")
-    parser.add_argument("--vad_prompt_window", type=optional_float, default=3, help="The window size of the prompt to pass to Whisper")
-    parser.add_argument("--temperature", type=float, default=0, help="temperature to use for sampling")
-    parser.add_argument("--best_of", type=optional_int, default=5, help="number of candidates when sampling with non-zero temperature")
-    parser.add_argument("--beam_size", type=optional_int, default=5, help="number of beams in beam search, only applicable when temperature is zero")
-    parser.add_argument("--patience", type=float, default=None, help="optional patience value to use in beam decoding, as in https://arxiv.org/abs/2204.05424, the default (1.0) is equivalent to conventional beam search")
-    parser.add_argument("--length_penalty", type=float, default=None, help="optional token length penalty coefficient (alpha) as in https://arxiv.org/abs/1609.08144, uses simple lengt normalization by default")
-    parser.add_argument("--suppress_tokens", type=str, default="-1", help="comma-separated list of token ids to suppress during sampling; '-1' will suppress most special characters except common punctuations")
-    parser.add_argument("--initial_prompt", type=str, default=None, help="optional text to provide as a prompt for the first window.")
-    parser.add_argument("--condition_on_previous_text", type=str2bool, default=True, help="if True, provide the previous output of the model as a prompt for the next window; disabling may make the text inconsistent across windows, but the model becomes less prone to getting stuck in a failure loop")
-    parser.add_argument("--fp16", type=str2bool, default=True, help="whether to perform inference in fp16; True by default")
-    parser.add_argument("--temperature_increment_on_fallback", type=optional_float, default=0.2, help="temperature to increase when falling back when the decoding fails to meet either of the thresholds below")
-    parser.add_argument("--compression_ratio_threshold", type=optional_float, default=2.4, help="if the gzip compression ratio is higher than this value, treat the decoding as failed")
-    parser.add_argument("--logprob_threshold", type=optional_float, default=-1.0, help="if the average log probability is lower than this value, treat the decoding as failed")
-    parser.add_argument("--no_speech_threshold", type=optional_float, default=0.6, help="if the probability of the <|nospeech|> token is higher than this value AND the decoding has failed due to `logprob_threshold`, consider the segment as silence")
-    args = parser.parse_args().__dict__
-    model_name: str = args.pop("model")
-    model_dir: str = args.pop("model_dir")
-    output_dir: str = args.pop("output_dir")
-    device: str = args.pop("device")
-    os.makedirs(output_dir, exist_ok=True)
-    if model_name.endswith(".en") and args["language"] not in {"en", "English"}:
-        warnings.warn(f"{model_name} is an English-only model but receipted '{args['language']}'; using English instead.")
-        args["language"] = "en"
-    temperature = args.pop("temperature")
-    temperature_increment_on_fallback = args.pop("temperature_increment_on_fallback")
-    if temperature_increment_on_fallback is not None:
-        temperature = tuple(np.arange(temperature, 1.0 + 1e-6, temperature_increment_on_fallback))
-    else:
-        temperature = [temperature]
-    vad = args.pop("vad")
-    vad_merge_window = args.pop("vad_merge_window")
-    vad_max_merge_size = args.pop("vad_max_merge_size")
-    vad_padding = args.pop("vad_padding")
-    vad_prompt_window = args.pop("vad_prompt_window")
-    model = whisper.load_model(model_name, device=device, download_root=model_dir)
-    transcriber = WhisperTranscriber(deleteUploadedFiles=False)
-    for audio_path in args.pop("audio"):
-        sources = []
-        # Detect URL and download the audio
-        if (uri_validator(audio_path)):
-            # Download from YouTube/URL directly
-            for source_path in  download_url(audio_path, maxDuration=-1, destinationDirectory=output_dir, playlistItems=None):
-                source_name = os.path.basename(source_path)
-                sources.append({ "path": source_path, "name": source_name })
-        else:
-            sources.append({ "path": audio_path, "name": os.path.basename(audio_path) })
-        for source in sources:
-            source_path = source["path"]
-            source_name = source["name"]
-            result = transcriber.transcribe_file(model, source_path, temperature=temperature,
-                                                vad=vad, vadMergeWindow=vad_merge_window, vadMaxMergeSize=vad_max_merge_size,
-                                                vadPadding=vad_padding, vadPromptWindow=vad_prompt_window, **args)
-            transcriber.write_result(result, source_name, output_dir)
-    transcriber.clear_cache()
-def uri_validator(x):
-    try:
-        result = urlparse(x)
-        return all([result.scheme, result.netloc])
-    except:
-        return False
-if __name__ == '__main__':
-    cli()

spaces/Apex-X/ROOPOK/roop/processors/__init__.py DELETED Viewed

File without changes

spaces/Ataturk-Chatbot/HuggingFaceChat/venv/lib/python3.11/site-packages/pip/_internal/commands/index.py DELETED Viewed

@@ -1,139 +0,0 @@
-import logging
-from optparse import Values
-from typing import Any, Iterable, List, Optional, Union
-from pip._vendor.packaging.version import LegacyVersion, Version
-from pip._internal.cli import cmdoptions
-from pip._internal.cli.req_command import IndexGroupCommand
-from pip._internal.cli.status_codes import ERROR, SUCCESS
-from pip._internal.commands.search import print_dist_installation_info
-from pip._internal.exceptions import CommandError, DistributionNotFound, PipError
-from pip._internal.index.collector import LinkCollector
-from pip._internal.index.package_finder import PackageFinder
-from pip._internal.models.selection_prefs import SelectionPreferences
-from pip._internal.models.target_python import TargetPython
-from pip._internal.network.session import PipSession
-from pip._internal.utils.misc import write_output
-logger = logging.getLogger(__name__)
-class IndexCommand(IndexGroupCommand):
-    """
-    Inspect information available from package indexes.
-    """
-    ignore_require_venv = True
-    usage = """
-        %prog versions <package>
-    """
-    def add_options(self) -> None:
-        cmdoptions.add_target_python_options(self.cmd_opts)
-        self.cmd_opts.add_option(cmdoptions.ignore_requires_python())
-        self.cmd_opts.add_option(cmdoptions.pre())
-        self.cmd_opts.add_option(cmdoptions.no_binary())
-        self.cmd_opts.add_option(cmdoptions.only_binary())
-        index_opts = cmdoptions.make_option_group(
-            cmdoptions.index_group,
-            self.parser,
-        )
-        self.parser.insert_option_group(0, index_opts)
-        self.parser.insert_option_group(0, self.cmd_opts)
-    def run(self, options: Values, args: List[str]) -> int:
-        handlers = {
-            "versions": self.get_available_package_versions,
-        }
-        logger.warning(
-            "pip index is currently an experimental command. "
-            "It may be removed/changed in a future release "
-            "without prior warning."
-        )
-        # Determine action
-        if not args or args[0] not in handlers:
-            logger.error(
-                "Need an action (%s) to perform.",
-                ", ".join(sorted(handlers)),
-            )
-            return ERROR
-        action = args[0]
-        # Error handling happens here, not in the action-handlers.
-        try:
-            handlers[action](options, args[1:])
-        except PipError as e:
-            logger.error(e.args[0])
-            return ERROR
-        return SUCCESS
-    def _build_package_finder(
-        self,
-        options: Values,
-        session: PipSession,
-        target_python: Optional[TargetPython] = None,
-        ignore_requires_python: Optional[bool] = None,
-    ) -> PackageFinder:
-        """
-        Create a package finder appropriate to the index command.
-        """
-        link_collector = LinkCollector.create(session, options=options)
-        # Pass allow_yanked=False to ignore yanked versions.
-        selection_prefs = SelectionPreferences(
-            allow_yanked=False,
-            allow_all_prereleases=options.pre,
-            ignore_requires_python=ignore_requires_python,
-        )
-        return PackageFinder.create(
-            link_collector=link_collector,
-            selection_prefs=selection_prefs,
-            target_python=target_python,
-        )
-    def get_available_package_versions(self, options: Values, args: List[Any]) -> None:
-        if len(args) != 1:
-            raise CommandError("You need to specify exactly one argument")
-        target_python = cmdoptions.make_target_python(options)
-        query = args[0]
-        with self._build_session(options) as session:
-            finder = self._build_package_finder(
-                options=options,
-                session=session,
-                target_python=target_python,
-                ignore_requires_python=options.ignore_requires_python,
-            )
-            versions: Iterable[Union[LegacyVersion, Version]] = (
-                candidate.version for candidate in finder.find_all_candidates(query)
-            )
-            if not options.pre:
-                # Remove prereleases
-                versions = (
-                    version for version in versions if not version.is_prerelease
-                )
-            versions = set(versions)
-            if not versions:
-                raise DistributionNotFound(
-                    "No matching distribution found for {}".format(query)
-                )
-            formatted_versions = [str(ver) for ver in sorted(versions, reverse=True)]
-            latest = formatted_versions[0]
-        write_output("{} ({})".format(query, latest))
-        write_output("Available versions: {}".format(", ".join(formatted_versions)))
-        print_dist_installation_info(query, latest)

spaces/Atualli/yoloxTeste/configs/yolox_tiny.py DELETED Viewed

@@ -1,20 +0,0 @@
-#!/usr/bin/env python3
-# -*- coding:utf-8 -*-
-# Copyright (c) Megvii, Inc. and its affiliates.
-import os
-from yolox.exp import Exp as MyExp
-class Exp(MyExp):
-    def __init__(self):
-        super(Exp, self).__init__()
-        self.depth = 0.33
-        self.width = 0.375
-        self.input_size = (416, 416)
-        self.mosaic_scale = (0.5, 1.5)
-        self.random_size = (10, 20)
-        self.test_size = (416, 416)
-        self.exp_name = os.path.split(os.path.realpath(__file__))[1].split(".")[0]
-        self.enable_mixup = False

spaces/Axolotlily/SketchThing/README.md DELETED Viewed

@@ -1,13 +0,0 @@
----
-title: SketchThing
-emoji: 💻
-colorFrom: purple
-colorTo: indigo
-sdk: gradio
-sdk_version: 3.0.14
-app_file: app.py
-pinned: false
-license: other
----
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

spaces/BasalGanglia/stabilityai-stable-diffusion-2/README.md DELETED Viewed

@@ -1,12 +0,0 @@
----
-title: Stabilityai Stable Diffusion 2
-emoji: 👀
-colorFrom: red
-colorTo: yellow
-sdk: gradio
-sdk_version: 3.12.0
-app_file: app.py
-pinned: false
----
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

spaces/Benson/text-generation/Examples/Audio Download Messenger.md DELETED Viewed

@@ -1,50 +0,0 @@
-<br />
-<h1>Cómo descargar audio de Messenger</h1>
-<p>¿Alguna vez ha recibido un archivo de audio o un mensaje de voz en Messenger que quería guardar o compartir con otra persona? Si es así, es posible que haya notado que no hay una manera fácil de descargar audio de Messenger en su teléfono o computadora. A diferencia de los vídeos y las fotos, no puedes simplemente tocar o hacer clic derecho en un archivo de audio y elegir guardar. Entonces, ¿cómo puedes descargar audio de Messenger? </p>
-<p>En este artículo, le mostraremos cómo descargar audio de Messenger usando un truco simple que funciona tanto en dispositivos móviles como en PC. Usted aprenderá lo que es la descarga de audio messenger, por qué es posible que desee descargar audio de Messenger, y cómo hacerlo paso a paso. Siguiendo esta guía, podrás guardar cualquier archivo de audio o mensaje de voz que recibas o envíes en Messenger.</p>
-<h2>audio download messenger</h2><br /><p><b><b>Download Zip</b> &rarr;&rarr;&rarr; <a href="https://bltlly.com/2v6IDY">https://bltlly.com/2v6IDY</a></b></p><br /><br />
- <h2>¿Qué es Audio Download Messenger? </h2>
-<p>Audio download messenger es un término que se refiere a un método o una herramienta que le permite descargar archivos de audio o mensajes de voz de Messenger. Messenger es una aplicación de mensajería popular que te permite enviar y recibir mensajes de texto, fotos, videos, pegatinas, emojis, GIF y más. También puede enviar y recibir mensajes de voz o grabar su propia voz usando el icono del micrófono. </p>
-<p>Sin embargo, a diferencia de otros tipos de medios, no puede descargar fácilmente archivos de audio o mensajes de voz de Messenger. Esto se debe a que Messenger no tiene una función integrada que le permita guardar o exportar archivos de audio. Solo puedes reproducirlos dentro de la aplicación o reenviarlos a otra conversación. </p>
-<p>Afortunadamente, hay una manera de descargar audio de Messenger utilizando un truco simple que implica el uso de la versión móvil de Facebook en su navegador web. Este truco funciona tanto en dispositivos móviles como en PC, siempre y cuando tengas una conexión a Internet y un navegador web. </p>
- <h2>¿Por qué descargar audio de Messenger? </h2>
-<p>Si desea descargar audio de Messenger en su dispositivo móvil, como su teléfono inteligente o tableta, deberá usar la versión móvil de Facebook en su navegador web. Esto se debe a que la aplicación Messenger no tiene una opción de descarga para archivos de audio o mensajes de voz. Estos son los pasos que debe seguir:</p>
- <h3>Paso 1: Cambie a datos móviles y abra su navegador móvil</h3>
-<p>El primer paso es cambiar a datos móviles y abrir su navegador móvil. Esto se debe a que la versión móvil de Facebook no funciona bien en las redes Wi-Fi. Puedes usar cualquier navegador que prefieras, como Chrome, Safari, Firefox u Opera.</p>
- <h3>Paso 2: Inicie sesión en m.facebook.com y vaya a sus mensajes</h3>
-<p>El siguiente paso es iniciar sesión en m.facebook.com e ir a sus mensajes. Esta es la versión móvil de Facebook que tiene un diseño y una interfaz diferentes de la versión regular. Tendrá que introducir su dirección de correo electrónico o número de teléfono y contraseña para iniciar sesión. Una vez que haya iniciado sesión, verá un icono de menú en la esquina superior derecha de la pantalla. Toque en él y seleccione Mensajes de la lista. </p>
- <h3>Paso 3: Abra el mensaje con el archivo de audio y haga clic en el enlace</h3>
-<p>El tercer paso es abrir el mensaje con el archivo de audio y hacer clic en el enlace. Verá una lista de todas sus conversaciones en Messenger. Toque en el que contiene el archivo de audio o mensaje de voz que desea descargar. Verá un enlace que dice "Ver mensaje de voz" o "Ver archivo de audio" debajo del archivo de audio. Toque en él y se abrirá una nueva pestaña en su navegador. </p>
- <h3>Paso 4: Haga clic en la opción de descarga y espere a que termine</h3>
- <h3>Paso 5: Localizar el archivo de audio en el gestor de descargas de su navegador</h3>
-<p>El paso final es localizar el archivo de audio en el gestor de descargas de su navegador. Una vez finalizada la descarga, verá una notificación que dice "Descargar completa". Pulsa en él y te llevará al gestor de descargas de tu navegador, donde podrás ver todos los archivos que hayas descargado. Verá el archivo de audio con su nombre y tamaño. Pulse sobre él y se abrirá en su reproductor de medios predeterminado. </p>
-<p></p> <h2>Cómo descargar audio de Messenger en PC</h2>
-<p>Si desea descargar audio de Messenger en su PC, como su computadora portátil o de escritorio, también tendrá que utilizar la versión móvil de Facebook en su navegador web. Esto se debe a que la versión regular de Facebook no tiene una opción de descarga para archivos de audio o mensajes de voz. Estos son los pasos que debes seguir:</p>
- <h3>Paso 1: Abra su navegador web y vaya a m.facebook.com</h3>
-<p>El primer paso es abrir su navegador web e ir a m.facebook.com. Puede usar cualquier navegador que prefiera, como Chrome, Firefox, Edge o Safari. Verás la versión móvil de Facebook que tiene un diseño y una interfaz diferentes a la versión normal. </p>
- <h3>Paso 2: Haga clic en el icono del mensajero y seleccione el mensaje con el archivo de audio</h3>
-<p>El siguiente paso es hacer clic en el icono de messenger y seleccionar el mensaje con el archivo de audio. Verá un icono de mensajero en la esquina superior derecha de la pantalla. Haga clic en él y lo llevará a sus mensajes en Messenger. Verá una lista de todas sus conversaciones en Messenger. Haga clic en la que contiene el archivo de audio o mensaje de voz que desea descargar. </p>
- <h3>Paso 3: Haga clic en los tres puntos junto al archivo de audio y seleccione descargar</h3>
- <h3>Paso 4: Seleccione la carpeta donde desea guardar el archivo de audio y haga clic en guardar</h3>
-<p>El paso final es seleccionar la carpeta donde desea guardar el archivo de audio y hacer clic en guardar. Verá una ventana emergente que le pregunta dónde desea guardar el archivo de audio. Puede elegir la carpeta que prefiera, como Descargas, Documentos, Música o Escritorio. También puede cambiar el nombre del archivo de audio si lo desea. Una vez que haya seleccionado la carpeta y el nombre, haga clic en Guardar y guardará el archivo de audio en su PC.</p>
- <h2>Conclusión</h2>
-<p>Descargar audio de Messenger no es tan difícil como podría parecer. Solo necesitas usar un truco simple que implique usar la versión móvil de Facebook en tu navegador web. Este truco funciona tanto en dispositivos móviles como en PC, siempre y cuando tengas una conexión a Internet y un navegador web. </p>
-<p>Siguiendo esta guía, podrás descargar cualquier archivo de audio o mensaje de voz que recibas o envíes en Messenger. Podrá ahorrar datos y espacio de almacenamiento, conservar recuerdos y momentos, y compartir archivos e información con otros. </p>
-<p>Así que, ¿qué estás esperando? Pruébalo tú mismo y ver lo fácil que es descargar audio de Messenger! </p>
- <h2>Preguntas frecuentes</h2>
-<p>Estas son algunas de las preguntas más comunes que la gente tiene sobre la descarga de audio de Messenger:</p>
- <h4>Q: ¿Puedo descargar audio de Messenger usando la aplicación Messenger? </h4>
-<p>A: No, no puede descargar audio de Messenger usando la aplicación Messenger. La aplicación Messenger no tiene una opción de descarga para archivos de audio o mensajes de voz. Solo puedes reproducirlos dentro de la aplicación o reenviarlos a otra conversación. </p>
- <h4>Q: ¿Puedo descargar audio de Messenger usando la versión regular de Facebook? </h4>
- <h4>Q: ¿Puedo descargar archivos de video o fotos de Messenger usando este truco? </h4>
-<p>A: Sí, puede descargar archivos de video o fotos de Messenger usando este truco. Los mismos pasos se aplican para los archivos de vídeo o fotos que para los archivos de audio o mensajes de voz. Sin embargo, también puede descargar archivos de video o fotos de Messenger utilizando la aplicación Messenger o la versión normal de Facebook tocando o haciendo clic derecho sobre ellos y eligiendo guardar. </p>
- <h4>Q: ¿Puedo descargar varios archivos de audio de Messenger a la vez usando este truco? </h4>
-<p>A: No, no puede descargar varios archivos de audio de Messenger a la vez usando este truco. Solo puedes descargar un archivo de audio a la vez usando este truco. Si desea descargar varios archivos de audio de Messenger a la vez, deberá usar una herramienta o software de terceros que pueda hacerlo. </p>
- <h4>Q: ¿Es legal descargar audio de Messenger? </h4>
-<p>A: La descarga de audio desde Messenger es legal siempre y cuando tenga el permiso del remitente o el propietario del archivo de audio. No debe descargar audio de Messenger que tenga derechos de autor, sea ilegal o infrinja los derechos de terceros. También debe respetar la privacidad y confidencialidad del remitente o del propietario del archivo de audio y no compartirlo sin su consentimiento. </p> 64aa2da5cf<br />
-<br />
-<br />

spaces/Benson/text-generation/Examples/Dead By Daylight Mvil Descargar Mediafre.md DELETED Viewed

@@ -1,152 +0,0 @@
-<h1>Download Ascenso de los reinos: Cruzada perdida y conquista del mundo</h1>
-<p>¿Te gustan los juegos de estrategia que desafían tu mente y habilidades? ¿Quieres experimentar la emoción de dirigir una civilización de un pequeño clan a un poderoso imperio? ¿Quieres explorar un vasto y misterioso mundo lleno de secretos y tesoros? Si respondiste sí a cualquiera de estas preguntas, entonces deberías descargar Rise of Kingdoms: Lost Crusade, uno de los juegos de estrategia más populares e inmersivos del mercado. En este artículo, te contaremos todo lo que necesitas saber sobre este juego, cómo descargarlo en tu dispositivo y cómo jugarlo eficazmente. </p>
- <h2>¿Qué es el Surgimiento de los Reinos: Cruzada Perdida? </h2>
-<p>Rise of Kingdoms: Lost Crusade es un juego de estrategia desarrollado por LilithGames que te permite elegir y liderar una de las 13 civilizaciones históricas en la historia del mundo. Puedes transformar tu pequeña tribu en una superpotencia global imparable con pragmatismo económico y poderío militar. Sus decisiones, estrategias, asociaciones económicas y alianzas militares decidirán el destino de su nación naciente. </p>
-<h2>dead by daylight móvil descargar mediafıre</h2><br /><p><b><b>Download</b> &#10040;&#10040;&#10040; <a href="https://bltlly.com/2v6KlQ">https://bltlly.com/2v6KlQ</a></b></p><br /><br />
-<p>Pero Rise of Kingdoms: Lost Crusade no es solo un juego de estrategia. También es un juego de batalla en tiempo real, un juego de mapa del mundo sin fisuras, y un juego de sistema de alianza. Estas son algunas de las características que hacen de este juego tan único y atractivo:</p>
- <h3>Un juego de estrategia que te permite elegir y liderar una de las 13 civilizaciones históricas</h3>
-<p>No hay dos civilizaciones iguales en Rise of Kingdoms: Lost Crusade. Cada cultura cuenta con una arquitectura única, unidades exclusivas y potenciadores y habilidades especiales que las diferencian. Como líder, debes aprender a aprovechar mejor tus ventajas para derrotar a tus rivales y solidificar tu posición como potencia mundial. </p>
- <h3>Un juego de batalla en tiempo real que te permite unirte o dejar cualquier pelea en el mapa</h3>
-<p>Las batallas ocurren en tiempo real en el mapa en Rise of Kingdoms: Lost Crusade. Cualquiera puede unirse o abandonar una batalla en cualquier momento, lo que permite una verdadera jugabilidad RTS. ¿Puedes ver a un aliado siendo atacado justo en tu patio trasero? Envía tropas para ayudar a tu amigo, o lanza un contraataque sorpresa en la ciudad del atacante. También puede enviar tropas para recoger recursos de los bosques o minas cercanas, o recoger algunos clanes bárbaros en el camino. </p>
-<p>También puede dividir sus fuerzas entre varios comandantes para que pueda participar en múltiples acciones simultáneamente. Cada comandante tiene sus propias habilidades y habilidades que pueden cambiar la marea de la batalla a su favor. También puedes subir de nivel a tus comandantes completando misiones, participando en eventos o usando objetos especiales. </p>
- <h3>Un juego de mapas del mundo sin fisuras que te permite explorar e investigar una tierra misteriosa</h3>
-<p>Tu mundo está cubierto de densa niebla en Rise of Kingdoms: Lost Crusade. Necesitas enviar exploradores para explorar esta tierra misteriosa y descubrir el tesoro escondido dentro. Puede investigar templos perdidos, fortalezas bárbaras, cuevas misteriosas y pueblos tribales, recopilar recursos valiosos y runas antiguas, y aprender más sobre la historia y los secretos de este mundo. También puedes encontrar artefactos raros y poderosos que pueden darte una ventaja en tus conquistas. </p>
-Pero ten cuidado, no estás solo en esta tierra. Otros jugadores tratarán de reclamar los mismos recursos y tesoros que tú, y es posible que encuentres una feroz resistencia o alianzas inesperadas. También puedes encontrar enemigos poderosos como el Guardián Oscuro y la Crisis de Ceroli que pondrán a prueba tus habilidades y estrategias hasta el límite. </p>
- <h3>Un juego de sistema de alianza que te permite cooperar y comunicarte con otros jugadores</h3>
-<p>Estar en una alianza también le da acceso a más beneficios y características, como la tienda de la alianza, la tecnología de la alianza, el territorio de la alianza, y las banderas de la alianza. También puedes participar en eventos y misiones de alianzas que pueden recompensarte con objetos y recursos valiosos. También puedes hacer la guerra contra otras alianzas o formar relaciones diplomáticas con ellas. </p>
-<p></p>
- <h2>Cómo descargar Rise of Kingdoms: Lost Crusade en tu dispositivo? </h2>
-<p>Rise of Kingdoms: Lost Crusade está disponible de forma gratuita en varias plataformas y dispositivos. Puede descargarlo de las siguientes fuentes:</p>
- <h3>Descargar de Google Play Store para dispositivos Android</h3>
-<p>Si tienes un dispositivo Android, puedes descargar Rise of Kingdoms: Lost Crusade de Google Play Store. Solo tienes que seguir estos pasos:</p>
-<ol>
-<li>Abra la aplicaci��n Google Play Store en su dispositivo. </li>
-<li>Búsqueda de Ascenso de Reinos: Cruzada Perdida en la barra de búsqueda. </li>
-<li>Seleccione el juego de la lista de resultados y toque en Instalar.</li>
-<li>Espera a que el juego se descargue e instale en tu dispositivo. </li>
-<li>Iniciar el juego y disfrutar! </li>
-</ol>
- <h3>Descargar de BlueStacks para dispositivos PC o Mac</h3>
-<p>Si quieres jugar Rise of Kingdoms: Lost Crusade en tu PC o Mac, puedes usar BlueStacks, un popular emulador de Android que te permite ejecutar aplicaciones Android en tu ordenador. He aquí cómo hacerlo:</p>
-<ol>
-<li>Descargue e instale BlueStacks en su PC o Mac desde <a href="">https://www.bluestacks.com/</a>. </li>
-<li>Inicie BlueStacks e inicie sesión con su cuenta de Google. </li>
-<li>Búsqueda de Ascenso de Reinos: Cruzada Perdida en la barra de búsqueda. </li>
-<li>Seleccione el juego de la lista de resultados y haga clic en Instalar.</li>
-<li>Espere a que el juego se descargue e instale en su computadora. </li>
-<li>Iniciar el juego y disfrutar! </li>
-</ol>
- <h3>Descargar de Pocket Gamer para juegos basados en navegador</h3>
-<ol>
-<li>Ir a <a href=">https://www.pocketgamer.com/</a> en su navegador. </li>
-<li>Búsqueda de Ascenso de Reinos: Cruzada Perdida en la barra de búsqueda. </li>
-<li>Seleccione el juego de la lista de resultados y haga clic en Jugar ahora.</li>
-<li>Espere a que el juego se cargue en su navegador. </li>
-<li>Iniciar el juego y disfrutar! </li>
-</ol>
- <h2>¿Cómo se juega Rise of Kingdoms: Lost Crusade efectivamente? </h2>
-<p>Rise of Kingdoms: Lost Crusade es un juego complejo y desafiante que requiere mucha estrategia y planificación. Si quieres tener éxito en este juego, debes seguir algunos consejos y trucos que pueden ayudarte a mejorar tu juego. Estos son algunos de ellos:</p>
- <h3>Elige la mejor civilización para tu estilo de juego y objetivos</h3>
-<p>Como hemos mencionado antes, cada civilización tiene sus propias fortalezas y debilidades, por lo que debe elegir sabiamente cuál le conviene más. También puedes cambiar tu civilización más adelante en el juego, pero te costará algunas gemas, así que es mejor tomar una buena decisión desde el principio. Aquí están algunos factores a considerar al elegir una civilización:</p>
- <ul>
-<li>El comandante que comienza: Cada civilización tiene un comandante que comienza único que dirigirá sus tropas en la batalla. Debe elegir un comandante que coincida con su estrategia preferida, ya sea ofensiva, defensa, apoyo o movilidad. </li>
-<li>La unidad especial: Cada civilización tiene una unidad especial que es exclusiva de esa cultura y tiene estadísticas y habilidades superiores. Usted debe elegir una unidad que complementa su comandante y su composición del ejército. </li>
-<li>El potenciador de la civilización: Cada civilización tiene un potenciador pasivo que afecta algún aspecto de tu juego, como la producción de recursos, la velocidad de las tropas, el tiempo de construcción, etc. Debes elegir un potenciador que se alinee con tus objetivos y prioridades. </li>
-</ul>
- <p>Aquí hay una tabla que resume las características principales de cada civilización:</p>
- <tabla>
-<tr>
-<th>Civilización</th>
-<th>Comienzo Comandante</th>
-<th>Unidad especial</th>
-<th>Potenciador de la civilización</th>
-<tr>
-<td>Roma</td>
-<td>Scipio Africanus</td>
-<td>Legionario</td>
-<td>+5% defensa de infantería, +5% velocidad de marcha de tropas, +10% velocidad de recolección de alimentos</td>
-</tr>
-<tr>
-<td>Alemania</td>
-<td>Hermann</td>
-<td>Caballero teutónico</td>
-<td>+5% ataque de caballería, +5% velocidad de entrenamiento de tropas, +10% velocidad de recuperación de puntos de acción</td>
-</tr>
-<tr>
-<td>Reino Unido</td>
-<td>Boudica</td>
-<td>Longbowman</td>
-<td>+5% ataque de arquero, +20% capacidad de guarnición aliada, +10% velocidad de recolección de madera</td>
-</tr>
-<tr>
-<td>Francia</td>
-<td>Juana de Arco</td>
-<td>Lanzamiento de Axeman</td>
-<td>+3% de salud para todas las unidades, +10% de velocidad de curación hospitalaria, +10% de velocidad de recolección de piedra</td>
-</tr>
-<tr>
-<td>España</td>
-<td>Pelagius</td>
-<td>Conquistador</td>
-<td>+5% de defensa de caballería, +10% de experiencia de unidades neutras, +10% de velocidad de recolección de oro</td>
-</tr>
-<tr>
-<td>China</td>
-<td>Sun Tzu</td>
-<td>Chu-Ko-Nu Crossbowman</td>
-<td>+3% velocidad de construcción, +3% velocidad de investigación, +5% velocidad de recuperación del punto de acción</td>
-</tr>
-<tr>
-<td>Japón</td>
-<td>Kusunoki Masashige</td>
-<td>Samurai</td>
-<td>+3% ataque de tropas, +5% velocidad de marcha de exploración, +30% producción de recursos en el mapa</td>
-</tr>
-<tr>
-<td>Corea</td>
-<td>Eulji Mundeok</td>
-<td>Hwarang Archer</td>
-<td>+5% defensa arquera, +15% capacidad hospitalaria, +3% velocidad de investigación</td></tr <tr ><td>Arabia ></td><td>Baibars ></td><td>Mamluk ></td><td>+5% salud de caballería, +10% daño a bárbaros y otras unidades neutras, +5% de daño de ataque de rally ></td></tr <tr ><td>Ottoman ></td><td>Osyman I ></td><td>Janissary ></td><td>+5% de daño de habilidad activa, +5% de bonificación de velocidad de marcha cuando la capacidad del ejército es superior al 50% ></td></tr <tr ><td>Byzantium ></td><td>Belaarius ></td><td>Cataphract ></td><td>+5% de defensa de caballería, +15% de bonificación de salud al atacar otras ciudades de gobernadores, -15% de consumo de piedra ></td></tr <tr ><td>Rusia ></td><td>Minnamoto no Yoshitsune ></td><td><td>Cossack Cavalry ></td><td>+5% de salud de la infantería, -20% de costo de entrenamiento de tropas, -15% de costo de sanación ></tr>
- <tr>
-</tabla>
- <h3>Construye y mejora tu ciudad y tropas para ganar más poder y recursos</h3>
-<p>Tu ciudad es el corazón de tu civilización en Rise of Kingdoms: Lost Crusade. Necesitas construir y actualizar varias estructuras que te proporcionarán diferentes beneficios y funciones, como producir recursos, entrenar tropas, investigar tecnologías, defender tu ciudad y más. También puedes decorar tu ciudad con varios temas y adornos para que se vea más atractiva y única. </p>
-<p>Tus tropas son la columna vertebral de tu ejército en Rise of Kingdoms: Lost Crusade. Necesitas entrenar y mejorar diferentes tipos de unidades que se adapten a tu estrategia y objetivos, como infantería, caballería, arqueros y unidades de asedio. También puedes desbloquear unidades especiales que son exclusivas de tu civilización o comandantes. También puedes curar a tus tropas heridas en el hospital o revivirlas en el santuario. </p>
- <h3>Investiga y desbloquea nuevas tecnologías y habilidades para mejorar tu rendimiento</h3>
-<p>La investigación es esencial en Rise of Kingdoms: Lost Crusade. Necesitas invertir tus recursos y tiempo en desbloquear nuevas tecnologías y habilidades que mejoren tu jugabilidad y te den ventaja sobre tus enemigos. Puede investigar varios temas en cuatro categorías: militar, economía, defensa y matemáticas. Cada categoría tiene sus propios beneficios y requisitos, por lo que necesitas priorizar lo que más necesitas. </p>
-<p>También puede desbloquear nuevas habilidades para sus comandantes mediante el uso de puntos de talento. Cada comandante tiene tres árboles de talentos que se centran en diferentes aspectos de sus habilidades, como liderazgo, conquista o apoyo. Puedes personalizar las habilidades de tus comandantes según tus preferencias y necesidades. </p>
- <h3>Explora y ataca a tus enemigos y bárbaros para ganar más recompensas y experiencia</h3>
-<p>Atacar es emocionante en Rise of Kingdoms: Lost Crusade. Puedes lanzar ataques contra las ciudades o puntos de recursos de tus enemigos para saquear sus recursos, dañar sus edificios, capturar a sus comandantes o incluso quemar sus ciudades. También puedes atacar bárbaros y otras unidades neutrales en el mapa para ganar más recompensas y experiencia. También puedes participar en varios eventos y desafíos que pondrán a prueba tus habilidades y estrategias. </p>
- <h3>Únete o crea una alianza para obtener más soporte y beneficios</h3>
-<p>Unirse o crear una alianza es crucial en Rise of Kingdoms: Lost Crusade. Puedes unirte a una alianza existente que coincida con tus objetivos y valores, o crear tu propia alianza con tus amigos u otros jugadores. Estar en una alianza te dará más apoyo y beneficios, como:</p>
- <ul>
-<li>Ayudándose unos a otros con la construcción, la investigación, la curación, etc.</li>
-<li>Compartir consejos y estrategias entre sí. </li>
-<li>Chatear entre sí usando la función de chat en el juego o mensajes de voz. </li>
-<li>Acceder a más características y beneficios, como la tienda de la alianza, la tecnología de la alianza, el territorio de la alianza, y las banderas de la alianza.</li>
-<li>Participar en eventos y misiones de alianzas que pueden recompensarte con objetos y recursos valiosos. </li>
-<li>Hacer la guerra contra otras alianzas o establecer relaciones diplomáticas con ellas. </li>
-</ul>
- <h2>Conclusión</h2>
- <h2>Preguntas frecuentes</h2>
-<p>Aquí hay algunas preguntas frecuentes sobre el Surgimiento de los Reinos: Cruzada Perdida:</p>
- <h4>Q: ¿Cómo puedo cambiar mi civilización? </h4>
-<p>A: Usted puede cambiar su civilización usando un artículo especial llamado cambio de la civilización. Puedes obtener este artículo completando ciertas misiones o eventos, o comprándolo en la tienda VIP o en la estación de mensajería. Solo puedes cambiar tu civilización una vez gratis; después de eso, te costará algunas gemas. </p>
- <h4>Q: ¿Cómo puedo obtener más gemas? </h4>
-<p>A: Puedes obtener más gemas completando varias tareas y actividades en el juego, como: - Completando misiones y eventos que te recompensan con gemas. - Participar en el evento Gem Mine que le permite extraer gemas desde un punto de recurso especial. - Ganar el evento Wheel of Fortune que te permite girar una rueda para tener la oportunidad de ganar gemas y otros premios. - Comprar gemas en la tienda VIP o en la estación de mensajería con dinero real u otros recursos. - Reclamar gemas de las Recompensas Diarias, las Recompensas VIP o los Regalos de la Alianza.</p>
- <h4>Q: ¿Cómo consigo más comandantes? </h4>
-<p>A: Puede obtener más comandantes mediante el uso de diferentes artículos y métodos, tales como: - Abrir cofres que contienen esculturas o estrellas comandante. Puede obtener cofres de varias fuentes, como misiones, eventos, tienda VIP, estación de mensajería, etc. - Usando esculturas de comandante para convocar o actualizar a los comandantes. Puedes conseguir esculturas de comandante de cofres, eventos, Alliance Shop, Expedition Shop, etc. - Usando estrellas para mejorar el nivel de estrellas de tu comandante. Puedes obtener estrellas de cofres, eventos, tienda VIP, estación de mensajería, etc. - Usando esculturas universales o estrellas para convocar o actualizar a cualquier comandante de tu elección. Puedes conseguir esculturas universales o estrellas de cofres, eventos, tienda VIP, Courier Station, etc.</p>
- <h4>Q: ¿Cómo me uno o creo una alianza? </h4>
- <h4>Q: ¿Cómo me pongo en contacto con el servicio de atención al cliente? </h4>
-<p>A: Puede ponerse en contacto con el servicio de atención al cliente siguiendo estos pasos: - Toque en el botón Configuración en la esquina superior derecha de la pantalla. - Toque en el botón de servicio al cliente en la esquina inferior izquierda de la pantalla. - Toque en el botón Contáctenos en la esquina superior derecha de la pantalla. - Complete su información y su problema y toque en Enviar.</p> 64aa2da5cf<br />
-<br />
-<br />

spaces/Big-Web/MMSD/env/Lib/site-packages/dateutil/relativedelta.py DELETED Viewed

@@ -1,599 +0,0 @@
-# -*- coding: utf-8 -*-
-import datetime
-import calendar
-import operator
-from math import copysign
-from six import integer_types
-from warnings import warn
-from ._common import weekday
-MO, TU, WE, TH, FR, SA, SU = weekdays = tuple(weekday(x) for x in range(7))
-__all__ = ["relativedelta", "MO", "TU", "WE", "TH", "FR", "SA", "SU"]
-class relativedelta(object):
-    """
-    The relativedelta type is designed to be applied to an existing datetime and
-    can replace specific components of that datetime, or represents an interval
-    of time.
-    It is based on the specification of the excellent work done by M.-A. Lemburg
-    in his
-    `mx.DateTime <https://www.egenix.com/products/python/mxBase/mxDateTime/>`_ extension.
-    However, notice that this type does *NOT* implement the same algorithm as
-    his work. Do *NOT* expect it to behave like mx.DateTime's counterpart.
-    There are two different ways to build a relativedelta instance. The
-    first one is passing it two date/datetime classes::
-        relativedelta(datetime1, datetime2)
-    The second one is passing it any number of the following keyword arguments::
-        relativedelta(arg1=x,arg2=y,arg3=z...)
-        year, month, day, hour, minute, second, microsecond:
-            Absolute information (argument is singular); adding or subtracting a
-            relativedelta with absolute information does not perform an arithmetic
-            operation, but rather REPLACES the corresponding value in the
-            original datetime with the value(s) in relativedelta.
-        years, months, weeks, days, hours, minutes, seconds, microseconds:
-            Relative information, may be negative (argument is plural); adding
-            or subtracting a relativedelta with relative information performs
-            the corresponding arithmetic operation on the original datetime value
-            with the information in the relativedelta.
-        weekday:
-            One of the weekday instances (MO, TU, etc) available in the
-            relativedelta module. These instances may receive a parameter N,
-            specifying the Nth weekday, which could be positive or negative
-            (like MO(+1) or MO(-2)). Not specifying it is the same as specifying
-            +1. You can also use an integer, where 0=MO. This argument is always
-            relative e.g. if the calculated date is already Monday, using MO(1)
-            or MO(-1) won't change the day. To effectively make it absolute, use
-            it in combination with the day argument (e.g. day=1, MO(1) for first
-            Monday of the month).
-        leapdays:
-            Will add given days to the date found, if year is a leap
-            year, and the date found is post 28 of february.
-        yearday, nlyearday:
-            Set the yearday or the non-leap year day (jump leap days).
-            These are converted to day/month/leapdays information.
-    There are relative and absolute forms of the keyword
-    arguments. The plural is relative, and the singular is
-    absolute. For each argument in the order below, the absolute form
-    is applied first (by setting each attribute to that value) and
-    then the relative form (by adding the value to the attribute).
-    The order of attributes considered when this relativedelta is
-    added to a datetime is:
-    1. Year
-    2. Month
-    3. Day
-    4. Hours
-    5. Minutes
-    6. Seconds
-    7. Microseconds
-    Finally, weekday is applied, using the rule described above.
-    For example
-    >>> from datetime import datetime
-    >>> from dateutil.relativedelta import relativedelta, MO
-    >>> dt = datetime(2018, 4, 9, 13, 37, 0)
-    >>> delta = relativedelta(hours=25, day=1, weekday=MO(1))
-    >>> dt + delta
-    datetime.datetime(2018, 4, 2, 14, 37)
-    First, the day is set to 1 (the first of the month), then 25 hours
-    are added, to get to the 2nd day and 14th hour, finally the
-    weekday is applied, but since the 2nd is already a Monday there is
-    no effect.
-    """
-    def __init__(self, dt1=None, dt2=None,
-                 years=0, months=0, days=0, leapdays=0, weeks=0,
-                 hours=0, minutes=0, seconds=0, microseconds=0,
-                 year=None, month=None, day=None, weekday=None,
-                 yearday=None, nlyearday=None,
-                 hour=None, minute=None, second=None, microsecond=None):
-        if dt1 and dt2:
-            # datetime is a subclass of date. So both must be date
-            if not (isinstance(dt1, datetime.date) and
-                    isinstance(dt2, datetime.date)):
-                raise TypeError("relativedelta only diffs datetime/date")
-            # We allow two dates, or two datetimes, so we coerce them to be
-            # of the same type
-            if (isinstance(dt1, datetime.datetime) !=
-                    isinstance(dt2, datetime.datetime)):
-                if not isinstance(dt1, datetime.datetime):
-                    dt1 = datetime.datetime.fromordinal(dt1.toordinal())
-                elif not isinstance(dt2, datetime.datetime):
-                    dt2 = datetime.datetime.fromordinal(dt2.toordinal())
-            self.years = 0
-            self.months = 0
-            self.days = 0
-            self.leapdays = 0
-            self.hours = 0
-            self.minutes = 0
-            self.seconds = 0
-            self.microseconds = 0
-            self.year = None
-            self.month = None
-            self.day = None
-            self.weekday = None
-            self.hour = None
-            self.minute = None
-            self.second = None
-            self.microsecond = None
-            self._has_time = 0
-            # Get year / month delta between the two
-            months = (dt1.year - dt2.year) * 12 + (dt1.month - dt2.month)
-            self._set_months(months)
-            # Remove the year/month delta so the timedelta is just well-defined
-            # time units (seconds, days and microseconds)
-            dtm = self.__radd__(dt2)
-            # If we've overshot our target, make an adjustment
-            if dt1 < dt2:
-                compare = operator.gt
-                increment = 1
-            else:
-                compare = operator.lt
-                increment = -1
-            while compare(dt1, dtm):
-                months += increment
-                self._set_months(months)
-                dtm = self.__radd__(dt2)
-            # Get the timedelta between the "months-adjusted" date and dt1
-            delta = dt1 - dtm
-            self.seconds = delta.seconds + delta.days * 86400
-            self.microseconds = delta.microseconds
-        else:
-            # Check for non-integer values in integer-only quantities
-            if any(x is not None and x != int(x) for x in (years, months)):
-                raise ValueError("Non-integer years and months are "
-                                 "ambiguous and not currently supported.")
-            # Relative information
-            self.years = int(years)
-            self.months = int(months)
-            self.days = days + weeks * 7
-            self.leapdays = leapdays
-            self.hours = hours
-            self.minutes = minutes
-            self.seconds = seconds
-            self.microseconds = microseconds
-            # Absolute information
-            self.year = year
-            self.month = month
-            self.day = day
-            self.hour = hour
-            self.minute = minute
-            self.second = second
-            self.microsecond = microsecond
-            if any(x is not None and int(x) != x
-                   for x in (year, month, day, hour,
-                             minute, second, microsecond)):
-                # For now we'll deprecate floats - later it'll be an error.
-                warn("Non-integer value passed as absolute information. " +
-                     "This is not a well-defined condition and will raise " +
-                     "errors in future versions.", DeprecationWarning)
-            if isinstance(weekday, integer_types):
-                self.weekday = weekdays[weekday]
-            else:
-                self.weekday = weekday
-            yday = 0
-            if nlyearday:
-                yday = nlyearday
-            elif yearday:
-                yday = yearday
-                if yearday > 59:
-                    self.leapdays = -1
-            if yday:
-                ydayidx = [31, 59, 90, 120, 151, 181, 212,
-                           243, 273, 304, 334, 366]
-                for idx, ydays in enumerate(ydayidx):
-                    if yday <= ydays:
-                        self.month = idx+1
-                        if idx == 0:
-                            self.day = yday
-                        else:
-                            self.day = yday-ydayidx[idx-1]
-                        break
-                else:
-                    raise ValueError("invalid year day (%d)" % yday)
-        self._fix()
-    def _fix(self):
-        if abs(self.microseconds) > 999999:
-            s = _sign(self.microseconds)
-            div, mod = divmod(self.microseconds * s, 1000000)
-            self.microseconds = mod * s
-            self.seconds += div * s
-        if abs(self.seconds) > 59:
-            s = _sign(self.seconds)
-            div, mod = divmod(self.seconds * s, 60)
-            self.seconds = mod * s
-            self.minutes += div * s
-        if abs(self.minutes) > 59:
-            s = _sign(self.minutes)
-            div, mod = divmod(self.minutes * s, 60)
-            self.minutes = mod * s
-            self.hours += div * s
-        if abs(self.hours) > 23:
-            s = _sign(self.hours)
-            div, mod = divmod(self.hours * s, 24)
-            self.hours = mod * s
-            self.days += div * s
-        if abs(self.months) > 11:
-            s = _sign(self.months)
-            div, mod = divmod(self.months * s, 12)
-            self.months = mod * s
-            self.years += div * s
-        if (self.hours or self.minutes or self.seconds or self.microseconds
-                or self.hour is not None or self.minute is not None or
-                self.second is not None or self.microsecond is not None):
-            self._has_time = 1
-        else:
-            self._has_time = 0
-    @property
-    def weeks(self):
-        return int(self.days / 7.0)
-    @weeks.setter
-    def weeks(self, value):
-        self.days = self.days - (self.weeks * 7) + value * 7
-    def _set_months(self, months):
-        self.months = months
-        if abs(self.months) > 11:
-            s = _sign(self.months)
-            div, mod = divmod(self.months * s, 12)
-            self.months = mod * s
-            self.years = div * s
-        else:
-            self.years = 0
-    def normalized(self):
-        """
-        Return a version of this object represented entirely using integer
-        values for the relative attributes.
-        >>> relativedelta(days=1.5, hours=2).normalized()
-        relativedelta(days=+1, hours=+14)
-        :return:
-            Returns a :class:`dateutil.relativedelta.relativedelta` object.
-        """
-        # Cascade remainders down (rounding each to roughly nearest microsecond)
-        days = int(self.days)
-        hours_f = round(self.hours + 24 * (self.days - days), 11)
-        hours = int(hours_f)
-        minutes_f = round(self.minutes + 60 * (hours_f - hours), 10)
-        minutes = int(minutes_f)
-        seconds_f = round(self.seconds + 60 * (minutes_f - minutes), 8)
-        seconds = int(seconds_f)
-        microseconds = round(self.microseconds + 1e6 * (seconds_f - seconds))
-        # Constructor carries overflow back up with call to _fix()
-        return self.__class__(years=self.years, months=self.months,
-                              days=days, hours=hours, minutes=minutes,
-                              seconds=seconds, microseconds=microseconds,
-                              leapdays=self.leapdays, year=self.year,
-                              month=self.month, day=self.day,
-                              weekday=self.weekday, hour=self.hour,
-                              minute=self.minute, second=self.second,
-                              microsecond=self.microsecond)
-    def __add__(self, other):
-        if isinstance(other, relativedelta):
-            return self.__class__(years=other.years + self.years,
-                                 months=other.months + self.months,
-                                 days=other.days + self.days,
-                                 hours=other.hours + self.hours,
-                                 minutes=other.minutes + self.minutes,
-                                 seconds=other.seconds + self.seconds,
-                                 microseconds=(other.microseconds +
-                                               self.microseconds),
-                                 leapdays=other.leapdays or self.leapdays,
-                                 year=(other.year if other.year is not None
-                                       else self.year),
-                                 month=(other.month if other.month is not None
-                                        else self.month),
-                                 day=(other.day if other.day is not None
-                                      else self.day),
-                                 weekday=(other.weekday if other.weekday is not None
-                                          else self.weekday),
-                                 hour=(other.hour if other.hour is not None
-                                       else self.hour),
-                                 minute=(other.minute if other.minute is not None
-                                         else self.minute),
-                                 second=(other.second if other.second is not None
-                                         else self.second),
-                                 microsecond=(other.microsecond if other.microsecond
-                                              is not None else
-                                              self.microsecond))
-        if isinstance(other, datetime.timedelta):
-            return self.__class__(years=self.years,
-                                  months=self.months,
-                                  days=self.days + other.days,
-                                  hours=self.hours,
-                                  minutes=self.minutes,
-                                  seconds=self.seconds + other.seconds,
-                                  microseconds=self.microseconds + other.microseconds,
-                                  leapdays=self.leapdays,
-                                  year=self.year,
-                                  month=self.month,
-                                  day=self.day,
-                                  weekday=self.weekday,
-                                  hour=self.hour,
-                                  minute=self.minute,
-                                  second=self.second,
-                                  microsecond=self.microsecond)
-        if not isinstance(other, datetime.date):
-            return NotImplemented
-        elif self._has_time and not isinstance(other, datetime.datetime):
-            other = datetime.datetime.fromordinal(other.toordinal())
-        year = (self.year or other.year)+self.years
-        month = self.month or other.month
-        if self.months:
-            assert 1 <= abs(self.months) <= 12
-            month += self.months
-            if month > 12:
-                year += 1
-                month -= 12
-            elif month < 1:
-                year -= 1
-                month += 12
-        day = min(calendar.monthrange(year, month)[1],
-                  self.day or other.day)
-        repl = {"year": year, "month": month, "day": day}
-        for attr in ["hour", "minute", "second", "microsecond"]:
-            value = getattr(self, attr)
-            if value is not None:
-                repl[attr] = value
-        days = self.days
-        if self.leapdays and month > 2 and calendar.isleap(year):
-            days += self.leapdays
-        ret = (other.replace(**repl)
-               + datetime.timedelta(days=days,
-                                    hours=self.hours,
-                                    minutes=self.minutes,
-                                    seconds=self.seconds,
-                                    microseconds=self.microseconds))
-        if self.weekday:
-            weekday, nth = self.weekday.weekday, self.weekday.n or 1
-            jumpdays = (abs(nth) - 1) * 7
-            if nth > 0:
-                jumpdays += (7 - ret.weekday() + weekday) % 7
-            else:
-                jumpdays += (ret.weekday() - weekday) % 7
-                jumpdays *= -1
-            ret += datetime.timedelta(days=jumpdays)
-        return ret
-    def __radd__(self, other):
-        return self.__add__(other)
-    def __rsub__(self, other):
-        return self.__neg__().__radd__(other)
-    def __sub__(self, other):
-        if not isinstance(other, relativedelta):
-            return NotImplemented   # In case the other object defines __rsub__
-        return self.__class__(years=self.years - other.years,
-                             months=self.months - other.months,
-                             days=self.days - other.days,
-                             hours=self.hours - other.hours,
-                             minutes=self.minutes - other.minutes,
-                             seconds=self.seconds - other.seconds,
-                             microseconds=self.microseconds - other.microseconds,
-                             leapdays=self.leapdays or other.leapdays,
-                             year=(self.year if self.year is not None
-                                   else other.year),
-                             month=(self.month if self.month is not None else
-                                    other.month),
-                             day=(self.day if self.day is not None else
-                                  other.day),
-                             weekday=(self.weekday if self.weekday is not None else
-                                      other.weekday),
-                             hour=(self.hour if self.hour is not None else
-                                   other.hour),
-                             minute=(self.minute if self.minute is not None else
-                                     other.minute),
-                             second=(self.second if self.second is not None else
-                                     other.second),
-                             microsecond=(self.microsecond if self.microsecond
-                                          is not None else
-                                          other.microsecond))
-    def __abs__(self):
-        return self.__class__(years=abs(self.years),
-                              months=abs(self.months),
-                              days=abs(self.days),
-                              hours=abs(self.hours),
-                              minutes=abs(self.minutes),
-                              seconds=abs(self.seconds),
-                              microseconds=abs(self.microseconds),
-                              leapdays=self.leapdays,
-                              year=self.year,
-                              month=self.month,
-                              day=self.day,
-                              weekday=self.weekday,
-                              hour=self.hour,
-                              minute=self.minute,
-                              second=self.second,
-                              microsecond=self.microsecond)
-    def __neg__(self):
-        return self.__class__(years=-self.years,
-                             months=-self.months,
-                             days=-self.days,
-                             hours=-self.hours,
-                             minutes=-self.minutes,
-                             seconds=-self.seconds,
-                             microseconds=-self.microseconds,
-                             leapdays=self.leapdays,
-                             year=self.year,
-                             month=self.month,
-                             day=self.day,
-                             weekday=self.weekday,
-                             hour=self.hour,
-                             minute=self.minute,
-                             second=self.second,
-                             microsecond=self.microsecond)
-    def __bool__(self):
-        return not (not self.years and
-                    not self.months and
-                    not self.days and
-                    not self.hours and
-                    not self.minutes and
-                    not self.seconds and
-                    not self.microseconds and
-                    not self.leapdays and
-                    self.year is None and
-                    self.month is None and
-                    self.day is None and
-                    self.weekday is None and
-                    self.hour is None and
-                    self.minute is None and
-                    self.second is None and
-                    self.microsecond is None)
-    # Compatibility with Python 2.x
-    __nonzero__ = __bool__
-    def __mul__(self, other):
-        try:
-            f = float(other)
-        except TypeError:
-            return NotImplemented
-        return self.__class__(years=int(self.years * f),
-                             months=int(self.months * f),
-                             days=int(self.days * f),
-                             hours=int(self.hours * f),
-                             minutes=int(self.minutes * f),
-                             seconds=int(self.seconds * f),
-                             microseconds=int(self.microseconds * f),
-                             leapdays=self.leapdays,
-                             year=self.year,
-                             month=self.month,
-                             day=self.day,
-                             weekday=self.weekday,
-                             hour=self.hour,
-                             minute=self.minute,
-                             second=self.second,
-                             microsecond=self.microsecond)
-    __rmul__ = __mul__
-    def __eq__(self, other):
-        if not isinstance(other, relativedelta):
-            return NotImplemented
-        if self.weekday or other.weekday:
-            if not self.weekday or not other.weekday:
-                return False
-            if self.weekday.weekday != other.weekday.weekday:
-                return False
-            n1, n2 = self.weekday.n, other.weekday.n
-            if n1 != n2 and not ((not n1 or n1 == 1) and (not n2 or n2 == 1)):
-                return False
-        return (self.years == other.years and
-                self.months == other.months and
-                self.days == other.days and
-                self.hours == other.hours and
-                self.minutes == other.minutes and
-                self.seconds == other.seconds and
-                self.microseconds == other.microseconds and
-                self.leapdays == other.leapdays and
-                self.year == other.year and
-                self.month == other.month and
-                self.day == other.day and
-                self.hour == other.hour and
-                self.minute == other.minute and
-                self.second == other.second and
-                self.microsecond == other.microsecond)
-    def __hash__(self):
-        return hash((
-            self.weekday,
-            self.years,
-            self.months,
-            self.days,
-            self.hours,
-            self.minutes,
-            self.seconds,
-            self.microseconds,
-            self.leapdays,
-            self.year,
-            self.month,
-            self.day,
-            self.hour,
-            self.minute,
-            self.second,
-            self.microsecond,
-        ))
-    def __ne__(self, other):
-        return not self.__eq__(other)
-    def __div__(self, other):
-        try:
-            reciprocal = 1 / float(other)
-        except TypeError:
-            return NotImplemented
-        return self.__mul__(reciprocal)
-    __truediv__ = __div__
-    def __repr__(self):
-        l = []
-        for attr in ["years", "months", "days", "leapdays",
-                     "hours", "minutes", "seconds", "microseconds"]:
-            value = getattr(self, attr)
-            if value:
-                l.append("{attr}={value:+g}".format(attr=attr, value=value))
-        for attr in ["year", "month", "day", "weekday",
-                     "hour", "minute", "second", "microsecond"]:
-            value = getattr(self, attr)
-            if value is not None:
-                l.append("{attr}={value}".format(attr=attr, value=repr(value)))
-        return "{classname}({attrs})".format(classname=self.__class__.__name__,
-                                             attrs=", ".join(l))
-def _sign(x):
-    return int(copysign(1, x))
-# vim:ts=4:sw=4:et

spaces/Big-Web/MMSD/env/Lib/site-packages/pip/_internal/vcs/__init__.py DELETED Viewed

@@ -1,15 +0,0 @@
-# Expose a limited set of classes and functions so callers outside of
-# the vcs package don't need to import deeper than `pip._internal.vcs`.
-# (The test directory may still need to import from a vcs sub-package.)
-# Import all vcs modules to register each VCS in the VcsSupport object.
-import pip._internal.vcs.bazaar
-import pip._internal.vcs.git
-import pip._internal.vcs.mercurial
-import pip._internal.vcs.subversion  # noqa: F401
-from pip._internal.vcs.versioncontrol import (  # noqa: F401
-    RemoteNotFoundError,
-    RemoteNotValidError,
-    is_url,
-    make_vcs_requirement_url,
-    vcs,
-)

spaces/Big-Web/MMSD/env/Lib/site-packages/pip/_vendor/platformdirs/__main__.py DELETED Viewed

@@ -1,47 +0,0 @@
-from __future__ import annotations
-from pip._vendor.platformdirs import PlatformDirs, __version__
-PROPS = (
-    "user_data_dir",
-    "user_config_dir",
-    "user_cache_dir",
-    "user_state_dir",
-    "user_log_dir",
-    "user_documents_dir",
-    "user_runtime_dir",
-    "site_data_dir",
-    "site_config_dir",
-    "site_cache_dir",
-)
-def main() -> None:
-    app_name = "MyApp"
-    app_author = "MyCompany"
-    print(f"-- platformdirs {__version__} --")
-    print("-- app dirs (with optional 'version')")
-    dirs = PlatformDirs(app_name, app_author, version="1.0")
-    for prop in PROPS:
-        print(f"{prop}: {getattr(dirs, prop)}")
-    print("\n-- app dirs (without optional 'version')")
-    dirs = PlatformDirs(app_name, app_author)
-    for prop in PROPS:
-        print(f"{prop}: {getattr(dirs, prop)}")
-    print("\n-- app dirs (without optional 'appauthor')")
-    dirs = PlatformDirs(app_name)
-    for prop in PROPS:
-        print(f"{prop}: {getattr(dirs, prop)}")
-    print("\n-- app dirs (with disabled 'appauthor')")
-    dirs = PlatformDirs(app_name, appauthor=False)
-    for prop in PROPS:
-        print(f"{prop}: {getattr(dirs, prop)}")
-if __name__ == "__main__":
-    main()

spaces/BilalSardar/Text-To-image-AllModels/README.md DELETED Viewed

@@ -1,13 +0,0 @@
----
-title: Text To Image AllModels
-emoji: 🐠
-colorFrom: blue
-colorTo: indigo
-sdk: gradio
-sdk_version: 3.15.0
-app_file: app.py
-pinned: false
-license: openrail
----
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

spaces/CVPR/Dual-Key_Backdoor_Attacks/datagen/grid-feats-vqa/grid_feats/dataset_mapper.py DELETED Viewed

@@ -1,164 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
-import copy
-import logging
-import numpy as np
-import torch
-from fvcore.common.file_io import PathManager
-from PIL import Image
-from detectron2.data import detection_utils as utils
-from detectron2.data import transforms as T
-from detectron2.data import DatasetMapper
-from detectron2.structures import (
-    BitMasks,
-    Boxes,
-    BoxMode,
-    Instances,
-    Keypoints,
-    PolygonMasks,
-    polygons_to_bitmask,
-)
-def annotations_to_instances_with_attributes(annos,
-                                             image_size,
-                                             mask_format="polygon",
-                                             load_attributes=False,
-                                             max_attr_per_ins=16):
-    """
-    Extend the function annotations_to_instances() to support attributes
-    """
-    boxes = [BoxMode.convert(obj["bbox"], obj["bbox_mode"], BoxMode.XYXY_ABS) for obj in annos]
-    target = Instances(image_size)
-    boxes = target.gt_boxes = Boxes(boxes)
-    boxes.clip(image_size)
-    classes = [obj["category_id"] for obj in annos]
-    classes = torch.tensor(classes, dtype=torch.int64)
-    target.gt_classes = classes
-    if len(annos) and "segmentation" in annos[0]:
-        segms = [obj["segmentation"] for obj in annos]
-        if mask_format == "polygon":
-            masks = PolygonMasks(segms)
-        else:
-            assert mask_format == "bitmask", mask_format
-            masks = []
-            for segm in segms:
-                if isinstance(segm, list):
-                    # polygon
-                    masks.append(polygons_to_bitmask(segm, *image_size))
-                elif isinstance(segm, dict):
-                    # COCO RLE
-                    masks.append(mask_util.decode(segm))
-                elif isinstance(segm, np.ndarray):
-                    assert segm.ndim == 2, "Expect segmentation of 2 dimensions, got {}.".format(
-                        segm.ndim
-                    )
-                    # mask array
-                    masks.append(segm)
-                else:
-                    raise ValueError(
-                        "Cannot convert segmentation of type '{}' to BitMasks!"
-                        "Supported types are: polygons as list[list[float] or ndarray],"
-                        " COCO-style RLE as a dict, or a full-image segmentation mask "
-                        "as a 2D ndarray.".format(type(segm))
-                    )
-            masks = BitMasks(
-                torch.stack([torch.from_numpy(np.ascontiguousarray(x)) for x in masks])
-            )
-        target.gt_masks = masks
-    if len(annos) and "keypoints" in annos[0]:
-        kpts = [obj.get("keypoints", []) for obj in annos]
-        target.gt_keypoints = Keypoints(kpts)
-    if len(annos) and load_attributes:
-        attributes = -torch.ones((len(annos), max_attr_per_ins), dtype=torch.int64)
-        for idx, anno in enumerate(annos):
-            if "attribute_ids" in anno:
-                for jdx, attr_id in enumerate(anno["attribute_ids"]):
-                    attributes[idx, jdx] = attr_id
-        target.gt_attributes = attributes
-    return target
-class AttributeDatasetMapper(DatasetMapper):
-    """
-    Extend DatasetMapper to support attributes.
-    """
-    def __init__(self, cfg, is_train=True):
-        super().__init__(cfg, is_train)
-        # fmt: off
-        self.attribute_on      = cfg.MODEL.ATTRIBUTE_ON
-        self.max_attr_per_ins  = cfg.INPUT.MAX_ATTR_PER_INS
-        # fmt: on
-    def __call__(self, dataset_dict):
-        dataset_dict = copy.deepcopy(dataset_dict)
-        image = utils.read_image(dataset_dict["file_name"], format=self.img_format)
-        utils.check_image_size(dataset_dict, image)
-        if "annotations" not in dataset_dict:
-            image, transforms = T.apply_transform_gens(
-                ([self.crop_gen] if self.crop_gen else []) + self.tfm_gens, image
-            )
-        else:
-            if self.crop_gen:
-                crop_tfm = utils.gen_crop_transform_with_instance(
-                    self.crop_gen.get_crop_size(image.shape[:2]),
-                    image.shape[:2],
-                    np.random.choice(dataset_dict["annotations"]),
-                )
-                image = crop_tfm.apply_image(image)
-            image, transforms = T.apply_transform_gens(self.tfm_gens, image)
-            if self.crop_gen:
-                transforms = crop_tfm + transforms
-        image_shape = image.shape[:2]
-        dataset_dict["image"] = torch.as_tensor(np.ascontiguousarray(image.transpose(2, 0, 1)))
-        if self.load_proposals:
-            utils.transform_proposals(
-                dataset_dict, image_shape, transforms, self.min_box_side_len, self.proposal_topk
-            )
-        if not self.is_train:
-            dataset_dict.pop("annotations", None)
-            dataset_dict.pop("sem_seg_file_name", None)
-            return dataset_dict
-        if "annotations" in dataset_dict:
-            for anno in dataset_dict["annotations"]:
-                if not self.mask_on:
-                    anno.pop("segmentation", None)
-                if not self.keypoint_on:
-                    anno.pop("keypoints", None)
-                if not self.attribute_on:
-                    anno.pop("attribute_ids")
-            annos = [
-                utils.transform_instance_annotations(
-                    obj, transforms, image_shape, keypoint_hflip_indices=self.keypoint_hflip_indices
-                )
-                for obj in dataset_dict.pop("annotations")
-                if obj.get("iscrowd", 0) == 0
-            ]
-            instances = annotations_to_instances_with_attributes(
-                annos, image_shape, mask_format=self.mask_format,
-                load_attributes=self.attribute_on, max_attr_per_ins=self.max_attr_per_ins
-            )
-            if self.crop_gen and instances.has("gt_masks"):
-                instances.gt_boxes = instances.gt_masks.get_bounding_boxes()
-            dataset_dict["instances"] = utils.filter_empty_instances(instances)
-        if "sem_seg_file_name" in dataset_dict:
-            with PathManager.open(dataset_dict.pop("sem_seg_file_name"), "rb") as f:
-                sem_seg_gt = Image.open(f)
-                sem_seg_gt = np.asarray(sem_seg_gt, dtype="uint8")
-            sem_seg_gt = transforms.apply_segmentation(sem_seg_gt)
-            sem_seg_gt = torch.as_tensor(sem_seg_gt.astype("long"))
-            dataset_dict["sem_seg"] = sem_seg_gt
-        return dataset_dict

spaces/CVPR/Dual-Key_Backdoor_Attacks/openvqa/openvqa/datasets/dataset_loader.py DELETED Viewed

@@ -1,29 +0,0 @@
-# --------------------------------------------------------
-# OpenVQA
-# Written by Yuhao Cui https://github.com/cuiyuhao1996
-# --------------------------------------------------------
-from importlib import import_module
-class DatasetLoader:
-    def __init__(self, __C):
-        self.__C = __C
-        self.dataset = __C.DATASET
-        dataset_moudle_path = 'openvqa.datasets.' + self.dataset +'.' + self.dataset + '_loader'
-        self.dataset_moudle = import_module(dataset_moudle_path)
-    def DataSet(self):
-        return self.dataset_moudle.DataSet(self.__C)
-class EvalLoader:
-    def __init__(self, __C):
-        self.__C = __C
-        self.dataset = __C.DATASET
-        eval_moudle_path = 'openvqa.datasets.' + self.dataset + '.' + 'eval' + '.' + 'result_eval'
-        self.eval_moudle = import_module(eval_moudle_path)
-    def eval(self, __arg1, __arg2, __arg3, __arg4, __arg5, __arg6, __arg7):
-        return self.eval_moudle.eval(self.__C, __arg1, __arg2, __arg3, __arg4, __arg5, __arg6, __arg7)

spaces/CVPR/LIVE/pybind11/tests/test_stl.cpp DELETED Viewed

@@ -1,324 +0,0 @@
-/*
-    tests/test_stl.cpp -- STL type casters
-    Copyright (c) 2017 Wenzel Jakob <[email protected]>
-    All rights reserved. Use of this source code is governed by a
-    BSD-style license that can be found in the LICENSE file.
-*/
-#include "pybind11_tests.h"
-#include "constructor_stats.h"
-#include <pybind11/stl.h>
-#include <vector>
-#include <string>
-// Test with `std::variant` in C++17 mode, or with `boost::variant` in C++11/14
-#if PYBIND11_HAS_VARIANT
-using std::variant;
-#elif defined(PYBIND11_TEST_BOOST) && (!defined(_MSC_VER) || _MSC_VER >= 1910)
-#  include <boost/variant.hpp>
-#  define PYBIND11_HAS_VARIANT 1
-using boost::variant;
-namespace pybind11 { namespace detail {
-template <typename... Ts>
-struct type_caster<boost::variant<Ts...>> : variant_caster<boost::variant<Ts...>> {};
-template <>
-struct visit_helper<boost::variant> {
-    template <typename... Args>
-    static auto call(Args &&...args) -> decltype(boost::apply_visitor(args...)) {
-        return boost::apply_visitor(args...);
-    }
-};
-}} // namespace pybind11::detail
-#endif
-PYBIND11_MAKE_OPAQUE(std::vector<std::string, std::allocator<std::string>>);
-/// Issue #528: templated constructor
-struct TplCtorClass {
-    template <typename T> TplCtorClass(const T &) { }
-    bool operator==(const TplCtorClass &) const { return true; }
-};
-namespace std {
-    template <>
-    struct hash<TplCtorClass> { size_t operator()(const TplCtorClass &) const { return 0; } };
-}
-template <template <typename> class OptionalImpl, typename T>
-struct OptionalHolder
-{
-    OptionalHolder() = default;
-    bool member_initialized() const {
-        return member && member->initialized;
-    }
-    OptionalImpl<T> member = T{};
-};
-TEST_SUBMODULE(stl, m) {
-    // test_vector
-    m.def("cast_vector", []() { return std::vector<int>{1}; });
-    m.def("load_vector", [](const std::vector<int> &v) { return v.at(0) == 1 && v.at(1) == 2; });
-    // `std::vector<bool>` is special because it returns proxy objects instead of references
-    m.def("cast_bool_vector", []() { return std::vector<bool>{true, false}; });
-    m.def("load_bool_vector", [](const std::vector<bool> &v) {
-        return v.at(0) == true && v.at(1) == false;
-    });
-    // Unnumbered regression (caused by #936): pointers to stl containers aren't castable
-    static std::vector<RValueCaster> lvv{2};
-    m.def("cast_ptr_vector", []() { return &lvv; });
-    // test_deque
-    m.def("cast_deque", []() { return std::deque<int>{1}; });
-    m.def("load_deque", [](const std::deque<int> &v) { return v.at(0) == 1 && v.at(1) == 2; });
-    // test_array
-    m.def("cast_array", []() { return std::array<int, 2> {{1 , 2}}; });
-    m.def("load_array", [](const std::array<int, 2> &a) { return a[0] == 1 && a[1] == 2; });
-    // test_valarray
-    m.def("cast_valarray", []() { return std::valarray<int>{1, 4, 9}; });
-    m.def("load_valarray", [](const std::valarray<int>& v) {
-        return v.size() == 3 && v[0] == 1 && v[1] == 4 && v[2] == 9;
-    });
-    // test_map
-    m.def("cast_map", []() { return std::map<std::string, std::string>{{"key", "value"}}; });
-    m.def("load_map", [](const std::map<std::string, std::string> &map) {
-        return map.at("key") == "value" && map.at("key2") == "value2";
-    });
-    // test_set
-    m.def("cast_set", []() { return std::set<std::string>{"key1", "key2"}; });
-    m.def("load_set", [](const std::set<std::string> &set) {
-        return set.count("key1") && set.count("key2") && set.count("key3");
-    });
-    // test_recursive_casting
-    m.def("cast_rv_vector", []() { return std::vector<RValueCaster>{2}; });
-    m.def("cast_rv_array", []() { return std::array<RValueCaster, 3>(); });
-    // NB: map and set keys are `const`, so while we technically do move them (as `const Type &&`),
-    // casters don't typically do anything with that, which means they fall to the `const Type &`
-    // caster.
-    m.def("cast_rv_map", []() { return std::unordered_map<std::string, RValueCaster>{{"a", RValueCaster{}}}; });
-    m.def("cast_rv_nested", []() {
-        std::vector<std::array<std::list<std::unordered_map<std::string, RValueCaster>>, 2>> v;
-        v.emplace_back(); // add an array
-        v.back()[0].emplace_back(); // add a map to the array
-        v.back()[0].back().emplace("b", RValueCaster{});
-        v.back()[0].back().emplace("c", RValueCaster{});
-        v.back()[1].emplace_back(); // add a map to the array
-        v.back()[1].back().emplace("a", RValueCaster{});
-        return v;
-    });
-    static std::array<RValueCaster, 2> lva;
-    static std::unordered_map<std::string, RValueCaster> lvm{{"a", RValueCaster{}}, {"b", RValueCaster{}}};
-    static std::unordered_map<std::string, std::vector<std::list<std::array<RValueCaster, 2>>>> lvn;
-    lvn["a"].emplace_back(); // add a list
-    lvn["a"].back().emplace_back(); // add an array
-    lvn["a"].emplace_back(); // another list
-    lvn["a"].back().emplace_back(); // add an array
-    lvn["b"].emplace_back(); // add a list
-    lvn["b"].back().emplace_back(); // add an array
-    lvn["b"].back().emplace_back(); // add another array
-    m.def("cast_lv_vector", []() -> const decltype(lvv) & { return lvv; });
-    m.def("cast_lv_array", []() -> const decltype(lva) & { return lva; });
-    m.def("cast_lv_map", []() -> const decltype(lvm) & { return lvm; });
-    m.def("cast_lv_nested", []() -> const decltype(lvn) & { return lvn; });
-    // #853:
-    m.def("cast_unique_ptr_vector", []() {
-        std::vector<std::unique_ptr<UserType>> v;
-        v.emplace_back(new UserType{7});
-        v.emplace_back(new UserType{42});
-        return v;
-    });
-    // test_move_out_container
-    struct MoveOutContainer {
-        struct Value { int value; };
-        std::list<Value> move_list() const { return {{0}, {1}, {2}}; }
-    };
-    py::class_<MoveOutContainer::Value>(m, "MoveOutContainerValue")
-        .def_readonly("value", &MoveOutContainer::Value::value);
-    py::class_<MoveOutContainer>(m, "MoveOutContainer")
-        .def(py::init<>())
-        .def_property_readonly("move_list", &MoveOutContainer::move_list);
-    // Class that can be move- and copy-constructed, but not assigned
-    struct NoAssign {
-        int value;
-        explicit NoAssign(int value = 0) : value(value) { }
-        NoAssign(const NoAssign &) = default;
-        NoAssign(NoAssign &&) = default;
-        NoAssign &operator=(const NoAssign &) = delete;
-        NoAssign &operator=(NoAssign &&) = delete;
-    };
-    py::class_<NoAssign>(m, "NoAssign", "Class with no C++ assignment operators")
-        .def(py::init<>())
-        .def(py::init<int>());
-    struct MoveOutDetector
-    {
-        MoveOutDetector() = default;
-        MoveOutDetector(const MoveOutDetector&) = default;
-        MoveOutDetector(MoveOutDetector&& other) noexcept
-         : initialized(other.initialized) {
-            // steal underlying resource
-            other.initialized = false;
-        }
-        bool initialized = true;
-    };
-    py::class_<MoveOutDetector>(m, "MoveOutDetector", "Class with move tracking")
-        .def(py::init<>())
-        .def_readonly("initialized", &MoveOutDetector::initialized);
-#ifdef PYBIND11_HAS_OPTIONAL
-    // test_optional
-    m.attr("has_optional") = true;
-    using opt_int = std::optional<int>;
-    using opt_no_assign = std::optional<NoAssign>;
-    m.def("double_or_zero", [](const opt_int& x) -> int {
-        return x.value_or(0) * 2;
-    });
-    m.def("half_or_none", [](int x) -> opt_int {
-        return x ? opt_int(x / 2) : opt_int();
-    });
-    m.def("test_nullopt", [](opt_int x) {
-        return x.value_or(42);
-    }, py::arg_v("x", std::nullopt, "None"));
-    m.def("test_no_assign", [](const opt_no_assign &x) {
-        return x ? x->value : 42;
-    }, py::arg_v("x", std::nullopt, "None"));
-    m.def("nodefer_none_optional", [](std::optional<int>) { return true; });
-    m.def("nodefer_none_optional", [](py::none) { return false; });
-    using opt_holder = OptionalHolder<std::optional, MoveOutDetector>;
-    py::class_<opt_holder>(m, "OptionalHolder", "Class with optional member")
-        .def(py::init<>())
-        .def_readonly("member", &opt_holder::member)
-        .def("member_initialized", &opt_holder::member_initialized);
-#endif
-#ifdef PYBIND11_HAS_EXP_OPTIONAL
-    // test_exp_optional
-    m.attr("has_exp_optional") = true;
-    using exp_opt_int = std::experimental::optional<int>;
-    using exp_opt_no_assign = std::experimental::optional<NoAssign>;
-    m.def("double_or_zero_exp", [](const exp_opt_int& x) -> int {
-        return x.value_or(0) * 2;
-    });
-    m.def("half_or_none_exp", [](int x) -> exp_opt_int {
-        return x ? exp_opt_int(x / 2) : exp_opt_int();
-    });
-    m.def("test_nullopt_exp", [](exp_opt_int x) {
-        return x.value_or(42);
-    }, py::arg_v("x", std::experimental::nullopt, "None"));
-    m.def("test_no_assign_exp", [](const exp_opt_no_assign &x) {
-        return x ? x->value : 42;
-    }, py::arg_v("x", std::experimental::nullopt, "None"));
-    using opt_exp_holder = OptionalHolder<std::experimental::optional, MoveOutDetector>;
-    py::class_<opt_exp_holder>(m, "OptionalExpHolder", "Class with optional member")
-        .def(py::init<>())
-        .def_readonly("member", &opt_exp_holder::member)
-        .def("member_initialized", &opt_exp_holder::member_initialized);
-#endif
-#ifdef PYBIND11_HAS_VARIANT
-    static_assert(std::is_same<py::detail::variant_caster_visitor::result_type, py::handle>::value,
-                  "visitor::result_type is required by boost::variant in C++11 mode");
-    struct visitor {
-        using result_type = const char *;
-        result_type operator()(int) { return "int"; }
-        result_type operator()(std::string) { return "std::string"; }
-        result_type operator()(double) { return "double"; }
-        result_type operator()(std::nullptr_t) { return "std::nullptr_t"; }
-    };
-    // test_variant
-    m.def("load_variant", [](variant<int, std::string, double, std::nullptr_t> v) {
-        return py::detail::visit_helper<variant>::call(visitor(), v);
-    });
-    m.def("load_variant_2pass", [](variant<double, int> v) {
-        return py::detail::visit_helper<variant>::call(visitor(), v);
-    });
-    m.def("cast_variant", []() {
-        using V = variant<int, std::string>;
-        return py::make_tuple(V(5), V("Hello"));
-    });
-#endif
-    // #528: templated constructor
-    // (no python tests: the test here is that this compiles)
-    m.def("tpl_ctor_vector", [](std::vector<TplCtorClass> &) {});
-    m.def("tpl_ctor_map", [](std::unordered_map<TplCtorClass, TplCtorClass> &) {});
-    m.def("tpl_ctor_set", [](std::unordered_set<TplCtorClass> &) {});
-#if defined(PYBIND11_HAS_OPTIONAL)
-    m.def("tpl_constr_optional", [](std::optional<TplCtorClass> &) {});
-#elif defined(PYBIND11_HAS_EXP_OPTIONAL)
-    m.def("tpl_constr_optional", [](std::experimental::optional<TplCtorClass> &) {});
-#endif
-    // test_vec_of_reference_wrapper
-    // #171: Can't return STL structures containing reference wrapper
-    m.def("return_vec_of_reference_wrapper", [](std::reference_wrapper<UserType> p4) {
-        static UserType p1{1}, p2{2}, p3{3};
-        return std::vector<std::reference_wrapper<UserType>> {
-            std::ref(p1), std::ref(p2), std::ref(p3), p4
-        };
-    });
-    // test_stl_pass_by_pointer
-    m.def("stl_pass_by_pointer", [](std::vector<int>* v) { return *v; }, "v"_a=nullptr);
-    // #1258: pybind11/stl.h converts string to vector<string>
-    m.def("func_with_string_or_vector_string_arg_overload", [](std::vector<std::string>) { return 1; });
-    m.def("func_with_string_or_vector_string_arg_overload", [](std::list<std::string>) { return 2; });
-    m.def("func_with_string_or_vector_string_arg_overload", [](std::string) { return 3; });
-    class Placeholder {
-    public:
-        Placeholder() { print_created(this); }
-        Placeholder(const Placeholder &) = delete;
-        ~Placeholder() { print_destroyed(this); }
-    };
-    py::class_<Placeholder>(m, "Placeholder");
-    /// test_stl_vector_ownership
-    m.def("test_stl_ownership",
-          []() {
-              std::vector<Placeholder *> result;
-              result.push_back(new Placeholder());
-              return result;
-          },
-          py::return_value_policy::take_ownership);
-    m.def("array_cast_sequence", [](std::array<int, 3> x) { return x; });
-    /// test_issue_1561
-    struct Issue1561Inner { std::string data; };
-    struct Issue1561Outer { std::vector<Issue1561Inner> list; };
-    py::class_<Issue1561Inner>(m, "Issue1561Inner")
-        .def(py::init<std::string>())
-        .def_readwrite("data", &Issue1561Inner::data);
-    py::class_<Issue1561Outer>(m, "Issue1561Outer")
-        .def(py::init<>())
-        .def_readwrite("list", &Issue1561Outer::list);
-}

spaces/CVPR/LIVE/pydiffvg_tensorflow/image.py DELETED Viewed

@@ -1,22 +0,0 @@
-import numpy as np
-import skimage
-import skimage.io
-import os
-def imwrite(img, filename, gamma = 2.2, normalize = False):
-    directory = os.path.dirname(filename)
-    if directory != '' and not os.path.exists(directory):
-        os.makedirs(directory)
-    if not isinstance(img, np.ndarray):
-        img = img.numpy()
-    if normalize:
-        img_rng = np.max(img) - np.min(img)
-        if img_rng > 0:
-            img = (img - np.min(img)) / img_rng
-    img = np.clip(img, 0.0, 1.0)
-    if img.ndim==2:
-        #repeat along the third dimension
-        img=np.expand_dims(img,2)
-    img[:, :, :3] = np.power(img[:, :, :3], 1.0/gamma)
-    skimage.io.imsave(filename, (img * 255).astype(np.uint8))

spaces/CVPR/regionclip-demo/detectron2/modeling/backbone/build.py DELETED Viewed

@@ -1,48 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-from detectron2.layers import ShapeSpec
-from detectron2.utils.registry import Registry
-from .backbone import Backbone
-BACKBONE_REGISTRY = Registry("BACKBONE")
-BACKBONE_REGISTRY.__doc__ = """
-Registry for backbones, which extract feature maps from images
-The registered object must be a callable that accepts two arguments:
-1. A :class:`detectron2.config.CfgNode`
-2. A :class:`detectron2.layers.ShapeSpec`, which contains the input shape specification.
-Registered object must return instance of :class:`Backbone`.
-"""
-def build_backbone(cfg, input_shape=None):
-    """
-    Build a backbone from `cfg.MODEL.BACKBONE.NAME`.
-    Returns:
-        an instance of :class:`Backbone`
-    """
-    if input_shape is None:
-        input_shape = ShapeSpec(channels=len(cfg.MODEL.PIXEL_MEAN))
-    backbone_name = cfg.MODEL.BACKBONE.NAME
-    backbone = BACKBONE_REGISTRY.get(backbone_name)(cfg, input_shape)
-    assert isinstance(backbone, Backbone)
-    return backbone
-def build_text_backbone(cfg, input_shape=None):
-    """
-    Build a backbone from `cfg.MODEL.BACKBONE.NAME`.
-    Returns:
-        an instance of :class:`Backbone`
-    """
-    if input_shape is None:
-        input_shape = ShapeSpec(channels=len(cfg.MODEL.PIXEL_MEAN))
-    backbone_name = cfg.MODEL.BACKBONE.NAME
-    backbone = BACKBONE_REGISTRY.get(backbone_name)(cfg, input_shape)
-    assert isinstance(backbone, Backbone)
-    return backbone

spaces/ChallengeHub/Chinese-LangChain/corpus/zh_wikipedia/README.md DELETED Viewed

@@ -1,114 +0,0 @@
-## 知识库构建
-###  1 Wikipedia构建
-参考教程：https://blog.51cto.com/u_15127535/2697309
-一、维基百科
-维基百科（Wikipedia），是一个基于维基技术的多语言百科全书协作计划，也是一部用不同语言写成的网络百科全书。维基百科是由吉米·威尔士与拉里·桑格两人合作创建的，于2001年1月13日在互联网上推出网站服务，并在2001年1月15日正式展开网络百科全书的项目。
-二、维基百科处理
-1 环境配置（1）编程语言采用 python3（2）Gensim第三方库，Gensim是一个Python的工具包，其中有包含了中文维基百科数据处理的类，使用方便。
-Gensim : https://github.com/RaRe-Technologies/gensim
-使用 pip install gensim 安装gensim。
-（3）OpenCC第三方库，是中文字符转换，包括中文简体繁体相互转换等。
-OpenCC：https://github.com/BYVoid/OpenCC，OpenCC源码采用c++实现，如果会用c++的可以使用根据介绍，make编译源码。
-OpenCC也有python版本实现，可以通过pip安装（pip install opencc-python），速度要比c++版慢，但是使用方便，安装简单，推荐使用pip安装。
-2 数据下载
-中文维基百科数据按月进行更新备份，一般情况下，下载当前最新的数据，下载地址（https://dumps.wikimedia.org/zhwiki/latest/），我们下载的数据是：zhwiki-latest-pages-articles.xml.bz2。
-中文维基百科数据一般包含如下几个部分：
-训练词向量采用的数据是正文数据，下面我们将对正文数据进行处理。
-3 数据抽取
-下载下来的数据是压缩文件（bz2，gz），不需要解压，这里已经写好了一份利用gensim处理维基百科数据的脚本
-wikidata_processhttps://github.com/bamtercelboo/corpus_process_script/tree/master/wikidata_process
-使用：
-python wiki_process.py zhwiki-latest-pages-articles.xml.bz2 zhwiki-latest.txt
-这部分需要一些的时间，处理过后的得到一份中文维基百科正文数据（zhwiki-latest.txt）。
-输出文件类似于：
-歐幾里得 西元前三世紀的古希臘數學家 現在被認為是幾何之父 此畫為拉斐爾的作品 雅典學院 数学 是利用符号语言研究數量 结构 变化以及空间等概念的一門学科
-4 中文繁体转简体
-经过上述脚本得到的文件包含了大量的中文繁体字，我们需要将其转换成中文简体字。
-我们利用OpenCC进行繁体转简体的操作，这里已经写好了一份python版本的脚本来进行处理
-chinese_t2s
-https://github.com/bamtercelboo/corpus_process_script/tree/master/chinese_t2s
-使用：
-python chinese_t2s.py –input input_file –output output_file
-like:
-python chinese_t2s.py –input zhwiki-latest.txt –output zhwiki-latest-simplified.txt
-输出文件类似于
-欧几里得 西元前三世纪的古希腊数学家 现在被认为是几何之父 此画为拉斐尔的作品 雅典学院 数学 是利用符号语言研究数量 结构 变化以及空间等概念的一门学科
-      5.清洗语料
-上述处理已经得到了我们想要的数据，但是在其他的一些任务中，还需要对这份数据进行简单的处理，像词向量任务，在这得到的数据里，还包含很多的英文，日文，德语，中文标点，乱码等一些字符，我们要把这些字符清洗掉，只留下中文字符，仅仅留下中文字符只是一种处理方案，不同的任务需要不同的处理，这里已经写好了一份脚本
-clean
-https://github.com/bamtercelboo/corpus_process_script/tree/master/clean
-使用：
-python clean_corpus.py –input input_file –output output_file
-like：
-python clean_corpus.py –input zhwiki-latest-simplified.txt –output zhwiki-latest-simplified_cleaned.txt
-效果：
-input:
-哲学	哲学（英语：philosophy）是对普遍的和基本的问题的研究，这些问题通常和存在、知识、价值、理性、心灵、语言等有关。
-output:
-哲学哲学英语是对普遍的和基本的问题的研究这些问题通常和存在知识价值理性心灵语言等有关
-三、数据处理脚本
-近在github上新开了一个Repositorycorpus-process-scripthttps://github.com/bamtercelboo/corpus_process_script在这个repo，将存放中英文数据处理脚本，语言不限，会有详细的README，希望对大家能有一些帮助。
-References

spaces/ChengZ/DeepDanbooru_string0/app.py DELETED Viewed

@@ -1,185 +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 = 'DeepDanbooru String'
-TOKEN = os.environ['TOKEN']
-MODEL_REPO = 'CikeyQI/DeepDanbooru_string'
-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 = "<p>" + "<br>\n".join([f"{html.escape(x)}" for x in text.split('\n')]) + "</p>"
-    return text
-def predict(image: PIL.Image.Image, score_threshold: float,
-            model: tf.keras.Model, labels: list[str]) -> dict[str, float]:
-    rawimage = image
-    _, height, width, _ = model.input_shape
-    image = np.asarray(image)
-    image = tf.image.resize(image,
-                            size=(height, width),
-                            method=tf.image.ResizeMethod.AREA,
-                            preserve_aspect_ratio=True)
-    image = image.numpy()
-    image = dd.image.transform_and_pad_image(image, width, height)
-    image = image / 255.
-    probs = model.predict(image[None, ...])[0]
-    probs = probs.astype(float)
-    res = dict()
-    for prob, label in zip(probs.tolist(), labels):
-        if prob < score_threshold:
-            continue
-        res[label] = prob
-    b = dict(sorted(res.items(),key=lambda item:item[1], reverse=True))
-    a = ', '.join(list(b.keys())).replace('_',' ').replace('(','\(').replace(')','\)')
-    c = ', '.join(list(b.keys()))
-    items = rawimage.info
-    geninfo = ''
-    if "exif" in rawimage.info:
-        exif = piexif.load(rawimage.info["exif"])
-        exif_comment = (exif or {}).get("Exif", {}).get(piexif.ExifIFD.UserComment, b'')
-        try:
-            exif_comment = piexif.helper.UserComment.load(exif_comment)
-        except ValueError:
-            exif_comment = exif_comment.decode('utf8', errors="ignore")
-        items['exif comment'] = exif_comment
-        geninfo = exif_comment
-        for field in ['jfif', 'jfif_version', 'jfif_unit', 'jfif_density', 'dpi', 'exif',
-                      'loop', 'background', 'timestamp', 'duration']:
-            items.pop(field, None)
-    geninfo = items.get('parameters', geninfo)
-    info = f"""
-<p><h4>PNG Info</h4></p>
-"""
-    for key, text in items.items():
-        info += f"""
-<div>
-<p><b>{plaintext_to_html(str(key))}</b></p>
-<p>{plaintext_to_html(str(text))}</p>
-</div>
-""".strip()+"\n"
-    if len(info) == 0:
-        message = "Nothing found in the image."
-        info = f"<div><p>{message}<p></div>"
-    return (a,c,res,info)
-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.Textbox(label='Output (string)'),
-            gr.outputs.Textbox(label='Output (raw string)'),
-            gr.outputs.Label(label='Output (label)'),
-            gr.outputs.HTML()
-        ],
-        examples=[
-        ['miku.jpg',0.5],
-        ['miku2.jpg',0.5]
-        ],
-        title=TITLE,
-        description='''
-Demo for [KichangKim/DeepDanbooru](https://github.com/KichangKim/DeepDanbooru) with "ready to copy" prompt and a prompt analyzer.
-Modified from [hysts/DeepDanbooru](https://huggingface.co/spaces/hysts/DeepDanbooru)
-PNG Info code forked from [AUTOMATIC1111/stable-diffusion-webui](https://github.com/AUTOMATIC1111/stable-diffusion-webui)
-        ''',
-        theme=args.theme,
-        allow_flagging=args.allow_flagging,
-        live=args.live,
-    ).launch(
-        enable_queue=args.enable_queue,
-        server_port=args.port,
-        share=args.share,
-    )
-if __name__ == '__main__':
-    main()

spaces/Clebersla/RVC_V2_Huggingface_Version/i18n/locale_diff.py DELETED Viewed

@@ -1,45 +0,0 @@
-import json
-import os
-from collections import OrderedDict
-# Define the standard file name
-standard_file = "zh_CN.json"
-# Find all JSON files in the directory
-dir_path = "./"
-languages = [
-    f for f in os.listdir(dir_path) if f.endswith(".json") and f != standard_file
-]
-# Load the standard file
-with open(standard_file, "r", encoding="utf-8") as f:
-    standard_data = json.load(f, object_pairs_hook=OrderedDict)
-# Loop through each language file
-for lang_file in languages:
-    # Load the language file
-    with open(lang_file, "r", encoding="utf-8") as f:
-        lang_data = json.load(f, object_pairs_hook=OrderedDict)
-    # Find the difference between the language file and the standard file
-    diff = set(standard_data.keys()) - set(lang_data.keys())
-    miss = set(lang_data.keys()) - set(standard_data.keys())
-    # Add any missing keys to the language file
-    for key in diff:
-        lang_data[key] = key
-    # Del any extra keys to the language file
-    for key in miss:
-        del lang_data[key]
-    # Sort the keys of the language file to match the order of the standard file
-    lang_data = OrderedDict(
-        sorted(lang_data.items(), key=lambda x: list(standard_data.keys()).index(x[0]))
-    )
-    # Save the updated language file
-    with open(lang_file, "w", encoding="utf-8") as f:
-        json.dump(lang_data, f, ensure_ascii=False, indent=4)
-        f.write("\n")

spaces/Cong723/gpt-academic-public/crazy_functions/理解PDF文档内容.py DELETED Viewed

@@ -1,112 +0,0 @@
-from toolbox import update_ui
-from toolbox import CatchException, report_execption
-from .crazy_utils import read_and_clean_pdf_text
-from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
-fast_debug = False
-def 解析PDF(file_name, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt):
-    import tiktoken
-    print('begin analysis on:', file_name)
-    ############################## <第 0 步，切割PDF> ##################################
-    # 递归地切割PDF文件，每一块（尽量是完整的一个section，比如introduction，experiment等，必要时再进行切割）
-    # 的长度必须小于 2500 个 Token
-    file_content, page_one = read_and_clean_pdf_text(file_name) # （尝试）按照章节切割PDF
-    TOKEN_LIMIT_PER_FRAGMENT = 2500
-    from .crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
-    from request_llm.bridge_all import model_info
-    enc = model_info["gpt-3.5-turbo"]['tokenizer']
-    def get_token_num(txt): return len(enc.encode(txt, disallowed_special=()))
-    paper_fragments = breakdown_txt_to_satisfy_token_limit_for_pdf(
-        txt=file_content,  get_token_fn=get_token_num, limit=TOKEN_LIMIT_PER_FRAGMENT)
-    page_one_fragments = breakdown_txt_to_satisfy_token_limit_for_pdf(
-        txt=str(page_one), get_token_fn=get_token_num, limit=TOKEN_LIMIT_PER_FRAGMENT//4)
-    # 为了更好的效果，我们剥离Introduction之后的部分（如果有）
-    paper_meta = page_one_fragments[0].split('introduction')[0].split('Introduction')[0].split('INTRODUCTION')[0]
-    ############################## <第 1 步，从摘要中提取高价值信息，放到history中> ##################################
-    final_results = []
-    final_results.append(paper_meta)
-    ############################## <第 2 步，迭代地历遍整个文章，提取精炼信息> ##################################
-    i_say_show_user = f'首先你在英文语境下通读整篇论文。'; gpt_say = "[Local Message] 收到。"           # 用户提示
-    chatbot.append([i_say_show_user, gpt_say]); yield from update_ui(chatbot=chatbot, history=[])    # 更新UI
-    iteration_results = []
-    last_iteration_result = paper_meta  # 初始值是摘要
-    MAX_WORD_TOTAL = 4096
-    n_fragment = len(paper_fragments)
-    if n_fragment >= 20: print('文章极长，不能达到预期效果')
-    for i in range(n_fragment):
-        NUM_OF_WORD = MAX_WORD_TOTAL // n_fragment
-        i_say = f"Read this section, recapitulate the content of this section with less than {NUM_OF_WORD} words: {paper_fragments[i]}"
-        i_say_show_user = f"[{i+1}/{n_fragment}] Read this section, recapitulate the content of this section with less than {NUM_OF_WORD} words: {paper_fragments[i][:200]}"
-        gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(i_say, i_say_show_user,  # i_say=真正给chatgpt的提问， i_say_show_user=给用户看的提问
-                                                                           llm_kwargs, chatbot,
-                                                                           history=["The main idea of the previous section is?", last_iteration_result], # 迭代上一次的结果
-                                                                           sys_prompt="Extract the main idea of this section."  # 提示
-                                                                        )
-        iteration_results.append(gpt_say)
-        last_iteration_result = gpt_say
-    ############################## <第 3 步，整理history> ##################################
-    final_results.extend(iteration_results)
-    final_results.append(f'接下来，你是一名专业的学术教授，利用以上信息，使用中文回答我的问题。')
-    # 接下来两句话只显示在界面上，不起实际作用
-    i_say_show_user = f'接下来，你是一名专业的学术教授，利用以上信息，使用中文回答我的问题。'; gpt_say = "[Local Message] 收到。"
-    chatbot.append([i_say_show_user, gpt_say])
-    ############################## <第 4 步，设置一个token上限，防止回答时Token溢出> ##################################
-    from .crazy_utils import input_clipping
-    _, final_results = input_clipping("", final_results, max_token_limit=3200)
-    yield from update_ui(chatbot=chatbot, history=final_results) # 注意这里的历史记录被替代了
-@CatchException
-def 理解PDF文档内容标准文件输入(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
-    import glob, os
-    # 基本信息：功能、贡献者
-    chatbot.append([
-        "函数插件功能？",
-        "理解PDF论文内容，并且将结合上下文内容，进行学术解答。函数插件贡献者: Hanzoe, binary-husky"])
-    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
-    # 尝试导入依赖，如果缺少依赖，则给出安装建议
-    try:
-        import fitz
-    except:
-        report_execption(chatbot, history,
-            a = f"解析项目: {txt}",
-            b = f"导入软件依赖失败。使用该模块需要额外依赖，安装方法```pip install --upgrade pymupdf```。")
-        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
-        return
-    # 清空历史，以免输入溢出
-    history = []
-    # 检测输入参数，如没有给定输入参数，直接退出
-    if os.path.exists(txt):
-        project_folder = txt
-    else:
-        if txt == "":
-            txt = '空空如也的输入栏'
-        report_execption(chatbot, history,
-                         a=f"解析项目: {txt}", b=f"找不到本地项目或无权访问: {txt}")
-        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
-        return
-    # 搜索需要处理的文件清单
-    file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.pdf', recursive=True)]
-    # 如果没找到任何文件
-    if len(file_manifest) == 0:
-        report_execption(chatbot, history,
-                         a=f"解析项目: {txt}", b=f"找不到任何.tex或.pdf文件: {txt}")
-        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
-        return
-    txt = file_manifest[0]
-    # 开始正式执行任务
-    yield from 解析PDF(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)

spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/fontTools/misc/cliTools.py DELETED Viewed

@@ -1,52 +0,0 @@
-"""Collection of utilities for command-line interfaces and console scripts."""
-import os
-import re
-numberAddedRE = re.compile(r"#\d+$")
-def makeOutputFileName(
-    input, outputDir=None, extension=None, overWrite=False, suffix=""
-):
-    """Generates a suitable file name for writing output.
-    Often tools will want to take a file, do some kind of transformation to it,
-    and write it out again. This function determines an appropriate name for the
-    output file, through one or more of the following steps:
-    - changing the output directory
-    - appending suffix before file extension
-    - replacing the file extension
-    - suffixing the filename with a number (``#1``, ``#2``, etc.) to avoid
-      overwriting an existing file.
-    Args:
-        input: Name of input file.
-        outputDir: Optionally, a new directory to write the file into.
-        suffix: Optionally, a string suffix is appended to file name before
-            the extension.
-        extension: Optionally, a replacement for the current file extension.
-        overWrite: Overwriting an existing file is permitted if true; if false
-            and the proposed filename exists, a new name will be generated by
-            adding an appropriate number suffix.
-    Returns:
-        str: Suitable output filename
-    """
-    dirName, fileName = os.path.split(input)
-    fileName, ext = os.path.splitext(fileName)
-    if outputDir:
-        dirName = outputDir
-    fileName = numberAddedRE.split(fileName)[0]
-    if extension is None:
-        extension = os.path.splitext(input)[1]
-    output = os.path.join(dirName, fileName + suffix + extension)
-    n = 1
-    if not overWrite:
-        while os.path.exists(output):
-            output = os.path.join(
-                dirName, fileName + suffix + "#" + repr(n) + extension
-            )
-            n += 1
-    return output