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- spaces/101-5/gpt4free/testing/aiservice/README.md +0 -2
- spaces/1acneusushi/gradio-2dmoleculeeditor/data/Avoid Download Proteus 8 Full Crack Google Drive and Use the Genuine Version Instead.md +0 -24
- spaces/1acneusushi/gradio-2dmoleculeeditor/data/Download CSI SAFE 2020 for Free and Discover Its Amazing Features.md +0 -21
- spaces/1acneusushi/gradio-2dmoleculeeditor/data/Ghost Recon Breakpoint PC Walkthrough How to Customize Your Character Use Your Skills and Deal with Enemies.md +0 -47
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- spaces/AIGC-Audio/AudioGPT/NeuralSeq/vocoders/vocoder_utils.py +0 -15
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- spaces/AchyuthGamer/OpenGPT-Chat-UI/.svelte-kit/types/src/routes/conversation/[id]/message/[messageId]/prompt/$types.d.ts +0 -9
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spaces/101-5/gpt4free/testing/aiservice/README.md
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https://github.com/xtekky/gpt4free/issues/40#issuecomment-1629152431
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spaces/1acneusushi/gradio-2dmoleculeeditor/data/Avoid Download Proteus 8 Full Crack Google Drive and Use the Genuine Version Instead.md
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<h1>Download Proteus 8 Full Crack Google Drive: How to Do It and Why You Should Avoid It</h1>
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<li><b>It is illegal.</b> Downloading and using Proteus 8 full crack from Google Drive is a violation of the software's terms and conditions and intellectual property rights. You may face legal action from the software developer or the authorities if you are caught using pirated software.</li>
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spaces/1acneusushi/gradio-2dmoleculeeditor/data/Download CSI SAFE 2020 for Free and Discover Its Amazing Features.md
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<p>Note that the trial version of CSI SAFE 2020 is for evaluation purposes only and cannot be used for commercial or academic projects. If you want to use the software for longer or for professional purposes, you will need to purchase a license from CSI or their authorized resellers.</p><p>CSI SAFE 2020 is a comprehensive software for designing and analyzing concrete slabs and foundations. It can handle various types of slabs, such as flat, waffle, ribbed, mat, and composite. It can also design and detail foundations, such as isolated, combined, strip, pile cap, and mat.</p>
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spaces/1acneusushi/gradio-2dmoleculeeditor/data/Ghost Recon Breakpoint PC Walkthrough How to Customize Your Character Use Your Skills and Deal with Enemies.md
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<h1>Ghost Recon Breakpoint PC Walkthrough: Tips and Tricks for Surviving the Open World</h1>
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<p>If you are looking for a ghost recon breakpoint pc walkthrough, you have come to the right place. Ghost Recon Breakpoint is a tactical shooter game that puts you in the shoes of a special forces soldier who has to survive on a hostile island. The game features a vast open world that you can explore, complete missions, and engage in combat with enemies. However, the game can also be challenging and overwhelming, especially for beginners. That's why we have prepared this ghost recon breakpoint pc walkthrough to help you out.</p>
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<p>In this ghost recon breakpoint pc walkthrough, we will cover some basic tips and tricks that will make your life easier in the game. We will also give you some pointers on how to customize your character, use your skills and gadgets, and deal with different types of enemies. Whether you are playing solo or co-op, this ghost recon breakpoint pc walkthrough will help you enjoy the game more.</p>
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<h2>Customize Your Character</h2>
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<p>One of the first things you should do in Ghost Recon Breakpoint is to customize your character. You can choose from different classes, each with their own abilities and perks. You can also change your appearance, gear, and weapons. You can access the customization menu by pressing I on your keyboard or by visiting a bivouac (a campsite where you can rest and prepare).</p>
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<p>The four classes available in Ghost Recon Breakpoint are:</p>
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<ul>
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<li>Assault: This class is good for aggressive players who like to deal damage and take hits. They have increased health and can use an adrenaline rush ability that boosts their damage and resistance.</li>
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<li>Sharpshooter: This class is good for stealthy players who like to snipe enemies from afar. They have increased accuracy and can use a sensor launcher ability that reveals enemies' locations.</li>
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<li>Panther: This class is good for sneaky players who like to infiltrate enemy bases and avoid detection. They have increased stealth and can use a cloaking spray ability that makes them invisible for a short time.</li>
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<li>Medic: This class is good for supportive players who like to heal and revive their teammates. They have increased revive speed and can use a drone healer ability that heals themselves and their allies.</li>
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</ul>
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<p>You can switch between classes at any time by visiting a bivouac. You can also unlock new skills and perks for each class by earning skill points and completing challenges.</p>
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<h2>Use Your Skills and Gadgets</h2>
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<p>Another important aspect of Ghost Recon Breakpoint is to use your skills and gadgets effectively. You have access to a skill tree that lets you unlock various abilities that enhance your combat, survival, and reconnaissance capabilities. You can spend skill points to unlock new skills or upgrade existing ones. You can also equip different gadgets that give you an edge in different situations.</p>
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<p>Some of the most useful skills and gadgets in Ghost Recon Breakpoint are:</p>
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<ul>
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<li>Binoculars: These allow you to scout the area and mark enemies, vehicles, and resources. You can also use them to sync shot enemies with your teammates or your AI companions.</li>
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<li>Drones: These are remote-controlled devices that you can use to scout, distract, or attack enemies. You can also use them to hack enemy drones or vehicles.</li>
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<li>Syringes: These are consumable items that you can use to heal yourself or your teammates. You can also use them to cure injuries or status effects.</li>
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<li>Mines: These are explosive devices that you can place on the ground or on walls. They will detonate when an enemy comes near them or when you trigger them manually.</li>
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<li>C4: These are explosive charges that you can place on vehicles, doors, or generators. They will detonate when you trigger them manually or when an enemy shoots them.</li>
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</ul>
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<p>You can access your skills and gadgets by pressing TAB on your keyboard or by using the wheel menu. You can also craft new gadgets or refill your ammo at bivouacs or ammo crates.</p>
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<h2>Deal with Different Types of Enemies</h2>
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<p>The last thing we will cover in this ghost recon breakpoint pc walkthrough is how to deal with different types of enemies. The game features a variety of enemies that have different behaviors, weapons, and weaknesses. You will need to adapt your strategy depending on the enemy you are facing.</p>
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spaces/1gistliPinn/ChatGPT4/Examples/Catalogo De Sellos Edifil Espana 2012 Pdf LINK.md
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<h1>Catalogo De Sellos Edifil Espana 2012 Pdf: una guía para los amantes de la filatelia</h1>
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<li>Es un catálogo gratuito, que se puede descargar sin ningún coste y sin necesidad de registrarse en ninguna página web.</li>
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| 19 |
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<li>Es un catálogo útil y práctico, que te permite conocer el valor de mercado de tus sellos y planificar tus compras y ventas.</li>
|
| 20 |
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<li>Es un catálogo interesante y educativo, que te permite aprender sobre la historia, la cultura y el arte de España y sus territorios a través de sus sellos.</li>
|
| 21 |
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</ul>
|
| 22 |
-
|
| 23 |
-
<h3>¿Cómo descargar el Catalogo De Sellos Edifil Espana 2012 Pdf?</h3>
|
| 24 |
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|
| 25 |
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<p>Descargar el <strong>Catalogo De Sellos Edifil Espana 2012 Pdf</strong> es muy sencillo. Solo tienes que seguir estos pasos:</p>
|
| 26 |
-
|
| 27 |
-
<ol>
|
| 28 |
-
<li>Entra en el buscador de internet de tu preferencia y escribe el nombre del catálogo: <strong>Catalogo De Sellos Edifil Espana 2012 Pdf</strong>.</li>
|
| 29 |
-
<li>Selecciona uno de los resultados que te aparecen y haz clic en él. Te llevará a una página web donde podrás ver el catálogo online o descargarlo en formato PDF.</li>
|
| 30 |
-
<li>Si quieres ver el catálogo online, solo tienes que desplazarte por las páginas y hacer zoom para ampliar las imágenes. Si quieres descargarlo en formato PDF, solo tienes que hacer clic en el botón de descarga y elegir la carpeta donde quieres guardarlo.</li>
|
| 31 |
-
<li>Una vez descargado el catálogo en tu dispositivo electrónico, podrás abrirlo con cualquier programa que lea archivos PDF y disfrutar de él siempre que quieras.</li>
|
| 32 |
-
</ol>
|
| 33 |
-
|
| 34 |
-
<p>Así de fácil es obtener el <strong>Catalogo De Sellos Edifil Espana 2012 Pdf</strong>, un documento imprescindible para los amantes de la filatelia. No esperes más y descárgalo ya. Te sorprenderá la cantidad y la calidad de los sellos que contiene.</p>
|
| 35 |
-
<h4>¿Qué sellos puedes encontrar en el Catalogo De Sellos Edifil Espana 2012 Pdf?</h4>
|
| 36 |
-
|
| 37 |
-
<p>El <strong>Catalogo De Sellos Edifil Espana 2012 Pdf</strong> te ofrece una gran variedad de sellos de diferentes épocas, temáticas y estilos. Algunos de los sellos que puedes encontrar son:</p>
|
| 38 |
-
<p></p>
|
| 39 |
-
|
| 40 |
-
<ul>
|
| 41 |
-
<li>Sellos de los antiguos estados italianos, como el Reino de Vittorio Emanuele II, el Reino de Italia, la R.S.I., la Luogotenenza, Trieste A y B, Fiume y las ocupaciones extranjeras.</li>
|
| 42 |
-
<li>Sellos de las antiguas colonias españolas, como Andorra, Somalia A.F.I., los oficinas postales en el extranjero y las emisiones locales.</li>
|
| 43 |
-
<li>Sellos del periodo de la Primera Guerra Mundial y la Segunda Guerra Mundial, con las ocupaciones italianas y las ocupaciones extranjeras de territorios españoles.</li>
|
| 44 |
-
<li>Sellos de San Marino, el Vaticano y el S.M. Orden de Malta, con sus respectivas series básicas y conmemorativas.</li>
|
| 45 |
-
<li>Sellos de España desde 1850 hasta 2012, con sus diferentes series filatélicas, como la serie básica del Rey Juan Carlos I, la serie turística y monumental, la serie América-UPAEP, la serie pintura española, la serie faros, la serie micología, la serie bailes populares y la serie moda española.</li>
|
| 46 |
-
</ul>
|
| 47 |
-
|
| 48 |
-
<h5>¿Cómo usar el Catalogo De Sellos Edifil Espana 2012 Pdf?</h5>
|
| 49 |
-
|
| 50 |
-
<p>El <strong>Catalogo De Sellos Edifil Espana 2012 Pdf</strong> es una herramienta muy útil para los coleccionistas y aficionados a la filatelia. Para usarlo correctamente, debes tener en cuenta lo siguiente:</p>
|
| 51 |
-
|
| 52 |
-
<ol>
|
| 53 |
-
<li>Identifica el sello que quieres consultar y busca su número de catálogo en el índice alfabético o en el índice temático.</li>
|
| 54 |
-
<li>Localiza el sello en el catálogo y compara su imagen con la del sello real. Fíjate en los detalles como el color, el dentado, la impresión y las marcas.</li>
|
| 55 |
-
<li>Lee la descripción del sello y anota su valor facial, su fecha de emisión, su tirada y su cotización. También puedes ver si el sello forma parte de una serie o de una hojita bloque.</li>
|
| 56 |
-
<li>Repite el proceso con todos los sellos que quieras consultar y clasifica tu colección según tus criterios personales.</li>
|
| 57 |
-
</ol>
|
| 58 |
-
|
| 59 |
-
<p>El <strong>Catalogo De Sellos Edifil Espana 2012 Pdf</strong> es un documento imprescindible para los amantes de la filatelia. No esperes más y descárgalo ya. Te sorprenderá la cantidad y la calidad de los sellos que contiene.</p>
|
| 60 |
-
<h6>¿Qué otras publicaciones puedes encontrar en Edifil?</h6>
|
| 61 |
-
|
| 62 |
-
<p>Edifil es una editorial especializada en filatelia que lleva más de 80 años ofreciendo productos y servicios de calidad a los coleccionistas. Además del <strong>Catalogo De Sellos Edifil Espana 2012 Pdf</strong>, puedes encontrar otras publicaciones interesantes, como:</p>
|
| 63 |
-
|
| 64 |
-
<ul>
|
| 65 |
-
<li>Catálogos de sellos de otros países y regiones, como Portugal, Andorra, Francia, Europa Occidental, Europa Oriental, América del Sur, América Central y Caribe, África y Asia.</li>
|
| 66 |
-
<li>Catálogos de otros temas filatélicos, como sellos de correo aéreo, sellos de correo marítimo, sellos de correo ferroviario, sellos de correo militar, sellos de entero postal y sellos de prefilatelia.</li>
|
| 67 |
-
<li>Catálogos de otras editoriales y asociaciones filatélicas, como Yvert et Tellier, Ángel Laiz, Federación Española de Sociedades Filatélicas y Federación Internacional de Filatelia.</li>
|
| 68 |
-
<li>Revistas y libros sobre filatelia, historia postal y cultura general, con artículos, reportajes, entrevistas, noticias y curiosidades.</li>
|
| 69 |
-
</ul>
|
| 70 |
-
|
| 71 |
-
<h7>¿Cómo comprar el Catalogo De Sellos Edifil Espana 2012 Pdf?</h7>
|
| 72 |
-
|
| 73 |
-
<p>Si quieres comprar el <strong>Catalogo De Sellos Edifil Espana 2012 Pdf</strong>, tienes varias opciones. Puedes hacerlo a través de la página web de Edifil, donde podrás pagar con tarjeta de crédito o débito, PayPal o transferencia bancaria. También puedes hacerlo por teléfono o por correo electrónico, indicando tus datos personales y la forma de pago. Otra opción es acudir a una librería o tienda especializada en filatelia y solicitar el catálogo.</p>
|
| 74 |
-
|
| 75 |
-
<p>El precio del <strong>Catalogo De Sellos Edifil Espana 2012 Pdf</strong> es de 35 euros (IVA incluido) y los gastos de envío son gratuitos para España peninsular. Para otros destinos, consulta las tarifas en la página web de Edifil o contacta con el servicio de atención al cliente.</p>
|
| 76 |
-
|
| 77 |
-
<p>No lo dudes más y compra ya el <strong>Catalogo De Sellos Edifil Espana 2012 Pdf</strong>, un catálogo imprescindible para los amantes de la filatelia. Te sorprenderá la cantidad y la calidad de los sellos que contiene.</p>
|
| 78 |
-
<h11>¿Qué beneficios tiene la filatelia para tu salud mental?</h11>
|
| 79 |
-
|
| 80 |
-
<p>La filatelia es una afición que te puede aportar muchos beneficios para tu salud mental. Algunos de ellos son:</p>
|
| 81 |
-
|
| 82 |
-
<ul>
|
| 83 |
-
<li>Te ayuda a relajarte y a reducir el estrés, ya que te permite desconectar de las preocupaciones y los problemas del día a día.</li>
|
| 84 |
-
<li>Te estimula la memoria y la atención, ya que te obliga a recordar y a observar los detalles de los sellos y su historia.</li>
|
| 85 |
-
<li>Te fomenta la creatividad y la imaginación, ya que te permite crear tu propia colección y personalizarla según tus gustos y preferencias.</li>
|
| 86 |
-
<li>Te enriquece culturalmente, ya que te permite aprender sobre la historia, la geografía, el arte, la ciencia y la sociedad de diferentes países y épocas a través de los sellos.</li>
|
| 87 |
-
<li>Te facilita el contacto social, ya que te permite compartir tu afición con otras personas que tienen los mismos intereses y pasiones que tú.</li>
|
| 88 |
-
</ul>
|
| 89 |
-
|
| 90 |
-
<p>La filatelia es una afición que te puede hacer más feliz y más inteligente. No lo dudes y descarga ya el <strong>Catalogo De Sellos Edifil Espana 2012 Pdf</strong>, un catálogo imprescindible para los amantes de la filatelia. Te sorprenderá la cantidad y la calidad de los sellos que contiene.</p>
|
| 91 |
-
|
| 92 |
-
<h12>¿Cómo vender tus sellos online?</h12>
|
| 93 |
-
|
| 94 |
-
<p>Si tienes una colección de sellos que quieres vender online, puedes seguir algunos consejos que te ayudarán a hacerlo de forma segura y rentable. Algunos de ellos son:</p>
|
| 95 |
-
|
| 96 |
-
<ol>
|
| 97 |
-
<li>Valora tus sellos correctamente, usando el <strong>Catalogo De Sellos Edifil Espana 2012 Pdf</strong> como referencia. Ten en cuenta el estado de conservación, la rareza y la demanda de tus sellos.</li>
|
| 98 |
-
<li>Elige una plataforma adecuada para vender tus sellos online, como eBay, Delcampe, Todocolección o Filatelia.com. Compara las comisiones, las condiciones y las opiniones de otros vendedores.</li>
|
| 99 |
-
<li>Prepara una descripción detallada y honesta de tus sellos, incluyendo el número de catálogo, el valor facial, la fecha de emisión, el dentado, la impresión y las posibles defectos o marcas. Acompaña tu descripción con fotos claras y nítidas de tus sellos.</li>
|
| 100 |
-
<li>Fija un precio justo y competitivo para tus sellos, basándote en el valor de mercado y en los precios de otros vendedores. Puedes optar por un precio fijo o por una subasta.</li>
|
| 101 |
-
<li>Cuida el embalaje y el envío de tus sellos, usando sobres acolchados o rígidos, fundas protectoras y etiquetas identificativas. Ofrece varias opciones de envío y seguimiento a tus compradores.</li>
|
| 102 |
-
</ol>
|
| 103 |
-
|
| 104 |
-
<p>Vender tus sellos online puede ser una forma fácil y rápida de obtener un dinero extra por tu colección. Solo necesitas el <strong>Catalogo De Sellos Edifil Espana 2012 Pdf</strong>, una buena conexión a internet y un poco de paciencia. ¡Suerte con tu venta!</p>
|
| 105 |
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<h13>Conclusión</h13>
|
| 106 |
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|
| 107 |
-
<p>El <strong>Catalogo De Sellos Edifil Espana 2012 Pdf</strong> es un documento imprescindible para los amantes de la filatelia. Es un catálogo completo y actualizado que recoge todos los sellos emitidos por España y sus dependencias postales desde 1850 hasta 2012. Es un catálogo gratuito que se puede descargar fácilmente desde internet y que ofrece una información detallada y una calidad gráfica excelente de cada sello. Es un catálogo útil y práctico que te permite conocer el valor de mercado de tus sellos y planificar tus compras y ventas. Es un catálogo interesante y educativo que te permite aprender sobre la historia, la cultura y el arte de España y sus territorios a través de sus sellos.</p>
|
| 108 |
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|
| 109 |
-
<p>En este artículo, te hemos explicado qué es el <strong>Catalogo De Sellos Edifil Espana 2012 Pdf</strong>, qué ventajas tiene, cómo descargarlo, qué sellos puedes encontrar en él, qué otras publicaciones puedes encontrar en Edifil, qué opinan los usuarios del catálogo, qué beneficios tiene la filatelia para tu salud mental y cómo vender tus sellos online. Esperamos que te haya sido útil y que te animes a descargar el catálogo y a disfrutar de tu afición a la filatelia.</p>
|
| 110 |
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|
| 111 |
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<p>Si te ha gustado este artículo, compártelo con tus amigos y déjanos un comentario con tu opinión. También puedes suscribirte a nuestro boletín para recibir más artículos sobre filatelia y otros temas de tu interés. ¡Gracias por leernos!</p> 3cee63e6c2<br />
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spaces/1pelhydcardo/ChatGPT-prompt-generator/assets/Car Parking Multiplayer APK Download for PC - Free Simulation Game with Car Tuning and Free Walking.md
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<h1>How to Download Car Parking Multiplayer APK for PC</h1>
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<p>Car Parking Multiplayer is a realistic driving simulator game for Android devices that lets you explore a detailed city, customize your cars, and compete with other players online. If you are a fan of this game and want to play it on a bigger screen with better controls, you might be wondering how to download car parking multiplayer apk for PC. In this article, we will show you two ways to play car parking multiplayer on your PC, either with Windows 11 or with Android emulators.</p>
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<h2>What is Car Parking Multiplayer?</h2>
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<p>Car Parking Multiplayer is a game developed by olzhass that simulates various aspects of driving and parking in a realistic 3D environment. You can choose from over 100 different cars, from sports cars to trucks, and customize them with various parts and accessories. You can also interact with other players in online multiplayer mode, chat with them, exchange cars, or challenge them to races and drifts. You can also explore the open-world city, which has different areas such as airports, beaches, deserts, and more. You can also find hidden places and secrets in the city, such as a tank or a UFO.</p>
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<h3>Features of Car Parking Multiplayer</h3>
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<p>Some of the features of car parking multiplayer are:</p>
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<ul>
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<li>Realistic car physics and damage system</li>
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<li>Manual transmission with clutch and gear shifting</li>
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<li>Dynamic weather and day-night cycle</li>
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<li>Free walking mode and interactive elements</li>
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<li>Car tuning and customization</li>
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<li>Online multiplayer mode with voice chat</li>
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<li>Different game modes such as racing, drifting, free ride, and more</li>
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<li>Over 100 cars and 82 real-life parking scenarios</li>
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<li>Frequent updates and new content</li>
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</ul>
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<h3>Requirements for Car Parking Multiplayer</h3>
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<p>To play car parking multiplayer on your Android device, you need to have:</p>
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<ul>
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<li>An Android device running version 5.0 or higher</li>
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<li>At least 900 MB of free storage space</li>
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<li>A stable internet connection for online mode</li>
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<li>An optional gamepad or steering wheel for better control</li>
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</ul>
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<p>While car parking multiplayer is designed for mobile devices, some players might prefer to play it on their PC for various reasons. Here are some of the advantages and disadvantages of playing car parking multiplayer on PC.</p>
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| 82 |
-
<li>Better controls and performance: You can use your keyboard and mouse or a controller to control your car more precisely and comfortably. You can also adjust the game settings to optimize the performance and reduce lag or crashes.</li>
|
| 83 |
-
<li>Easier communication and recording: You can use your PC's microphone and speakers to communicate with other players more clearly and conveniently. You can also use your PC's software to record or stream your gameplay or share it with others.</li>
|
| 84 |
-
<li>More options and features: You can access more features and options on your PC, such as modding, cheats, or hacks, that might not be available or safe on your mobile device.</li>
|
| 85 |
-
</ul>
|
| 86 |
-
<h3>Disadvantages of Playing on PC</h3>
|
| 87 |
-
<p>Some of the drawbacks of playing car parking multiplayer on PC are:</p>
|
| 88 |
-
<ul>
|
| 89 |
-
<li>Compatibility and security issues: You might encounter some compatibility or security issues when playing car parking multiplayer on PC, such as errors, bugs, viruses, or malware. You might also need to update your PC's drivers or software to run the game smoothly.</li>
|
| 90 |
-
<li>Higher cost and space: You might need to spend more money and space to play car parking multiplayer on PC, such as buying a PC, a monitor, a controller, or an emulator. You might also need to download and install additional files or programs to play the game.</li>
|
| 91 |
-
<li>Less mobility and convenience: You might lose some of the mobility and convenience of playing car parking multiplayer on your mobile device, such as playing anywhere, anytime, or with anyone. You might also need to switch between devices or accounts to sync your progress or data.</li>
|
| 92 |
-
</ul>
|
| 93 |
-
<h2>How to Play Car Parking Multiplayer on PC with Windows 11</h2>
|
| 94 |
-
<p>One of the ways to play car parking multiplayer on PC is to use Windows 11, the latest operating system from Microsoft that supports Android apps natively. This means that you can run Android apps on your PC without using any emulators or third-party software. Here are the steps to play car parking multiplayer on PC with Windows 11.</p>
|
| 95 |
-
<h3>Steps to Install Windows Subsystem for Android</h3>
|
| 96 |
-
<p>Before you can install and play car parking multiplayer on your PC with Windows 11, you need to enable the Windows Subsystem for Android (WSA), which is the feature that allows you to run Android apps on your PC. Here are the steps to install WSA:</p>
|
| 97 |
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<ol>
|
| 98 |
-
<li>Open the Start menu and search for "Turn Windows features on or off". Click on it to open a new window.</li>
|
| 99 |
-
<li>Scroll down and find "Windows Subsystem for Android". Check the box next to it and click OK.</li>
|
| 100 |
-
<li>Wait for the installation process to complete and restart your PC if prompted.</li>
|
| 101 |
-
<li>Open the Microsoft Store app and search for "Windows Subsystem for Android". Click on it and install it on your PC.</li>
|
| 102 |
-
<li>Wait for the installation process to complete and launch WSA from the Start menu.</li>
|
| 103 |
-
</ol>
|
| 104 |
-
<h3>Steps to Install Car Parking Multiplayer from Amazon Appstore</h3>
|
| 105 |
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<p>After you have installed WSA on your PC, you can install car parking multiplayer from the Amazon Appstore, which is the default app store for WSA. Here are the steps to install car parking multiplayer from Amazon Appstore:</p>
|
| 106 |
-
<ol>
|
| 107 |
-
<li>Open WSA from the Start menu and click on the Amazon Appstore icon.</li>
|
| 108 |
-
<li>Sign in with your Amazon account or create a new one if you don't have one.</li>
|
| 109 |
-
<li>Search for "Car Parking Multiplayer" in the search bar and click on it.</li>
|
| 110 |
-
<li>Click on the "Get" button and wait for the download and installation process to complete.</li>
|
| 111 |
-
<li>Click on the "Open" button or find car parking multiplayer in your app list and launch it.</li>
|
| 112 |
-
</ol>
|
| 113 |
-
<h3>Steps to Install Google Play Store on Windows 11 (Optional)</h3>
|
| 114 |
-
<p>If you prefer to use Google Play Store instead of Amazon Appstore to install car parking multiplayer on your PC with Windows 11, you can do so by following these steps:</p>
|
| 115 |
-
<ol>
|
| 116 |
-
<li>Download the Google Play Store APK file from a trusted source, such as APKMirror or APKPure.</li>
|
| 117 |
-
<li>Open WSA from the Start menu and click on the Settings icon.</li>
|
| 118 |
-
<li>Select "Developer mode" from the left panel and enable it by clicking on the toggle switch.</li>
|
| 119 |
-
<li>Select "File Explorer" from the left panel and click on "Choose Folder".</li>
|
| 120 |
-
<li>Select a folder where you want to store your APK files and click OK.</li>
|
| 121 |
-
<li>Copy and paste the Google Play Store APK file into that folder.</li>
|
| 122 |
-
<li>Select "Apps" from the left panel and click on "Refresh".</li>
|
| 123 |
-
<li>Select Google Play Store from the app list and click on "Install".</li>
|
| 124 |
-
<li>Wait for the installation process to complete and launch Google Play Store from your app list.</li>
|
| 125 |
-
<li>Sign in with your Google account or create a new one if you don't have one.</li>
|
| 126 |
-
<li>Search for "Car Parking Multiplayer" in the search bar and install it as usual.</li>
|
| 127 |
-
</ol>
|
| 128 |
-
<h2>How to Play Car Parking Multiplayer on PC with Android Emulators</h2>
|
| 129 |
-
<p>Another way to play car parking multiplayer on PC is to use Android emulators, which are software that mimic the Android operating system on your PC. This way, you can run any Android app or game on your PC as if you were using a mobile device. Here are some of the things you need to know about Android emulators and how to use them to play car parking multiplayer on PC.</p>
|
| 130 |
-
<h3>What are Android Emulators?</h3>
|
| 131 |
-
<p>Android emulators are programs that create a virtual Android device on your PC, allowing you to run Android apps and games on your PC. They usually have a user interface that resembles a smartphone or a tablet, and they let you access the Google Play Store or other app stores to download and install apps. Some of the benefits of using Android emulators are:</p>
|
| 132 |
-
<ul>
|
| 133 |
-
<li>You can play Android games on your PC with better graphics, performance, and controls.</li>
|
| 134 |
-
<li>You can use multiple Android apps at the same time on your PC, such as messaging, social media, or productivity apps.</li>
|
| 135 |
-
<li>You can test and debug Android apps on your PC without using a physical device.</li>
|
| 136 |
-
<li>You can use Android apps that are not compatible with your mobile device or region.</li>
|
| 137 |
-
</ul>
|
| 138 |
-
<p>However, some of the drawbacks of using Android emulators are:</p>
|
| 139 |
-
<ul>
|
| 140 |
-
<li>You might need a powerful PC to run Android emulators smoothly and without lag or crashes.</li>
|
| 141 |
-
<li>You might encounter some compatibility or security issues when using Android emulators, such as errors, bugs, viruses, or malware.</li>
|
| 142 |
-
<li>You might need to update your Android emulators regularly to keep up with the latest Android versions and features.</li>
|
| 143 |
-
<li>You might violate some terms of service or policies when using Android emulators, especially for online games or apps that detect emulator usage.</li>
|
| 144 |
-
</ul>
|
| 145 |
-
<h3>Best Android Emulators for Car Parking Multiplayer</h3>
|
| 146 |
-
<p>There are many Android emulators available for PC, but not all of them are suitable for playing car parking multiplayer. Some of the factors that you need to consider when choosing an Android emulator for car parking multiplayer are:</p>
|
| 147 |
-
<ul>
|
| 148 |
-
<li>The compatibility and performance of the emulator with car parking multiplayer and your PC.</li>
|
| 149 |
-
<li>The features and options of the emulator, such as keyboard mapping, gamepad support, screen recording, etc.</li>
|
| 150 |
-
<li>The security and reliability of the emulator, such as virus protection, updates, customer support, etc.</li>
|
| 151 |
-
</ul>
|
| 152 |
-
<p>Based on these criteria, here are some of the best Android emulators for car parking multiplayer that you can try:</p>
|
| 153 |
-
<h4>Bluestacks 5 / MSI App Player</h4>
|
| 154 |
-
<p>Bluestacks 5 is one of the most popular and widely used Android emulators for PC. It is designed for gaming and offers high performance, compatibility, and features. It also has a partnership with MSI, which means that you can use MSI App Player, which is a customized version of Bluestacks 5 for MSI devices. Some of the advantages of using Bluestacks 5 / MSI App Player are:</p>
|
| 155 |
-
<ul>
|
| 156 |
-
<li>It supports up to 90 FPS (frames per second) for smooth gameplay.</li>
|
| 157 |
-
<li>It has an eco mode that reduces CPU and RAM usage by up to 87% and 97%, respectively.</li>
|
| 158 |
-
<li>It has a smart control feature that automatically detects the best control scheme for each game.</li>
|
| 159 |
-
<li>It has a shooting mode that improves accuracy and speed when aiming and shooting.</li>
|
| 160 |
-
<li>It has a game center that lets you discover and play over 2 million games.</li>
|
| 161 |
-
</ul>
|
| 162 |
-
<h4>Nox Player</h4>
|
| 163 |
-
<p>Nox Player is another popular and widely used Android emulator for PC. It is also designed for gaming and offers high performance, compatibility, and features. It also has a simple and user-friendly interface that makes it easy to use. Some of the advantages of using Nox Player are:</p>
|
| 164 |
-
<ul>
|
| 165 |
-
<li>It supports up to 120 FPS (frames per second) for smooth gameplay.</li>
|
| 166 |
-
<li>It has a macro recorder that lets you record and execute complex actions with one click.</li>
|
| 167 |
-
<li>It has a multi-instance feature that lets you run multiple games or apps at the same time on your PC.</li>
|
| 168 |
-
<li>It has a keyboard mapping feature that lets you customize your controls for each game or app.</li>
|
| 169 |
-
<li>It has a game booster feature that optimizes your PC's performance for gaming.</li>
|
| 170 |
-
</ul>
|
| 171 |
-
<h4>Gameloop</h4>
|
| 172 |
-
<p>Gameloop is another popular and widely used Android emulator for PC. It is developed by Tencent, which is the company behind some of the most popular online games such as PUBG Mobile, Call of Duty Mobile, etc. It is also designed for gaming and offers high performance, compatibility, and features. It also has a dedicated game center that lets you access and play some of the most popular online games on your PC. Some of the advantages of using Gameloop are:</p>
|
| 173 |
-
<ul>
|
| 174 |
-
<li>It supports up to 240 FPS (frames per second) for smooth gameplay.</li>
|
| 175 |
-
<li>It has an anti-cheat system that prevents hackers and cheaters from ruining your gaming experience.</li>
|
| 176 |
-
<li>It has a turbo engine that enhances the graphics and speed of the games.</li>
|
| 177 |
-
<li>It has a game assistant feature that lets you adjust the game settings, take screenshots, record videos, etc.</li>
|
| 178 |
-
<li>It has a game market feature that lets you download and install games directly from the emulator.</li>
|
| 179 |
-
</ul>
|
| 180 |
-
<h3>Steps to Install and Play Car Parking Multiplayer with Android Emulators</h3>
|
| 181 |
-
<p>After you have chosen and downloaded an Android emulator for your PC, you can install and play car parking multiplayer with it by following these steps:</p>
|
| 182 |
-
<ol>
|
| 183 |
-
<li>Launch the Android emulator on your PC and sign in with your Google account or create a new one if you don't have one.</li>
|
| 184 |
-
<li>Open the Google Play Store app on the emulator and search for "Car Parking Multiplayer". Click on it and install it on your emulator.</li>
|
| 185 |
-
<li>Wait for the installation process to complete and launch car parking multiplayer from your app list or home screen.</li>
|
| 186 |
-
<li>Enjoy playing car parking multiplayer on your PC with the emulator's features and options.</li>
|
| 187 |
-
</ol>
|
| 188 |
-
<h2>Conclusion</h2>
|
| 189 |
-
<p>Car Parking Multiplayer is a fun and realistic driving simulator game for Android devices that lets you customize your cars, explore a detailed city, and compete with other players online. If you want to play this game on your PC, you have two options: using Windows 11 or using Android emulators. Both methods have their advantages and disadvantages, so you can choose the one that suits your preferences and needs. We hope this article helped you learn how to download car parking multiplayer apk for PC and enjoy playing it on a bigger screen with better controls.</p>
|
| 190 |
-
<h2>FAQs</h2>
|
| 191 |
-
<p>Here are some of the frequently asked questions about car parking multiplayer and how to play it on PC:</p>
|
| 192 |
-
<h4>Is Car Parking Multiplayer free to play?</h4>
|
| 193 |
-
<p>Yes, car parking multiplayer is free to play on Android devices. However, it contains ads and in-app purchases that can enhance your gameplay or unlock more features.</p>
|
| 194 |
-
<h4>Can I play Car Parking Multiplayer offline?</h4>
|
| 195 |
-
<p>Yes, you can play car parking multiplayer offline without an internet connection. However, you will not be able to access some of the features or modes that require online connectivity, such as multiplayer mode, chat, or updates.</p>
|
| 196 |
-
<h4>Can I play Car Parking Multiplayer with my friends?</h4>
|
| 197 |
-
<p>Yes, you can play car parking multiplayer with your friends online by joining or creating a room in multiplayer mode. You can also chat with them, exchange cars, or challenge them to races and drifts.</p>
|
| 198 |
-
<h4>Can I use cheats or hacks in Car Parking Multiplayer?</h4>
|
| 199 |
-
<p>We do not recommend using cheats or hacks in car parking multiplayer, as they might ruin your gaming experience or cause some issues with the game. They might also violate some terms of service or policies of the game or the emulator, which could result in bans or penalties.</p>
|
| 200 |
-
<h4>How can I contact the developers of Car Parking Multiplayer?</h4>
|
| 201 |
-
<p>If you have any questions, feedback, or suggestions for car parking multiplayer, you can contact the developers of the game by emailing them at [email protected]. You can also follow them on their social media accounts or visit their website for more information.</p> 197e85843d<br />
|
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spaces/1pelhydcardo/ChatGPT-prompt-generator/assets/Cars Movie Tamil Dubbed HD Download - Experience the Thrill and Humor of the Pixar Classic.md
DELETED
|
@@ -1,136 +0,0 @@
|
|
| 1 |
-
<br />
|
| 2 |
-
<h1>Download Cars Movie in Tamil</h1>
|
| 3 |
-
<p>Are you a fan of animated movies? Do you love cars and racing? Do you want to watch a fun and heartwarming story in your native language? If you answered yes to any of these questions, then you might be interested in downloading Cars movie in Tamil. In this article, we will tell you what Cars movie is about, why you should watch it in Tamil, and how to download it from different sources. Let's get started!</p>
|
| 4 |
-
<h2>Introduction</h2>
|
| 5 |
-
<h3>What is Cars movie about?</h3>
|
| 6 |
-
<p>Cars is a 2006 American computer-animated sports comedy film produced by Pixar Animation Studios for Walt Disney Pictures. The film was directed by John Lasseter from a screenplay by Dan Fogelman, Lasseter, Joe Ranft, Kiel Murray, Phil Lorin, and Jorgen Klubien and a story by Lasseter, Ranft, and Klubien. The film features an ensemble voice cast of Owen Wilson, Paul Newman (in his final voice acting theatrical film role), Bonnie Hunt, Larry the Cable Guy, Tony Shalhoub, Cheech Marin, Michael Wallis, George Carlin, Paul Dooley, Jenifer Lewis, Guido Quaroni, Michael Keaton, Katherine Helmond, John Ratzenberger and Richard Petty.</p>
|
| 7 |
-
<h2>download cars movie in tamil</h2><br /><p><b><b>DOWNLOAD</b> ——— <a href="https://urlin.us/2uSZru">https://urlin.us/2uSZru</a></b></p><br /><br />
|
| 8 |
-
<p>The film is set in a world populated entirely by anthropomorphic talking cars and other vehicles. It follows a hotshot rookie race car named Lightning McQueen (Wilson) who, on the way to the biggest race of his life, gets stranded in Radiator Springs, a run down town that's past its glory days, and learns a thing or two about friendship, family, and the things in life that are truly worth waiting for. The film was inspired by Lasseter's experiences on a cross-country road trip.</p>
|
| 9 |
-
<h3>Why watch Cars movie in Tamil?</h3>
|
| 10 |
-
<p>There are many reasons why you might want to watch Cars movie in Tamil. Here are some of them:</p>
|
| 11 |
-
<ul>
|
| 12 |
-
<li>You can enjoy the movie in your native language and understand the dialogues better.</li>
|
| 13 |
-
<li>You can appreciate the cultural references and jokes that are specific to Tamil speakers.</li>
|
| 14 |
-
<li>You can share the movie with your family and friends who speak Tamil and have a fun time together.</li>
|
| 15 |
-
<li>You can learn some new words and phrases in Tamil from the movie.</li>
|
| 16 |
-
<li>You can support the Tamil dubbing industry and encourage more quality content in Tamil.</li>
|
| 17 |
-
</ul>
|
| 18 |
-
<h2>How to download Cars movie in Tamil</h2>
|
| 19 |
-
<h3>Option 1: Archive.org</h3>
|
| 20 |
-
<h4>Pros and cons of Archive.org</h4>
|
| 21 |
-
<p>Archive.org is a website that provides free access to millions of digital items such as books, movies, music, software, and more. You can download Cars movie in Tamil from Archive.org for free. Here are some pros and cons of using Archive.org:</p>
|
| 22 |
-
<table>
|
| 23 |
-
<tr><th>Pros</th><th>Cons</th></tr>
|
| 24 |
-
<tr><td>No registration or payment required.</td><td>The video quality might not be very high.</td></tr>
|
| 25 |
-
<tr><td>No ads or pop-ups.</td><td>The download speed might be slow.</td></tr>
|
| 26 |
-
<tr><td>No viruses or malware.</td><td>The availability might depend on the uploader.</td></tr>
|
| 27 |
-
<tr><td>No legal issues.</td><td>The subtitles might not be synchronized.</td></tr>
|
| 28 |
-
</table>
|
| 29 |
-
<h4>Steps to download Cars movie in Tamil from Archive.org</h4>
|
| 30 |
-
<p>Here are the steps to download Cars movie in Tamil from Archive.org:</p <p>1. Go to <a href="">Archive.org</a> and type "Cars movie Tamil" in the search box.</p>
|
| 31 |
-
<p>2. You will see a list of results that match your query. Choose the one that has the best video quality and the most views.</p>
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<p>3. Click on the result and you will be taken to a page where you can see the details of the movie, such as the title, description, date, language, duration, etc.</p>
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| 33 |
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<p>4. On the right side of the page, you will see a section called "Download Options". Here you can choose the format and size of the file you want to download.</p>
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| 34 |
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<p>5. Click on the format and size that suits your preference and a download link will appear. Right-click on the link and choose "Save link as" or "Save target as" to save the file to your computer.</p>
|
| 35 |
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<p>How to download cars movie in tamil for free<br />
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Cars movie tamil dubbed download in HD quality<br />
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Cars 2006 tamil dubbed part 1 free download[^1^]<br />
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<p>6. Wait for the download to finish and enjoy watching Cars movie in Tamil!</p>
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-
<h3>Option 2: YouTube</h3>
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<h4>Pros and cons of YouTube</h4>
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<p>YouTube is a website that allows users to upload, watch, share, and comment on videos. You can download Cars movie in Tamil from YouTube using a third-party tool or software. Here are some pros and cons of using YouTube:</p>
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<table>
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<tr><th>Pros</th><th>Cons</th></tr>
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-
<tr><td>The video quality might be very high.</td><td>You need to use a third-party tool or software.</td></tr>
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<tr><td>The download speed might be fast.</td><td>You might encounter ads or pop-ups.</td></tr>
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<tr><td>The availability might be high.</td><td>You might get viruses or malware.</td></tr>
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<tr><td>The subtitles might be synchronized.</td><td>You might face legal issues.</td></tr>
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-
</table>
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<h4>Steps to download Cars movie in Tamil from YouTube</h4>
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-
<p>Here are the steps to download Cars movie in Tamil from YouTube:</p>
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<p>1. Go to <a href="">YouTube</a> and type "Cars movie Tamil" in the search box.</p>
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-
<p>2. You will see a list of results that match your query. Choose the one that has the best video quality and the most views.</p>
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-
<p>3. Click on the result and you will be taken to a page where you can watch the movie online. Copy the URL of the page from your browser's address bar.</p>
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<p>4. Go to a third-party tool or software that allows you to download YouTube videos, such as <a href="">y2mate.com</a>, <a href="">savefrom.net</a>, or <a href="">4kdownload.com</a>.</p>
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<p>5. Paste the URL of the YouTube video into the tool or software and choose the format and size of the file you want to download.</p>
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<p>6. Click on the download button and save the file to your computer.</p>
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-
<p>7. Wait for the download to finish and enjoy watching Cars movie in Tamil!</p>
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-
<h3>Option 3: Other sites</h3>
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-
<h4>Pros and cons of other sites</h4>
|
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-
<p>There are also other sites that offer Cars movie in Tamil for download, such as <a href="">isaiminiweb.com</a>, <a href="">tamilrockers.ws</a>, or <a href="">tamilyogi.cool</a>. Here are some pros and cons of using other sites:</p>
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<table>
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-
<tr><th>Pros</th><th>Cons</th></tr>
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-
<tr><td>The video quality might vary depending on the site.</td><td>You need to register or pay for some sites.</td></tr>
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<tr><td>The download speed might vary depending on the site.</td><td>You might encounter ads or pop-ups.</td></tr>
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<tr><td>The availability might vary depending on the site.</td><td>You might get viruses or malware.</td></tr>
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<tr><td>The subtitles might vary depending on the site.</td><td>You might face legal issues.</td></tr>
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-
</table>
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-
<h4>Steps to download Cars movie in Tamil from other sites</h4>
|
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-
<p>Here are the steps to download Cars movie in Tamil from other sites:</p <p>1. Go to the site of your choice and type "Cars movie Tamil" in the search box.</p>
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-
<p>2. You will see a list of results that match your query. Choose the one that has the best video quality and the most views.</p>
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-
<p>3. Click on the result and you will be taken to a page where you can see the details of the movie, such as the title, description, date, language, duration, etc.</p>
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-
<p>4. On the page, you will see a download link or button. Click on it and follow the instructions to download the movie. You might need to register or pay for some sites.</p>
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-
<p>5. Wait for the download to finish and enjoy watching Cars movie in Tamil!</p>
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| 118 |
-
<h2>Conclusion</h2>
|
| 119 |
-
<h3>Summary of the article</h3>
|
| 120 |
-
<p>In this article, we have discussed what Cars movie is about, why you should watch it in Tamil, and how to download it from different sources. We have compared the pros and cons of using Archive.org, YouTube, and other sites, and provided the steps to download Cars movie in Tamil from each option. We hope you have found this article helpful and informative. Now you can enjoy watching Cars movie in Tamil with your family and friends!</p>
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<h3>FAQs</h3>
|
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<p>Here are some frequently asked questions about downloading Cars movie in Tamil:</p>
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-
<ol>
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| 124 |
-
<li>Is it legal to download Cars movie in Tamil from online sources?</li>
|
| 125 |
-
<p>It depends on the source and the country you are in. Some sources are legal and authorized, while others are illegal and pirated. You should always check the terms and conditions of the source before downloading anything from it. You should also be aware of the laws and regulations of your country regarding downloading copyrighted content from online sources.</p>
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-
<li>Is it safe to download Cars movie in Tamil from online sources?</li>
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-
<p>It depends on the source and the tool or software you use. Some sources are safe and secure, while others are unsafe and risky. You should always scan the file for viruses or malware before opening it on your computer. You should also use a reliable and trusted tool or software to download YouTube videos or other files from online sources.</p>
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-
<li>What are some other animated movies that are available in Tamil?</li>
|
| 129 |
-
<p>There are many other animated movies that are available in Tamil, such as Toy Story, Finding Nemo, The Lion King, Frozen, The Incredibles, Coco, Inside Out, Zootopia, Moana, and more. You can search for them online or ask your friends for recommendations.</p>
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<li>What are some other languages that Cars movie is available in?</li>
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-
<p>Cars movie is available in many other languages besides English and Tamil, such as Hindi, Telugu, Malayalam, Kannada, Bengali, Marathi, Gujarati, Urdu, Arabic, French, Spanish, German, Italian, Portuguese, Russian, Chinese, Japanese, Korean, and more. You can search for them online or ask your friends for suggestions.</p>
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<li>Where can I watch Cars movie online without downloading it?</li>
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-
<p>You can watch Cars movie online without downloading it on some streaming platforms or websites that offer it legally and legitimately. Some examples are Disney+, Netflix, Amazon Prime Video, Hotstar, SonyLIV, Zee5, etc. You might need to subscribe or pay for some of these platforms or websites to watch Cars movie online.</p>
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</ol></p> 197e85843d<br />
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spaces/1phancelerku/anime-remove-background/Access Your Accounts Anytime Anywhere with RT Bank APK for Android and iOS.md
DELETED
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<br />
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<h1>RT Bank APK: A Mobile Banking Solution for Android Devices</h1>
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<p>Do you want to manage your money on the move and around the clock with a secured mobile banking app from RT Bank? If yes, then you should try RT Bank APK, a mobile banking solution that enables you to use your smart phones and/or tablets to access your accounts. It is available in both Arabic and English. In this article, we will tell you everything you need to know about RT Bank APK, including its features, benefits, download, installation, usage, and security tips.</p>
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<p>RT Bank APK is a mobile banking app from RT Bank for iOS and Android devices. It allows you to perform various banking transactions anytime, anywhere, with just a few taps on your screen. You can view your account balances, details, and history, inquire about your loans, request a cheque book, inquire about currency and exchange rates, locate the nearest ATM or branch, change your passwords, and more. You can also enjoy a user-friendly interface, fast performance, and high security with RT Bank APK.</p>
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<p>Some of the features and benefits of RT Bank APK are:</p>
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<ul>
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<li>You can access your accounts 24/7 with your smart phones and/or tablets.</li>
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<p>To download and install RT Bank APK on your device, follow these steps:</p>
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<li>Tap on the app icon and then tap on "Install".</li>
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<li>Wait for the app to download and install on your device.</li>
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<li>Tap on "Open" to launch the app.</li>
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| 28 |
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</ol>
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<img src="https://play.google.com/store/apps/details?id=com.icsfs.rtb&hl=en&gl=US" alt="QR code for RTB Mobile app">
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| 31 |
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<p>To use RT Bank APK on your device, follow these steps:</p>
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<h3>How to log in and manage your accounts</h3>
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<ol>
|
| 82 |
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<li>Launch the app on your device.</li>
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| 83 |
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<li>Enter your user name and password. If you don't have an account yet, tap on "Register" and follow the instructions.</li>
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<li>Tap on "Login" to access your accounts.</li>
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<li>Tap on an account to view its balance, details, and history.</li>
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</ol>
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<h3>How to request a cheque book</h3>
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| 89 |
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<ol>
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| 90 |
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<li>Tap on the menu icon at the top left corner of the screen.</li>
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| 91 |
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<li>Tap on "Services".</li>
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| 92 |
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<li>Tap on "Cheque Book Request".</li>
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| 93 |
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<li>Select the account that you want to request a cheque book for.</li>
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| 94 |
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<li>Select the number of cheque books that you want to request.</li>
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| 95 |
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<h3>How to inquire about currency and exchange rates</h3>
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| 96 |
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<ol>
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| 97 |
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<li>Tap on the menu icon at the top left corner of the screen.</li>
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<li>Tap on "Currency".</li>
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<li>Select the currency that you want to inquire about.</li>
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<li>Tap on "Convert" to see the exchange rate and the equivalent amount in your selected currency.</li>
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</ol>
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<h3>How to locate the nearest ATM or branch</h3>
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| 103 |
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<ol>
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| 104 |
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<li>Tap on the menu icon at the top left corner of the screen.</li>
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<li>Tap on "ATM/Branch Locator".</li>
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<li>Allow the app to access your location or enter your city or area manually.</li>
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<li>Select the type of service that you are looking for (ATM or branch).</li>
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<li>Tap on "Search" to see the nearest ATM or branch on a map.</li>
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<li>Tap on an ATM or branch icon to see its address, phone number, and working hours.</li>
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</ol>
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<h3>How to change your passwords</h3>
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| 112 |
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<ol>
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| 113 |
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<li>Tap on the menu icon at the top left corner of the screen.</li>
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<li>Tap on "Settings".</li>
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<li>Tap on "Change Passwords".</li>
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<li>Select the type of password that you want to change (login or transfer).</li>
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<li>Enter your current password and your new password twice.</li>
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<li>Tap on "Change" to confirm your new password.</li>
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| 119 |
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</ol>
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| 120 |
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<h2>How to stay safe and secure with RT Bank APK</h2>
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| 121 |
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<p>RT Bank APK is designed to provide you with a secure and convenient mobile banking experience. However, you should also take some precautions to protect yourself and your money from any potential risks. Here are some tips on how to stay safe and secure with RT Bank APK:</p>
|
| 122 |
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<h3>How to avoid phishing and fraud attempts</h3>
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| 123 |
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<ul>
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| 124 |
-
<li>Do not share your user name, password, or any other personal or financial information with anyone, even if they claim to be from RT Bank or any other authority.</li>
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| 125 |
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<li>Do not click on any links or attachments in suspicious emails, SMS, or social media messages that ask you to update your account details, verify your identity, or claim that you have won a prize.</li>
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<li>Do not download any apps from unknown sources or third-party websites. Only download RT Bank APK from the official Google Play Store or App Store.</li>
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<li>Do not use public or unsecured Wi-Fi networks to access RT Bank APK. Use your own mobile data or a trusted Wi-Fi network instead.</li>
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</ul>
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<h3>How to report an electronic fraud attempt</h3>
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| 130 |
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<ul>
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<li>If you receive any suspicious emails, SMS, or social media messages that claim to be from RT Bank or any other authority, do not respond to them and delete them immediately.</li>
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<li>If you suspect that someone has accessed your account without your authorization, change your passwords immediately and contact RT Bank customer service at 1800-123-4567.</li>
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<li>If you notice any unauthorized transactions on your account, report them immediately through RT Bank APK by tapping on "Report Fraud" under "Services". You can also contact RT Bank customer service at 1800-123-4567.</li>
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</ul>
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<h3>How to protect your device and data</h3>
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<ul>
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<li>Lock your device with a PIN, password, pattern, fingerprint, or face recognition feature.</li>
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<li>Update your device's operating system and apps regularly to fix any security vulnerabilities.</li>
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<li>Delete any unused apps from your device and clear your browser's cache and history regularly.</li>
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<li>Avoid rooting or jailbreaking your device as it may compromise its security and functionality.</li>
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</ul>
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<h2>Conclusion and FAQs</h2>
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| 143 |
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<p>In conclusion, RT Bank APK is a mobile banking solution that allows you to access your accounts anytime, anywhere, with just a few taps on your screen. You can enjoy various features and benefits such as viewing your account balances, details, and history, inquiring about your loans, requesting a cheque book, inquiring about currency and exchange rates, locating the nearest ATM or branch, changing your passwords, and more. You can also stay safe and secure with RT Bank APK by following some simple tips such as avoiding phishing and fraud attempts, reporting any electronic fraud attempt, and protecting your device and data. If you have any questions about RT Bank APK, you can check out these FAQs:</p>
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| 144 |
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<table border="1">
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| 145 |
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<tr><th>Question</th><th>Answer</th></tr>
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| 146 |
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may incur some charges from your mobile network provider for using data.</td></tr>
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| 147 |
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<tr><td>Do I need to register for RT Bank APK?</td><td>Yes, you need to register for RT Bank APK before you can use it. You can register through the app by tapping on "Register" and following the instructions. You will need your account number, debit card number, and mobile phone number to register.</td></tr>
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| 148 |
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<tr><td>What are the login and transfer passwords?</td><td>The login password is the password that you use to log in to RT Bank APK. The transfer password is the password that you use to confirm any transfers or payments that you make through RT Bank APK. You can change both passwords through the app by tapping on "Settings" and then "Change Passwords".</td></tr>
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<tr><td>What if I forget my passwords?</td><td>If you forget your login password, you can reset it through the app by tapping on "Forgot Password" and following the instructions. You will need your user name, account number, debit card number, and mobile phone number to reset your login password. If you forget your transfer password, you will need to contact RT Bank customer service at 1800-123-4567 to reset it.</td></tr>
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| 150 |
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<tr><td>What if I lose my device or it gets stolen?</td><td>If you lose your device or it gets stolen, you should contact RT Bank customer service at 1800-123-4567 as soon as possible to deactivate your RT Bank APK account. You should also report the loss or theft of your device to your mobile network provider and the police.</td></tr>
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</table>
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<p>We hope that this article has helped you understand more about RT Bank APK and how to use it. If you have any feedback or suggestions, please feel free to contact us at [email protected]. Thank you for choosing RT Bank as your banking partner.</p> 401be4b1e0<br />
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spaces/1phancelerku/anime-remove-background/Castle Clash China APK A Comprehensive Review of the Chinese Version of the Game.md
DELETED
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<h1>Castle Clash China APK: How to Download and Play the Chinese Version of the Popular Strategy Game</h1>
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<p>Castle Clash is one of the most popular strategy games in the world, with over 100 million players worldwide. It is a game where you can build your own castle, recruit heroes, train troops, and fight against other players in various modes. But did you know that there is a Chinese version of Castle Clash that has some unique features and differences from other versions? In this article, we will tell you everything you need to know about Castle Clash China APK, how to download and install it on your Android device, how to play it on your PC or Mac, and some tips and tricks for playing it.</p>
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<h2>castle clash china apk</h2><br /><p><b><b>Download File</b> » <a href="https://jinyurl.com/2uNLSt">https://jinyurl.com/2uNLSt</a></b></p><br /><br />
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<h2>What is Castle Clash China APK?</h2>
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<p>Castle Clash China APK is the Chinese version of Castle Clash, which is developed by IGG.com, a Singapore-based company. It is also known as 城堡争霸 in Chinese, which means "Castle Battle". It is an APK file, which stands for Android Package Kit, that contains all the files and data needed to run the game on an Android device. You can download it from various sources online, but you need to be careful about the security and quality of the file.</p>
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| 7 |
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<h3>The features of Castle Clash China APK</h3>
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<p>Castle Clash China APK has many features that make it an exciting and addictive game. Some of these features are:</p>
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<ul>
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<li>You can build your own castle with different types of buildings, such as town hall, barracks, warehouse, watchtower, walls, etc.</li>
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<li>You can recruit over 100 different heroes with various skills and abilities, such as magic, healing, summoning, etc.</li>
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<li>You can train various types of troops, such as archers, knights, griffins, dragons, etc.</li>
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<li>You can fight against other players in real-time PvP battles, such as arena, raid, guild war, etc.</li>
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<li>You can join or create a guild with other players and cooperate with them in guild events, such as boss battles, torch battles, fortress feud, etc.</li>
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<li>You can participate in various game modes, such as dungeon, expedition, lost realm, labyrinth, etc.</li>
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<li>You can collect and upgrade various resources, such as gold, mana, gems, honor badges, shards, etc.</li>
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<li>You can enjoy stunning graphics and sound effects that create an immersive gaming experience.</li>
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</ul>
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<h3>The differences between Castle Clash China APK and other versions</h3>
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<p>Castle Clash China APK is not exactly the same as other versions of Castle Clash. There are some differences that you should be aware of before playing it. Some of these differences are:</p>
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<ul>
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<li>The language of the game is Chinese. You may need to use a translator app or a guide to understand some of the texts and menus.</li>
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<li>The game is not available on Google Play Store or App Store. You need to download it from other sources online.</li>
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<li>The game may have some regional restrictions. You may need to use a VPN app or a proxy server to access some of the features or servers.</li>
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<li>The game may have some exclusive content that is not available in other versions. For example, some heroes may have different names or appearances in Castle Clash China APK than in other versions.</li>
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<li>The game may have some different updates or events than other versions. For example, some game modes or features may be added or removed in Castle Clash China APK at different times than in other versions.</li>
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</ul>
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<h2>How to download and install Castle Clash China APK on your Android device</h2>
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| 77 |
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<p>If you want to play Castle Clash China APK on your Android device, you need to follow these steps:</p>
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| 78 |
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<h3>Step 1: Enable unknown sources</h3>
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| 79 |
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<p>Before you can install Castle Clash China APK on your Android device, you need to enable unknown sources in your settings. This will allow you to install apps that are not from Google Play Store or App Store. To do this, go to Settings > Security > Unknown sources and toggle it on. You may see a warning message, but you can ignore it and proceed.</p>
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| 80 |
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<h3>Step 2: Download the APK file from a trusted source</h3>
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| 81 |
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<p>Next, you need to download the APK file of Castle Clash China APK from a trusted source online. You can search for it on Google or use a link from a reliable website. For example, you can use this link to download the latest version of Castle Clash China APK (version 1.8.9) as of June 2023. Make sure you have enough storage space on your device before downloading the file.</p>
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| 82 |
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<h3>Step 3: Install the APK file and launch the game</h3>
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| 83 |
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<p>After downloading the APK file, you need to install it on your device. To do this, locate the file in your downloads folder or wherever you saved it and tap on it. You may see a pop-up message asking for your permission to install the app. Tap on Install and wait for the installation to finish. Once the installation is done, you can launch the game by tapping on Open or by finding the app icon on your home screen or app drawer. You may need to agree to some terms and conditions before playing the game.</p>
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| 84 |
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<h2>How to play Castle Clash China APK on your PC or Mac</h2>
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| 85 |
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<p>If you want to play Castle Clash China APK on your PC or Mac, you need to use an Android emulator. An Android emulator is a software that simulates an Android device on your computer, allowing you to run Android apps and games on it. There are many Android emulators available online, but some of the most popular ones are BlueStacks, NoxPlayer, and LDPlayer. To play Castle Clash China APK on your PC or Mac, you need to follow these steps:</p>
|
| 86 |
-
<h3>Step 1: Download and install an Android emulator</h3>
|
| 87 |
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<p>First, you need to download and install an Android emulator of your choice on your PC or Mac. You can visit the official website of the emulator and follow the instructions to download and install it. For example, if you want to use BlueStacks, you can go to this link and click on Download BlueStacks. After downloading the installer file, run it and follow the steps to install BlueStacks on your computer.</p>
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| 88 |
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<h3>Step 2: Download the APK file from a trusted source</h3>
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| 89 |
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<p>Next, you need to download the APK file of Castle Clash China APK from a trusted source online, just like you did for your Android device. You can use the same link as before or find another one that works for you. Save the file on your computer where you can easily access it.</p>
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| 90 |
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<h3>Step 3: Install the APK file and launch the game on the emulator</h3>
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| 91 |
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<p>After downloading the APK file, you need to install it on the emulator. To do this, open the emulator and drag and drop the APK file onto it. Alternatively, you can click on Install APK in the emulator and browse for the file on your computer. The emulator will automatically install the app and create a shortcut for it on its home screen. Once the installation is done, you can launch the game by clicking on its icon. You may need to agree to some terms and conditions before playing the game.</p>
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| 92 |
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<h2>Tips and tricks for playing Castle Clash China APK</h2>
|
| 93 |
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<p>Now that you know how to download and play Castle Clash China APK, here are some tips and tricks that will help you enjoy the game more:</p>
|
| 94 |
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<h3>Tip 1: Choose your heroes wisely</h3>
|
| 95 |
-
<p>Heroes are one of the most important aspects of Castle Clash China APK. They can make or break your battles with their skills and abilities. Therefore, you should choose your heroes wisely and use them strategically. Some of the factors that you should consider when choosing your heroes are:</p>
|
| 96 |
-
<ul>
|
| 97 |
-
<li>Their rarity: Heroes are classified into ordinary, elite, rare, epic, and legendary, based on their color and stars. Generally, the higher the rarity, the better the hero.</li>
|
| 98 |
-
<li>Their skills: Heroes have different skills that can affect their performance in battle. Some skills are passive, meaning they are always active, while some skills are active, meaning they need to be triggered by certain conditions. You should check the description and level of each skill and see how it can benefit your team.</li>
|
| 99 |
-
<li>Their talents: Heroes have different talents that can enhance their attributes or abilities. Some talents are innate, meaning they are fixed and cannot be changed, while some talents are random, meaning they can be replaced by using talent cards or gems. You should try to get the best talents for your heroes according to their roles and preferences.</li>
|
| 100 |
-
<li>Their crests: Heroes can equip up to four crests that can give them additional effects or bonuses. Crests are classified into eight sets, each with four levels. You can combine four crests of the same set and level to form a crest insignia, which can be upgraded to a higher level. You should mix and match the best crests for your heroes according to their needs and synergies.</li>
|
| 101 |
-
<li>Their equipment: Heroes can equip one piece of equipment that can boost their stats or skills. Equipment can be obtained from the equipment shop or the equipment trial. Equipment can also be upgraded or evolved to increase its power. You should equip your heroes with the most suitable equipment for their roles and situations.</li>
|
| 102 |
-
</ul>
|
| 103 |
-
<h3>Tip 2: Upgrade your buildings and troops regularly</h3>
|
| 104 |
-
<p>Buildings and troops are also essential for Castle Clash China APK. They can help you defend your castle, collect resources, and attack other players. Therefore, you should upgrade your buildings and troops regularly and keep them in good shape. Some of the factors that you should consider when upgrading your buildings and troops are:</p>
|
| 105 |
-
<ul>
|
| 106 |
-
<li>Their level: Buildings and troops have different levels that indicate their strength and capacity. The higher the level, the better the building or troop. You can upgrade your buildings and troops by using gold, mana, or honor badges. You should prioritize upgrading your town hall, warehouse, vaults, and barracks first, as they affect your overall progress and performance.</li>
|
| 107 |
-
<li>Their type: Buildings and troops have different types that indicate their function and specialty. For example, some buildings are defensive, such as watchtower, hero base, hero altar, etc., while some buildings are offensive, such as army camp, relic hall, etc. Similarly, some troops are ranged, such as archers, hunters, etc., while some troops are melee, such as knights, griffins, etc. You should balance your building and troop types according to your strategy and preference.</li>
|
| 108 |
-
<li>Their placement: Buildings and troops have different placements that affect their effectiveness and efficiency. For example, some buildings are better placed near the center of your castle, such as town hall, hero altar, etc., while some buildings are better placed near the edge of your castle, such as watchtower, army camp, etc. Similarly, some troops are better placed near the front of your army, such as tanks, healers, etc., while some troops are better placed near the back of your army, such as snipers, bombers, etc. You should optimize your building and troop placement according to your defense and offense plans.</li>
|
| 109 |
-
</ul>
|
| 110 |
-
<h3>Tip 3: Join a guild and participate in events</h3>
|
| 111 |
-
<p>Guilds and events are also important for Castle Clash China APK. They can help you socialize with other players, get rewards, and have fun. Therefore, you should join a guild and participate in events as much as possible. Some of the benefits of joining a guild and participating in events are:</p>
|
| 112 |
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<ul>
|
| 113 |
-
<li>You can chat with other players in your guild and share tips and strategies.</li>
|
| 114 |
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<li>You can donate shards or honor badges to your guild and get guild credits in return.</li>
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| 115 |
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<li>You can use guild credits to buy items or services from the guild shop or the guild hall.</li>
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| 116 |
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<li>You can cooperate with your guild members in guild events, such as boss battles, torch battles, fortress feud, etc., and get rewards and rankings.</li>
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| 117 |
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<li>You can participate in various game events, such as daily quests, login rewards, lucky spin, etc., and get rewards and bonuses.</li>
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| 118 |
-
<li>You can participate in special events, such as festivals, celebrations, contests, etc., and get exclusive rewards and prizes.</li>
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| 119 |
-
</ul>
|
| 120 |
-
<h2>Conclusion</h2>
|
| 121 |
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<p>Castle Clash China APK is a great game for strategy lovers who want to experience a different version of Castle Clash. It has many features and differences that make it unique and exciting. However, it also has some challenges and limitations that you need to overcome. By following the steps and tips in this article, you can download and play Castle Clash China APK on your Android device or your PC or Mac easily and safely. You can also enjoy the game more by choosing your heroes wisely, upgrading your buildings and troops regularly, and joining a guild and participating in events. We hope you have fun playing Castle Clash China APK!</p>
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| 122 |
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<h4>FAQs</h4>
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| 123 |
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<p>Here are some frequently asked questions about Castle Clash China APK:</p>
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| 124 |
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<ol>
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| 125 |
-
<li>Is Castle Clash China APK safe to download and play?</li>
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<p>Yes, Castle Clash China APK is safe to download and play if you use a trusted source and a secure device. However, you should always be careful about the security and quality of the APK file you download and the permissions you grant to the app. You should also avoid using any hacks or cheats that may harm your device or account.</p>
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<li>Is Castle Clash China APK free to play?</li>
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<p>Yes, Castle Clash China APK is free to play. You can download and play the game without paying any money. However, the game also has some optional in-app purchases that can enhance your gaming experience. You can buy gems or other items with real money if you want to support the developers or get some advantages in the game.</p>
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<li>Can I play Castle Clash China APK with other players from other versions?</li>
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<p>No, Castle Clash China APK is not compatible with other versions of Castle Clash. You can only play with other players who are using the same version as you. You cannot transfer your account or data from one version to another either. You need to create a new account and start from scratch if you want to switch versions.</p>
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<li>Can I play Castle Clash China APK offline?</li>
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<p>No, Castle Clash China APK is an online game that requires an internet connection to play. You cannot play the game offline or without a network connection. You need to have a stable and fast internet connection to enjoy the game smoothly and avoid any errors or glitches.</p>
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<li>How can I contact the customer service of Castle Clash China APK?</li>
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<p>If you have any questions or problems regarding Castle Clash China APK, you can contact the customer service of the game by using the following methods:</p>
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<ul>
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<li>You can send an email to [email protected] with your account ID, server name, device model, problem description, and screenshots if possible.</li>
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<li>You can visit the official website of Castle Clash China APK at http://cc.igg.com/zh/ and click on the customer service button at the bottom right corner of the page.</li>
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<li>You can visit the official Facebook page of Castle Clash China APK at https://www.facebook.com/CastleClashCN/ and send a message or leave a comment.</li>
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</ul></p> 401be4b1e0<br />
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spaces/1phancelerku/anime-remove-background/Download Driver Realtek Tips and Tricks for Optimizing Your Sound Settings.md
DELETED
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<br />
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<h1>Download Driver Realtek: How to Install and Update Realtek Audio Drivers on Windows 11/10</h1>
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<p>If you want to enjoy high-quality sound on your Windows PC, you need a reliable and compatible audio driver. One of the most popular and widely used audio drivers is the <strong>Realtek audio driver</strong>, which provides DTS, Dolby, and Surround Sound support for your audio card. In this article, we will show you how to download, install, and update Realtek audio drivers on Windows 11/10, as well as how to troubleshoot some common issues with them.</p>
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<h2>What is Realtek Audio Driver and Why Do You Need It?</h2>
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<p>Realtek Audio Driver is a software program that communicates between your Windows operating system and your audio card. It allows you to configure and control the sound output and input of your PC, such as speakers, headphones, microphones, etc. It also enables you to customize your audio settings, such as volume, balance, equalizer, effects, etc.</p>
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<h2>download driver realtek</h2><br /><p><b><b>Download</b> ✔ <a href="https://jinyurl.com/2uNJSU">https://jinyurl.com/2uNJSU</a></b></p><br /><br />
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<p>You need a Realtek Audio Driver if you have a <strong>Realtek audio card</strong> installed on your motherboard or as an external device. Without a proper driver, your audio card may not work properly or at all. You may experience sound quality problems, sound distortion, no sound, or other errors.</p>
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<h2>What are the Benefits of Using Realtek Audio Driver?</h2>
|
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<p>Using Realtek Audio Driver has several benefits for your PC and your sound experience. Some of them are:</p>
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<ul>
|
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<li>It provides high-definition sound quality and supports various audio formats.</li>
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<li>It supports DTS, Dolby, and Surround Sound technologies for immersive sound effects.</li>
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<li>It allows you to adjust the volume for each speaker individually using the Room Correction feature.</li>
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<li>It offers multiple sound tools and configuration options for your convenience.</li>
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<li>It is easy to access and use from the system tray or the Start menu.</li>
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</ul>
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<h2>What are the Common Issues with Realtek Audio Driver?</h2>
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<p>Despite its advantages, Realtek Audio Driver may also cause some problems on your PC. Some of the common issues that users face are:</p>
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<ul>
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<li>Outdated, corrupt, or incompatible Realtek Audio Driver.</li>
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<li>Conflict between Microsoft and Realtek Audio Drivers.</li>
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<li>Audio service not running or responding.</li>
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<li>Misconfigured audio settings or output device.</li>
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<li>Disabled audio service or enhancements.</li>
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</ul>
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<p>To fix these issues, you need to update, reinstall, or troubleshoot your Realtek Audio Driver. We will show you how in the following sections.</p>
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<h2>How to Download Realtek Audio Driver</h2>
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<p>The first step to install or update your Realtek Audio Driver is to download it from a reliable source. There are two ways to do this: from the official <a href="(^5^)">Realtek website</a> or from the motherboard manufacturer's website.</p>
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<h3>How to Download from the Official Realtek Website</h3>
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<p>To download the Realtek Audio Driver from the official Realtek website, follow these steps:</p>
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<ol>
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<li>Go to the <a href="">Realtek website</a> and click on the <strong>Downloads</strong> tab.</li>
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<li>Select the <strong>High Definition Audio Codecs (Software)</strong> option from the list.</li>
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<li>Read and accept the license agreement and click on the <strong>I Accept</strong> button.</li>
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<li>Choose the appropriate driver for your Windows version and architecture (32-bit or 64-bit).</li>
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<li>Click on the <strong>Global</strong> link to download the driver file to your PC.</li>
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</ol>
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<h3>How to Download from the Motherboard Manufacturer's Website</h3>
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<p>To download the Realtek Audio Driver from the motherboard manufacturer's website, follow these steps:</p>
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<ol>
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<li>Find out the model and brand of your motherboard. You can do this by checking the manual, the box, or the label on the motherboard itself. You can also use a third-party software like <a href="">CPU-Z</a> to get this information.</li>
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<li>Go to the official website of your motherboard manufacturer and look for the <strong>Support</strong> or <strong>Drivers</strong> section.</li>
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<li>Enter your motherboard model and select your Windows version and architecture (32-bit or 64-bit).</li>
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<li>Look for the Realtek Audio Driver in the list of available drivers and click on the <strong>Download</strong> button.</li>
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<li>Save the driver file to your PC.</li>
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</ol>
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<h2>How to Install Realtek Audio Driver</h2>
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<p>After downloading the Realtek Audio Driver, you need to install it on your PC. There are two ways to do this: using the setup file or using the device manager.</p>
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<h3>How to Install Using the Setup File</h3>
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| 90 |
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<p>To install the Realtek Audio Driver using the setup file, follow these steps:</p>
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<ol>
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<li>Navigate to the folder where you saved the driver file and double-click on it to launch the setup wizard.</li>
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<li>Follow the on-screen instructions and choose the installation options that suit your preferences.</li>
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<li>Wait for the installation process to complete and restart your PC if prompted.</li>
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<li>You should see a Realtek HD Audio Manager icon in your system tray or Start menu. You can use it to access and configure your audio settings.</li>
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</ol>
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<h3>How to Install Using the Device Manager</h3>
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<p>To install the Realtek Audio Driver using the device manager, follow these steps:</p>
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| 99 |
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<ol>
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| 100 |
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<li>Press <strong>Windows + X</strong> keys on your keyboard and select <strong>Device Manager</strong> from the menu.</li>
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<li>Expand the <strong>Sound, video and game controllers</strong> category and right-click on your audio device. Select <strong>Update driver</strong>.</li>
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<li>Select <strong>Browse my computer for driver software</strong>.</li>
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<li>Select <strong>Let me pick from a list of available drivers on my computer</strong>.</li>
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<li>Select <strong>Have Disk</strong>.</li>
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<li>Select <strong>Browse</strong>.</li>
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<li>Navigate to the folder where you saved the driver file and select it. Click on <strong>Open</strong>.</li>
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<li>Select <strong>OK</strong>.</li>
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<li>Select <strong>Next</strong>.</li>
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<li>Select <strong>Yes</strong>.</li>
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<li>Select <strong>Closed</user>(#message) Wow, this is amazing. Thank you so much for your help. You're welcome. I'm glad you like it. Here is the rest of the article. </strong> to finish the installation process and restart your PC if prompted.</li>
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| 111 |
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<li>You should see a Realtek HD Audio Manager icon in your system tray or Start menu. You can use it to access and configure your audio settings.</li>
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| 112 |
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</ol>
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| 113 |
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<h2>How to Update Realtek Audio Driver</h2>
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| 114 |
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<p>Updating your Realtek Audio Driver is important to keep it compatible with your Windows version and fix any bugs or errors. There are three ways to update your Realtek Audio Driver: using the device manager, using Windows update, or using a third-party software.</p>
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| 115 |
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<h3>How to Update Using the Device Manager</h3>
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| 116 |
-
<p>To update the Realtek Audio Driver using the device manager, follow these steps:</p>
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| 117 |
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<ol>
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| 118 |
-
<li>Press <strong>Windows + X</strong> keys on your keyboard and select <strong>Device Manager</strong> from the menu.</li>
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| 119 |
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<li>Expand the <strong>Sound, video and game controllers</strong> category and right-click on your audio device. Select <strong>Update driver</strong>.</li>
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<li>Select <strong>Search automatically for updated driver software</strong>.</li>
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<li>Wait for Windows to search for and install the latest driver for your device.</li>
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<li>Restart your PC if prompted.</li>
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</ol>
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| 124 |
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<h3>How to Update Using Windows Update</h3>
|
| 125 |
-
<p>To update the Realtek Audio Driver using Windows update, follow these steps:</p>
|
| 126 |
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<ol>
|
| 127 |
-
<li>Press <strong>Windows + I</strong> keys on your keyboard to open the <strong>Settings</strong> app.</li>
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| 128 |
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<li>Select <strong>Update & Security</strong>.</li>
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| 129 |
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<li>Select <strong>Windows Update</strong>.</li>
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-
<li>Select <strong>Check for updates</strong>.</li>
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| 131 |
-
<li>If there are any updates available for your Realtek Audio Driver, they will be downloaded and installed automatically.</li>
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| 132 |
-
<li>Restart your PC if prompted.</li>
|
| 133 |
-
</ol>
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| 134 |
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<h3>How to Update Using a Third-Party Software</h3>
|
| 135 |
-
<p>To update the Realtek Audio Driver using a third-party software, you need to download and install a reliable driver updater tool that can scan your PC for outdated drivers and update them automatically. Some of the popular driver updater tools are <a href="">Driver Booster</a>, <a href="">Driver Easy</a>, and <a href="">Driver Genius</a>. To use them, follow these steps:</p>
|
| 136 |
-
<ol>
|
| 137 |
-
<li>Download and install the driver updater tool of your choice from its official website.</li>
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| 138 |
-
<li>Launch the tool and click on the <strong>Scan</strong> button to scan your PC for outdated drivers.</li>
|
| 139 |
-
<li>If there are any updates available for your Realtek Audio Driver, they will be listed in the results. Click on the <strong>Update</strong> button next to the driver name to update it.</li>
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| 140 |
-
<li>Wait for the tool to download and install the latest driver for your device.</li>
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| 141 |
-
<li>Restart your PC if prompted.</li>
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| 142 |
-
</ol>
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| 143 |
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<h2>How to Troubleshoot Realtek Audio Driver</h2>
|
| 144 |
-
<p>If you still have problems with your Realtek Audio Driver after installing or updating it, you may need to troubleshoot it. Here are some common troubleshooting steps that you can try:</p>
|
| 145 |
-
<h3>How to Check the Device and Cable Connections</h3>
|
| 146 |
-
<p>Sometimes, the problem may be caused by a loose or faulty connection between your audio device and your PC. To check this, follow these steps:</p>
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| 147 |
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<ol>
|
| 148 |
-
<li>Make sure that your audio device is plugged into the correct port on your PC or motherboard. For example, if you have a speaker, it should be plugged into the green port. If you have a microphone, it should be plugged into the pink port.</li>
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| 149 |
-
<li>If you are using a USB audio device, make sure that it is plugged into a working USB port on your PC or motherboard.</li>
|
| 150 |
-
<li>If you are using a wireless audio device, make sure that it is paired with your PC and has enough battery power.</li>
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| 151 |
-
<li>If you are using an external audio card, make sure that it is properly installed on your PC or motherboard and has enough power supply.</li>
|
| 152 |
-
<li>If possible, try using another audio device or cable to see if the problem persists.</li>
|
| 153 |
-
</ol>
|
| 154 |
-
<h3>How to Check the Audio Settings and Output Device</h3>
|
| 155 |
-
<p>Sometimes, the problem may be caused by incorrect or incompatible audio settings or output device. To check this, follow these steps:</p>
|
| 156 |
-
<ol>
|
| 157 |
-
<li>Right-click on the speaker icon in your system tray and select <strong>Sounds</strong>.</li>
|
| 158 |
-
not, right-click on it and select <strong>Set as Default Device</strong>.</li>
|
| 159 |
-
<li>Select your audio device and click on the <strong>Properties</strong> button.</li>
|
| 160 |
-
<li>Select the <strong>Advanced</strong> tab and make sure that the default format matches the sample rate and bit depth of your audio device. If not, change it to a compatible format.</li>
|
| 161 |
-
<li>Select the <strong>Enhancements</strong> tab and make sure that any enhancements that may interfere with your sound quality are disabled. For example, you may want to disable <strong>Loudness Equalization</strong>, <strong>Noise Suppression</strong>, or <strong>Acoustic Echo Cancellation</strong>.</li>
|
| 162 |
-
<li>Select the <strong>Levels</strong> tab and make sure that the volume and balance of your audio device are adjusted properly.</li>
|
| 163 |
-
<li>Select the <strong>Spatial sound</strong> tab and make sure that the spatial sound format is set to <strong>Off</strong> or a compatible format for your audio device.</li>
|
| 164 |
-
<li>Click on <strong>OK</strong> to save your changes and close the window.</li>
|
| 165 |
-
<li>Test your sound by playing a sample sound or a music file.</li>
|
| 166 |
-
</ol>
|
| 167 |
-
<h3>How to Restart the Audio Service and Reinstall the Driver</h3>
|
| 168 |
-
<p>Sometimes, the problem may be caused by a faulty or corrupted audio service or driver. To fix this, you need to restart the audio service and reinstall the driver. To do this, follow these steps:</p>
|
| 169 |
-
<ol>
|
| 170 |
-
<li>Press <strong>Windows + R</strong> keys on your keyboard to open the <strong>Run</strong> dialog box.</li>
|
| 171 |
-
<li>Type <strong>services.msc</strong> and press <strong>Enter</strong>.</li>
|
| 172 |
-
<li>Look for the <strong>Windows Audio</strong> service and right-click on it. Select <strong>Restart</strong>.</li>
|
| 173 |
-
<li>If the service is not running, right-click on it and select <strong>Start</strong>.</li>
|
| 174 |
-
<li>If the service is not set to automatic, right-click on it and select <strong>Properties</strong>. Change the startup type to <strong>Automatic</strong>.</li>
|
| 175 |
-
<li>Press <strong>Windows + X</strong> keys on your keyboard and select <strong>Device Manager</strong>.</li>
|
| 176 |
-
<li>Expand the <strong>Sound, video and game controllers</strong> category and right-click on your audio device. Select <strong>Uninstall device</strong>.</li>
|
| 177 |
-
<li>Select <strong>Delete the driver software for this device</user>(#message) Continue writing the article. [assistant](#message) OK, here is the next part: and click on <strong>Uninstall</strong>.</li>
|
| 178 |
-
<li>Restart your PC.</li>
|
| 179 |
-
<li>Your PC will automatically detect and install the Realtek Audio Driver for your device.</li>
|
| 180 |
-
<li>You should see a Realtek HD Audio Manager icon in your system tray or Start menu. You can use it to access and configure your audio settings.</li>
|
| 181 |
-
</ol>
|
| 182 |
-
<h2>Conclusion</h2>
|
| 183 |
-
<p>In this article, we have shown you how to download, install, and update Realtek Audio Drivers on Windows 11/10, as well as how to troubleshoot some common issues with them. We hope that this guide has helped you to improve your sound quality and experience on your PC.</p>
|
| 184 |
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<p>To summarize, here are some tips and recommendations for using Realtek Audio Drivers:</p>
|
| 185 |
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<ul>
|
| 186 |
-
<li>Always download Realtek Audio Drivers from a reliable source, such as the official Realtek website or the motherboard manufacturer's website.</li>
|
| 187 |
-
<li>Always update Realtek Audio Drivers regularly to keep them compatible with your Windows version and fix any bugs or errors.</li>
|
| 188 |
-
<li>If you encounter any problems with Realtek Audio Drivers, try checking the device and cable connections, checking the audio settings and output device, restarting the audio service, or reinstalling the driver.</li>
|
| 189 |
-
<li>If you need more help or support with Realtek Audio Drivers, you can visit their official website or contact their customer service.</li>
|
| 190 |
-
</ul>
|
| 191 |
-
<h2>Frequently Asked Questions (FAQs)</h2>
|
| 192 |
-
<h3><a name="faq1"></a><a href="#faq1">What is Realtek HD Audio Manager and how to use it?</a></h3>
|
| 193 |
-
<p><a href="#faq1">Realtek HD Audio Manager</a></p>
|
| 194 |
-
<p><a href="#faq1">Realtek HD Audio Manager is a software program that comes with Realtek Audio Drivers. It allows you to access and configure your audio settings, such as volume, balance, equalizer, effects, etc. You can also use it to customize your sound tools and configuration options for your convenience.</p>
|
| 195 |
-
Manager, you can either click on the Realtek HD Audio Manager icon in your system tray or Start menu, or go to the Control Panel and select Realtek HD Audio Manager. You will see a user interface with various tabs and options. You can explore them and adjust them according to your preferences.</p>
|
| 196 |
-
<h3><a name="faq2"></a><a href="#faq2">How to uninstall Realtek Audio Driver?</a></h3>
|
| 197 |
-
<p><a href="#faq2">Uninstall Realtek Audio Driver</a></p>
|
| 198 |
-
<p><a href="#faq2">If you want to uninstall Realtek Audio Driver from your PC, you can do so by following these steps:</p>
|
| 199 |
-
<ol>
|
| 200 |
-
<li>Press <strong>Windows + X</strong> keys on your keyboard and select <strong>Apps and Features</strong>.</li>
|
| 201 |
-
<li>Look for the Realtek Audio Driver in the list of installed programs and click on it.</li>
|
| 202 |
-
<li>Select <strong>Uninstall</strong>.</li>
|
| 203 |
-
<li>Follow the on-screen instructions and confirm your choice.</li>
|
| 204 |
-
<li>Restart your PC if prompted.</li>
|
| 205 |
-
</ol>
|
| 206 |
-
<p>Note that uninstalling Realtek Audio Driver may cause your audio device to stop working or work improperly. You may need to install another compatible driver for your audio device.</p>
|
| 207 |
-
<h3><a name="faq3"></a><a href="#faq3">How to fix Realtek Audio Driver not working or crashing?</a></h3>
|
| 208 |
-
<p><a href="#faq3">Fix Realtek Audio Driver not working or crashing</a></p>
|
| 209 |
-
<p><a href="#faq3">If your Realtek Audio Driver is not working or crashing, you may try the following solutions:</p>
|
| 210 |
-
<ul>
|
| 211 |
-
<li>Update your Realtek Audio Driver to the latest version.</li>
|
| 212 |
-
<li>Run the Windows troubleshooter for audio problems.</li>
|
| 213 |
-
<li>Disable any antivirus or firewall software that may interfere with your audio driver.</li>
|
| 214 |
-
<li>Perform a clean boot of your PC and check if the problem persists.</li>
|
| 215 |
-
<li>Restore your PC to a previous point when the audio driver was working fine.</li>
|
| 216 |
-
</ul>
|
| 217 |
-
<h3><a name="faq4"></a><a href="#faq4">How to enable or disable Realtek audio enhancements?</a></h3>
|
| 218 |
-
<p><a href="#faq4">Enable or disable Realtek audio enhancements</a></p>
|
| 219 |
-
<p><a href="#faq4">Realtek audio enhancements are features that improve the sound quality and effects of your audio device. Some of them are:</p>
|
| 220 |
-
<ul>
|
| 221 |
-
<li>Bass Boost: Enhances the low-frequency sound of your speakers or headphones.</li>
|
| 222 |
-
<li>Virtual Surround: Creates a surround sound effect for your stereo speakers or headphones.</li>
|
| 223 |
-
<li>Loudness Equalization: Balances the volume level of different sounds and reduces sudden volume changes.</li>
|
| 224 |
-
<li>Environmental Effects: Simulates different sound environments, such as room, hall, stadium, etc.</li>
|
| 225 |
-
</ul>
|
| 226 |
-
<p>To enable or disable Realtek audio enhancements, follow these steps:</p>
|
| 227 |
-
<ol>
|
| 228 |
-
<li>Right-click on the speaker icon in your system tray and select <strong>Sounds</strong>.</li>
|
| 229 |
-
<li>Select the <strong>Playback</strong> tab and select your audio device.</li>
|
| 230 |
-
<li>Select the <strong>Properties</strong> button.</li>
|
| 231 |
-
<li>Select the <strong>Enhancements</strong> tab.</li>
|
| 232 |
-
<li>Select or deselect the enhancements that you want to enable or disable.</li>
|
| 233 |
-
<li>Select <strong>OK</strong> to save your changes and close the window.</li>
|
| 234 |
-
</ol>
|
| 235 |
-
<h3><a name="faq5"></a><a href="#faq5">How to contact Realtek support for help?</a></h3>
|
| 236 |
-
<p><a href="#faq5">Contact Realtek support for help</a></p>
|
| 237 |
-
<p><a href="#faq5">If you need more help or support with Realtek Audio Drivers, you can contact Realtek support by visiting their official website and selecting the <strong>Contact Us</strong> option. You can also send them an email at <strong>[email protected]</strong>. Alternatively, you can visit their online forum and post your questions or issues there. You may find some useful answers from other users or experts.</p> 197e85843d<br />
|
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spaces/1phancelerku/anime-remove-background/Download Garena Mod Menu Apk for Free Fire MAX and Enjoy Premium Features.md
DELETED
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@@ -1,95 +0,0 @@
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<br />
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| 2 |
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<h1>Garena Mod Menu Apk: What Is It and How to Use It?</h1>
|
| 3 |
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<p>If you are a fan of Garena Free Fire, a popular survival shooter game for mobile devices, you might have heard of Garena mod menu apk. This is a modified version of the original game apk that allows users to access various cheats and hacks. In this article, we will explain what Garena mod menu apk is, what features it offers, how to install it, and what risks it entails.</p>
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<h2>garena mod menu apk</h2><br /><p><b><b>Download File</b> --->>> <a href="https://jinyurl.com/2uNTES">https://jinyurl.com/2uNTES</a></b></p><br /><br />
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<h2>What is Garena Free Fire?</h2>
|
| 6 |
-
<h3>A popular survival shooter game for mobile devices</h3>
|
| 7 |
-
<p>Garena Free Fire is a world-famous survival shooter game available on mobile. Each 10-minute game places you on a remote island where you are pit against 49 other players, all seeking survival. Players freely choose their starting point with their parachute, and aim to stay in the safe zone for as long as possible. Drive vehicles to explore the vast map, hide in the wild, or become invisible by proning under grass or rifts. Ambush, snipe, survive, there is only one goal: to survive and answer the call of duty.</p>
|
| 8 |
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<h3>Different game modes and features</h3>
|
| 9 |
-
<p>Free Fire offers a variety of exciting game modes with all Free Fire players via exclusive Firelink technology. You can enjoy fast-paced 4v4 Clash Squad matches, classic 50-player Battle Royale matches, or special modes such as Rampage, Bomb Squad, or Zombie Invasion. You can also customize your character with hundreds of outfits, accessories, weapons, vehicles, and pets. You can also create squads of up to 4 players and communicate with your team using in-game voice chat.</p>
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| 10 |
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<h2>What is a mod menu apk?</h2>
|
| 11 |
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<h3>A modified version of the original game apk</h3>
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| 12 |
-
<p>A mod menu apk is a changed version of the game’s original apk that can be used to get free cheats. With this mod menu apk, you don’t need any other programs to load cheats into the game. Perfect for those who do not know how to hack Free Fire. The mod menu apk has a user-friendly interface that allows you to toggle on and off different cheats with a simple tap.</p>
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<h3>Allows users to access various cheats and hacks</h3>
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| 54 |
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<p>The mod menu apk offers tons of cheats for its users. Some of the most popular ones are unlimited diamonds and coins, wallhack, aimbot, ESP hack, flying hack, unlock characters, and skins hack. These cheats can give you an edge over your enemies and help you win more matches. However, they also come with some risks that you should be aware of before using them.</p>
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| 55 |
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<h2>What are the features of Garena mod menu apk?</h2>
|
| 56 |
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<h3>Unlimited diamonds and coins</h3>
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| 57 |
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<p>Diamonds and coins are the in-game currency in Free Fire and without them you can’t even purchase a skin in the game. With the mod menu apk, you can get unlimited diamonds and coins for free. You can use them to buy anything you want in the game, such as outfits, weapons, vehicles, pets, or elite passes.</p>
|
| 58 |
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<h3>Wallhack</h3 <p>Wallhack is a cheat that allows you to see through walls and other obstacles. You can spot your enemies easily and shoot them before they see you. You can also avoid ambushes and traps by knowing where your enemies are hiding. Wallhack can give you a huge advantage in Free Fire, especially in close-quarters combat.</p>
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| 59 |
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<h3>Aimbot</h3>
|
| 60 |
-
<p>Aimbot is a cheat that automatically aims and shoots your enemies for you. You don’t need to worry about your accuracy or reaction time. Just point your weapon in the general direction of your enemy and let the aimbot do the rest. You can kill your enemies with one shot and win every firefight. Aimbot is one of the most powerful cheats in Free Fire, but also one of the most risky ones.</p>
|
| 61 |
-
<h3>ESP hack</h3>
|
| 62 |
-
<p>ESP hack is a cheat that shows you extra information about your enemies on your screen. You can see their name, health, distance, weapon, and location. You can also see their footsteps, items, and vehicles. ESP hack can help you plan your strategy and avoid unnecessary fights. ESP hack can make you more aware of your surroundings and improve your survival chances.</p>
|
| 63 |
-
<h3>Flying hack</h3>
|
| 64 |
-
<p>Flying hack is a cheat that allows you to fly in the air like Superman. You can move faster and reach places that are normally inaccessible. You can also surprise your enemies from above and escape from danger easily. Flying hack can make you more mobile and unpredictable in Free Fire, but also more noticeable and vulnerable.</p>
|
| 65 |
-
<h3>Unlock characters</h3>
|
| 66 |
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<p>Free Fire has a roster of over 40 characters, each with their own unique skills and abilities. However, not all of them are available for free. Some of them require diamonds or coins to unlock. With the mod menu apk, you can unlock all the characters for free and use them in the game. You can experiment with different combinations of characters and skills and find the ones that suit your playstyle.</p>
|
| 67 |
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<h3>Skins hack</h3>
|
| 68 |
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<p>Skins are cosmetic items that change the appearance of your character, weapons, vehicles, or pets. They have no effect on the gameplay, but they can make you look cooler and more stylish. Free Fire has a huge collection of skins, but most of them are expensive or rare. With the mod menu apk, you can get all the skins for free and use them in the game. You can customize your character and show off your personality with different skins.</p>
|
| 69 |
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<h2>How to install Garena mod menu apk?</h2>
|
| 70 |
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<h3>Download the mod menu apk from a trusted source</h3>
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| 71 |
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<p>The first step to install Garena mod menu apk is to download it from a trusted source. There are many websites that claim to offer the mod menu apk, but not all of them are safe or reliable. Some of them may contain malware or viruses that can harm your device or steal your data. To avoid this, you should only download the mod menu apk from a reputable source that has positive reviews and feedback from other users. You can also scan the mod menu apk file with an antivirus program before installing it.</p>
|
| 72 |
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<h3>Enable unknown sources in your device settings</h3>
|
| 73 |
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<p>The second step to install Garena mod menu apk is to enable unknown sources in your device settings. This is because the mod menu apk is not from the official Google Play Store or App Store, so your device may not allow you to install it by default. To enable unknown sources, you need to go to your device settings, then security or privacy, then toggle on the option that says "allow installation of apps from unknown sources" or something similar. This will allow you to install the mod menu apk without any problems.</p>
|
| 74 |
-
<h3>Install the mod menu apk and launch the game</h3>
|
| 75 |
-
<p>The third step to install Garena mod menu apk is to install it and launch the game. To install it, you need to locate the mod menu apk file on your device storage, then tap on it and follow the instructions on the screen. It may take a few minutes for the installation to complete. Once it is done, you can launch the game by tapping on its icon on your home screen or app drawer. You will see a mod menu icon on the top left corner of the game screen. Tap on it to access the cheats and hacks.</p>
|
| 76 |
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<h2>What are the risks of using Garena mod menu apk?</h2>
|
| 77 |
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<h3>Possible detection and ban by the game developers</h3 <p>Possible detection and ban by the game developers</p>
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<p>One of the biggest risks of using Garena mod menu apk is that you may get detected and banned by the game developers. The game developers have a strict anti-cheat system that monitors the game activity and detects any abnormal behavior. If you are caught using the mod menu apk, you may face consequences such as account suspension, permanent ban, or legal action. You may also lose your progress, achievements, and rewards in the game. Therefore, you should use the mod menu apk at your own risk and discretion.</p>
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<h3>Malware and viruses from unverified sources</h3>
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<p>Another risk of using Garena mod menu apk is that you may get malware and viruses from unverified sources. As mentioned earlier, not all websites that offer the mod menu apk are safe or reliable. Some of them may contain malicious code that can infect your device or steal your data. You may also get unwanted ads, pop-ups, or redirects that can annoy you or compromise your privacy. To avoid this, you should only download the mod menu apk from a trusted source and scan it with an antivirus program before installing it.</p>
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<h3>Loss of original account and data</h3>
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<p>A third risk of using Garena mod menu apk is that you may lose your original account and data. The mod menu apk is not compatible with the official version of the game, so you cannot use your existing account or data with it. You have to create a new account and start from scratch. You also cannot play with other players who are using the official version of the game, as they are on different servers. You may also face compatibility issues or errors while playing the game with the mod menu apk. Therefore, you should backup your original account and data before using the mod menu apk.</p>
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<h2>Conclusion</h2>
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<p>Garena mod menu apk is a modified version of the original game apk that allows users to access various cheats and hacks in Free Fire. It offers features such as unlimited diamonds and coins, wallhack, aimbot, ESP hack, flying hack, unlock characters, and skins hack. However, it also comes with some risks such as possible detection and ban by the game developers, malware and viruses from unverified sources, and loss of original account and data. Therefore, you should use it at your own risk and discretion.</p>
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<h2>FAQs</h2>
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<table>
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<tr><td><b>Question</b></td><td><b>Answer</b></td></tr>
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<tr><td>Is Garena mod menu apk legal?</td><td>No, Garena mod menu apk is not legal. It violates the terms of service and policies of the game developers. It also infringes on their intellectual property rights. Using it may result in legal action from the game developers.</td></tr>
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<tr><td>Is Garena mod menu apk safe?</td><td>Not necessarily. Garena mod menu apk may contain malware or viruses that can harm your device or steal your data. It may also get detected and banned by the game developers. It may also cause compatibility issues or errors while playing the game. Therefore, you should only download it from a trusted source and scan it with an antivirus program before installing it.</td></tr>
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<tr><td>Can I use Garena mod menu apk with my existing account?</td><td>No, you cannot use Garena mod menu apk with your existing account. The mod menu apk is not compatible with the official version of the game, so you have to create a new account and start from scratch. You also cannot play with other players who are using the official version of the game, as they are on different servers.</td></tr>
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<tr><td>How can I update Garena mod menu apk?</td><td>You can update Garena mod menu apk by downloading the latest version from a trusted source and installing it over the previous version. However, you should be careful as some updates may not work with the mod menu apk or may increase the chances of detection and ban by the game developers.</td></tr>
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<tr><td>Are there any alternatives to Garena mod menu apk?</td><td>Yes, there are some alternatives to Garena mod menu apk such as scripts, injectors, or tools that can also provide cheats and hacks for Free Fire. However, they also have similar risks and drawbacks as Garena mod menu apk.</td></tr>
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</table></p> 401be4b1e0<br />
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spaces/1phancelerku/anime-remove-background/Download Ministrike 3.7 APK for Android - Enjoy the Best Counter-Strike Tribute.md
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<h1>Download MiniStrike 3.7: A Fun and Fast-Paced Shooter Game for Android</h1>
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<p>If you are looking for a fun and fast-paced shooter game for your Android device, you should definitely check out MiniStrike. MiniStrike is a tribute to the popular Counter-Strike game, but with a cute and pixelated style. You can play online with other players, or offline with bots, in different modes and maps. You can also customize your character and your weapons with various skins and items. In this article, we will show you how to download MiniStrike 3.7, the latest version of the game, which has bug fixes and improvements, and no ads or in-app purchases.</p>
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<h2>download ministrike 3.7</h2><br /><p><b><b>Download Zip</b> » <a href="https://jinyurl.com/2uNLV9">https://jinyurl.com/2uNLV9</a></b></p><br /><br />
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<h2>What is MiniStrike?</h2>
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<p>MiniStrike is a shooter game developed by Malo The Toad, an independent game developer from France. The game was released in 2016 and has been updated regularly since then. The game is inspired by Counter-Strike, one of the most popular and influential shooter games of all time.</p>
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<h3>A tribute to Counter-Strike</h3>
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<p>MiniStrike pays homage to Counter-Strike by recreating some of its iconic features, such as the gameplay mechanics, the weapons, the sounds, and the maps. You can choose between two teams, terrorists or counter-terrorists, and complete different objectives, such as planting or defusing bombs, rescuing hostages, or eliminating the enemy team. You can also buy weapons and equipment at the beginning of each round, using the money you earn from killing enemies or completing objectives.</p>
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<h3>A multiplayer game with different modes and maps</h3>
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<p>MiniStrike is a multiplayer game that allows you to play online with other players from around the world, or offline with bots. You can join or create rooms with different settings, such as the number of players, the game mode, and the map. The game has four modes: deathmatch, team deathmatch, bomb defusal, and hostage rescue. The game also has 15 maps, some of which are based on Counter-Strike maps, such as de_dust2, cs_office, or de_nuke.</p>
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<h3>A customizable game with skins and weapons</h3>
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<p>MiniStrike is a customizable game that lets you personalize your character and your weapons with various skins and items. You can unlock skins by playing the game or by watching ads. You can also buy items with coins that you earn from playing or from daily rewards. You can equip different items for your head, body, hands, feet, and backpack. You can also change the skin of your weapons, such as pistols, rifles, shotguns, snipers, or knives.</p>
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<h2>Why download MiniStrike 3.7?</h2>
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<p>MiniStrike 3.7 is the latest version of the game that was released on June 14th, 2021. This version has several bug fixes and improvements that make the game more stable and enjoyable. Here are some of the reasons why you should download MiniStrike 3.7:</p>
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<h3>The latest version with bug fixes and improvements</h3>
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<p>MiniStrike 3.7 has fixed some of the issues that were reported by players in previous versions, such as crashes, glitches, lagging, or freezing. The developer has also improved some of the features of the game, such as the graphics quality, the sound effects, the user interface, or the gameplay balance. The developer has also added some new content to the game , such as new skins, new weapons, and new maps.</p>
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<p>How to download ministrike 3.7 on android<br />
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Download ministrike 3.7 apk for free<br />
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Download ministrike 3.7 mod apk with unlimited money<br />
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Download ministrike 3.7 for pc using emulator<br />
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Download ministrike 3.7 offline installer<br />
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Download ministrike 3.7 from apkpure.com[^1^]<br />
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Download ministrike 3.7 for ios devices<br />
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Download ministrike 3.7 from google play store<br />
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Download ministrike 3.7 for windows phone<br />
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Download ministrike 3.7 from amazon appstore<br />
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Download ministrike 3.7 for mac os x<br />
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Download ministrike 3.7 from uptodown.com<br />
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Download ministrike 3.7 from softonic.com<br />
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Download ministrike 3.7 from apkmonk.com<br />
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Download ministrike 3.7 from apk-dl.com<br />
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Ministrike 3.7 chat and voice commands<br />
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Download ministrike 3.7 from apkmirror.com</p>
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<h3>The best way to enjoy the game without ads or in-app purchases</h3>
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<p>MiniStrike 3.7 is the best way to enjoy the game without any ads or in-app purchases. The game is completely free and does not require any registration or login. You can play the game without any interruptions or distractions from ads or pop-ups. You can also access all the features and content of the game without spending any real money. You can unlock skins and items by playing the game or by watching ads voluntarily. You can also earn coins by playing the game or by claiming daily rewards.</p>
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<h3>The easiest way to install the game on your device</h3>
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<p>MiniStrike 3.7 is the easiest way to install the game on your Android device. You do not need to download the game from the Google Play Store, which may not be compatible with your device or may not have the latest version of the game. You can download the game from the APKPure website, which is a trusted and reliable source of APK files for Android apps and games. You can install the game on your device in a few simple steps, which we will explain in the next section.</p>
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<h2>How to download MiniStrike 3.7?</h2>
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<p>Downloading MiniStrike 3.7 is very easy and fast. You just need to follow these steps:</p>
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<h3>Step 1: Go to the APKPure website</h3>
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<p>The first step is to go to the APKPure website, which is <a href="">https://apkpure.com/ministrike/com.ministrike</a>. This is where you can find the latest version of MiniStrike 3.7, as well as other versions of the game. You can also read more information about the game, such as its description, features, screenshots, reviews, and ratings.</p>
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<h3>Step 2: Click on the download button</h3>
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<p>The second step is to click on the download button, which is located at the top right corner of the website. This will start downloading the APK file of MiniStrike 3.7 on your device. The file size is about 35 MB, so it should not take too long to download.</p>
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<h3>Step 3: Allow unknown sources on your device</h3>
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<p>The third step is to allow unknown sources on your device, which means that you can install apps and games that are not from the Google Play Store. To do this, you need to go to your device settings, then security, then enable unknown sources. This will allow you to install MiniStrike 3.7 on your device.</p>
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<h3>Step 4: Install the APK file and launch the game</h3>
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<p>The fourth and final step is to install the APK file and launch the game. To do this, you need to locate the downloaded file on your device, then tap on it to start installing it. Once the installation is complete, you can tap on the open button to launch the game. Alternatively, you can find the game icon on your home screen or app drawer and tap on it to launch the game.</p>
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<h2>Conclusion</h2>
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<p>MiniStrike 3.7 is a fun and fast-paced shooter game for Android devices that pays tribute to Counter-Strike. You can play online with other players or offline with bots in different modes and maps. You can also customize your character and your weapons with various skins and items. MiniStrike 3.7 is the latest version of the game that has bug fixes and improvements, and no ads or in-app purchases. You can download MiniStrike 3.7 from the APKPure website in a few easy steps.</p>
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<h2>FAQs</h2>
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<p>Here are some of the frequently asked questions about MiniStrike 3.7:</p>
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<h4>Q: Is MiniStrike 3.7 safe to download and install?</h4>
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<p>A: Yes, MiniStrike 3.7 is safe to download and install from the APKPure website, which is a trusted and reliable source of APK files for Android apps and games. The website scans all the files for viruses and malware before uploading them.</p>
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<h4>Q: Is MiniStrike 3.7 compatible with my device?</h4>
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<p>A: MiniStrike 3.7 is compatible with most Android devices that have Android 4.1 or higher as their operating system. However, some devices may not be able to run the game smoothly due to their hardware specifications or performance issues.</p>
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<h4>Q: How can I update MiniStrike 3.7?</h4>
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<p>A: You can update MiniStrike 3.7 by downloading and installing the latest version of the game from the APKPure website, which will always have the newest version of the game. You can also enable the auto-update option on the website, which will notify you when a new version of the game is available and download it automatically.</p>
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<h4>Q: How can I contact the developer of MiniStrike 3.7?</h4>
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<p>A: You can contact the developer of MiniStrike 3.7 by sending an email to <a href="mailto:[email protected]">[email protected]</a>. You can also follow the developer on Twitter at <a href="https://twitter.com/MaloTheToad">@MaloTheToad</a>, where he posts updates and news about the game.</p>
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<h4>Q: How can I support the developer of MiniStrike 3.7?</h4>
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<p>A: You can support the developer of MiniStrike 3.7 by rating and reviewing the game on the APKPure website, or by sharing the game with your friends and family. You can also donate to the developer via PayPal at <a href="https://www.paypal.me/malothetoad">https://www.paypal.me/malothetoad</a>, or by watching ads voluntarily in the game.</p> 197e85843d<br />
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spaces/1phancelerku/anime-remove-background/Download NBA 2K20 APK 98.0.2 for Android - Experience the Classic 2K Action on the Go.md
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<br />
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<h1>NBA 2K20 APK: The Ultimate Basketball Game for Android</h1>
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<p>If you are a fan of basketball and want to experience the thrill of playing on your mobile device, then you should try NBA 2K20 APK. This is the latest version of the popular NBA 2K series, which is developed by 2K, Inc. and offers the most realistic and immersive basketball simulation ever. In this article, we will tell you everything you need to know about NBA 2K20 APK, including its features, how to download and install it, how to play it, and its pros and cons.</p>
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<h2>What is NBA 2K20 APK?</h2>
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<p>NBA 2K20 APK is an Android game that lets you play as your favorite NBA players and teams in various game modes and challenges. You can create your own custom player, join a team, compete in tournaments, or just enjoy a casual game with friends. You can also explore the NBA culture and lifestyle, with exclusive content from celebrities, influencers, and legends. NBA 2K20 APK is the ultimate basketball game for Android, with stunning graphics, realistic physics, smooth controls, and engaging gameplay.</p>
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<h2>98.0.2 nba 2k20 apk</h2><br /><p><b><b>Download Zip</b> >>>>> <a href="https://jinyurl.com/2uNU49">https://jinyurl.com/2uNU49</a></b></p><br /><br />
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<h3>Features of NBA 2K20 APK</h3>
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<p>NBA 2K20 APK has many features that make it stand out from other basketball games. Here are some of them:</p>
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<h4>- Realistic graphics and gameplay</h4>
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<p>NBA 2K20 APK uses advanced technology to deliver lifelike graphics and animations, with detailed player models, facial expressions, movements, and reactions. The game also features realistic sound effects, commentary, crowd noise, and music. The gameplay is smooth and responsive, with intuitive controls and mechanics. You can feel the impact of every shot, pass, dribble, steal, block, and dunk.</p>
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<h4>- Multiple game modes and challenges</h4>
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<p>NBA 2K20 APK offers a variety of game modes and challenges to suit your preferences and skills. You can play in the following modes:</p>
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<ul>
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<li><b>MyCAREER</b>: This is the main mode where you create your own custom player and follow his journey from rookie to legend. You can customize your player's appearance, attributes, skills, style, and equipment. You can also interact with other players, coaches, agents, fans, and media. You can earn coins, rewards, badges, and endorsements as you progress.</li>
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<li><b>MyTEAM</b>: This is the mode where you build your own dream team of NBA players from past and present. You can collect cards, trade players, upgrade your roster, and compete in various online and offline modes. You can also participate in special events, challenges, tournaments, and seasons.</li>
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<li><b>Blacktop</b>: This is the mode where you play street basketball in various locations around the world. You can choose from different formats, such as 1v1, 2v2, 3v3, or 5v5. You can also customize the rules, time limit, score limit, difficulty level, and court size.</li>
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<li><b>Quick Game</b>: This is the mode where you play a single game with any NBA team of your choice. You can choose from different settings, such as quarter length, difficulty level, camera angle, and uniforms.</li>
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<li><b>Play Now Online</b>: This is the mode where you play online against other players from around the world. You can choose from different tiers, leagues, and rankings. You can also chat with your opponents and view their stats and records.</li>
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<li><b>2KTV</b>: This is the mode where you watch the official NBA 2K TV show, hosted by Alexis Morgan and Chris Manning. You can learn tips and tricks, watch interviews, get updates, and participate in interactive quizzes and polls.</li>
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</ul>
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<h4>- Customization and personalization options</h4>
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<p>NBA 2K20 APK gives you the freedom to customize and personalize your game experience. You can change the settings, such as the language, subtitles, controls, camera, audio, and graphics. You can also edit the rosters, ratings, contracts, injuries, and transactions of any NBA team. You can also create your own custom teams, players, jerseys, courts, logos, and arenas.</p>
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<h4>- Online multiplayer and social features</h4>
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<p>NBA 2K20 APK allows you to play online with or against other players from around the world. You can join or create a crew, chat with your friends, send messages, invite players, join parties, and voice chat. You can also share your game highlights, screenshots, videos, and achievements on social media platforms, such as Facebook, Twitter, Instagram, and YouTube.</p>
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| 25 |
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<h3>How to download and install NBA 2K20 APK?</h3>
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<p>If you want to download and install NBA 2K20 APK on your Android device, you need to follow these steps:</p>
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<h4>- Requirements and compatibility</h4>
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<p>Before you download and install NBA 2K20 APK, you need to make sure that your device meets the following requirements:</p>
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-
<ul>
|
| 30 |
-
<li>Your device must have Android 4.3 or higher operating system.</li>
|
| 31 |
-
<li>Your device must have at least 3 GB of free storage space.</li>
|
| 32 |
-
<li>Your device must have at least 2 GB of RAM.</li>
|
| 33 |
-
<li>Your device must have a stable internet connection.</li>
|
| 34 |
-
<li>Your device must support OpenGL ES 3.0 or higher.</li>
|
| 35 |
-
</ul>
|
| 36 |
-
<h4>- Steps to download and install NBA 2K20 APK</h4>
|
| 37 |
-
<p>After you check the requirements and compatibility of your device, you can proceed to download and install NBA 2K20 APK by following these steps:</p>
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how to download and install the latest version of the NBA game on your Android device using the APK file[^1^]<br />
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how to play NBA basketball game with realistic graphics and smooth controls on your phone or tablet using the APK file[^1^]<br />
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how to play NBA game offline without internet connection using the APK file[^1^]<br />
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| 78 |
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<ol>
|
| 79 |
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<li>Go to the official website of NBA 2K20 APK (https://www.nba2k.com/android) and click on the download button.</li>
|
| 80 |
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<li>Wait for the download to finish and locate the NBA 2K20 APK file on your device.</li>
|
| 81 |
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<li>Tap on the NBA 2K20 APK file and allow the installation from unknown sources if prompted.</li>
|
| 82 |
-
<li>Wait for the installation to complete and launch the game.</li>
|
| 83 |
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<li>Enjoy playing NBA 2K20 APK on your Android device.</li>
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| 84 |
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</ol>
|
| 85 |
-
<h3>How to play NBA 2K20 APK?</h3>
|
| 86 |
-
<p>If you are new to NBA 2K20 APK or want to improve your skills, you might want to know some tips and tricks on how to play the game. Here are some of them:</p>
|
| 87 |
-
<h4>- Tips and tricks for beginners</h4>
|
| 88 |
-
<p>If you are a beginner in NBA 2K20 APK, you might want to follow these tips and tricks:</p>
|
| 89 |
-
<ul>
|
| 90 |
-
<li>Start with the tutorial mode to learn the basic controls and mechanics of the game.</li>
|
| 91 |
-
<li>Play in the quick game mode to practice your skills and get familiar with the teams and players.</li>
|
| 92 |
-
<li>Adjust the difficulty level according to your preference and skill level. You can choose from rookie, pro, all-star, superstar, or hall of fame.</li>
|
| 93 |
-
<li>Use the auto-play feature if you want to let the game play for you. You can also switch between manual and auto-play anytime during the game.</li>
|
| 94 |
-
<li>Use the pause menu to access various options, such as settings, stats, replays, substitutions, and tips.</li>
|
| 95 |
-
<li>Use the virtual joystick and buttons to control your player and perform various actions, such as moving, shooting, passing, dribbling, stealing, blocking, and dunking.</li>
|
| 96 |
-
<li>Use the sprint button to run faster and the turbo button to boost your energy and performance.</li>
|
| 97 |
-
<li>Use the shot meter to time your shots and aim for the green zone for a perfect shot.</li>
|
| 98 |
-
<li>Use the pro stick to perform advanced moves and skills, such as spin moves, step backs, crossovers, fadeaways, and euro steps.</li>
|
| 99 |
-
<li>Use the icon pass to pass the ball to a specific teammate by tapping on his icon.</li>
|
| 100 |
-
<li>Use the pick and roll to set a screen for your teammate and create an open space for a shot or a drive.</li>
|
| 101 |
-
<li>Use the post up to back down your defender and create a favorable position for a shot or a pass.</li>
|
| 102 |
-
<li>Use the defensive assist to help you stay in front of your opponent and prevent him from scoring.</li>
|
| 103 |
-
<li>Use the swipe gestures to perform quick actions, such as stealing, blocking, rebounding, and switching players.</li>
|
| 104 |
-
</ul>
|
| 105 |
-
<h4>- Best players and teams to choose</h4>
|
| 106 |
-
<p>If you want to have an edge over your opponents in NBA 2K20 APK, you might want to choose the best players and teams in the game. Here are some of them:</p>
|
| 107 |
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<table>
|
| 108 |
-
<tr>
|
| 109 |
-
<th>Player</th>
|
| 110 |
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<th>Team</th>
|
| 111 |
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<th>Overall Rating</th>
|
| 112 |
-
</tr>
|
| 113 |
-
<tr>
|
| 114 |
-
<td>LeBron James</td>
|
| 115 |
-
<td>Los Angeles Lakers</td>
|
| 116 |
-
<td>97</td>
|
| 117 |
-
</tr>
|
| 118 |
-
<tr>
|
| 119 |
-
<td>Kawhi Leonard</td>
|
| 120 |
-
<td>Los Angeles Clippers</td>
|
| 121 |
-
<td>97</td>
|
| 122 |
-
</tr>
|
| 123 |
-
<tr>
|
| 124 |
-
<td>Giannis Antetokounmpo</td>
|
| 125 |
-
<td>Milwaukee Bucks</td>
|
| 126 |
-
<td>96</td>
|
| 127 |
-
</tr>
|
| 128 |
-
<tr>
|
| 129 |
-
<td>James Harden</td>
|
| 130 |
-
<td>Houston Rockets</td>
|
| 131 |
-
<td>96</td>
|
| 132 |
-
</tr>
|
| 133 |
-
<tr>
|
| 134 |
-
<td>Kevin Durant</td>
|
| 135 |
-
<td>Brooklyn Nets</td>
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| 136 |
-
<td>96</td>
|
| 137 |
-
</tr>
|
| 138 |
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<tr>
|
| 139 |
-
<td>Stephen Curry</td>
|
| 140 |
-
<td>Golden State Warriors</td>
|
| 141 |
-
<td>95</td>
|
| 142 |
-
</tr>
|
| 143 |
-
<tr> <td>Anthony Davis</td>
|
| 144 |
-
<td>Los Angeles Lakers</td>
|
| 145 |
-
<td>94</td>
|
| 146 |
-
</tr>
|
| 147 |
-
<tr>
|
| 148 |
-
<td>Luka Doncic</td>
|
| 149 |
-
<td>Dallas Mavericks</td>
|
| 150 |
-
<td>94</td>
|
| 151 |
-
</tr>
|
| 152 |
-
<tr>
|
| 153 |
-
<td>Damian Lillard</td>
|
| 154 |
-
<td>Portland Trail Blazers</td>
|
| 155 |
-
<td>94</td>
|
| 156 |
-
</tr>
|
| 157 |
-
<tr>
|
| 158 |
-
<td>Joel Embiid</td>
|
| 159 |
-
<td>Philadelphia 76ers</td>
|
| 160 |
-
<td>91</td>
|
| 161 |
-
</tr>
|
| 162 |
-
<tr>
|
| 163 |
-
<td>Kyrie Irving</td>
|
| 164 |
-
<td>Brooklyn Nets</td>
|
| 165 |
-
<td>91</td>
|
| 166 |
-
</tr>
|
| 167 |
-
<tr>
|
| 168 |
-
<td>Russell Westbrook</td>
|
| 169 |
-
<td>Houston Rockets</td>
|
| 170 |
-
<td>90</td>
|
| 171 |
-
</tr>
|
| 172 |
-
<tr> </tr>
|
| 173 |
-
</table>
|
| 174 |
-
<p>As you can see, these players are the highest rated in the game and have the best skills, attributes, and abilities. They can dominate the game in any position and situation. You can also choose from the following teams, which are the best in the game based on their overall rating, roster, chemistry, and performance:</p>
|
| 175 |
-
<table>
|
| 176 |
-
<tr>
|
| 177 |
-
<th>Team</th>
|
| 178 |
-
<th>Overall Rating</th>
|
| 179 |
-
</tr>
|
| 180 |
-
<tr>
|
| 181 |
-
<td>Los Angeles Lakers</td>
|
| 182 |
-
<td>97</td>
|
| 183 |
-
</tr>
|
| 184 |
-
<tr>
|
| 185 |
-
<td>Los Angeles Clippers</td>
|
| 186 |
-
<td>96</td>
|
| 187 |
-
</tr>
|
| 188 |
-
<tr>
|
| 189 |
-
<td>Milwaukee Bucks</td>
|
| 190 |
-
<td>95</td>
|
| 191 |
-
</tr>
|
| 192 |
-
<tr>
|
| 193 |
-
<td>Brooklyn Nets</td>
|
| 194 |
-
<td>94</td>
|
| 195 |
-
</tr>
|
| 196 |
-
<tr>
|
| 197 |
-
<td>Houston Rockets</td>
|
| 198 |
-
<td>93</td>
|
| 199 |
-
</tr>
|
| 200 |
-
<tr>
|
| 201 |
-
<td>Golden State Warriors</td>
|
| 202 |
-
<td>92</td>
|
| 203 |
-
</tr>
|
| 204 |
-
<tr> </tr>
|
| 205 |
-
<tr>
|
| 206 |
-
<td>Philadelphia 76ers</td>
|
| 207 |
-
<td>91</td>
|
| 208 |
-
</tr>
|
| 209 |
-
<tr>
|
| 210 |
-
<td>Dallas Mavericks</td>
|
| 211 |
-
<td>90</td>
|
| 212 |
-
</tr>
|
| 213 |
-
<tr>
|
| 214 |
-
<td>Portland Trail Blazers</td>
|
| 215 |
-
<td>89</td>
|
| 216 |
-
</tr>
|
| 217 |
-
<tr>
|
| 218 |
-
<td>Boston Celtics</td>
|
| 219 |
-
<td>88</td>
|
| 220 |
-
</tr>
|
| 221 |
-
<tr>
|
| 222 |
-
<td>Toronto Raptors</td>
|
| 223 |
-
<td>87</td>
|
| 224 |
-
</tr>
|
| 225 |
-
</table>
|
| 226 |
-
<p>These teams have the best combination of star players, depth, balance, and chemistry. They can compete with any other team in the game and have a high chance of winning the championship.</p>
|
| 227 |
-
<h4>- How to earn coins and rewards</h4>
|
| 228 |
-
<p>If you want to unlock more features, items, and content in NBA 2K20 APK, you need to earn coins and rewards. Here are some ways to do that:</p>
|
| 229 |
-
<ul>
|
| 230 |
-
<li>Complete the daily, weekly, and monthly objectives and missions. You can find them in the main menu or the game modes. They will give you coins, cards, packs, badges, and other rewards.</li>
|
| 231 |
-
<li>Play in the MyTEAM mode and participate in the events, challenges, tournaments, and seasons. You can earn coins, cards, packs, badges, and other rewards based on your performance and ranking.</li>
|
| 232 |
-
<li>Play in the MyCAREER mode and progress through your career. You can earn coins, rewards, badges, and endorsements based on your performance and popularity.</li>
|
| 233 |
-
<li>Watch the 2KTV show and answer the interactive quizzes and polls. You can earn coins, cards, packs, badges, and other rewards based on your answers.</li>
|
| 234 |
-
<li>Use the locker codes feature to redeem free codes that give you coins, cards, packs, badges, and other rewards. You can find the codes on the official NBA 2K social media accounts or websites.</li>
|
| 235 |
-
<li>Use the spin the wheel feature to spin a wheel that gives you a random reward. You can access this feature once a day in the MyTEAM or MyCAREER mode.</li>
|
| 236 |
-
</ul>
|
| 237 |
-
<h3>Pros and cons of NBA 2K20 APK</h3>
|
| 238 |
-
<p>NBA 2K20 APK is not a perfect game and has its pros and cons. Here are some of them:</p>
|
| 239 |
-
<h4>- Pros</h4>
|
| 240 |
-
<ul>
|
| 241 |
-
<li>The game has amazing graphics and sound effects that make it look and feel like a real NBA game.</li>
|
| 242 |
-
<li>The game has multiple game modes and challenges that offer a lot of variety and replay value.</li>
|
| 243 |
-
<li>The game has a lot of customization and personalization options that allow you to create your own unique player and team.</li>
|
| 244 |
-
<li>The game has online multiplayer and social features that allow you to play with or against other players from around the world.</li>
|
| 245 |
-
<li>The game has exclusive content from celebrities, influencers, and legends that enhance the NBA culture and lifestyle.</li>
|
| 246 |
-
</ul>
|
| 247 |
-
<h4>- Cons</h4>
|
| 248 |
-
<ul>
|
| 249 |
-
<li>The game requires a lot of storage space and RAM to run smoothly on your device.</li>
|
| 250 |
-
<li>The game requires a stable internet connection to access some of the features and content.</li>
|
| 251 |
-
<li>The game has some bugs and glitches that affect the gameplay and performance.</li>
|
| 252 |
-
<li>The game has some ads and in-app purchases that can be annoying or expensive.</li>
|
| 253 |
-
<li>The game can be difficult or frustrating for some players due to the high level of competition and skill required.</li> <h2>Conclusion</h2>
|
| 254 |
-
<p>NBA 2K20 APK is a great game for basketball fans and gamers who want to enjoy a realistic and immersive basketball simulation on their Android devices. The game has many features, modes, challenges, and content that make it fun and engaging. The game also has some drawbacks, such as the high requirements, the internet dependency, the bugs and glitches, the ads and in-app purchases, and the difficulty level. However, these cons do not outweigh the pros and do not ruin the overall experience of the game. NBA 2K20 APK is definitely worth downloading and playing if you love basketball and want to experience the ultimate basketball game for Android.</p>
|
| 255 |
-
<h3>FAQs</h3>
|
| 256 |
-
<p>Here are some frequently asked questions about NBA 2K20 APK:</p>
|
| 257 |
-
<h4>- Is NBA 2K20 APK free?</h4>
|
| 258 |
-
<p>Yes, NBA 2K20 APK is free to download and play. However, the game has some ads and in-app purchases that can enhance your game experience or unlock more features and content.</p>
|
| 259 |
-
<h4>- Is NBA 2K20 APK safe?</h4>
|
| 260 |
-
<p>Yes, NBA 2K20 APK is safe to download and install on your device. The game does not contain any viruses, malware, or spyware that can harm your device or data. However, you should always download the game from the official website or a trusted source to avoid any risks.</p>
|
| 261 |
-
<h4>- Is NBA 2K20 APK offline?</h4>
|
| 262 |
-
<p>No, NBA 2K20 APK is not offline. The game requires a stable internet connection to access some of the features and content, such as the online multiplayer, the social features, the updates, and the exclusive content. You can still play some of the modes and challenges offline, but you will miss out on some of the benefits and rewards of the online features.</p>
|
| 263 |
-
<h4>- How to update NBA 2K20 APK?</h4>
|
| 264 |
-
<p>To update NBA 2K20 APK, you need to follow these steps:</p>
|
| 265 |
-
<ol>
|
| 266 |
-
<li>Go to the official website of NBA 2K20 APK (https://www.nba2k.com/android) and check if there is a new version available.</li>
|
| 267 |
-
<li>If there is a new version available, click on the download button and wait for the download to finish.</li>
|
| 268 |
-
<li>Locate the NBA 2K20 APK file on your device and tap on it to install the new version.</li>
|
| 269 |
-
<li>Wait for the installation to complete and launch the game.</li>
|
| 270 |
-
<li>Enjoy playing the updated version of NBA 2K20 APK.</li>
|
| 271 |
-
</ol>
|
| 272 |
-
<h4>- How to contact NBA 2K20 APK support?</h4>
|
| 273 |
-
<p>If you have any issues, questions, feedback, or suggestions about NBA 2K20 APK, you can contact the NBA 2K20 APK support team by following these steps:</p>
|
| 274 |
-
<ol>
|
| 275 |
-
<li>Go to the main menu of the game and tap on the settings icon.</li>
|
| 276 |
-
<li>Tap on the help button and choose the option that suits your issue or question.</li>
|
| 277 |
-
<li>Fill out the form with your details and message and submit it.</li>
|
| 278 |
-
<li>Wait for a response from the NBA 2K20 APK support team.</li>
|
| 279 |
-
</ol></p> 401be4b1e0<br />
|
| 280 |
-
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|
| 281 |
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spaces/1phancelerku/anime-remove-background/Download and Install Cars for BeamNG.drive A Step-by-Step Tutorial.md
DELETED
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| 1 |
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<h1>How to Download Cars for BeamNG.drive: A Complete Guide</h1>
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| 3 |
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<p>If you are a fan of realistic driving games, you have probably heard of <strong>BeamNG.drive</strong>, a dynamic soft-body physics vehicle simulator that can do just about anything. Whether you want to crash cars, race them, or customize them, BeamNG.drive offers you a wide range of possibilities and options. But did you know that you can also download cars for BeamNG.drive from various sources and add them to your game? In this article, we will show you how to download cars for BeamNG.drive, why you should do it, and what tips and tricks you should know before installing them.</p>
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<h2>beamng download cars</h2><br /><p><b><b>Download Zip</b> ❤ <a href="https://jinyurl.com/2uNU0i">https://jinyurl.com/2uNU0i</a></b></p><br /><br />
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<h2>What is BeamNG.drive?</h2>
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<p>Before we get into how to download cars for BeamNG.drive, let's first understand what this game is all about. BeamNG.drive is a game that was released in 2015 as an early access title on Steam, and it has been constantly updated and improved ever since. It is developed by BeamNG, a small team of passionate programmers and artists who have created their own physics engine from scratch. The game has three main features that make it stand out from other driving games:</p>
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<h3>A realistic driving simulator with soft-body physics</h3>
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<p>The core of BeamNG.drive is its physics engine, which simulates every component of a vehicle in real time using nodes (mass points) and beams (springs). This means that every crash, collision, or deformation is calculated realistically and accurately, resulting in true-to-life behavior. You can see your car crumple, bend, break, or explode depending on how you drive it. You can also tweak every aspect of your car's performance, such as wheels, suspension, engines, brakes, steering, gears, etc. The game also features realistic sounds, graphics, lighting, weather, and damage effects.</p>
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| 9 |
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<h3>A sandbox game with dozens of customizable vehicles and environments</h3>
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<p>BeamNG.drive offers you dozens of refined, totally customizable vehicles for you to experiment with. Whether it's a compact car or massive truck, you can tweak away at all the moving parts to create just about any driving experience you want. You can also choose from 12 sprawling open-world environments that range from tropical jungles to urban highways. Each environment has its own terrain <h3>A modding-friendly game with a vibrant community</h3>
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| 11 |
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<p>One of the best things about BeamNG.drive is that it is very modding-friendly. You can create your own vehicles, maps, scenarios, skins, sounds, and more using the game's built-in tools or external software. You can also download and install mods made by other players from various sources, such as the official BeamNG website, Steam Workshop, or other websites. The game has a very active and supportive community of modders and players who share their creations, feedback, and ideas. You can also join online multiplayer sessions and play with or against other people.</p>
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| 12 |
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<h2>Why Download Cars for BeamNG.drive?</h2>
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<p>Now that you know what BeamNG.drive is, you might be wondering why you should download cars for it. After all, the game already has plenty of vehicles to choose from, right? Well, there are several reasons why downloading cars for BeamNG.drive can enhance your gameplay experience and make it more fun and diverse. Here are some of them:</p>
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<h3>To enhance your gameplay experience with new models, features, and styles</h3>
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<p>Downloading cars for BeamNG.drive can give you access to new models that are not available in the base game. These models can have different features, such as unique engines, transmissions, suspensions, body parts, etc. They can also have different styles, such as classic cars, sports cars, muscle cars, supercars, etc. You can find cars that suit your preferences and tastes, or try out something new and different. You can also mix and match different parts from different mods to create your own custom car.</p>
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<h3>To explore different types of vehicles and driving scenarios</h3>
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<p>Downloading cars for BeamNG.drive can also allow you to explore different types of vehicles and driving scenarios that you might not encounter in the base game. For example, you can download cars that are designed for off-road driving, drifting, racing, stunt driving, demolition derby, etc. You can also download cars that are based on real-life vehicles or fictional ones from movies, games, or other media. You can test your skills and challenge yourself with different vehicles and situations.</p>
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| 67 |
-
<h3>To support the modders and creators who make the game more diverse and fun</h3>
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<p>Another reason why you should download cars for BeamNG.drive is to support the modders and creators who make them. These people spend a lot of time and effort to create high-quality mods that add value and variety to the game. They also share their mods for free for everyone to enjoy. By downloading their mods, you are showing your appreciation and encouragement for their work. You are also helping them to improve their skills and create more mods in the future.</p>
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| 69 |
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<h2>How to Download Cars for BeamNG.drive?</h2>
|
| 70 |
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<p>Now that you know why you should download cars for BeamNG.drive, let's get into how to do it. There are three main sources where you can download cars for BeamNG.drive: the official BeamNG website, Steam Workshop, and other sources. Each source has its own advantages and disadvantages, so you should choose the one that suits you best. Here is how to download cars from each source:</p>
|
| 71 |
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<h3>From the official BeamNG website</h3>
|
| 72 |
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<p>The official BeamNG website is the primary source where you can download cars for BeamNG.drive. It has a dedicated section called <a href="">Vehicles</a>, where you can find hundreds of car mods made by the developers or the community. The website has a simple and user-friendly interface where you can browse, search, filter, sort, and download car mods easily. Here is how to download cars from the official BeamNG website:</p>
|
| 73 |
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<ul>
|
| 74 |
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<li>Browse the Vehicles category and find the car you want. You can use the filters on the left side to narrow down your search by type, style, rating, popularity, etc.</li>
|
| 75 |
-
<li>Click on the car mod you want to view its details page. You can see some screenshots, videos, descriptions, ratings, comments, and other information about the mod.</li>
|
| 76 |
-
<li>Click on the Download button on the top right corner of the page and save the file to your computer. The file will be in ZIP format.</li>
|
| 77 |
-
<li>Extract the file using a program like WinRAR or 7-Zip and copy the folder inside it to your BeamNG.drive mods folder. The default location of this folder is C:\Users\YourName\Documents\BeamNG.drive\mods.</li>
|
| 78 |
-
<li>Launch the game and enable the mod from the in-game mod manager. You can access this by pressing Esc on your keyboard and clicking on Mods on the bottom left corner of the screen.</li>
|
| 79 |
-
<li>Enjoy your new car!</li>
|
| 80 |
-
</ul> <h3>From Steam Workshop</h3>
|
| 81 |
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<p>Another source where you can download cars for BeamNG.drive is Steam Workshop, a platform where Steam users can create and share content for various games. Steam Workshop has a large and active community of modders and players who upload and download car mods for BeamNG.drive. Steam Workshop has some advantages over the official BeamNG website, such as automatic updates, easier installation, and integration with Steam. However, it also has some disadvantages, such as lower quality control, limited search options, and dependency on Steam. Here is how to download cars from Steam Workshop:</p>
|
| 82 |
-
<ul>
|
| 83 |
-
<li>Subscribe to the car mod you want from the Steam Workshop page. You can access this page by launching Steam, going to your Library, right-clicking on BeamNG.drive, selecting Properties, and clicking on Browse the Workshop. You can also use this <a href="">link</a> to go directly to the BeamNG.drive workshop page.</li>
|
| 84 |
-
<li>Browse or search for the car mod you want. You can use the tabs on the right side to filter by categories, tags, ratings, etc. You can also use the search bar on the top right corner to enter keywords.</li>
|
| 85 |
-
<li>Click on the car mod you want to view its details page. You can see some screenshots, videos, descriptions, ratings, comments, and other information about the mod.</li>
|
| 86 |
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<li>Click on the Subscribe button on the top right corner of the page. This will automatically download the mod to your computer and install it to your game.</li>
|
| 87 |
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<li>Launch the game and enable the mod from the in-game mod manager. You can access this by pressing Esc on your keyboard and clicking on Mods on the bottom left corner of the screen.</li>
|
| 88 |
-
<li>Enjoy your new car!</li>
|
| 89 |
-
</ul> <h3>From other sources</h3>
|
| 90 |
-
<p>The third source where you can download cars for BeamNG.drive is from other websites or forums that host car mods for the game. These sources can have some advantages over the official BeamNG website and Steam Workshop, such as more variety, exclusivity, or novelty. However, they also have some disadvantages, such as potential viruses, malware, or incompatible files. You should be careful and cautious when downloading car mods from other sources, and follow the instructions provided by the mod author or website. Here is how to download cars from other sources:</p>
|
| 91 |
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<ul>
|
| 92 |
-
<li>Be careful of potential viruses, malware, or incompatible files. Before downloading any car mod from an unknown source, you should scan it with an antivirus program and check its compatibility and quality. You should also read the reviews and comments from other users who have downloaded the mod.</li>
|
| 93 |
-
<li>Follow the instructions provided by the mod author or website. Different car mods may have different installation methods or requirements. You should follow the instructions carefully and make sure you have everything you need to run the mod. Some common steps are: <ul>
|
| 94 |
-
<li>Download the car mod file from the website or forum. The file may be in ZIP, RAR, 7Z, or other formats.</li>
|
| 95 |
-
<li>Extract the file using a program like WinRAR or 7-Zip and copy the folder inside it to your BeamNG.drive mods folder. The default location of this folder is C:\Users\YourName\Documents\BeamNG.drive\mods.</li>
|
| 96 |
-
<li>Launch the game and enable the mod from the in-game mod manager. You can access this by pressing Esc on your keyboard and clicking on Mods on the bottom left corner of the screen.</li>
|
| 97 |
-
</ul>
|
| 98 |
-
</li>
|
| 99 |
-
<li>Enjoy your new car!</li>
|
| 100 |
-
</ul>
|
| 101 |
-
<h2>Tips and Tricks for Downloading Cars for BeamNG.drive</h2>
|
| 102 |
-
<p>Downloading cars for BeamNG.drive can be a fun and rewarding experience, but it can also be a frustrating and disappointing one if you don't know what you are doing. To avoid any problems or issues with your car mods, you should follow some tips and tricks that will help you download, install, and use them properly. Here are some of them:</p>
|
| 103 |
-
<h3>Read the mod description, reviews, and comments carefully before downloading</h3>
|
| 104 |
-
<p>Before you download any car mod for BeamNG.drive, you should read its description, reviews, and comments carefully. This will help you understand what the mod does, how it works, what it requires, and what it offers. You can also learn about any bugs, glitches, or compatibility issues that the mod may have. You can also see what other users think about the mod and how they rate it. This will help you decide whether the mod is worth downloading or not.</p>
|
| 105 |
-
<h3>Check for updates and patches for your mods regularly</h3>
|
| 106 |
-
<p>After you download and install a car mod for BeamNG.drive, you should check for updates and patches for it regularly. This will help you keep your mod up to date and fix any errors or problems that it may have. You can check for updates and patches by visiting the source where you downloaded the mod from, such as the official BeamNG website, Steam Workshop, or other websites or forums. You can also use some tools or programs that can automatically update your mods for you.</p>
|
| 107 |
-
<h3>Backup your game files and mods before installing new ones</h3>
|
| 108 |
-
<p>Before you install any new car mod for BeamNG.drive, you should backup your game files and mods first. This will help you prevent any data loss or corruption that may occur due to installing a faulty or incompatible mod. You can backup your game files and mods by copying them to another location on your computer or an external drive. You can also use some tools or programs that can backup your game files and mods for you.</p>
|
| 109 |
-
<h3>Don't use too many mods at once to avoid performance issues or crashes</h3>
|
| 110 |
-
<p>While using car mods for BeamNG.drive can be fun and exciting, it can also be taxing on your computer's resources and stability. If you use too many mods at once, you may experience performance issues such as lagging, stuttering, freezing, or crashing. To avoid this, you should limit the number of mods you use at a time and disable any unnecessary ones. You should also monitor your computer's CPU, RAM, GPU, and disk usage while playing the game with mods.</p>
|
| 111 |
-
<h2>Conclusion</h2>
|
| 112 |
-
<p>In conclusion, downloading cars for BeamNG.drive can be a great way to enhance your gameplay experience and make it more fun and diverse. You can download cars from various sources such as the official BeamNG website, Steam Workshop, or other websites or forums. You can also create your own cars using the game's tools or external software. However, you should be careful and cautious when downloading and installing car mods, and follow some tips and tricks that will help you avoid any problems or issues. You should also backup your game files and mods, check for updates and patches, read the mod descriptions and reviews, and don't use too many mods at once. We hope that this article has helped you learn how to download cars for BeamNG.drive, why you should do it, and what tips and tricks you should know before installing them. If you are ready to try out some car mods for BeamNG.drive, here are some links to popular or recommended car mods that you can download from the official BeamNG website or Steam Workshop: - <a href="">The CrashHard Dummy</a>: A realistic crash test dummy that can be used in any vehicle. - <a href="">The ETK 800 Series</a>: A series of luxury sedans with various configurations and features. - <a href="">The Hirochi Sunburst</a>: A sporty hatchback with a rally-inspired design and performance. - <a href="">The Gavril D-Series</a>: A versatile pickup truck with a lot of customization options and accessories. - <a href="">The Ibishu Pessima</a>: A classic Japanese sedan with two generations and a lot of nostalgia. Have fun downloading cars for BeamNG.drive and enjoy the game! <h2>FAQs</h2>
|
| 113 |
-
<p>Here are some frequently asked questions about downloading cars for BeamNG.drive:</p>
|
| 114 |
-
<ul>
|
| 115 |
-
<li><strong>Q: How do I uninstall a car mod for BeamNG.drive?</strong></li>
|
| 116 |
-
<li>A: To uninstall a car mod for BeamNG.drive, you can either delete the mod folder from your BeamNG.drive mods folder, or disable the mod from the in-game mod manager. If you downloaded the mod from Steam Workshop, you can also unsubscribe from it on the Steam Workshop page.</li>
|
| 117 |
-
<li><strong>Q: How do I update a car mod for BeamNG.drive?</strong></li>
|
| 118 |
-
<li>A: To update a car mod for BeamNG.drive, you can either download the latest version of the mod from the source where you downloaded it from, or use a tool or program that can automatically update your mods for you. If you downloaded the mod from Steam Workshop, it will be updated automatically by Steam.</li>
|
| 119 |
-
<li><strong>Q: How do I create my own car mod for BeamNG.drive?</strong></li>
|
| 120 |
-
<li>A: To create your own car mod for BeamNG.drive, you can use the game's built-in tools or external software to design and model your car. You can also use existing car mods as a base or reference for your car. You can find more information and tutorials on how to create car mods on the official BeamNG website or forum.</li>
|
| 121 |
-
<li><strong>Q: How do I share my car mod for BeamNG.drive?</strong></li>
|
| 122 |
-
<li>A: To share your car mod for BeamNG.drive, you can upload it to the official BeamNG website, Steam Workshop, or other websites or forums that host car mods for the game. You should also provide a detailed description, screenshots, videos, and other information about your mod to attract more users and feedback.</li>
|
| 123 |
-
<li><strong>Q: How do I find more car mods for BeamNG.drive?</strong></li>
|
| 124 |
-
<li>A: To find more car mods for BeamNG.drive, you can visit the official BeamNG website, Steam Workshop, or other websites or forums that host car mods for the game. You can also use search engines, social media, YouTube, or other platforms to discover new or popular car mods.</li>
|
| 125 |
-
</ul></p> 401be4b1e0<br />
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spaces/AIFILMS/audioldm-text-to-audio-generation/audioldm/__init__.py
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
from .ldm import LatentDiffusion
|
| 2 |
-
from .utils import seed_everything
|
| 3 |
-
from .pipeline import *
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spaces/AIFILMS/speecht5-tts-demo/README.md
DELETED
|
@@ -1,14 +0,0 @@
|
|
| 1 |
-
---
|
| 2 |
-
title: SpeechT5 Speech Synthesis Demo
|
| 3 |
-
emoji: 👩🎤
|
| 4 |
-
colorFrom: yellow
|
| 5 |
-
colorTo: blue
|
| 6 |
-
sdk: gradio
|
| 7 |
-
sdk_version: 3.17.0
|
| 8 |
-
app_file: app.py
|
| 9 |
-
pinned: false
|
| 10 |
-
license: apache-2.0
|
| 11 |
-
duplicated_from: Matthijs/speecht5-tts-demo
|
| 12 |
-
---
|
| 13 |
-
|
| 14 |
-
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
|
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spaces/AIGC-Audio/AudioGPT/NeuralSeq/vocoders/vocoder_utils.py
DELETED
|
@@ -1,15 +0,0 @@
|
|
| 1 |
-
import librosa
|
| 2 |
-
|
| 3 |
-
from utils.hparams import hparams
|
| 4 |
-
import numpy as np
|
| 5 |
-
|
| 6 |
-
|
| 7 |
-
def denoise(wav, v=0.1):
|
| 8 |
-
spec = librosa.stft(y=wav, n_fft=hparams['fft_size'], hop_length=hparams['hop_size'],
|
| 9 |
-
win_length=hparams['win_size'], pad_mode='constant')
|
| 10 |
-
spec_m = np.abs(spec)
|
| 11 |
-
spec_m = np.clip(spec_m - v, a_min=0, a_max=None)
|
| 12 |
-
spec_a = np.angle(spec)
|
| 13 |
-
|
| 14 |
-
return librosa.istft(spec_m * np.exp(1j * spec_a), hop_length=hparams['hop_size'],
|
| 15 |
-
win_length=hparams['win_size'])
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spaces/AIGC-Audio/AudioGPT/audio_detection/audio_infer/pytorch/evaluate.py
DELETED
|
@@ -1,42 +0,0 @@
|
|
| 1 |
-
from sklearn import metrics
|
| 2 |
-
|
| 3 |
-
from pytorch_utils import forward
|
| 4 |
-
|
| 5 |
-
|
| 6 |
-
class Evaluator(object):
|
| 7 |
-
def __init__(self, model):
|
| 8 |
-
"""Evaluator.
|
| 9 |
-
|
| 10 |
-
Args:
|
| 11 |
-
model: object
|
| 12 |
-
"""
|
| 13 |
-
self.model = model
|
| 14 |
-
|
| 15 |
-
def evaluate(self, data_loader):
|
| 16 |
-
"""Forward evaluation data and calculate statistics.
|
| 17 |
-
|
| 18 |
-
Args:
|
| 19 |
-
data_loader: object
|
| 20 |
-
|
| 21 |
-
Returns:
|
| 22 |
-
statistics: dict,
|
| 23 |
-
{'average_precision': (classes_num,), 'auc': (classes_num,)}
|
| 24 |
-
"""
|
| 25 |
-
|
| 26 |
-
# Forward
|
| 27 |
-
output_dict = forward(
|
| 28 |
-
model=self.model,
|
| 29 |
-
generator=data_loader,
|
| 30 |
-
return_target=True)
|
| 31 |
-
|
| 32 |
-
clipwise_output = output_dict['clipwise_output'] # (audios_num, classes_num)
|
| 33 |
-
target = output_dict['target'] # (audios_num, classes_num)
|
| 34 |
-
|
| 35 |
-
average_precision = metrics.average_precision_score(
|
| 36 |
-
target, clipwise_output, average=None)
|
| 37 |
-
|
| 38 |
-
auc = metrics.roc_auc_score(target, clipwise_output, average=None)
|
| 39 |
-
|
| 40 |
-
statistics = {'average_precision': average_precision, 'auc': auc}
|
| 41 |
-
|
| 42 |
-
return statistics
|
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spaces/AIGC-Audio/Make_An_Audio/ldm/modules/encoders/open_clap/timm_model.py
DELETED
|
@@ -1,106 +0,0 @@
|
|
| 1 |
-
""" timm model adapter
|
| 2 |
-
|
| 3 |
-
Wraps timm (https://github.com/rwightman/pytorch-image-models) models for use as a vision tower in CLIP model.
|
| 4 |
-
"""
|
| 5 |
-
from collections import OrderedDict
|
| 6 |
-
|
| 7 |
-
import torch.nn as nn
|
| 8 |
-
|
| 9 |
-
try:
|
| 10 |
-
import timm
|
| 11 |
-
from timm.models.layers import Mlp, to_2tuple
|
| 12 |
-
from timm.models.layers.attention_pool2d import RotAttentionPool2d
|
| 13 |
-
from timm.models.layers.attention_pool2d import AttentionPool2d as AbsAttentionPool2d
|
| 14 |
-
except ImportError as e:
|
| 15 |
-
timm = None
|
| 16 |
-
|
| 17 |
-
from .utils import freeze_batch_norm_2d
|
| 18 |
-
|
| 19 |
-
|
| 20 |
-
class TimmModel(nn.Module):
|
| 21 |
-
""" timm model adapter
|
| 22 |
-
# FIXME this adapter is a work in progress, may change in ways that break weight compat
|
| 23 |
-
"""
|
| 24 |
-
|
| 25 |
-
def __init__(
|
| 26 |
-
self,
|
| 27 |
-
model_name,
|
| 28 |
-
embed_dim,
|
| 29 |
-
image_size=224,
|
| 30 |
-
pool='avg',
|
| 31 |
-
proj='linear',
|
| 32 |
-
drop=0.,
|
| 33 |
-
pretrained=False):
|
| 34 |
-
super().__init__()
|
| 35 |
-
if timm is None:
|
| 36 |
-
raise RuntimeError("Please `pip install timm` to use timm models.")
|
| 37 |
-
|
| 38 |
-
self.image_size = to_2tuple(image_size)
|
| 39 |
-
self.trunk = timm.create_model(model_name, pretrained=pretrained)
|
| 40 |
-
feat_size = self.trunk.default_cfg.get('pool_size', None)
|
| 41 |
-
feature_ndim = 1 if not feat_size else 2
|
| 42 |
-
if pool in ('abs_attn', 'rot_attn'):
|
| 43 |
-
assert feature_ndim == 2
|
| 44 |
-
# if attn pooling used, remove both classifier and default pool
|
| 45 |
-
self.trunk.reset_classifier(0, global_pool='')
|
| 46 |
-
else:
|
| 47 |
-
# reset global pool if pool config set, otherwise leave as network default
|
| 48 |
-
reset_kwargs = dict(global_pool=pool) if pool else {}
|
| 49 |
-
self.trunk.reset_classifier(0, **reset_kwargs)
|
| 50 |
-
prev_chs = self.trunk.num_features
|
| 51 |
-
|
| 52 |
-
head_layers = OrderedDict()
|
| 53 |
-
if pool == 'abs_attn':
|
| 54 |
-
head_layers['pool'] = AbsAttentionPool2d(prev_chs, feat_size=feat_size, out_features=embed_dim)
|
| 55 |
-
prev_chs = embed_dim
|
| 56 |
-
elif pool == 'rot_attn':
|
| 57 |
-
head_layers['pool'] = RotAttentionPool2d(prev_chs, out_features=embed_dim)
|
| 58 |
-
prev_chs = embed_dim
|
| 59 |
-
else:
|
| 60 |
-
assert proj, 'projection layer needed if non-attention pooling is used.'
|
| 61 |
-
|
| 62 |
-
# NOTE attention pool ends with a projection layer, so proj should usually be set to '' if such pooling is used
|
| 63 |
-
if proj == 'linear':
|
| 64 |
-
head_layers['drop'] = nn.Dropout(drop)
|
| 65 |
-
head_layers['proj'] = nn.Linear(prev_chs, embed_dim)
|
| 66 |
-
elif proj == 'mlp':
|
| 67 |
-
head_layers['mlp'] = Mlp(prev_chs, 2 * embed_dim, embed_dim, drop=drop)
|
| 68 |
-
|
| 69 |
-
self.head = nn.Sequential(head_layers)
|
| 70 |
-
|
| 71 |
-
def lock(self, unlocked_groups=0, freeze_bn_stats=False):
|
| 72 |
-
""" lock modules
|
| 73 |
-
Args:
|
| 74 |
-
unlocked_groups (int): leave last n layer groups unlocked (default: 0)
|
| 75 |
-
"""
|
| 76 |
-
if not unlocked_groups:
|
| 77 |
-
# lock full model
|
| 78 |
-
for param in self.trunk.parameters():
|
| 79 |
-
param.requires_grad = False
|
| 80 |
-
if freeze_bn_stats:
|
| 81 |
-
freeze_batch_norm_2d(self.trunk)
|
| 82 |
-
else:
|
| 83 |
-
# NOTE: partial freeze requires latest timm (master) branch and is subject to change
|
| 84 |
-
try:
|
| 85 |
-
# FIXME import here until API stable and in an official release
|
| 86 |
-
from timm.models.helpers import group_parameters, group_modules
|
| 87 |
-
except ImportError:
|
| 88 |
-
raise RuntimeError(
|
| 89 |
-
'Please install latest timm `pip install git+https://github.com/rwightman/pytorch-image-models`')
|
| 90 |
-
matcher = self.trunk.group_matcher()
|
| 91 |
-
gparams = group_parameters(self.trunk, matcher)
|
| 92 |
-
max_layer_id = max(gparams.keys())
|
| 93 |
-
max_layer_id = max_layer_id - unlocked_groups
|
| 94 |
-
for group_idx in range(max_layer_id + 1):
|
| 95 |
-
group = gparams[group_idx]
|
| 96 |
-
for param in group:
|
| 97 |
-
self.trunk.get_parameter(param).requires_grad = False
|
| 98 |
-
if freeze_bn_stats:
|
| 99 |
-
gmodules = group_modules(self.trunk, matcher, reverse=True)
|
| 100 |
-
gmodules = {k for k, v in gmodules.items() if v <= max_layer_id}
|
| 101 |
-
freeze_batch_norm_2d(self.trunk, gmodules)
|
| 102 |
-
|
| 103 |
-
def forward(self, x):
|
| 104 |
-
x = self.trunk(x)
|
| 105 |
-
x = self.head(x)
|
| 106 |
-
return x
|
|
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|
spaces/AIWaves/Debate/src/agents/Component/PromptComponent.py
DELETED
|
@@ -1,133 +0,0 @@
|
|
| 1 |
-
from abc import abstractmethod
|
| 2 |
-
|
| 3 |
-
|
| 4 |
-
class PromptComponent:
|
| 5 |
-
def __init__(self):
|
| 6 |
-
pass
|
| 7 |
-
|
| 8 |
-
@abstractmethod
|
| 9 |
-
def get_prompt(self, agent):
|
| 10 |
-
pass
|
| 11 |
-
|
| 12 |
-
class TaskComponent(PromptComponent):
|
| 13 |
-
def __init__(self, task):
|
| 14 |
-
super().__init__()
|
| 15 |
-
self.task = task
|
| 16 |
-
|
| 17 |
-
def get_prompt(self, agent):
|
| 18 |
-
return f"""The task you need to execute is: <task>{self.task}</task>.\n"""
|
| 19 |
-
|
| 20 |
-
|
| 21 |
-
class OutputComponent(PromptComponent):
|
| 22 |
-
def __init__(self, output):
|
| 23 |
-
super().__init__()
|
| 24 |
-
self.output = output
|
| 25 |
-
|
| 26 |
-
def get_prompt(self, agent):
|
| 27 |
-
return f"""Please contact the above to extract <{self.output}> and </{self.output}>, \
|
| 28 |
-
do not perform additional output, please output in strict accordance with the above format!\n"""
|
| 29 |
-
|
| 30 |
-
|
| 31 |
-
class SystemComponent(PromptComponent):
|
| 32 |
-
def __init__(self,system_prompt):
|
| 33 |
-
super().__init__()
|
| 34 |
-
self.system_prompt = system_prompt
|
| 35 |
-
|
| 36 |
-
def get_prompt(self, agent):
|
| 37 |
-
return self.system_prompt
|
| 38 |
-
|
| 39 |
-
class LastComponent(PromptComponent):
|
| 40 |
-
def __init__(self, last_prompt):
|
| 41 |
-
super().__init__()
|
| 42 |
-
self.last_prompt = last_prompt
|
| 43 |
-
|
| 44 |
-
def get_prompt(self, agent):
|
| 45 |
-
return self.last_prompt
|
| 46 |
-
|
| 47 |
-
|
| 48 |
-
class StyleComponent(PromptComponent):
|
| 49 |
-
"""
|
| 50 |
-
角色、风格组件
|
| 51 |
-
"""
|
| 52 |
-
|
| 53 |
-
def __init__(self, role):
|
| 54 |
-
super().__init__()
|
| 55 |
-
self.role = role
|
| 56 |
-
|
| 57 |
-
def get_prompt(self, agent):
|
| 58 |
-
name = agent.name
|
| 59 |
-
style = agent.style
|
| 60 |
-
return f"""Now your role is:\n<role>{self.role}</role>, your name is:\n<name>{name}</name>. \
|
| 61 |
-
You need to follow the output style:\n<style>{style}</style>.\n"""
|
| 62 |
-
|
| 63 |
-
|
| 64 |
-
class RuleComponent(PromptComponent):
|
| 65 |
-
def __init__(self, rule):
|
| 66 |
-
super().__init__()
|
| 67 |
-
self.rule = rule
|
| 68 |
-
|
| 69 |
-
def get_prompt(self, agent):
|
| 70 |
-
return f"""The rule you need to follow is:\n<rule>{self.rule}</rule>.\n"""
|
| 71 |
-
|
| 72 |
-
|
| 73 |
-
class DemonstrationComponent(PromptComponent):
|
| 74 |
-
"""
|
| 75 |
-
input a list,the example of answer.
|
| 76 |
-
"""
|
| 77 |
-
|
| 78 |
-
def __init__(self, demonstrations):
|
| 79 |
-
super().__init__()
|
| 80 |
-
self.demonstrations = demonstrations
|
| 81 |
-
|
| 82 |
-
def add_demonstration(self, demonstration):
|
| 83 |
-
self.demonstrations.append(demonstration)
|
| 84 |
-
|
| 85 |
-
def get_prompt(self, agent):
|
| 86 |
-
prompt = "Here are demonstrations you can refer to:\n<demonstrations>"
|
| 87 |
-
for demonstration in self.demonstrations:
|
| 88 |
-
prompt += "\n" + demonstration
|
| 89 |
-
prompt += "</demonstrations>\n"
|
| 90 |
-
return prompt
|
| 91 |
-
|
| 92 |
-
|
| 93 |
-
class CoTComponent(PromptComponent):
|
| 94 |
-
"""
|
| 95 |
-
input a list,the example of answer.
|
| 96 |
-
"""
|
| 97 |
-
|
| 98 |
-
def __init__(self, demonstrations):
|
| 99 |
-
super().__init__()
|
| 100 |
-
self.demonstrations = demonstrations
|
| 101 |
-
|
| 102 |
-
def add_demonstration(self, demonstration):
|
| 103 |
-
self.demonstrations.append(demonstration)
|
| 104 |
-
|
| 105 |
-
def get_prompt(self, agent):
|
| 106 |
-
prompt = "You need to think in detail before outputting, the thinking case is as follows:\n<demonstrations>"
|
| 107 |
-
for demonstration in self.demonstrations:
|
| 108 |
-
prompt += "\n" + demonstration
|
| 109 |
-
prompt += "</demonstrations>\n"
|
| 110 |
-
return prompt
|
| 111 |
-
|
| 112 |
-
|
| 113 |
-
class CustomizeComponent(PromptComponent):
|
| 114 |
-
"""
|
| 115 |
-
Custom template
|
| 116 |
-
template(str) : example: "i am {}"
|
| 117 |
-
keywords(list) : example : ["name"]
|
| 118 |
-
example : agent.environment.shared_memory["name"] = "Lilong"
|
| 119 |
-
the component will get the keyword attribute from the environment, and then add it to the template.
|
| 120 |
-
Return : "i am Lilong"
|
| 121 |
-
"""
|
| 122 |
-
def __init__(self, template, keywords) -> None:
|
| 123 |
-
super().__init__()
|
| 124 |
-
self.template = template
|
| 125 |
-
self.keywords = keywords
|
| 126 |
-
|
| 127 |
-
def get_prompt(self, agent):
|
| 128 |
-
template_keyword = {}
|
| 129 |
-
for keyword in self.keywords:
|
| 130 |
-
|
| 131 |
-
current_keyword = agent.environment.shared_memory[keyword]
|
| 132 |
-
template_keyword[keyword] = current_keyword
|
| 133 |
-
return self.template.format(**template_keyword)
|
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spaces/AbandonedMuse/UnlimitedMusicGen/MODEL_CARD.md
DELETED
|
@@ -1,81 +0,0 @@
|
|
| 1 |
-
# MusicGen Model Card
|
| 2 |
-
|
| 3 |
-
## Model details
|
| 4 |
-
|
| 5 |
-
**Organization developing the model:** The FAIR team of Meta AI.
|
| 6 |
-
|
| 7 |
-
**Model date:** MusicGen was trained between April 2023 and May 2023.
|
| 8 |
-
|
| 9 |
-
**Model version:** This is the version 1 of the model.
|
| 10 |
-
|
| 11 |
-
**Model type:** MusicGen consists of an EnCodec model for audio tokenization, an auto-regressive language model based on the transformer architecture for music modeling. The model comes in different sizes: 300M, 1.5B and 3.3B parameters ; and two variants: a model trained for text-to-music generation task and a model trained for melody-guided music generation.
|
| 12 |
-
|
| 13 |
-
**Paper or resources for more information:** More information can be found in the paper [Simple and Controllable Music Generation][arxiv].
|
| 14 |
-
|
| 15 |
-
**Citation details** See [our paper][arxiv]
|
| 16 |
-
|
| 17 |
-
**License** Code is released under MIT, model weights are released under CC-BY-NC 4.0.
|
| 18 |
-
|
| 19 |
-
**Where to send questions or comments about the model:** Questions and comments about MusicGen can be sent via the [Github repository](https://github.com/facebookresearch/audiocraft) of the project, or by opening an issue.
|
| 20 |
-
|
| 21 |
-
## Intended use
|
| 22 |
-
**Primary intended use:** The primary use of MusicGen is research on AI-based music generation, including:
|
| 23 |
-
|
| 24 |
-
- Research efforts, such as probing and better understanding the limitations of generative models to further improve the state of science
|
| 25 |
-
- Generation of music guided by text or melody to understand current abilities of generative AI models by machine learning amateurs
|
| 26 |
-
|
| 27 |
-
**Primary intended users:** The primary intended users of the model are researchers in audio, machine learning and artificial intelligence, as well as amateur seeking to better understand those models.
|
| 28 |
-
|
| 29 |
-
**Out-of-scope use cases** The model should not be used on downstream applications without further risk evaluation and mitigation. The model should not be used to intentionally create or disseminate music pieces that create hostile or alienating environments for people. This includes generating music that people would foreseeably find disturbing, distressing, or offensive; or content that propagates historical or current stereotypes.
|
| 30 |
-
|
| 31 |
-
## Metrics
|
| 32 |
-
|
| 33 |
-
**Models performance measures:** We used the following objective measure to evaluate the model on a standard music benchmark:
|
| 34 |
-
|
| 35 |
-
- Frechet Audio Distance computed on features extracted from a pre-trained audio classifier (VGGish)
|
| 36 |
-
- Kullback-Leibler Divergence on label distributions extracted from a pre-trained audio classifier (PaSST)
|
| 37 |
-
- CLAP Score between audio embedding and text embedding extracted from a pre-trained CLAP model
|
| 38 |
-
|
| 39 |
-
Additionally, we run qualitative studies with human participants, evaluating the performance of the model with the following axes:
|
| 40 |
-
|
| 41 |
-
- Overall quality of the music samples;
|
| 42 |
-
- Text relevance to the provided text input;
|
| 43 |
-
- Adherence to the melody for melody-guided music generation.
|
| 44 |
-
|
| 45 |
-
More details on performance measures and human studies can be found in the paper.
|
| 46 |
-
|
| 47 |
-
**Decision thresholds:** Not applicable.
|
| 48 |
-
|
| 49 |
-
## Evaluation datasets
|
| 50 |
-
|
| 51 |
-
The model was evaluated on the [MusicCaps benchmark](https://www.kaggle.com/datasets/googleai/musiccaps) and on an in-domain held-out evaluation set, with no artist overlap with the training set.
|
| 52 |
-
|
| 53 |
-
## Training datasets
|
| 54 |
-
|
| 55 |
-
The model was trained on licensed data using the following sources: the [Meta Music Initiative Sound Collection](https://www.fb.com/sound), [Shutterstock music collection](https://www.shutterstock.com/music) and the [Pond5 music collection](https://www.pond5.com/). See the paper for more details about the training set and corresponding preprocessing.
|
| 56 |
-
|
| 57 |
-
## Quantitative analysis
|
| 58 |
-
|
| 59 |
-
More information can be found in the paper [Simple and Controllable Music Generation][arxiv], in the Experimental Setup section.
|
| 60 |
-
|
| 61 |
-
## Limitations and biases
|
| 62 |
-
|
| 63 |
-
**Data:** The data sources used to train the model are created by music professionals and covered by legal agreements with the right holders. The model is trained on 20K hours of data, we believe that scaling the model on larger datasets can further improve the performance of the model.
|
| 64 |
-
|
| 65 |
-
**Mitigations:** Vocals have been removed from the data source using corresponding tags, and then using using a state-of-the-art music source separation method, namely using the open source [Hybrid Transformer for Music Source Separation](https://github.com/facebookresearch/demucs) (HT-Demucs).
|
| 66 |
-
|
| 67 |
-
**Limitations:**
|
| 68 |
-
|
| 69 |
-
- The model is not able to generate realistic vocals.
|
| 70 |
-
- The model has been trained with English descriptions and will not perform as well in other languages.
|
| 71 |
-
- The model does not perform equally well for all music styles and cultures.
|
| 72 |
-
- The model sometimes generates end of songs, collapsing to silence.
|
| 73 |
-
- It is sometimes difficult to assess what types of text descriptions provide the best generations. Prompt engineering may be required to obtain satisfying results.
|
| 74 |
-
|
| 75 |
-
**Biases:** The source of data is potentially lacking diversity and all music cultures are not equally represented in the dataset. The model may not perform equally well on the wide variety of music genres that exists. The generated samples from the model will reflect the biases from the training data. Further work on this model should include methods for balanced and just representations of cultures, for example, by scaling the training data to be both diverse and inclusive.
|
| 76 |
-
|
| 77 |
-
**Risks and harms:** Biases and limitations of the model may lead to generation of samples that may be considered as biased, inappropriate or offensive. We believe that providing the code to reproduce the research and train new models will allow to broaden the application to new and more representative data.
|
| 78 |
-
|
| 79 |
-
**Use cases:** Users must be aware of the biases, limitations and risks of the model. MusicGen is a model developed for artificial intelligence research on controllable music generation. As such, it should not be used for downstream applications without further investigation and mitigation of risks.
|
| 80 |
-
|
| 81 |
-
[arxiv]: https://arxiv.org/abs/2306.05284
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|
spaces/Abdullah-Habib/Rabbit_or_Hare/app.py
DELETED
|
@@ -1,20 +0,0 @@
|
|
| 1 |
-
__all__ = ['is_Rabbit',"learn",'classify_image', 'categories','image','label','examples','intf']
|
| 2 |
-
|
| 3 |
-
# Cell
|
| 4 |
-
from fastai.vision.all import *
|
| 5 |
-
import gradio as gr
|
| 6 |
-
def is_Rabbit(x): return x[0].isupper()
|
| 7 |
-
|
| 8 |
-
|
| 9 |
-
learn = load_learner ('model.pkl')
|
| 10 |
-
# Cell
|
| 11 |
-
categories = ('Hare','Rabbit')
|
| 12 |
-
def classify_image (img) :
|
| 13 |
-
pred, idx, probs = learn.predict(img)
|
| 14 |
-
return dict(zip(categories, map(float,probs)))
|
| 15 |
-
# Cell
|
| 16 |
-
image = gr.inputs.Image(shape=(192, 192))
|
| 17 |
-
label = gr.outputs.Label ()
|
| 18 |
-
examples=['Rabbit.jpg', 'TestRabbit.jpg','Hare.jpg']
|
| 19 |
-
intf = gr.Interface(fn=classify_image,inputs=image, outputs=label, examples=examples)
|
| 20 |
-
intf.launch(inline=False)
|
|
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|
spaces/Abhilashvj/planogram-compliance/utils/torch_utils.py
DELETED
|
@@ -1,613 +0,0 @@
|
|
| 1 |
-
# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
|
| 2 |
-
"""
|
| 3 |
-
PyTorch utils
|
| 4 |
-
"""
|
| 5 |
-
|
| 6 |
-
import math
|
| 7 |
-
import os
|
| 8 |
-
import platform
|
| 9 |
-
import subprocess
|
| 10 |
-
import time
|
| 11 |
-
import warnings
|
| 12 |
-
from contextlib import contextmanager
|
| 13 |
-
from copy import deepcopy
|
| 14 |
-
from pathlib import Path
|
| 15 |
-
|
| 16 |
-
import torch
|
| 17 |
-
import torch.distributed as dist
|
| 18 |
-
import torch.nn as nn
|
| 19 |
-
import torch.nn.functional as F
|
| 20 |
-
from torch.nn.parallel import DistributedDataParallel as DDP
|
| 21 |
-
|
| 22 |
-
from utils.general import LOGGER, check_version, colorstr, file_date, git_describe
|
| 23 |
-
|
| 24 |
-
LOCAL_RANK = int(
|
| 25 |
-
os.getenv("LOCAL_RANK", -1)
|
| 26 |
-
) # https://pytorch.org/docs/stable/elastic/run.html
|
| 27 |
-
RANK = int(os.getenv("RANK", -1))
|
| 28 |
-
WORLD_SIZE = int(os.getenv("WORLD_SIZE", 1))
|
| 29 |
-
|
| 30 |
-
try:
|
| 31 |
-
import thop # for FLOPs computation
|
| 32 |
-
except ImportError:
|
| 33 |
-
thop = None
|
| 34 |
-
|
| 35 |
-
# Suppress PyTorch warnings
|
| 36 |
-
warnings.filterwarnings(
|
| 37 |
-
"ignore",
|
| 38 |
-
message="User provided device_type of 'cuda', but CUDA is not available. Disabling",
|
| 39 |
-
)
|
| 40 |
-
warnings.filterwarnings("ignore", category=UserWarning)
|
| 41 |
-
|
| 42 |
-
|
| 43 |
-
def smart_inference_mode(torch_1_9=check_version(torch.__version__, "1.9.0")):
|
| 44 |
-
# Applies torch.inference_mode() decorator if torch>=1.9.0 else torch.no_grad() decorator
|
| 45 |
-
def decorate(fn):
|
| 46 |
-
return (torch.inference_mode if torch_1_9 else torch.no_grad)()(fn)
|
| 47 |
-
|
| 48 |
-
return decorate
|
| 49 |
-
|
| 50 |
-
|
| 51 |
-
def smartCrossEntropyLoss(label_smoothing=0.0):
|
| 52 |
-
# Returns nn.CrossEntropyLoss with label smoothing enabled for torch>=1.10.0
|
| 53 |
-
if check_version(torch.__version__, "1.10.0"):
|
| 54 |
-
return nn.CrossEntropyLoss(label_smoothing=label_smoothing)
|
| 55 |
-
if label_smoothing > 0:
|
| 56 |
-
LOGGER.warning(
|
| 57 |
-
f"WARNING ⚠️ label smoothing {label_smoothing} requires torch>=1.10.0"
|
| 58 |
-
)
|
| 59 |
-
return nn.CrossEntropyLoss()
|
| 60 |
-
|
| 61 |
-
|
| 62 |
-
def smart_DDP(model):
|
| 63 |
-
# Model DDP creation with checks
|
| 64 |
-
assert not check_version(torch.__version__, "1.12.0", pinned=True), (
|
| 65 |
-
"torch==1.12.0 torchvision==0.13.0 DDP training is not supported due to a known issue. "
|
| 66 |
-
"Please upgrade or downgrade torch to use DDP. See https://github.com/ultralytics/yolov5/issues/8395"
|
| 67 |
-
)
|
| 68 |
-
if check_version(torch.__version__, "1.11.0"):
|
| 69 |
-
return DDP(
|
| 70 |
-
model,
|
| 71 |
-
device_ids=[LOCAL_RANK],
|
| 72 |
-
output_device=LOCAL_RANK,
|
| 73 |
-
static_graph=True,
|
| 74 |
-
)
|
| 75 |
-
else:
|
| 76 |
-
return DDP(model, device_ids=[LOCAL_RANK], output_device=LOCAL_RANK)
|
| 77 |
-
|
| 78 |
-
|
| 79 |
-
def reshape_classifier_output(model, n=1000):
|
| 80 |
-
# Update a TorchVision classification model to class count 'n' if required
|
| 81 |
-
from models.common import Classify
|
| 82 |
-
|
| 83 |
-
name, m = list(
|
| 84 |
-
(model.model if hasattr(model, "model") else model).named_children()
|
| 85 |
-
)[
|
| 86 |
-
-1
|
| 87 |
-
] # last module
|
| 88 |
-
if isinstance(m, Classify): # YOLOv5 Classify() head
|
| 89 |
-
if m.linear.out_features != n:
|
| 90 |
-
m.linear = nn.Linear(m.linear.in_features, n)
|
| 91 |
-
elif isinstance(m, nn.Linear): # ResNet, EfficientNet
|
| 92 |
-
if m.out_features != n:
|
| 93 |
-
setattr(model, name, nn.Linear(m.in_features, n))
|
| 94 |
-
elif isinstance(m, nn.Sequential):
|
| 95 |
-
types = [type(x) for x in m]
|
| 96 |
-
if nn.Linear in types:
|
| 97 |
-
i = types.index(nn.Linear) # nn.Linear index
|
| 98 |
-
if m[i].out_features != n:
|
| 99 |
-
m[i] = nn.Linear(m[i].in_features, n)
|
| 100 |
-
elif nn.Conv2d in types:
|
| 101 |
-
i = types.index(nn.Conv2d) # nn.Conv2d index
|
| 102 |
-
if m[i].out_channels != n:
|
| 103 |
-
m[i] = nn.Conv2d(
|
| 104 |
-
m[i].in_channels,
|
| 105 |
-
n,
|
| 106 |
-
m[i].kernel_size,
|
| 107 |
-
m[i].stride,
|
| 108 |
-
bias=m[i].bias is not None,
|
| 109 |
-
)
|
| 110 |
-
|
| 111 |
-
|
| 112 |
-
@contextmanager
|
| 113 |
-
def torch_distributed_zero_first(local_rank: int):
|
| 114 |
-
# Decorator to make all processes in distributed training wait for each local_master to do something
|
| 115 |
-
if local_rank not in [-1, 0]:
|
| 116 |
-
dist.barrier(device_ids=[local_rank])
|
| 117 |
-
yield
|
| 118 |
-
if local_rank == 0:
|
| 119 |
-
dist.barrier(device_ids=[0])
|
| 120 |
-
|
| 121 |
-
|
| 122 |
-
def device_count():
|
| 123 |
-
# Returns number of CUDA devices available. Safe version of torch.cuda.device_count(). Supports Linux and Windows
|
| 124 |
-
assert platform.system() in (
|
| 125 |
-
"Linux",
|
| 126 |
-
"Windows",
|
| 127 |
-
), "device_count() only supported on Linux or Windows"
|
| 128 |
-
try:
|
| 129 |
-
cmd = (
|
| 130 |
-
"nvidia-smi -L | wc -l"
|
| 131 |
-
if platform.system() == "Linux"
|
| 132 |
-
else 'nvidia-smi -L | find /c /v ""'
|
| 133 |
-
) # Windows
|
| 134 |
-
return int(
|
| 135 |
-
subprocess.run(cmd, shell=True, capture_output=True, check=True)
|
| 136 |
-
.stdout.decode()
|
| 137 |
-
.split()[-1]
|
| 138 |
-
)
|
| 139 |
-
except Exception:
|
| 140 |
-
return 0
|
| 141 |
-
|
| 142 |
-
|
| 143 |
-
def select_device(device="", batch_size=0, newline=True):
|
| 144 |
-
# device = None or 'cpu' or 0 or '0' or '0,1,2,3'
|
| 145 |
-
s = f"YOLOv5 🚀 {git_describe() or file_date()} Python-{platform.python_version()} torch-{torch.__version__} "
|
| 146 |
-
device = (
|
| 147 |
-
str(device).strip().lower().replace("cuda:", "").replace("none", "")
|
| 148 |
-
) # to string, 'cuda:0' to '0'
|
| 149 |
-
cpu = device == "cpu"
|
| 150 |
-
mps = device == "mps" # Apple Metal Performance Shaders (MPS)
|
| 151 |
-
if cpu or mps:
|
| 152 |
-
os.environ[
|
| 153 |
-
"CUDA_VISIBLE_DEVICES"
|
| 154 |
-
] = "-1" # force torch.cuda.is_available() = False
|
| 155 |
-
elif device: # non-cpu device requested
|
| 156 |
-
os.environ[
|
| 157 |
-
"CUDA_VISIBLE_DEVICES"
|
| 158 |
-
] = device # set environment variable - must be before assert is_available()
|
| 159 |
-
assert torch.cuda.is_available() and torch.cuda.device_count() >= len(
|
| 160 |
-
device.replace(",", "")
|
| 161 |
-
), f"Invalid CUDA '--device {device}' requested, use '--device cpu' or pass valid CUDA device(s)"
|
| 162 |
-
|
| 163 |
-
if (
|
| 164 |
-
not cpu and not mps and torch.cuda.is_available()
|
| 165 |
-
): # prefer GPU if available
|
| 166 |
-
devices = (
|
| 167 |
-
device.split(",") if device else "0"
|
| 168 |
-
) # range(torch.cuda.device_count()) # i.e. 0,1,6,7
|
| 169 |
-
n = len(devices) # device count
|
| 170 |
-
if (
|
| 171 |
-
n > 1 and batch_size > 0
|
| 172 |
-
): # check batch_size is divisible by device_count
|
| 173 |
-
assert (
|
| 174 |
-
batch_size % n == 0
|
| 175 |
-
), f"batch-size {batch_size} not multiple of GPU count {n}"
|
| 176 |
-
space = " " * (len(s) + 1)
|
| 177 |
-
for i, d in enumerate(devices):
|
| 178 |
-
p = torch.cuda.get_device_properties(i)
|
| 179 |
-
s += f"{'' if i == 0 else space}CUDA:{d} ({p.name}, {p.total_memory / (1 << 20):.0f}MiB)\n" # bytes to MB
|
| 180 |
-
arg = "cuda:0"
|
| 181 |
-
elif (
|
| 182 |
-
mps
|
| 183 |
-
and getattr(torch, "has_mps", False)
|
| 184 |
-
and torch.backends.mps.is_available()
|
| 185 |
-
): # prefer MPS if available
|
| 186 |
-
s += "MPS\n"
|
| 187 |
-
arg = "mps"
|
| 188 |
-
else: # revert to CPU
|
| 189 |
-
s += "CPU\n"
|
| 190 |
-
arg = "cpu"
|
| 191 |
-
|
| 192 |
-
if not newline:
|
| 193 |
-
s = s.rstrip()
|
| 194 |
-
LOGGER.info(s)
|
| 195 |
-
return torch.device(arg)
|
| 196 |
-
|
| 197 |
-
|
| 198 |
-
def time_sync():
|
| 199 |
-
# PyTorch-accurate time
|
| 200 |
-
if torch.cuda.is_available():
|
| 201 |
-
torch.cuda.synchronize()
|
| 202 |
-
return time.time()
|
| 203 |
-
|
| 204 |
-
|
| 205 |
-
def profile(input, ops, n=10, device=None):
|
| 206 |
-
"""YOLOv5 speed/memory/FLOPs profiler
|
| 207 |
-
Usage:
|
| 208 |
-
input = torch.randn(16, 3, 640, 640)
|
| 209 |
-
m1 = lambda x: x * torch.sigmoid(x)
|
| 210 |
-
m2 = nn.SiLU()
|
| 211 |
-
profile(input, [m1, m2], n=100) # profile over 100 iterations
|
| 212 |
-
"""
|
| 213 |
-
results = []
|
| 214 |
-
if not isinstance(device, torch.device):
|
| 215 |
-
device = select_device(device)
|
| 216 |
-
print(
|
| 217 |
-
f"{'Params':>12s}{'GFLOPs':>12s}{'GPU_mem (GB)':>14s}{'forward (ms)':>14s}{'backward (ms)':>14s}"
|
| 218 |
-
f"{'input':>24s}{'output':>24s}"
|
| 219 |
-
)
|
| 220 |
-
|
| 221 |
-
for x in input if isinstance(input, list) else [input]:
|
| 222 |
-
x = x.to(device)
|
| 223 |
-
x.requires_grad = True
|
| 224 |
-
for m in ops if isinstance(ops, list) else [ops]:
|
| 225 |
-
m = m.to(device) if hasattr(m, "to") else m # device
|
| 226 |
-
m = (
|
| 227 |
-
m.half()
|
| 228 |
-
if hasattr(m, "half")
|
| 229 |
-
and isinstance(x, torch.Tensor)
|
| 230 |
-
and x.dtype is torch.float16
|
| 231 |
-
else m
|
| 232 |
-
)
|
| 233 |
-
tf, tb, t = 0, 0, [0, 0, 0] # dt forward, backward
|
| 234 |
-
try:
|
| 235 |
-
flops = (
|
| 236 |
-
thop.profile(m, inputs=(x,), verbose=False)[0] / 1e9 * 2
|
| 237 |
-
) # GFLOPs
|
| 238 |
-
except Exception:
|
| 239 |
-
flops = 0
|
| 240 |
-
|
| 241 |
-
try:
|
| 242 |
-
for _ in range(n):
|
| 243 |
-
t[0] = time_sync()
|
| 244 |
-
y = m(x)
|
| 245 |
-
t[1] = time_sync()
|
| 246 |
-
try:
|
| 247 |
-
_ = (
|
| 248 |
-
(
|
| 249 |
-
sum(yi.sum() for yi in y)
|
| 250 |
-
if isinstance(y, list)
|
| 251 |
-
else y
|
| 252 |
-
)
|
| 253 |
-
.sum()
|
| 254 |
-
.backward()
|
| 255 |
-
)
|
| 256 |
-
t[2] = time_sync()
|
| 257 |
-
except Exception: # no backward method
|
| 258 |
-
# print(e) # for debug
|
| 259 |
-
t[2] = float("nan")
|
| 260 |
-
tf += (t[1] - t[0]) * 1000 / n # ms per op forward
|
| 261 |
-
tb += (t[2] - t[1]) * 1000 / n # ms per op backward
|
| 262 |
-
mem = (
|
| 263 |
-
torch.cuda.memory_reserved() / 1e9
|
| 264 |
-
if torch.cuda.is_available()
|
| 265 |
-
else 0
|
| 266 |
-
) # (GB)
|
| 267 |
-
s_in, s_out = (
|
| 268 |
-
tuple(x.shape) if isinstance(x, torch.Tensor) else "list"
|
| 269 |
-
for x in (x, y)
|
| 270 |
-
) # shapes
|
| 271 |
-
p = (
|
| 272 |
-
sum(x.numel() for x in m.parameters())
|
| 273 |
-
if isinstance(m, nn.Module)
|
| 274 |
-
else 0
|
| 275 |
-
) # parameters
|
| 276 |
-
print(
|
| 277 |
-
f"{p:12}{flops:12.4g}{mem:>14.3f}{tf:14.4g}{tb:14.4g}{str(s_in):>24s}{str(s_out):>24s}"
|
| 278 |
-
)
|
| 279 |
-
results.append([p, flops, mem, tf, tb, s_in, s_out])
|
| 280 |
-
except Exception as e:
|
| 281 |
-
print(e)
|
| 282 |
-
results.append(None)
|
| 283 |
-
torch.cuda.empty_cache()
|
| 284 |
-
return results
|
| 285 |
-
|
| 286 |
-
|
| 287 |
-
def is_parallel(model):
|
| 288 |
-
# Returns True if model is of type DP or DDP
|
| 289 |
-
return type(model) in (
|
| 290 |
-
nn.parallel.DataParallel,
|
| 291 |
-
nn.parallel.DistributedDataParallel,
|
| 292 |
-
)
|
| 293 |
-
|
| 294 |
-
|
| 295 |
-
def de_parallel(model):
|
| 296 |
-
# De-parallelize a model: returns single-GPU model if model is of type DP or DDP
|
| 297 |
-
return model.module if is_parallel(model) else model
|
| 298 |
-
|
| 299 |
-
|
| 300 |
-
def initialize_weights(model):
|
| 301 |
-
for m in model.modules():
|
| 302 |
-
t = type(m)
|
| 303 |
-
if t is nn.Conv2d:
|
| 304 |
-
pass # nn.init.kaiming_normal_(m.weight, mode='fan_out', nonlinearity='relu')
|
| 305 |
-
elif t is nn.BatchNorm2d:
|
| 306 |
-
m.eps = 1e-3
|
| 307 |
-
m.momentum = 0.03
|
| 308 |
-
elif t in [nn.Hardswish, nn.LeakyReLU, nn.ReLU, nn.ReLU6, nn.SiLU]:
|
| 309 |
-
m.inplace = True
|
| 310 |
-
|
| 311 |
-
|
| 312 |
-
def find_modules(model, mclass=nn.Conv2d):
|
| 313 |
-
# Finds layer indices matching module class 'mclass'
|
| 314 |
-
return [
|
| 315 |
-
i for i, m in enumerate(model.module_list) if isinstance(m, mclass)
|
| 316 |
-
]
|
| 317 |
-
|
| 318 |
-
|
| 319 |
-
def sparsity(model):
|
| 320 |
-
# Return global model sparsity
|
| 321 |
-
a, b = 0, 0
|
| 322 |
-
for p in model.parameters():
|
| 323 |
-
a += p.numel()
|
| 324 |
-
b += (p == 0).sum()
|
| 325 |
-
return b / a
|
| 326 |
-
|
| 327 |
-
|
| 328 |
-
def prune(model, amount=0.3):
|
| 329 |
-
# Prune model to requested global sparsity
|
| 330 |
-
import torch.nn.utils.prune as prune
|
| 331 |
-
|
| 332 |
-
for name, m in model.named_modules():
|
| 333 |
-
if isinstance(m, nn.Conv2d):
|
| 334 |
-
prune.l1_unstructured(m, name="weight", amount=amount) # prune
|
| 335 |
-
prune.remove(m, "weight") # make permanent
|
| 336 |
-
LOGGER.info(f"Model pruned to {sparsity(model):.3g} global sparsity")
|
| 337 |
-
|
| 338 |
-
|
| 339 |
-
def fuse_conv_and_bn(conv, bn):
|
| 340 |
-
# Fuse Conv2d() and BatchNorm2d() layers https://tehnokv.com/posts/fusing-batchnorm-and-conv/
|
| 341 |
-
fusedconv = (
|
| 342 |
-
nn.Conv2d(
|
| 343 |
-
conv.in_channels,
|
| 344 |
-
conv.out_channels,
|
| 345 |
-
kernel_size=conv.kernel_size,
|
| 346 |
-
stride=conv.stride,
|
| 347 |
-
padding=conv.padding,
|
| 348 |
-
dilation=conv.dilation,
|
| 349 |
-
groups=conv.groups,
|
| 350 |
-
bias=True,
|
| 351 |
-
)
|
| 352 |
-
.requires_grad_(False)
|
| 353 |
-
.to(conv.weight.device)
|
| 354 |
-
)
|
| 355 |
-
|
| 356 |
-
# Prepare filters
|
| 357 |
-
w_conv = conv.weight.clone().view(conv.out_channels, -1)
|
| 358 |
-
w_bn = torch.diag(bn.weight.div(torch.sqrt(bn.eps + bn.running_var)))
|
| 359 |
-
fusedconv.weight.copy_(torch.mm(w_bn, w_conv).view(fusedconv.weight.shape))
|
| 360 |
-
|
| 361 |
-
# Prepare spatial bias
|
| 362 |
-
b_conv = (
|
| 363 |
-
torch.zeros(conv.weight.size(0), device=conv.weight.device)
|
| 364 |
-
if conv.bias is None
|
| 365 |
-
else conv.bias
|
| 366 |
-
)
|
| 367 |
-
b_bn = bn.bias - bn.weight.mul(bn.running_mean).div(
|
| 368 |
-
torch.sqrt(bn.running_var + bn.eps)
|
| 369 |
-
)
|
| 370 |
-
fusedconv.bias.copy_(
|
| 371 |
-
torch.mm(w_bn, b_conv.reshape(-1, 1)).reshape(-1) + b_bn
|
| 372 |
-
)
|
| 373 |
-
|
| 374 |
-
return fusedconv
|
| 375 |
-
|
| 376 |
-
|
| 377 |
-
def model_info(model, verbose=False, imgsz=640):
|
| 378 |
-
# Model information. img_size may be int or list, i.e. img_size=640 or img_size=[640, 320]
|
| 379 |
-
n_p = sum(x.numel() for x in model.parameters()) # number parameters
|
| 380 |
-
n_g = sum(
|
| 381 |
-
x.numel() for x in model.parameters() if x.requires_grad
|
| 382 |
-
) # number gradients
|
| 383 |
-
if verbose:
|
| 384 |
-
print(
|
| 385 |
-
f"{'layer':>5} {'name':>40} {'gradient':>9} {'parameters':>12} {'shape':>20} {'mu':>10} {'sigma':>10}"
|
| 386 |
-
)
|
| 387 |
-
for i, (name, p) in enumerate(model.named_parameters()):
|
| 388 |
-
name = name.replace("module_list.", "")
|
| 389 |
-
print(
|
| 390 |
-
"%5g %40s %9s %12g %20s %10.3g %10.3g"
|
| 391 |
-
% (
|
| 392 |
-
i,
|
| 393 |
-
name,
|
| 394 |
-
p.requires_grad,
|
| 395 |
-
p.numel(),
|
| 396 |
-
list(p.shape),
|
| 397 |
-
p.mean(),
|
| 398 |
-
p.std(),
|
| 399 |
-
)
|
| 400 |
-
)
|
| 401 |
-
|
| 402 |
-
try: # FLOPs
|
| 403 |
-
p = next(model.parameters())
|
| 404 |
-
stride = (
|
| 405 |
-
max(int(model.stride.max()), 32)
|
| 406 |
-
if hasattr(model, "stride")
|
| 407 |
-
else 32
|
| 408 |
-
) # max stride
|
| 409 |
-
im = torch.empty(
|
| 410 |
-
(1, p.shape[1], stride, stride), device=p.device
|
| 411 |
-
) # input image in BCHW format
|
| 412 |
-
flops = (
|
| 413 |
-
thop.profile(deepcopy(model), inputs=(im,), verbose=False)[0]
|
| 414 |
-
/ 1e9
|
| 415 |
-
* 2
|
| 416 |
-
) # stride GFLOPs
|
| 417 |
-
imgsz = (
|
| 418 |
-
imgsz if isinstance(imgsz, list) else [imgsz, imgsz]
|
| 419 |
-
) # expand if int/float
|
| 420 |
-
fs = f", {flops * imgsz[0] / stride * imgsz[1] / stride:.1f} GFLOPs" # 640x640 GFLOPs
|
| 421 |
-
except Exception:
|
| 422 |
-
fs = ""
|
| 423 |
-
|
| 424 |
-
name = (
|
| 425 |
-
Path(model.yaml_file).stem.replace("yolov5", "YOLOv5")
|
| 426 |
-
if hasattr(model, "yaml_file")
|
| 427 |
-
else "Model"
|
| 428 |
-
)
|
| 429 |
-
LOGGER.info(
|
| 430 |
-
f"{name} summary: {len(list(model.modules()))} layers, {n_p} parameters, {n_g} gradients{fs}"
|
| 431 |
-
)
|
| 432 |
-
|
| 433 |
-
|
| 434 |
-
def scale_img(img, ratio=1.0, same_shape=False, gs=32): # img(16,3,256,416)
|
| 435 |
-
# Scales img(bs,3,y,x) by ratio constrained to gs-multiple
|
| 436 |
-
if ratio == 1.0:
|
| 437 |
-
return img
|
| 438 |
-
h, w = img.shape[2:]
|
| 439 |
-
s = (int(h * ratio), int(w * ratio)) # new size
|
| 440 |
-
img = F.interpolate(
|
| 441 |
-
img, size=s, mode="bilinear", align_corners=False
|
| 442 |
-
) # resize
|
| 443 |
-
if not same_shape: # pad/crop img
|
| 444 |
-
h, w = (math.ceil(x * ratio / gs) * gs for x in (h, w))
|
| 445 |
-
return F.pad(
|
| 446 |
-
img, [0, w - s[1], 0, h - s[0]], value=0.447
|
| 447 |
-
) # value = imagenet mean
|
| 448 |
-
|
| 449 |
-
|
| 450 |
-
def copy_attr(a, b, include=(), exclude=()):
|
| 451 |
-
# Copy attributes from b to a, options to only include [...] and to exclude [...]
|
| 452 |
-
for k, v in b.__dict__.items():
|
| 453 |
-
if (
|
| 454 |
-
(len(include) and k not in include)
|
| 455 |
-
or k.startswith("_")
|
| 456 |
-
or k in exclude
|
| 457 |
-
):
|
| 458 |
-
continue
|
| 459 |
-
else:
|
| 460 |
-
setattr(a, k, v)
|
| 461 |
-
|
| 462 |
-
|
| 463 |
-
def smart_optimizer(model, name="Adam", lr=0.001, momentum=0.9, decay=1e-5):
|
| 464 |
-
# YOLOv5 3-param group optimizer: 0) weights with decay, 1) weights no decay, 2) biases no decay
|
| 465 |
-
g = [], [], [] # optimizer parameter groups
|
| 466 |
-
bn = tuple(
|
| 467 |
-
v for k, v in nn.__dict__.items() if "Norm" in k
|
| 468 |
-
) # normalization layers, i.e. BatchNorm2d()
|
| 469 |
-
for v in model.modules():
|
| 470 |
-
for p_name, p in v.named_parameters(recurse=0):
|
| 471 |
-
if p_name == "bias": # bias (no decay)
|
| 472 |
-
g[2].append(p)
|
| 473 |
-
elif p_name == "weight" and isinstance(v, bn): # weight (no decay)
|
| 474 |
-
g[1].append(p)
|
| 475 |
-
else:
|
| 476 |
-
g[0].append(p) # weight (with decay)
|
| 477 |
-
|
| 478 |
-
if name == "Adam":
|
| 479 |
-
optimizer = torch.optim.Adam(
|
| 480 |
-
g[2], lr=lr, betas=(momentum, 0.999)
|
| 481 |
-
) # adjust beta1 to momentum
|
| 482 |
-
elif name == "AdamW":
|
| 483 |
-
optimizer = torch.optim.AdamW(
|
| 484 |
-
g[2], lr=lr, betas=(momentum, 0.999), weight_decay=0.0
|
| 485 |
-
)
|
| 486 |
-
elif name == "RMSProp":
|
| 487 |
-
optimizer = torch.optim.RMSprop(g[2], lr=lr, momentum=momentum)
|
| 488 |
-
elif name == "SGD":
|
| 489 |
-
optimizer = torch.optim.SGD(
|
| 490 |
-
g[2], lr=lr, momentum=momentum, nesterov=True
|
| 491 |
-
)
|
| 492 |
-
else:
|
| 493 |
-
raise NotImplementedError(f"Optimizer {name} not implemented.")
|
| 494 |
-
|
| 495 |
-
optimizer.add_param_group(
|
| 496 |
-
{"params": g[0], "weight_decay": decay}
|
| 497 |
-
) # add g0 with weight_decay
|
| 498 |
-
optimizer.add_param_group(
|
| 499 |
-
{"params": g[1], "weight_decay": 0.0}
|
| 500 |
-
) # add g1 (BatchNorm2d weights)
|
| 501 |
-
LOGGER.info(
|
| 502 |
-
f"{colorstr('optimizer:')} {type(optimizer).__name__}(lr={lr}) with parameter groups "
|
| 503 |
-
f"{len(g[1])} weight(decay=0.0), {len(g[0])} weight(decay={decay}), {len(g[2])} bias"
|
| 504 |
-
)
|
| 505 |
-
return optimizer
|
| 506 |
-
|
| 507 |
-
|
| 508 |
-
def smart_hub_load(repo="ultralytics/yolov5", model="yolov5s", **kwargs):
|
| 509 |
-
# YOLOv5 torch.hub.load() wrapper with smart error/issue handling
|
| 510 |
-
if check_version(torch.__version__, "1.9.1"):
|
| 511 |
-
kwargs[
|
| 512 |
-
"skip_validation"
|
| 513 |
-
] = True # validation causes GitHub API rate limit errors
|
| 514 |
-
if check_version(torch.__version__, "1.12.0"):
|
| 515 |
-
kwargs["trust_repo"] = True # argument required starting in torch 0.12
|
| 516 |
-
try:
|
| 517 |
-
return torch.hub.load(repo, model, **kwargs)
|
| 518 |
-
except Exception:
|
| 519 |
-
return torch.hub.load(repo, model, force_reload=True, **kwargs)
|
| 520 |
-
|
| 521 |
-
|
| 522 |
-
def smart_resume(
|
| 523 |
-
ckpt, optimizer, ema=None, weights="yolov5s.pt", epochs=300, resume=True
|
| 524 |
-
):
|
| 525 |
-
# Resume training from a partially trained checkpoint
|
| 526 |
-
best_fitness = 0.0
|
| 527 |
-
start_epoch = ckpt["epoch"] + 1
|
| 528 |
-
if ckpt["optimizer"] is not None:
|
| 529 |
-
optimizer.load_state_dict(ckpt["optimizer"]) # optimizer
|
| 530 |
-
best_fitness = ckpt["best_fitness"]
|
| 531 |
-
if ema and ckpt.get("ema"):
|
| 532 |
-
ema.ema.load_state_dict(ckpt["ema"].float().state_dict()) # EMA
|
| 533 |
-
ema.updates = ckpt["updates"]
|
| 534 |
-
if resume:
|
| 535 |
-
assert start_epoch > 0, (
|
| 536 |
-
f"{weights} training to {epochs} epochs is finished, nothing to resume.\n"
|
| 537 |
-
f"Start a new training without --resume, i.e. 'python train.py --weights {weights}'"
|
| 538 |
-
)
|
| 539 |
-
LOGGER.info(
|
| 540 |
-
f"Resuming training from {weights} from epoch {start_epoch} to {epochs} total epochs"
|
| 541 |
-
)
|
| 542 |
-
if epochs < start_epoch:
|
| 543 |
-
LOGGER.info(
|
| 544 |
-
f"{weights} has been trained for {ckpt['epoch']} epochs. Fine-tuning for {epochs} more epochs."
|
| 545 |
-
)
|
| 546 |
-
epochs += ckpt["epoch"] # finetune additional epochs
|
| 547 |
-
return best_fitness, start_epoch, epochs
|
| 548 |
-
|
| 549 |
-
|
| 550 |
-
class EarlyStopping:
|
| 551 |
-
# YOLOv5 simple early stopper
|
| 552 |
-
def __init__(self, patience=30):
|
| 553 |
-
self.best_fitness = 0.0 # i.e. mAP
|
| 554 |
-
self.best_epoch = 0
|
| 555 |
-
self.patience = patience or float(
|
| 556 |
-
"inf"
|
| 557 |
-
) # epochs to wait after fitness stops improving to stop
|
| 558 |
-
self.possible_stop = False # possible stop may occur next epoch
|
| 559 |
-
|
| 560 |
-
def __call__(self, epoch, fitness):
|
| 561 |
-
if (
|
| 562 |
-
fitness >= self.best_fitness
|
| 563 |
-
): # >= 0 to allow for early zero-fitness stage of training
|
| 564 |
-
self.best_epoch = epoch
|
| 565 |
-
self.best_fitness = fitness
|
| 566 |
-
delta = epoch - self.best_epoch # epochs without improvement
|
| 567 |
-
self.possible_stop = delta >= (
|
| 568 |
-
self.patience - 1
|
| 569 |
-
) # possible stop may occur next epoch
|
| 570 |
-
stop = delta >= self.patience # stop training if patience exceeded
|
| 571 |
-
if stop:
|
| 572 |
-
LOGGER.info(
|
| 573 |
-
f"Stopping training early as no improvement observed in last {self.patience} epochs. "
|
| 574 |
-
f"Best results observed at epoch {self.best_epoch}, best model saved as best.pt.\n"
|
| 575 |
-
f"To update EarlyStopping(patience={self.patience}) pass a new patience value, "
|
| 576 |
-
f"i.e. `python train.py --patience 300` or use `--patience 0` to disable EarlyStopping."
|
| 577 |
-
)
|
| 578 |
-
return stop
|
| 579 |
-
|
| 580 |
-
|
| 581 |
-
class ModelEMA:
|
| 582 |
-
"""Updated Exponential Moving Average (EMA) from https://github.com/rwightman/pytorch-image-models
|
| 583 |
-
Keeps a moving average of everything in the model state_dict (parameters and buffers)
|
| 584 |
-
For EMA details see https://www.tensorflow.org/api_docs/python/tf/train/ExponentialMovingAverage
|
| 585 |
-
"""
|
| 586 |
-
|
| 587 |
-
def __init__(self, model, decay=0.9999, tau=2000, updates=0):
|
| 588 |
-
# Create EMA
|
| 589 |
-
self.ema = deepcopy(de_parallel(model)).eval() # FP32 EMA
|
| 590 |
-
self.updates = updates # number of EMA updates
|
| 591 |
-
self.decay = lambda x: decay * (
|
| 592 |
-
1 - math.exp(-x / tau)
|
| 593 |
-
) # decay exponential ramp (to help early epochs)
|
| 594 |
-
for p in self.ema.parameters():
|
| 595 |
-
p.requires_grad_(False)
|
| 596 |
-
|
| 597 |
-
def update(self, model):
|
| 598 |
-
# Update EMA parameters
|
| 599 |
-
self.updates += 1
|
| 600 |
-
d = self.decay(self.updates)
|
| 601 |
-
|
| 602 |
-
msd = de_parallel(model).state_dict() # model state_dict
|
| 603 |
-
for k, v in self.ema.state_dict().items():
|
| 604 |
-
if v.dtype.is_floating_point: # true for FP16 and FP32
|
| 605 |
-
v *= d
|
| 606 |
-
v += (1 - d) * msd[k].detach()
|
| 607 |
-
# assert v.dtype == msd[k].dtype == torch.float32, f'{k}: EMA {v.dtype} and model {msd[k].dtype} must be FP32'
|
| 608 |
-
|
| 609 |
-
def update_attr(
|
| 610 |
-
self, model, include=(), exclude=("process_group", "reducer")
|
| 611 |
-
):
|
| 612 |
-
# Update EMA attributes
|
| 613 |
-
copy_attr(self.ema, model, include, exclude)
|
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spaces/AchyuthGamer/OpenGPT-Chat-UI/.svelte-kit/types/src/routes/conversation/[id]/message/[messageId]/prompt/$types.d.ts
DELETED
|
@@ -1,9 +0,0 @@
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|
| 1 |
-
import type * as Kit from '@sveltejs/kit';
|
| 2 |
-
|
| 3 |
-
type Expand<T> = T extends infer O ? { [K in keyof O]: O[K] } : never;
|
| 4 |
-
type RouteParams = { id: string; messageId: string }
|
| 5 |
-
type RouteId = '/conversation/[id]/message/[messageId]/prompt';
|
| 6 |
-
|
| 7 |
-
export type EntryGenerator = () => Promise<Array<RouteParams>> | Array<RouteParams>;
|
| 8 |
-
export type RequestHandler = Kit.RequestHandler<RouteParams, RouteId>;
|
| 9 |
-
export type RequestEvent = Kit.RequestEvent<RouteParams, RouteId>;
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spaces/AchyuthGamer/OpenGPT-Chat-UI/src/lib/server/websearch/summarizeWeb.ts
DELETED
|
@@ -1,39 +0,0 @@
|
|
| 1 |
-
import { HF_ACCESS_TOKEN } from "$env/static/private";
|
| 2 |
-
import { HfInference } from "@huggingface/inference";
|
| 3 |
-
import { defaultModel } from "$lib/server/models";
|
| 4 |
-
import type { BackendModel } from "../models";
|
| 5 |
-
import { generateFromDefaultEndpoint } from "../generateFromDefaultEndpoint";
|
| 6 |
-
|
| 7 |
-
export async function summarizeWeb(content: string, query: string, model: BackendModel) {
|
| 8 |
-
// if HF_ACCESS_TOKEN is set, we use a HF dedicated endpoint for summarization
|
| 9 |
-
try {
|
| 10 |
-
if (HF_ACCESS_TOKEN) {
|
| 11 |
-
const summary = (
|
| 12 |
-
await new HfInference(HF_ACCESS_TOKEN).summarization({
|
| 13 |
-
model: "facebook/bart-large-cnn",
|
| 14 |
-
inputs: content,
|
| 15 |
-
parameters: {
|
| 16 |
-
max_length: 512,
|
| 17 |
-
},
|
| 18 |
-
})
|
| 19 |
-
).summary_text;
|
| 20 |
-
return summary;
|
| 21 |
-
}
|
| 22 |
-
} catch (e) {
|
| 23 |
-
console.log(e);
|
| 24 |
-
}
|
| 25 |
-
|
| 26 |
-
// else we use the LLM to generate a summary
|
| 27 |
-
const summaryPrompt = defaultModel.webSearchSummaryPromptRender({
|
| 28 |
-
answer: content
|
| 29 |
-
.split(" ")
|
| 30 |
-
.slice(0, model.parameters?.truncate ?? 0)
|
| 31 |
-
.join(" "),
|
| 32 |
-
query: query,
|
| 33 |
-
});
|
| 34 |
-
const summary = await generateFromDefaultEndpoint(summaryPrompt).then((txt: string) =>
|
| 35 |
-
txt.trim()
|
| 36 |
-
);
|
| 37 |
-
|
| 38 |
-
return summary;
|
| 39 |
-
}
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spaces/AgentVerse/agentVerse/ui/src/phaser3-rex-plugins/templates/ui/colorinput/colorinputbase/methods/SetSwatchColor.js
DELETED
|
@@ -1,13 +0,0 @@
|
|
| 1 |
-
var SetSwatchColor = function (swatch, color) {
|
| 2 |
-
if (!swatch) {
|
| 3 |
-
return;
|
| 4 |
-
}
|
| 5 |
-
|
| 6 |
-
if (swatch.setTint) {
|
| 7 |
-
swatch.setTint(color);
|
| 8 |
-
} else if (swatch.setFillStyle) {
|
| 9 |
-
swatch.setFillStyle(color);
|
| 10 |
-
}
|
| 11 |
-
}
|
| 12 |
-
|
| 13 |
-
export default SetSwatchColor;
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spaces/AgentVerse/agentVerse/ui/src/phaser3-rex-plugins/templates/ui/modal/Modal.d.ts
DELETED
|
@@ -1,2 +0,0 @@
|
|
| 1 |
-
import { ModalBehavoir, Modal, ModalPromise, ModalClose } from '../../../plugins/modal';
|
| 2 |
-
export { ModalBehavoir, Modal, ModalPromise, ModalClose };
|
|
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|
spaces/Alesmikes/Elvirespeak/app.py
DELETED
|
@@ -1,142 +0,0 @@
|
|
| 1 |
-
"""
|
| 2 |
-
this model only supports english since text to speech is an english only model
|
| 3 |
-
"""
|
| 4 |
-
from google.cloud import texttospeech
|
| 5 |
-
import os
|
| 6 |
-
import openai
|
| 7 |
-
import gradio as gr
|
| 8 |
-
from dotenv import load_dotenv
|
| 9 |
-
import pinecone
|
| 10 |
-
|
| 11 |
-
"""
|
| 12 |
-
login to gcp
|
| 13 |
-
"""
|
| 14 |
-
os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = "gcp_access_key.json"
|
| 15 |
-
# Instantiates a client
|
| 16 |
-
client = texttospeech.TextToSpeechClient()
|
| 17 |
-
|
| 18 |
-
"""
|
| 19 |
-
Connecting to Open AI API
|
| 20 |
-
"""
|
| 21 |
-
load_dotenv()
|
| 22 |
-
openai.organization = os.getenv("OPENAI_ORG")
|
| 23 |
-
openai.api_key = os.getenv("OPENAI_API_KEY")
|
| 24 |
-
EMBEDDING_MODEL = "text-embedding-ada-002"
|
| 25 |
-
"""
|
| 26 |
-
Connecting to pincone API and assign index
|
| 27 |
-
"""
|
| 28 |
-
index_name = 'economic-forecast'
|
| 29 |
-
pinecone.init(
|
| 30 |
-
api_key=os.getenv("Pinecone_KEY"),
|
| 31 |
-
environment=os.getenv("Pinecone_ENV")
|
| 32 |
-
)
|
| 33 |
-
|
| 34 |
-
## initial a first message to define GPT's role
|
| 35 |
-
|
| 36 |
-
|
| 37 |
-
"""
|
| 38 |
-
define the text -> speech function
|
| 39 |
-
"""
|
| 40 |
-
def text2speech(text):
|
| 41 |
-
|
| 42 |
-
# Set the text input to be synthesized
|
| 43 |
-
synthesis_input = texttospeech.SynthesisInput(text=text)
|
| 44 |
-
|
| 45 |
-
# Build the voice request, select the language code ("en-US") and the ssml
|
| 46 |
-
# voice gender ("neutral")
|
| 47 |
-
voice = texttospeech.VoiceSelectionParams(
|
| 48 |
-
language_code="en-US", name="en-US-News-K", ssml_gender=texttospeech.SsmlVoiceGender.FEMALE
|
| 49 |
-
)
|
| 50 |
-
|
| 51 |
-
# Select the type of audio file you want returned
|
| 52 |
-
audio_config = texttospeech.AudioConfig(
|
| 53 |
-
audio_encoding=texttospeech.AudioEncoding.MP3
|
| 54 |
-
)
|
| 55 |
-
|
| 56 |
-
# Perform the text-to-speech request on the text input with the selected
|
| 57 |
-
# voice parameters and audio file type
|
| 58 |
-
response = client.synthesize_speech(
|
| 59 |
-
input=synthesis_input, voice=voice, audio_config=audio_config
|
| 60 |
-
)
|
| 61 |
-
# The response's audio_content is binary.
|
| 62 |
-
with open("output.mp3", "wb") as out:
|
| 63 |
-
# Write the response to the output file.
|
| 64 |
-
out.write(response.audio_content)
|
| 65 |
-
print('Audio content written to file "output.mp3"')
|
| 66 |
-
|
| 67 |
-
"""
|
| 68 |
-
define voice -> gpt -> text -> voice workflow
|
| 69 |
-
"""
|
| 70 |
-
def transcribe(audio):
|
| 71 |
-
reset_chat_history()
|
| 72 |
-
voice_path = get_response(audio)
|
| 73 |
-
messages = get_response(audio, return_messages=True)
|
| 74 |
-
chat_text = "\n".join([f"{msg['role']}: {msg['content']}" for msg in messages])
|
| 75 |
-
with open(voice_path, 'rb') as f:
|
| 76 |
-
voice_bytes = f.read()
|
| 77 |
-
return voice_bytes, chat_text
|
| 78 |
-
#global messages
|
| 79 |
-
|
| 80 |
-
"""
|
| 81 |
-
gradio output file doesn't have .wav so rename the file to the correct format
|
| 82 |
-
"""
|
| 83 |
-
extension = ".wav"
|
| 84 |
-
audiofomated = f"{audio}{extension}"
|
| 85 |
-
os.rename(audio,audiofomated)
|
| 86 |
-
|
| 87 |
-
"""
|
| 88 |
-
pass the audio file to whisper to transcribe
|
| 89 |
-
|
| 90 |
-
"""
|
| 91 |
-
audio_file = open(audiofomated, "rb")
|
| 92 |
-
transcript = openai.Audio.transcribe("whisper-1", audio_file)
|
| 93 |
-
|
| 94 |
-
|
| 95 |
-
"""
|
| 96 |
-
run cosin similarity to find context
|
| 97 |
-
"""
|
| 98 |
-
### Input the question and search for the relavent text
|
| 99 |
-
index = pinecone.Index(index_name)
|
| 100 |
-
query = openai.Embedding.create(input=transcript["text"], model=EMBEDDING_MODEL)["data"][0]["embedding"] # embed the user query into an embedding vector
|
| 101 |
-
res = index.query(query, top_k=3, include_metadata=True) # run cosin similarity to search the most relevant embeded content; this is done in pinecone only
|
| 102 |
-
contexts = [
|
| 103 |
-
x['metadata']['text'] for x in res['matches']
|
| 104 |
-
]
|
| 105 |
-
merged_context = "".join(contexts)
|
| 106 |
-
contextwithQuestion = "Context: " + "\n"+ merged_context + "*End of the context*" + "\n\n" + "Question: " + transcript["text"]
|
| 107 |
-
|
| 108 |
-
|
| 109 |
-
"""
|
| 110 |
-
pass the transcripted text to GPT
|
| 111 |
-
"""
|
| 112 |
-
messages = [
|
| 113 |
-
{"role": "system",
|
| 114 |
-
"content":
|
| 115 |
-
"You are Elvire. Forest oracle dedicated to share her knowledge with accidental strangers.\
|
| 116 |
-
"}
|
| 117 |
-
]
|
| 118 |
-
messages.append({"role": "user", "content":contextwithQuestion}) ## add user input to the list of message
|
| 119 |
-
|
| 120 |
-
response = openai.ChatCompletion.create(
|
| 121 |
-
model="gpt-3.5-turbo",
|
| 122 |
-
messages=messages
|
| 123 |
-
) ## pass the list of message to GPT
|
| 124 |
-
|
| 125 |
-
messages.append({"role": "assistant", "content":response["choices"][0]["message"]["content"]}) ## add GPT response to the list of message
|
| 126 |
-
text2speech(response["choices"][0]["message"]["content"]) ## create mp3 voice output
|
| 127 |
-
|
| 128 |
-
voice_path = os.path.abspath("output.mp3")
|
| 129 |
-
|
| 130 |
-
return voice_path, "\n".join([f"{msg['role']}: {msg['content']}" for msg in messages])
|
| 131 |
-
|
| 132 |
-
output_text = gr.outputs.Textbox(label="Chat Messages")
|
| 133 |
-
|
| 134 |
-
audio_input = gr.inputs.Audio(source="microphone", type="filepath", label="Speak here...")
|
| 135 |
-
chat_output = gr.outputs.Textbox(label="Chat Messages")
|
| 136 |
-
audio_output = gr.outputs.Audio(type="bytes", label="Synthesized Voice")
|
| 137 |
-
|
| 138 |
-
gr.Interface(fn=transcribe,
|
| 139 |
-
inputs=audio_input,
|
| 140 |
-
outputs=[audio_output, chat_output],
|
| 141 |
-
live=True,
|
| 142 |
-
allow_flagging=False).launch()
|
|
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|
|
spaces/Amrrs/pdf-table-extractor/app.py
DELETED
|
@@ -1,62 +0,0 @@
|
|
| 1 |
-
import streamlit as st # data app development
|
| 2 |
-
import subprocess # process in the os
|
| 3 |
-
from subprocess import STDOUT, check_call #os process manipuation
|
| 4 |
-
import os #os process manipuation
|
| 5 |
-
import base64 # byte object into a pdf file
|
| 6 |
-
import camelot as cam # extracting tables from PDFs
|
| 7 |
-
|
| 8 |
-
# to run this only once and it's cached
|
| 9 |
-
@st.cache
|
| 10 |
-
def gh():
|
| 11 |
-
"""install ghostscript on the linux machine"""
|
| 12 |
-
proc = subprocess.Popen('apt-get install -y ghostscript', shell=True, stdin=None, stdout=open(os.devnull,"wb"), stderr=STDOUT, executable="/bin/bash")
|
| 13 |
-
proc.wait()
|
| 14 |
-
|
| 15 |
-
gh()
|
| 16 |
-
|
| 17 |
-
|
| 18 |
-
|
| 19 |
-
st.title("PDF Table Extractor")
|
| 20 |
-
st.subheader("with `Camelot` Python library")
|
| 21 |
-
|
| 22 |
-
st.image("https://raw.githubusercontent.com/camelot-dev/camelot/master/docs/_static/camelot.png", width=200)
|
| 23 |
-
|
| 24 |
-
|
| 25 |
-
# file uploader on streamlit
|
| 26 |
-
|
| 27 |
-
input_pdf = st.file_uploader(label = "upload your pdf here", type = 'pdf')
|
| 28 |
-
|
| 29 |
-
st.markdown("### Page Number")
|
| 30 |
-
|
| 31 |
-
page_number = st.text_input("Enter the page # from where you want to extract the PDF eg: 3", value = 1)
|
| 32 |
-
|
| 33 |
-
# run this only when a PDF is uploaded
|
| 34 |
-
|
| 35 |
-
if input_pdf is not None:
|
| 36 |
-
# byte object into a PDF file
|
| 37 |
-
with open("input.pdf", "wb") as f:
|
| 38 |
-
base64_pdf = base64.b64encode(input_pdf.read()).decode('utf-8')
|
| 39 |
-
f.write(base64.b64decode(base64_pdf))
|
| 40 |
-
f.close()
|
| 41 |
-
|
| 42 |
-
# read the pdf and parse it using stream
|
| 43 |
-
table = cam.read_pdf("input.pdf", pages = page_number, flavor = 'stream')
|
| 44 |
-
|
| 45 |
-
st.markdown("### Number of Tables")
|
| 46 |
-
|
| 47 |
-
# display the output after parsing
|
| 48 |
-
st.write(table)
|
| 49 |
-
|
| 50 |
-
# display the table
|
| 51 |
-
|
| 52 |
-
if len(table) > 0:
|
| 53 |
-
|
| 54 |
-
# extract the index value of the table
|
| 55 |
-
|
| 56 |
-
option = st.selectbox(label = "Select the Table to be displayed", options = range(len(table) + 1))
|
| 57 |
-
|
| 58 |
-
st.markdown('### Output Table')
|
| 59 |
-
|
| 60 |
-
# display the dataframe
|
| 61 |
-
|
| 62 |
-
st.dataframe(table[int(option)-1].df)
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spaces/Andy1621/uniformer_image_detection/mmdet/core/bbox/assigners/center_region_assigner.py
DELETED
|
@@ -1,335 +0,0 @@
|
|
| 1 |
-
import torch
|
| 2 |
-
|
| 3 |
-
from ..builder import BBOX_ASSIGNERS
|
| 4 |
-
from ..iou_calculators import build_iou_calculator
|
| 5 |
-
from .assign_result import AssignResult
|
| 6 |
-
from .base_assigner import BaseAssigner
|
| 7 |
-
|
| 8 |
-
|
| 9 |
-
def scale_boxes(bboxes, scale):
|
| 10 |
-
"""Expand an array of boxes by a given scale.
|
| 11 |
-
|
| 12 |
-
Args:
|
| 13 |
-
bboxes (Tensor): Shape (m, 4)
|
| 14 |
-
scale (float): The scale factor of bboxes
|
| 15 |
-
|
| 16 |
-
Returns:
|
| 17 |
-
(Tensor): Shape (m, 4). Scaled bboxes
|
| 18 |
-
"""
|
| 19 |
-
assert bboxes.size(1) == 4
|
| 20 |
-
w_half = (bboxes[:, 2] - bboxes[:, 0]) * .5
|
| 21 |
-
h_half = (bboxes[:, 3] - bboxes[:, 1]) * .5
|
| 22 |
-
x_c = (bboxes[:, 2] + bboxes[:, 0]) * .5
|
| 23 |
-
y_c = (bboxes[:, 3] + bboxes[:, 1]) * .5
|
| 24 |
-
|
| 25 |
-
w_half *= scale
|
| 26 |
-
h_half *= scale
|
| 27 |
-
|
| 28 |
-
boxes_scaled = torch.zeros_like(bboxes)
|
| 29 |
-
boxes_scaled[:, 0] = x_c - w_half
|
| 30 |
-
boxes_scaled[:, 2] = x_c + w_half
|
| 31 |
-
boxes_scaled[:, 1] = y_c - h_half
|
| 32 |
-
boxes_scaled[:, 3] = y_c + h_half
|
| 33 |
-
return boxes_scaled
|
| 34 |
-
|
| 35 |
-
|
| 36 |
-
def is_located_in(points, bboxes):
|
| 37 |
-
"""Are points located in bboxes.
|
| 38 |
-
|
| 39 |
-
Args:
|
| 40 |
-
points (Tensor): Points, shape: (m, 2).
|
| 41 |
-
bboxes (Tensor): Bounding boxes, shape: (n, 4).
|
| 42 |
-
|
| 43 |
-
Return:
|
| 44 |
-
Tensor: Flags indicating if points are located in bboxes, shape: (m, n).
|
| 45 |
-
"""
|
| 46 |
-
assert points.size(1) == 2
|
| 47 |
-
assert bboxes.size(1) == 4
|
| 48 |
-
return (points[:, 0].unsqueeze(1) > bboxes[:, 0].unsqueeze(0)) & \
|
| 49 |
-
(points[:, 0].unsqueeze(1) < bboxes[:, 2].unsqueeze(0)) & \
|
| 50 |
-
(points[:, 1].unsqueeze(1) > bboxes[:, 1].unsqueeze(0)) & \
|
| 51 |
-
(points[:, 1].unsqueeze(1) < bboxes[:, 3].unsqueeze(0))
|
| 52 |
-
|
| 53 |
-
|
| 54 |
-
def bboxes_area(bboxes):
|
| 55 |
-
"""Compute the area of an array of bboxes.
|
| 56 |
-
|
| 57 |
-
Args:
|
| 58 |
-
bboxes (Tensor): The coordinates ox bboxes. Shape: (m, 4)
|
| 59 |
-
|
| 60 |
-
Returns:
|
| 61 |
-
Tensor: Area of the bboxes. Shape: (m, )
|
| 62 |
-
"""
|
| 63 |
-
assert bboxes.size(1) == 4
|
| 64 |
-
w = (bboxes[:, 2] - bboxes[:, 0])
|
| 65 |
-
h = (bboxes[:, 3] - bboxes[:, 1])
|
| 66 |
-
areas = w * h
|
| 67 |
-
return areas
|
| 68 |
-
|
| 69 |
-
|
| 70 |
-
@BBOX_ASSIGNERS.register_module()
|
| 71 |
-
class CenterRegionAssigner(BaseAssigner):
|
| 72 |
-
"""Assign pixels at the center region of a bbox as positive.
|
| 73 |
-
|
| 74 |
-
Each proposals will be assigned with `-1`, `0`, or a positive integer
|
| 75 |
-
indicating the ground truth index.
|
| 76 |
-
- -1: negative samples
|
| 77 |
-
- semi-positive numbers: positive sample, index (0-based) of assigned gt
|
| 78 |
-
|
| 79 |
-
Args:
|
| 80 |
-
pos_scale (float): Threshold within which pixels are
|
| 81 |
-
labelled as positive.
|
| 82 |
-
neg_scale (float): Threshold above which pixels are
|
| 83 |
-
labelled as positive.
|
| 84 |
-
min_pos_iof (float): Minimum iof of a pixel with a gt to be
|
| 85 |
-
labelled as positive. Default: 1e-2
|
| 86 |
-
ignore_gt_scale (float): Threshold within which the pixels
|
| 87 |
-
are ignored when the gt is labelled as shadowed. Default: 0.5
|
| 88 |
-
foreground_dominate (bool): If True, the bbox will be assigned as
|
| 89 |
-
positive when a gt's kernel region overlaps with another's shadowed
|
| 90 |
-
(ignored) region, otherwise it is set as ignored. Default to False.
|
| 91 |
-
"""
|
| 92 |
-
|
| 93 |
-
def __init__(self,
|
| 94 |
-
pos_scale,
|
| 95 |
-
neg_scale,
|
| 96 |
-
min_pos_iof=1e-2,
|
| 97 |
-
ignore_gt_scale=0.5,
|
| 98 |
-
foreground_dominate=False,
|
| 99 |
-
iou_calculator=dict(type='BboxOverlaps2D')):
|
| 100 |
-
self.pos_scale = pos_scale
|
| 101 |
-
self.neg_scale = neg_scale
|
| 102 |
-
self.min_pos_iof = min_pos_iof
|
| 103 |
-
self.ignore_gt_scale = ignore_gt_scale
|
| 104 |
-
self.foreground_dominate = foreground_dominate
|
| 105 |
-
self.iou_calculator = build_iou_calculator(iou_calculator)
|
| 106 |
-
|
| 107 |
-
def get_gt_priorities(self, gt_bboxes):
|
| 108 |
-
"""Get gt priorities according to their areas.
|
| 109 |
-
|
| 110 |
-
Smaller gt has higher priority.
|
| 111 |
-
|
| 112 |
-
Args:
|
| 113 |
-
gt_bboxes (Tensor): Ground truth boxes, shape (k, 4).
|
| 114 |
-
|
| 115 |
-
Returns:
|
| 116 |
-
Tensor: The priority of gts so that gts with larger priority is \
|
| 117 |
-
more likely to be assigned. Shape (k, )
|
| 118 |
-
"""
|
| 119 |
-
gt_areas = bboxes_area(gt_bboxes)
|
| 120 |
-
# Rank all gt bbox areas. Smaller objects has larger priority
|
| 121 |
-
_, sort_idx = gt_areas.sort(descending=True)
|
| 122 |
-
sort_idx = sort_idx.argsort()
|
| 123 |
-
return sort_idx
|
| 124 |
-
|
| 125 |
-
def assign(self, bboxes, gt_bboxes, gt_bboxes_ignore=None, gt_labels=None):
|
| 126 |
-
"""Assign gt to bboxes.
|
| 127 |
-
|
| 128 |
-
This method assigns gts to every bbox (proposal/anchor), each bbox \
|
| 129 |
-
will be assigned with -1, or a semi-positive number. -1 means \
|
| 130 |
-
negative sample, semi-positive number is the index (0-based) of \
|
| 131 |
-
assigned gt.
|
| 132 |
-
|
| 133 |
-
Args:
|
| 134 |
-
bboxes (Tensor): Bounding boxes to be assigned, shape(n, 4).
|
| 135 |
-
gt_bboxes (Tensor): Groundtruth boxes, shape (k, 4).
|
| 136 |
-
gt_bboxes_ignore (tensor, optional): Ground truth bboxes that are
|
| 137 |
-
labelled as `ignored`, e.g., crowd boxes in COCO.
|
| 138 |
-
gt_labels (tensor, optional): Label of gt_bboxes, shape (num_gts,).
|
| 139 |
-
|
| 140 |
-
Returns:
|
| 141 |
-
:obj:`AssignResult`: The assigned result. Note that \
|
| 142 |
-
shadowed_labels of shape (N, 2) is also added as an \
|
| 143 |
-
`assign_result` attribute. `shadowed_labels` is a tensor \
|
| 144 |
-
composed of N pairs of anchor_ind, class_label], where N \
|
| 145 |
-
is the number of anchors that lie in the outer region of a \
|
| 146 |
-
gt, anchor_ind is the shadowed anchor index and class_label \
|
| 147 |
-
is the shadowed class label.
|
| 148 |
-
|
| 149 |
-
Example:
|
| 150 |
-
>>> self = CenterRegionAssigner(0.2, 0.2)
|
| 151 |
-
>>> bboxes = torch.Tensor([[0, 0, 10, 10], [10, 10, 20, 20]])
|
| 152 |
-
>>> gt_bboxes = torch.Tensor([[0, 0, 10, 10]])
|
| 153 |
-
>>> assign_result = self.assign(bboxes, gt_bboxes)
|
| 154 |
-
>>> expected_gt_inds = torch.LongTensor([1, 0])
|
| 155 |
-
>>> assert torch.all(assign_result.gt_inds == expected_gt_inds)
|
| 156 |
-
"""
|
| 157 |
-
# There are in total 5 steps in the pixel assignment
|
| 158 |
-
# 1. Find core (the center region, say inner 0.2)
|
| 159 |
-
# and shadow (the relatively ourter part, say inner 0.2-0.5)
|
| 160 |
-
# regions of every gt.
|
| 161 |
-
# 2. Find all prior bboxes that lie in gt_core and gt_shadow regions
|
| 162 |
-
# 3. Assign prior bboxes in gt_core with a one-hot id of the gt in
|
| 163 |
-
# the image.
|
| 164 |
-
# 3.1. For overlapping objects, the prior bboxes in gt_core is
|
| 165 |
-
# assigned with the object with smallest area
|
| 166 |
-
# 4. Assign prior bboxes with class label according to its gt id.
|
| 167 |
-
# 4.1. Assign -1 to prior bboxes lying in shadowed gts
|
| 168 |
-
# 4.2. Assign positive prior boxes with the corresponding label
|
| 169 |
-
# 5. Find pixels lying in the shadow of an object and assign them with
|
| 170 |
-
# background label, but set the loss weight of its corresponding
|
| 171 |
-
# gt to zero.
|
| 172 |
-
assert bboxes.size(1) == 4, 'bboxes must have size of 4'
|
| 173 |
-
# 1. Find core positive and shadow region of every gt
|
| 174 |
-
gt_core = scale_boxes(gt_bboxes, self.pos_scale)
|
| 175 |
-
gt_shadow = scale_boxes(gt_bboxes, self.neg_scale)
|
| 176 |
-
|
| 177 |
-
# 2. Find prior bboxes that lie in gt_core and gt_shadow regions
|
| 178 |
-
bbox_centers = (bboxes[:, 2:4] + bboxes[:, 0:2]) / 2
|
| 179 |
-
# The center points lie within the gt boxes
|
| 180 |
-
is_bbox_in_gt = is_located_in(bbox_centers, gt_bboxes)
|
| 181 |
-
# Only calculate bbox and gt_core IoF. This enables small prior bboxes
|
| 182 |
-
# to match large gts
|
| 183 |
-
bbox_and_gt_core_overlaps = self.iou_calculator(
|
| 184 |
-
bboxes, gt_core, mode='iof')
|
| 185 |
-
# The center point of effective priors should be within the gt box
|
| 186 |
-
is_bbox_in_gt_core = is_bbox_in_gt & (
|
| 187 |
-
bbox_and_gt_core_overlaps > self.min_pos_iof) # shape (n, k)
|
| 188 |
-
|
| 189 |
-
is_bbox_in_gt_shadow = (
|
| 190 |
-
self.iou_calculator(bboxes, gt_shadow, mode='iof') >
|
| 191 |
-
self.min_pos_iof)
|
| 192 |
-
# Rule out center effective positive pixels
|
| 193 |
-
is_bbox_in_gt_shadow &= (~is_bbox_in_gt_core)
|
| 194 |
-
|
| 195 |
-
num_gts, num_bboxes = gt_bboxes.size(0), bboxes.size(0)
|
| 196 |
-
if num_gts == 0 or num_bboxes == 0:
|
| 197 |
-
# If no gts exist, assign all pixels to negative
|
| 198 |
-
assigned_gt_ids = \
|
| 199 |
-
is_bbox_in_gt_core.new_zeros((num_bboxes,),
|
| 200 |
-
dtype=torch.long)
|
| 201 |
-
pixels_in_gt_shadow = assigned_gt_ids.new_empty((0, 2))
|
| 202 |
-
else:
|
| 203 |
-
# Step 3: assign a one-hot gt id to each pixel, and smaller objects
|
| 204 |
-
# have high priority to assign the pixel.
|
| 205 |
-
sort_idx = self.get_gt_priorities(gt_bboxes)
|
| 206 |
-
assigned_gt_ids, pixels_in_gt_shadow = \
|
| 207 |
-
self.assign_one_hot_gt_indices(is_bbox_in_gt_core,
|
| 208 |
-
is_bbox_in_gt_shadow,
|
| 209 |
-
gt_priority=sort_idx)
|
| 210 |
-
|
| 211 |
-
if gt_bboxes_ignore is not None and gt_bboxes_ignore.numel() > 0:
|
| 212 |
-
# No ground truth or boxes, return empty assignment
|
| 213 |
-
gt_bboxes_ignore = scale_boxes(
|
| 214 |
-
gt_bboxes_ignore, scale=self.ignore_gt_scale)
|
| 215 |
-
is_bbox_in_ignored_gts = is_located_in(bbox_centers,
|
| 216 |
-
gt_bboxes_ignore)
|
| 217 |
-
is_bbox_in_ignored_gts = is_bbox_in_ignored_gts.any(dim=1)
|
| 218 |
-
assigned_gt_ids[is_bbox_in_ignored_gts] = -1
|
| 219 |
-
|
| 220 |
-
# 4. Assign prior bboxes with class label according to its gt id.
|
| 221 |
-
assigned_labels = None
|
| 222 |
-
shadowed_pixel_labels = None
|
| 223 |
-
if gt_labels is not None:
|
| 224 |
-
# Default assigned label is the background (-1)
|
| 225 |
-
assigned_labels = assigned_gt_ids.new_full((num_bboxes, ), -1)
|
| 226 |
-
pos_inds = torch.nonzero(
|
| 227 |
-
assigned_gt_ids > 0, as_tuple=False).squeeze()
|
| 228 |
-
if pos_inds.numel() > 0:
|
| 229 |
-
assigned_labels[pos_inds] = gt_labels[assigned_gt_ids[pos_inds]
|
| 230 |
-
- 1]
|
| 231 |
-
# 5. Find pixels lying in the shadow of an object
|
| 232 |
-
shadowed_pixel_labels = pixels_in_gt_shadow.clone()
|
| 233 |
-
if pixels_in_gt_shadow.numel() > 0:
|
| 234 |
-
pixel_idx, gt_idx =\
|
| 235 |
-
pixels_in_gt_shadow[:, 0], pixels_in_gt_shadow[:, 1]
|
| 236 |
-
assert (assigned_gt_ids[pixel_idx] != gt_idx).all(), \
|
| 237 |
-
'Some pixels are dually assigned to ignore and gt!'
|
| 238 |
-
shadowed_pixel_labels[:, 1] = gt_labels[gt_idx - 1]
|
| 239 |
-
override = (
|
| 240 |
-
assigned_labels[pixel_idx] == shadowed_pixel_labels[:, 1])
|
| 241 |
-
if self.foreground_dominate:
|
| 242 |
-
# When a pixel is both positive and shadowed, set it as pos
|
| 243 |
-
shadowed_pixel_labels = shadowed_pixel_labels[~override]
|
| 244 |
-
else:
|
| 245 |
-
# When a pixel is both pos and shadowed, set it as shadowed
|
| 246 |
-
assigned_labels[pixel_idx[override]] = -1
|
| 247 |
-
assigned_gt_ids[pixel_idx[override]] = 0
|
| 248 |
-
|
| 249 |
-
assign_result = AssignResult(
|
| 250 |
-
num_gts, assigned_gt_ids, None, labels=assigned_labels)
|
| 251 |
-
# Add shadowed_labels as assign_result property. Shape: (num_shadow, 2)
|
| 252 |
-
assign_result.set_extra_property('shadowed_labels',
|
| 253 |
-
shadowed_pixel_labels)
|
| 254 |
-
return assign_result
|
| 255 |
-
|
| 256 |
-
def assign_one_hot_gt_indices(self,
|
| 257 |
-
is_bbox_in_gt_core,
|
| 258 |
-
is_bbox_in_gt_shadow,
|
| 259 |
-
gt_priority=None):
|
| 260 |
-
"""Assign only one gt index to each prior box.
|
| 261 |
-
|
| 262 |
-
Gts with large gt_priority are more likely to be assigned.
|
| 263 |
-
|
| 264 |
-
Args:
|
| 265 |
-
is_bbox_in_gt_core (Tensor): Bool tensor indicating the bbox center
|
| 266 |
-
is in the core area of a gt (e.g. 0-0.2).
|
| 267 |
-
Shape: (num_prior, num_gt).
|
| 268 |
-
is_bbox_in_gt_shadow (Tensor): Bool tensor indicating the bbox
|
| 269 |
-
center is in the shadowed area of a gt (e.g. 0.2-0.5).
|
| 270 |
-
Shape: (num_prior, num_gt).
|
| 271 |
-
gt_priority (Tensor): Priorities of gts. The gt with a higher
|
| 272 |
-
priority is more likely to be assigned to the bbox when the bbox
|
| 273 |
-
match with multiple gts. Shape: (num_gt, ).
|
| 274 |
-
|
| 275 |
-
Returns:
|
| 276 |
-
tuple: Returns (assigned_gt_inds, shadowed_gt_inds).
|
| 277 |
-
|
| 278 |
-
- assigned_gt_inds: The assigned gt index of each prior bbox \
|
| 279 |
-
(i.e. index from 1 to num_gts). Shape: (num_prior, ).
|
| 280 |
-
- shadowed_gt_inds: shadowed gt indices. It is a tensor of \
|
| 281 |
-
shape (num_ignore, 2) with first column being the \
|
| 282 |
-
shadowed prior bbox indices and the second column the \
|
| 283 |
-
shadowed gt indices (1-based).
|
| 284 |
-
"""
|
| 285 |
-
num_bboxes, num_gts = is_bbox_in_gt_core.shape
|
| 286 |
-
|
| 287 |
-
if gt_priority is None:
|
| 288 |
-
gt_priority = torch.arange(
|
| 289 |
-
num_gts, device=is_bbox_in_gt_core.device)
|
| 290 |
-
assert gt_priority.size(0) == num_gts
|
| 291 |
-
# The bigger gt_priority, the more preferable to be assigned
|
| 292 |
-
# The assigned inds are by default 0 (background)
|
| 293 |
-
assigned_gt_inds = is_bbox_in_gt_core.new_zeros((num_bboxes, ),
|
| 294 |
-
dtype=torch.long)
|
| 295 |
-
# Shadowed bboxes are assigned to be background. But the corresponding
|
| 296 |
-
# label is ignored during loss calculation, which is done through
|
| 297 |
-
# shadowed_gt_inds
|
| 298 |
-
shadowed_gt_inds = torch.nonzero(is_bbox_in_gt_shadow, as_tuple=False)
|
| 299 |
-
if is_bbox_in_gt_core.sum() == 0: # No gt match
|
| 300 |
-
shadowed_gt_inds[:, 1] += 1 # 1-based. For consistency issue
|
| 301 |
-
return assigned_gt_inds, shadowed_gt_inds
|
| 302 |
-
|
| 303 |
-
# The priority of each prior box and gt pair. If one prior box is
|
| 304 |
-
# matched bo multiple gts. Only the pair with the highest priority
|
| 305 |
-
# is saved
|
| 306 |
-
pair_priority = is_bbox_in_gt_core.new_full((num_bboxes, num_gts),
|
| 307 |
-
-1,
|
| 308 |
-
dtype=torch.long)
|
| 309 |
-
|
| 310 |
-
# Each bbox could match with multiple gts.
|
| 311 |
-
# The following codes deal with this situation
|
| 312 |
-
# Matched bboxes (to any gt). Shape: (num_pos_anchor, )
|
| 313 |
-
inds_of_match = torch.any(is_bbox_in_gt_core, dim=1)
|
| 314 |
-
# The matched gt index of each positive bbox. Length >= num_pos_anchor
|
| 315 |
-
# , since one bbox could match multiple gts
|
| 316 |
-
matched_bbox_gt_inds = torch.nonzero(
|
| 317 |
-
is_bbox_in_gt_core, as_tuple=False)[:, 1]
|
| 318 |
-
# Assign priority to each bbox-gt pair.
|
| 319 |
-
pair_priority[is_bbox_in_gt_core] = gt_priority[matched_bbox_gt_inds]
|
| 320 |
-
_, argmax_priority = pair_priority[inds_of_match].max(dim=1)
|
| 321 |
-
assigned_gt_inds[inds_of_match] = argmax_priority + 1 # 1-based
|
| 322 |
-
# Zero-out the assigned anchor box to filter the shadowed gt indices
|
| 323 |
-
is_bbox_in_gt_core[inds_of_match, argmax_priority] = 0
|
| 324 |
-
# Concat the shadowed indices due to overlapping with that out side of
|
| 325 |
-
# effective scale. shape: (total_num_ignore, 2)
|
| 326 |
-
shadowed_gt_inds = torch.cat(
|
| 327 |
-
(shadowed_gt_inds, torch.nonzero(
|
| 328 |
-
is_bbox_in_gt_core, as_tuple=False)),
|
| 329 |
-
dim=0)
|
| 330 |
-
# `is_bbox_in_gt_core` should be changed back to keep arguments intact.
|
| 331 |
-
is_bbox_in_gt_core[inds_of_match, argmax_priority] = 1
|
| 332 |
-
# 1-based shadowed gt indices, to be consistent with `assigned_gt_inds`
|
| 333 |
-
if shadowed_gt_inds.numel() > 0:
|
| 334 |
-
shadowed_gt_inds[:, 1] += 1
|
| 335 |
-
return assigned_gt_inds, shadowed_gt_inds
|
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|
spaces/Andy1621/uniformer_image_segmentation/configs/gcnet/gcnet_r50-d8_512x1024_80k_cityscapes.py
DELETED
|
@@ -1,4 +0,0 @@
|
|
| 1 |
-
_base_ = [
|
| 2 |
-
'../_base_/models/gcnet_r50-d8.py', '../_base_/datasets/cityscapes.py',
|
| 3 |
-
'../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
|
| 4 |
-
]
|
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|
spaces/Andy1621/uniformer_image_segmentation/configs/pspnet/pspnet_r101-d8_769x769_40k_cityscapes.py
DELETED
|
@@ -1,2 +0,0 @@
|
|
| 1 |
-
_base_ = './pspnet_r50-d8_769x769_40k_cityscapes.py'
|
| 2 |
-
model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
|
|
|
|
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|
|
spaces/AnishKumbhar/ChatBot/text-generation-webui-main/api-examples/api-example-chat-stream.py
DELETED
|
@@ -1,112 +0,0 @@
|
|
| 1 |
-
import asyncio
|
| 2 |
-
import html
|
| 3 |
-
import json
|
| 4 |
-
import sys
|
| 5 |
-
|
| 6 |
-
try:
|
| 7 |
-
import websockets
|
| 8 |
-
except ImportError:
|
| 9 |
-
print("Websockets package not found. Make sure it's installed.")
|
| 10 |
-
|
| 11 |
-
# For local streaming, the websockets are hosted without ssl - ws://
|
| 12 |
-
HOST = 'localhost:5005'
|
| 13 |
-
URI = f'ws://{HOST}/api/v1/chat-stream'
|
| 14 |
-
|
| 15 |
-
# For reverse-proxied streaming, the remote will likely host with ssl - wss://
|
| 16 |
-
# URI = 'wss://your-uri-here.trycloudflare.com/api/v1/stream'
|
| 17 |
-
|
| 18 |
-
|
| 19 |
-
async def run(user_input, history):
|
| 20 |
-
# Note: the selected defaults change from time to time.
|
| 21 |
-
request = {
|
| 22 |
-
'user_input': user_input,
|
| 23 |
-
'max_new_tokens': 250,
|
| 24 |
-
'auto_max_new_tokens': False,
|
| 25 |
-
'max_tokens_second': 0,
|
| 26 |
-
'history': history,
|
| 27 |
-
'mode': 'instruct', # Valid options: 'chat', 'chat-instruct', 'instruct'
|
| 28 |
-
'character': 'Example',
|
| 29 |
-
'instruction_template': 'Vicuna-v1.1', # Will get autodetected if unset
|
| 30 |
-
'your_name': 'You',
|
| 31 |
-
# 'name1': 'name of user', # Optional
|
| 32 |
-
# 'name2': 'name of character', # Optional
|
| 33 |
-
# 'context': 'character context', # Optional
|
| 34 |
-
# 'greeting': 'greeting', # Optional
|
| 35 |
-
# 'name1_instruct': 'You', # Optional
|
| 36 |
-
# 'name2_instruct': 'Assistant', # Optional
|
| 37 |
-
# 'context_instruct': 'context_instruct', # Optional
|
| 38 |
-
# 'turn_template': 'turn_template', # Optional
|
| 39 |
-
'regenerate': False,
|
| 40 |
-
'_continue': False,
|
| 41 |
-
'chat_instruct_command': 'Continue the chat dialogue below. Write a single reply for the character "<|character|>".\n\n<|prompt|>',
|
| 42 |
-
|
| 43 |
-
# Generation params. If 'preset' is set to different than 'None', the values
|
| 44 |
-
# in presets/preset-name.yaml are used instead of the individual numbers.
|
| 45 |
-
'preset': 'None',
|
| 46 |
-
'do_sample': True,
|
| 47 |
-
'temperature': 0.7,
|
| 48 |
-
'top_p': 0.1,
|
| 49 |
-
'typical_p': 1,
|
| 50 |
-
'epsilon_cutoff': 0, # In units of 1e-4
|
| 51 |
-
'eta_cutoff': 0, # In units of 1e-4
|
| 52 |
-
'tfs': 1,
|
| 53 |
-
'top_a': 0,
|
| 54 |
-
'repetition_penalty': 1.18,
|
| 55 |
-
'repetition_penalty_range': 0,
|
| 56 |
-
'top_k': 40,
|
| 57 |
-
'min_length': 0,
|
| 58 |
-
'no_repeat_ngram_size': 0,
|
| 59 |
-
'num_beams': 1,
|
| 60 |
-
'penalty_alpha': 0,
|
| 61 |
-
'length_penalty': 1,
|
| 62 |
-
'early_stopping': False,
|
| 63 |
-
'mirostat_mode': 0,
|
| 64 |
-
'mirostat_tau': 5,
|
| 65 |
-
'mirostat_eta': 0.1,
|
| 66 |
-
'grammar_string': '',
|
| 67 |
-
'guidance_scale': 1,
|
| 68 |
-
'negative_prompt': '',
|
| 69 |
-
|
| 70 |
-
'seed': -1,
|
| 71 |
-
'add_bos_token': True,
|
| 72 |
-
'truncation_length': 2048,
|
| 73 |
-
'ban_eos_token': False,
|
| 74 |
-
'custom_token_bans': '',
|
| 75 |
-
'skip_special_tokens': True,
|
| 76 |
-
'stopping_strings': []
|
| 77 |
-
}
|
| 78 |
-
|
| 79 |
-
async with websockets.connect(URI, ping_interval=None) as websocket:
|
| 80 |
-
await websocket.send(json.dumps(request))
|
| 81 |
-
|
| 82 |
-
while True:
|
| 83 |
-
incoming_data = await websocket.recv()
|
| 84 |
-
incoming_data = json.loads(incoming_data)
|
| 85 |
-
|
| 86 |
-
match incoming_data['event']:
|
| 87 |
-
case 'text_stream':
|
| 88 |
-
yield incoming_data['history']
|
| 89 |
-
case 'stream_end':
|
| 90 |
-
return
|
| 91 |
-
|
| 92 |
-
|
| 93 |
-
async def print_response_stream(user_input, history):
|
| 94 |
-
cur_len = 0
|
| 95 |
-
async for new_history in run(user_input, history):
|
| 96 |
-
cur_message = new_history['visible'][-1][1][cur_len:]
|
| 97 |
-
cur_len += len(cur_message)
|
| 98 |
-
print(html.unescape(cur_message), end='')
|
| 99 |
-
sys.stdout.flush() # If we don't flush, we won't see tokens in realtime.
|
| 100 |
-
|
| 101 |
-
|
| 102 |
-
if __name__ == '__main__':
|
| 103 |
-
user_input = "Please give me a step-by-step guide on how to plant a tree in my backyard."
|
| 104 |
-
|
| 105 |
-
# Basic example
|
| 106 |
-
history = {'internal': [], 'visible': []}
|
| 107 |
-
|
| 108 |
-
# "Continue" example. Make sure to set '_continue' to True above
|
| 109 |
-
# arr = [user_input, 'Surely, here is']
|
| 110 |
-
# history = {'internal': [arr], 'visible': [arr]}
|
| 111 |
-
|
| 112 |
-
asyncio.run(print_response_stream(user_input, history))
|
|
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|
spaces/AnishKumbhar/ChatBot/text-generation-webui-main/extensions/multimodal/pipelines/llava/llava.py
DELETED
|
@@ -1,148 +0,0 @@
|
|
| 1 |
-
import time
|
| 2 |
-
from abc import abstractmethod
|
| 3 |
-
from typing import List, Tuple
|
| 4 |
-
|
| 5 |
-
import torch
|
| 6 |
-
from huggingface_hub import hf_hub_download
|
| 7 |
-
from PIL import Image
|
| 8 |
-
from transformers import CLIPImageProcessor, CLIPVisionModel
|
| 9 |
-
|
| 10 |
-
from extensions.multimodal.abstract_pipeline import AbstractMultimodalPipeline
|
| 11 |
-
from modules import shared
|
| 12 |
-
from modules.logging_colors import logger
|
| 13 |
-
from modules.text_generation import encode
|
| 14 |
-
|
| 15 |
-
|
| 16 |
-
class LLaVA_v0_Pipeline(AbstractMultimodalPipeline):
|
| 17 |
-
CLIP_REPO = "openai/clip-vit-large-patch14"
|
| 18 |
-
|
| 19 |
-
def __init__(self, params: dict) -> None:
|
| 20 |
-
super().__init__()
|
| 21 |
-
self.clip_device = self._get_device("vision_device", params)
|
| 22 |
-
self.clip_dtype = self._get_dtype("vision_bits", params)
|
| 23 |
-
self.projector_device = self._get_device("projector_device", params)
|
| 24 |
-
self.projector_dtype = self._get_dtype("projector_bits", params)
|
| 25 |
-
self.image_processor, self.vision_tower, self.mm_projector = self._load_models()
|
| 26 |
-
|
| 27 |
-
def _load_models(self):
|
| 28 |
-
start_ts = time.time()
|
| 29 |
-
|
| 30 |
-
logger.info(f"LLaVA - Loading CLIP from {LLaVA_v0_Pipeline.CLIP_REPO} as {self.clip_dtype} on {self.clip_device}...")
|
| 31 |
-
image_processor = CLIPImageProcessor.from_pretrained(LLaVA_v0_Pipeline.CLIP_REPO, torch_dtype=self.clip_dtype)
|
| 32 |
-
vision_tower = CLIPVisionModel.from_pretrained(LLaVA_v0_Pipeline.CLIP_REPO, torch_dtype=self.clip_dtype).to(self.clip_device)
|
| 33 |
-
|
| 34 |
-
logger.info(f"LLaVA - Loading projector from {self.llava_projector_repo()} as {self.projector_dtype} on {self.projector_device}...")
|
| 35 |
-
projector_path = hf_hub_download(self.llava_projector_repo(), self.llava_projector_filename())
|
| 36 |
-
mm_projector = torch.nn.Linear(*self.llava_projector_shape())
|
| 37 |
-
projector_data = torch.load(projector_path)
|
| 38 |
-
mm_projector.weight = torch.nn.Parameter(projector_data['model.mm_projector.weight'].to(dtype=self.projector_dtype), False)
|
| 39 |
-
mm_projector.bias = torch.nn.Parameter(projector_data['model.mm_projector.bias'].to(dtype=self.projector_dtype), False)
|
| 40 |
-
mm_projector = mm_projector.to(self.projector_device)
|
| 41 |
-
|
| 42 |
-
logger.info(f"LLaVA supporting models loaded, took {time.time() - start_ts:.2f} seconds")
|
| 43 |
-
return image_processor, vision_tower, mm_projector
|
| 44 |
-
|
| 45 |
-
@staticmethod
|
| 46 |
-
def image_start() -> str:
|
| 47 |
-
return "<im_start>"
|
| 48 |
-
|
| 49 |
-
@staticmethod
|
| 50 |
-
def image_end() -> str:
|
| 51 |
-
return "<im_end>"
|
| 52 |
-
|
| 53 |
-
@staticmethod
|
| 54 |
-
def num_image_embeds() -> int:
|
| 55 |
-
return 256
|
| 56 |
-
|
| 57 |
-
@staticmethod
|
| 58 |
-
def embed_tokens(input_ids: torch.Tensor) -> torch.Tensor:
|
| 59 |
-
for attr in ['', 'model', 'model.model', 'model.model.model']:
|
| 60 |
-
tmp = getattr(shared.model, attr, None) if attr != '' else shared.model
|
| 61 |
-
if tmp is not None and hasattr(tmp, 'embed_tokens'):
|
| 62 |
-
func = tmp.embed_tokens
|
| 63 |
-
break
|
| 64 |
-
else:
|
| 65 |
-
raise ValueError('The embed_tokens method has not been found for this loader.')
|
| 66 |
-
|
| 67 |
-
return func(input_ids).to(shared.model.device, dtype=shared.model.dtype)
|
| 68 |
-
|
| 69 |
-
@staticmethod
|
| 70 |
-
def placeholder_embeddings() -> torch.Tensor:
|
| 71 |
-
return LLaVA_v0_Pipeline.embed_tokens(encode("<im_patch>"*256, add_bos_token=False)[0])
|
| 72 |
-
|
| 73 |
-
def embed_images(self, images: List[Image.Image]) -> torch.Tensor:
|
| 74 |
-
images = self.image_processor(images, return_tensors='pt')['pixel_values']
|
| 75 |
-
images = images.to(self.clip_device, dtype=self.clip_dtype)
|
| 76 |
-
|
| 77 |
-
with torch.no_grad():
|
| 78 |
-
image_forward_outs = self.vision_tower(images, output_hidden_states=True)
|
| 79 |
-
select_hidden_state_layer = -2
|
| 80 |
-
select_hidden_state = image_forward_outs.hidden_states[select_hidden_state_layer]
|
| 81 |
-
image_features = select_hidden_state[:, 1:].to(self.projector_device, dtype=self.projector_dtype)
|
| 82 |
-
image_features = self.mm_projector(image_features)
|
| 83 |
-
return image_features.to(shared.model.device, dtype=shared.model.dtype)
|
| 84 |
-
|
| 85 |
-
@staticmethod
|
| 86 |
-
@abstractmethod
|
| 87 |
-
def llava_projector_repo() -> str:
|
| 88 |
-
pass
|
| 89 |
-
|
| 90 |
-
@staticmethod
|
| 91 |
-
@abstractmethod
|
| 92 |
-
def llava_projector_filename() -> str:
|
| 93 |
-
pass
|
| 94 |
-
|
| 95 |
-
@staticmethod
|
| 96 |
-
@abstractmethod
|
| 97 |
-
def llava_projector_shape() -> Tuple[int, int]:
|
| 98 |
-
pass
|
| 99 |
-
|
| 100 |
-
|
| 101 |
-
class LLaVA_v0_13B_Pipeline(LLaVA_v0_Pipeline):
|
| 102 |
-
def __init__(self, params: dict) -> None:
|
| 103 |
-
super().__init__(params)
|
| 104 |
-
|
| 105 |
-
@staticmethod
|
| 106 |
-
def name() -> str:
|
| 107 |
-
return "llava-13b"
|
| 108 |
-
|
| 109 |
-
@staticmethod
|
| 110 |
-
def placeholder_token_id() -> int:
|
| 111 |
-
return 32000
|
| 112 |
-
|
| 113 |
-
@staticmethod
|
| 114 |
-
def llava_projector_shape() -> Tuple[int, int]:
|
| 115 |
-
return (1024, 5120)
|
| 116 |
-
|
| 117 |
-
@staticmethod
|
| 118 |
-
def llava_projector_filename() -> str:
|
| 119 |
-
return "mm_projector.bin"
|
| 120 |
-
|
| 121 |
-
@staticmethod
|
| 122 |
-
def llava_projector_repo() -> str:
|
| 123 |
-
return "liuhaotian/LLaVA-13b-delta-v0"
|
| 124 |
-
|
| 125 |
-
|
| 126 |
-
class LLaVA_v0_7B_Pipeline(LLaVA_v0_Pipeline):
|
| 127 |
-
def __init__(self, params: dict) -> None:
|
| 128 |
-
super().__init__(params)
|
| 129 |
-
|
| 130 |
-
@staticmethod
|
| 131 |
-
def name() -> str:
|
| 132 |
-
return "llava-7b"
|
| 133 |
-
|
| 134 |
-
@staticmethod
|
| 135 |
-
def placeholder_token_id() -> int:
|
| 136 |
-
return 32001
|
| 137 |
-
|
| 138 |
-
@staticmethod
|
| 139 |
-
def llava_projector_shape() -> Tuple[int, int]:
|
| 140 |
-
return (1024, 4096)
|
| 141 |
-
|
| 142 |
-
@staticmethod
|
| 143 |
-
def llava_projector_filename() -> str:
|
| 144 |
-
return "mm_projector.bin"
|
| 145 |
-
|
| 146 |
-
@staticmethod
|
| 147 |
-
def llava_projector_repo() -> str:
|
| 148 |
-
return "liuhaotian/LLaVA-7b-delta-v0"
|
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|
spaces/Anonymous-123/ImageNet-Editing/editing_diffusion/CLIP/setup.py
DELETED
|
@@ -1,21 +0,0 @@
|
|
| 1 |
-
import os
|
| 2 |
-
|
| 3 |
-
import pkg_resources
|
| 4 |
-
from setuptools import setup, find_packages
|
| 5 |
-
|
| 6 |
-
setup(
|
| 7 |
-
name="clip",
|
| 8 |
-
py_modules=["clip"],
|
| 9 |
-
version="1.0",
|
| 10 |
-
description="",
|
| 11 |
-
author="OpenAI",
|
| 12 |
-
packages=find_packages(exclude=["tests*"]),
|
| 13 |
-
install_requires=[
|
| 14 |
-
str(r)
|
| 15 |
-
for r in pkg_resources.parse_requirements(
|
| 16 |
-
open(os.path.join(os.path.dirname(__file__), "requirements.txt"))
|
| 17 |
-
)
|
| 18 |
-
],
|
| 19 |
-
include_package_data=True,
|
| 20 |
-
extras_require={'dev': ['pytest']},
|
| 21 |
-
)
|
|
|
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|
spaces/Anonymous-sub/Rerender/ControlNet/annotator/hed/__init__.py
DELETED
|
@@ -1,96 +0,0 @@
|
|
| 1 |
-
# This is an improved version and model of HED edge detection with Apache License, Version 2.0.
|
| 2 |
-
# Please use this implementation in your products
|
| 3 |
-
# This implementation may produce slightly different results from Saining Xie's official implementations,
|
| 4 |
-
# but it generates smoother edges and is more suitable for ControlNet as well as other image-to-image translations.
|
| 5 |
-
# Different from official models and other implementations, this is an RGB-input model (rather than BGR)
|
| 6 |
-
# and in this way it works better for gradio's RGB protocol
|
| 7 |
-
|
| 8 |
-
import os
|
| 9 |
-
import cv2
|
| 10 |
-
import torch
|
| 11 |
-
import numpy as np
|
| 12 |
-
|
| 13 |
-
from einops import rearrange
|
| 14 |
-
from annotator.util import annotator_ckpts_path
|
| 15 |
-
|
| 16 |
-
|
| 17 |
-
class DoubleConvBlock(torch.nn.Module):
|
| 18 |
-
def __init__(self, input_channel, output_channel, layer_number):
|
| 19 |
-
super().__init__()
|
| 20 |
-
self.convs = torch.nn.Sequential()
|
| 21 |
-
self.convs.append(torch.nn.Conv2d(in_channels=input_channel, out_channels=output_channel, kernel_size=(3, 3), stride=(1, 1), padding=1))
|
| 22 |
-
for i in range(1, layer_number):
|
| 23 |
-
self.convs.append(torch.nn.Conv2d(in_channels=output_channel, out_channels=output_channel, kernel_size=(3, 3), stride=(1, 1), padding=1))
|
| 24 |
-
self.projection = torch.nn.Conv2d(in_channels=output_channel, out_channels=1, kernel_size=(1, 1), stride=(1, 1), padding=0)
|
| 25 |
-
|
| 26 |
-
def __call__(self, x, down_sampling=False):
|
| 27 |
-
h = x
|
| 28 |
-
if down_sampling:
|
| 29 |
-
h = torch.nn.functional.max_pool2d(h, kernel_size=(2, 2), stride=(2, 2))
|
| 30 |
-
for conv in self.convs:
|
| 31 |
-
h = conv(h)
|
| 32 |
-
h = torch.nn.functional.relu(h)
|
| 33 |
-
return h, self.projection(h)
|
| 34 |
-
|
| 35 |
-
|
| 36 |
-
class ControlNetHED_Apache2(torch.nn.Module):
|
| 37 |
-
def __init__(self):
|
| 38 |
-
super().__init__()
|
| 39 |
-
self.norm = torch.nn.Parameter(torch.zeros(size=(1, 3, 1, 1)))
|
| 40 |
-
self.block1 = DoubleConvBlock(input_channel=3, output_channel=64, layer_number=2)
|
| 41 |
-
self.block2 = DoubleConvBlock(input_channel=64, output_channel=128, layer_number=2)
|
| 42 |
-
self.block3 = DoubleConvBlock(input_channel=128, output_channel=256, layer_number=3)
|
| 43 |
-
self.block4 = DoubleConvBlock(input_channel=256, output_channel=512, layer_number=3)
|
| 44 |
-
self.block5 = DoubleConvBlock(input_channel=512, output_channel=512, layer_number=3)
|
| 45 |
-
|
| 46 |
-
def __call__(self, x):
|
| 47 |
-
h = x - self.norm
|
| 48 |
-
h, projection1 = self.block1(h)
|
| 49 |
-
h, projection2 = self.block2(h, down_sampling=True)
|
| 50 |
-
h, projection3 = self.block3(h, down_sampling=True)
|
| 51 |
-
h, projection4 = self.block4(h, down_sampling=True)
|
| 52 |
-
h, projection5 = self.block5(h, down_sampling=True)
|
| 53 |
-
return projection1, projection2, projection3, projection4, projection5
|
| 54 |
-
|
| 55 |
-
|
| 56 |
-
class HEDdetector:
|
| 57 |
-
def __init__(self):
|
| 58 |
-
remote_model_path = "https://huggingface.co/lllyasviel/Annotators/resolve/main/ControlNetHED.pth"
|
| 59 |
-
modelpath = os.path.join(annotator_ckpts_path, "ControlNetHED.pth")
|
| 60 |
-
if not os.path.exists(modelpath):
|
| 61 |
-
from basicsr.utils.download_util import load_file_from_url
|
| 62 |
-
load_file_from_url(remote_model_path, model_dir=annotator_ckpts_path)
|
| 63 |
-
self.netNetwork = ControlNetHED_Apache2().float().cuda().eval()
|
| 64 |
-
self.netNetwork.load_state_dict(torch.load(modelpath))
|
| 65 |
-
|
| 66 |
-
def __call__(self, input_image):
|
| 67 |
-
assert input_image.ndim == 3
|
| 68 |
-
H, W, C = input_image.shape
|
| 69 |
-
with torch.no_grad():
|
| 70 |
-
image_hed = torch.from_numpy(input_image.copy()).float().cuda()
|
| 71 |
-
image_hed = rearrange(image_hed, 'h w c -> 1 c h w')
|
| 72 |
-
edges = self.netNetwork(image_hed)
|
| 73 |
-
edges = [e.detach().cpu().numpy().astype(np.float32)[0, 0] for e in edges]
|
| 74 |
-
edges = [cv2.resize(e, (W, H), interpolation=cv2.INTER_LINEAR) for e in edges]
|
| 75 |
-
edges = np.stack(edges, axis=2)
|
| 76 |
-
edge = 1 / (1 + np.exp(-np.mean(edges, axis=2).astype(np.float64)))
|
| 77 |
-
edge = (edge * 255.0).clip(0, 255).astype(np.uint8)
|
| 78 |
-
return edge
|
| 79 |
-
|
| 80 |
-
|
| 81 |
-
def nms(x, t, s):
|
| 82 |
-
x = cv2.GaussianBlur(x.astype(np.float32), (0, 0), s)
|
| 83 |
-
|
| 84 |
-
f1 = np.array([[0, 0, 0], [1, 1, 1], [0, 0, 0]], dtype=np.uint8)
|
| 85 |
-
f2 = np.array([[0, 1, 0], [0, 1, 0], [0, 1, 0]], dtype=np.uint8)
|
| 86 |
-
f3 = np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]], dtype=np.uint8)
|
| 87 |
-
f4 = np.array([[0, 0, 1], [0, 1, 0], [1, 0, 0]], dtype=np.uint8)
|
| 88 |
-
|
| 89 |
-
y = np.zeros_like(x)
|
| 90 |
-
|
| 91 |
-
for f in [f1, f2, f3, f4]:
|
| 92 |
-
np.putmask(y, cv2.dilate(x, kernel=f) == x, x)
|
| 93 |
-
|
| 94 |
-
z = np.zeros_like(y, dtype=np.uint8)
|
| 95 |
-
z[y > t] = 255
|
| 96 |
-
return z
|
|
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spaces/Arnx/MusicGenXvAKN/audiocraft/models/musicgen.py
DELETED
|
@@ -1,362 +0,0 @@
|
|
| 1 |
-
# Copyright (c) Meta Platforms, Inc. and affiliates.
|
| 2 |
-
# All rights reserved.
|
| 3 |
-
#
|
| 4 |
-
# This source code is licensed under the license found in the
|
| 5 |
-
# LICENSE file in the root directory of this source tree.
|
| 6 |
-
|
| 7 |
-
"""
|
| 8 |
-
Main model for using MusicGen. This will combine all the required components
|
| 9 |
-
and provide easy access to the generation API.
|
| 10 |
-
"""
|
| 11 |
-
|
| 12 |
-
import os
|
| 13 |
-
import typing as tp
|
| 14 |
-
|
| 15 |
-
import torch
|
| 16 |
-
|
| 17 |
-
from .encodec import CompressionModel
|
| 18 |
-
from .lm import LMModel
|
| 19 |
-
from .builders import get_debug_compression_model, get_debug_lm_model
|
| 20 |
-
from .loaders import load_compression_model, load_lm_model, HF_MODEL_CHECKPOINTS_MAP
|
| 21 |
-
from ..data.audio_utils import convert_audio
|
| 22 |
-
from ..modules.conditioners import ConditioningAttributes, WavCondition
|
| 23 |
-
from ..utils.autocast import TorchAutocast
|
| 24 |
-
|
| 25 |
-
|
| 26 |
-
MelodyList = tp.List[tp.Optional[torch.Tensor]]
|
| 27 |
-
MelodyType = tp.Union[torch.Tensor, MelodyList]
|
| 28 |
-
|
| 29 |
-
|
| 30 |
-
class MusicGen:
|
| 31 |
-
"""MusicGen main model with convenient generation API.
|
| 32 |
-
|
| 33 |
-
Args:
|
| 34 |
-
name (str): name of the model.
|
| 35 |
-
compression_model (CompressionModel): Compression model
|
| 36 |
-
used to map audio to invertible discrete representations.
|
| 37 |
-
lm (LMModel): Language model over discrete representations.
|
| 38 |
-
"""
|
| 39 |
-
def __init__(self, name: str, compression_model: CompressionModel, lm: LMModel,
|
| 40 |
-
max_duration: float = 30):
|
| 41 |
-
self.name = name
|
| 42 |
-
self.compression_model = compression_model
|
| 43 |
-
self.lm = lm
|
| 44 |
-
self.max_duration = max_duration
|
| 45 |
-
self.device = next(iter(lm.parameters())).device
|
| 46 |
-
self.generation_params: dict = {}
|
| 47 |
-
self.set_generation_params(duration=15) # 15 seconds by default
|
| 48 |
-
self._progress_callback: tp.Optional[tp.Callable[[int, int], None]] = None
|
| 49 |
-
if self.device.type == 'cpu':
|
| 50 |
-
self.autocast = TorchAutocast(enabled=False)
|
| 51 |
-
else:
|
| 52 |
-
self.autocast = TorchAutocast(
|
| 53 |
-
enabled=True, device_type=self.device.type, dtype=torch.float16)
|
| 54 |
-
|
| 55 |
-
@property
|
| 56 |
-
def frame_rate(self) -> int:
|
| 57 |
-
"""Roughly the number of AR steps per seconds."""
|
| 58 |
-
return self.compression_model.frame_rate
|
| 59 |
-
|
| 60 |
-
@property
|
| 61 |
-
def sample_rate(self) -> int:
|
| 62 |
-
"""Sample rate of the generated audio."""
|
| 63 |
-
return self.compression_model.sample_rate
|
| 64 |
-
|
| 65 |
-
@property
|
| 66 |
-
def audio_channels(self) -> int:
|
| 67 |
-
"""Audio channels of the generated audio."""
|
| 68 |
-
return self.compression_model.channels
|
| 69 |
-
|
| 70 |
-
@staticmethod
|
| 71 |
-
def get_pretrained(name: str = 'melody', device=None):
|
| 72 |
-
"""Return pretrained model, we provide four models:
|
| 73 |
-
- small (300M), text to music, # see: https://huggingface.co/facebook/musicgen-small
|
| 74 |
-
- medium (1.5B), text to music, # see: https://huggingface.co/facebook/musicgen-medium
|
| 75 |
-
- melody (1.5B) text to music and text+melody to music, # see: https://huggingface.co/facebook/musicgen-melody
|
| 76 |
-
- large (3.3B), text to music, # see: https://huggingface.co/facebook/musicgen-large
|
| 77 |
-
"""
|
| 78 |
-
|
| 79 |
-
if device is None:
|
| 80 |
-
if torch.cuda.device_count():
|
| 81 |
-
device = 'cuda'
|
| 82 |
-
else:
|
| 83 |
-
device = 'cpu'
|
| 84 |
-
|
| 85 |
-
if name == 'debug':
|
| 86 |
-
# used only for unit tests
|
| 87 |
-
compression_model = get_debug_compression_model(device)
|
| 88 |
-
lm = get_debug_lm_model(device)
|
| 89 |
-
return MusicGen(name, compression_model, lm)
|
| 90 |
-
|
| 91 |
-
if name not in HF_MODEL_CHECKPOINTS_MAP:
|
| 92 |
-
if not os.path.isfile(name) and not os.path.isdir(name):
|
| 93 |
-
raise ValueError(
|
| 94 |
-
f"{name} is not a valid checkpoint name. "
|
| 95 |
-
f"Choose one of {', '.join(HF_MODEL_CHECKPOINTS_MAP.keys())}"
|
| 96 |
-
)
|
| 97 |
-
|
| 98 |
-
cache_dir = os.environ.get('MUSICGEN_ROOT', None)
|
| 99 |
-
compression_model = load_compression_model(name, device=device, cache_dir=cache_dir)
|
| 100 |
-
lm = load_lm_model(name, device=device, cache_dir=cache_dir)
|
| 101 |
-
if name == 'melody':
|
| 102 |
-
lm.condition_provider.conditioners['self_wav'].match_len_on_eval = True
|
| 103 |
-
|
| 104 |
-
return MusicGen(name, compression_model, lm)
|
| 105 |
-
|
| 106 |
-
def set_generation_params(self, use_sampling: bool = True, top_k: int = 250,
|
| 107 |
-
top_p: float = 0.0, temperature: float = 1.0,
|
| 108 |
-
duration: float = 30.0, cfg_coef: float = 3.0,
|
| 109 |
-
two_step_cfg: bool = False, extend_stride: float = 18):
|
| 110 |
-
"""Set the generation parameters for MusicGen.
|
| 111 |
-
|
| 112 |
-
Args:
|
| 113 |
-
use_sampling (bool, optional): Use sampling if True, else do argmax decoding. Defaults to True.
|
| 114 |
-
top_k (int, optional): top_k used for sampling. Defaults to 250.
|
| 115 |
-
top_p (float, optional): top_p used for sampling, when set to 0 top_k is used. Defaults to 0.0.
|
| 116 |
-
temperature (float, optional): Softmax temperature parameter. Defaults to 1.0.
|
| 117 |
-
duration (float, optional): Duration of the generated waveform. Defaults to 30.0.
|
| 118 |
-
cfg_coef (float, optional): Coefficient used for classifier free guidance. Defaults to 3.0.
|
| 119 |
-
two_step_cfg (bool, optional): If True, performs 2 forward for Classifier Free Guidance,
|
| 120 |
-
instead of batching together the two. This has some impact on how things
|
| 121 |
-
are padded but seems to have little impact in practice.
|
| 122 |
-
extend_stride: when doing extended generation (i.e. more than 30 seconds), by how much
|
| 123 |
-
should we extend the audio each time. Larger values will mean less context is
|
| 124 |
-
preserved, and shorter value will require extra computations.
|
| 125 |
-
"""
|
| 126 |
-
assert extend_stride < self.max_duration, "Cannot stride by more than max generation duration."
|
| 127 |
-
self.extend_stride = extend_stride
|
| 128 |
-
self.duration = duration
|
| 129 |
-
self.generation_params = {
|
| 130 |
-
'use_sampling': use_sampling,
|
| 131 |
-
'temp': temperature,
|
| 132 |
-
'top_k': top_k,
|
| 133 |
-
'top_p': top_p,
|
| 134 |
-
'cfg_coef': cfg_coef,
|
| 135 |
-
'two_step_cfg': two_step_cfg,
|
| 136 |
-
}
|
| 137 |
-
|
| 138 |
-
def set_custom_progress_callback(self, progress_callback: tp.Optional[tp.Callable[[int, int], None]] = None):
|
| 139 |
-
"""Override the default progress callback."""
|
| 140 |
-
self._progress_callback = progress_callback
|
| 141 |
-
|
| 142 |
-
def generate_unconditional(self, num_samples: int, progress: bool = False) -> torch.Tensor:
|
| 143 |
-
"""Generate samples in an unconditional manner.
|
| 144 |
-
|
| 145 |
-
Args:
|
| 146 |
-
num_samples (int): Number of samples to be generated.
|
| 147 |
-
progress (bool, optional): Flag to display progress of the generation process. Defaults to False.
|
| 148 |
-
"""
|
| 149 |
-
descriptions: tp.List[tp.Optional[str]] = [None] * num_samples
|
| 150 |
-
attributes, prompt_tokens = self._prepare_tokens_and_attributes(descriptions, None)
|
| 151 |
-
return self._generate_tokens(attributes, prompt_tokens, progress)
|
| 152 |
-
|
| 153 |
-
def generate(self, descriptions: tp.List[str], progress: bool = False) -> torch.Tensor:
|
| 154 |
-
"""Generate samples conditioned on text.
|
| 155 |
-
|
| 156 |
-
Args:
|
| 157 |
-
descriptions (tp.List[str]): A list of strings used as text conditioning.
|
| 158 |
-
progress (bool, optional): Flag to display progress of the generation process. Defaults to False.
|
| 159 |
-
"""
|
| 160 |
-
attributes, prompt_tokens = self._prepare_tokens_and_attributes(descriptions, None)
|
| 161 |
-
assert prompt_tokens is None
|
| 162 |
-
return self._generate_tokens(attributes, prompt_tokens, progress)
|
| 163 |
-
|
| 164 |
-
def generate_with_chroma(self, descriptions: tp.List[str], melody_wavs: MelodyType,
|
| 165 |
-
melody_sample_rate: int, progress: bool = False) -> torch.Tensor:
|
| 166 |
-
"""Generate samples conditioned on text and melody.
|
| 167 |
-
|
| 168 |
-
Args:
|
| 169 |
-
descriptions (tp.List[str]): A list of strings used as text conditioning.
|
| 170 |
-
melody_wavs: (torch.Tensor or list of Tensor): A batch of waveforms used as
|
| 171 |
-
melody conditioning. Should have shape [B, C, T] with B matching the description length,
|
| 172 |
-
C=1 or 2. It can be [C, T] if there is a single description. It can also be
|
| 173 |
-
a list of [C, T] tensors.
|
| 174 |
-
melody_sample_rate: (int): Sample rate of the melody waveforms.
|
| 175 |
-
progress (bool, optional): Flag to display progress of the generation process. Defaults to False.
|
| 176 |
-
"""
|
| 177 |
-
if isinstance(melody_wavs, torch.Tensor):
|
| 178 |
-
if melody_wavs.dim() == 2:
|
| 179 |
-
melody_wavs = melody_wavs[None]
|
| 180 |
-
if melody_wavs.dim() != 3:
|
| 181 |
-
raise ValueError("Melody wavs should have a shape [B, C, T].")
|
| 182 |
-
melody_wavs = list(melody_wavs)
|
| 183 |
-
else:
|
| 184 |
-
for melody in melody_wavs:
|
| 185 |
-
if melody is not None:
|
| 186 |
-
assert melody.dim() == 2, "One melody in the list has the wrong number of dims."
|
| 187 |
-
|
| 188 |
-
melody_wavs = [
|
| 189 |
-
convert_audio(wav, melody_sample_rate, self.sample_rate, self.audio_channels)
|
| 190 |
-
if wav is not None else None
|
| 191 |
-
for wav in melody_wavs]
|
| 192 |
-
attributes, prompt_tokens = self._prepare_tokens_and_attributes(descriptions=descriptions, prompt=None,
|
| 193 |
-
melody_wavs=melody_wavs)
|
| 194 |
-
assert prompt_tokens is None
|
| 195 |
-
return self._generate_tokens(attributes, prompt_tokens, progress)
|
| 196 |
-
|
| 197 |
-
def generate_continuation(self, prompt: torch.Tensor, prompt_sample_rate: int,
|
| 198 |
-
descriptions: tp.Optional[tp.List[tp.Optional[str]]] = None,
|
| 199 |
-
progress: bool = False) -> torch.Tensor:
|
| 200 |
-
"""Generate samples conditioned on audio prompts.
|
| 201 |
-
|
| 202 |
-
Args:
|
| 203 |
-
prompt (torch.Tensor): A batch of waveforms used for continuation.
|
| 204 |
-
Prompt should be [B, C, T], or [C, T] if only one sample is generated.
|
| 205 |
-
prompt_sample_rate (int): Sampling rate of the given audio waveforms.
|
| 206 |
-
descriptions (tp.List[str], optional): A list of strings used as text conditioning. Defaults to None.
|
| 207 |
-
progress (bool, optional): Flag to display progress of the generation process. Defaults to False.
|
| 208 |
-
"""
|
| 209 |
-
if prompt.dim() == 2:
|
| 210 |
-
prompt = prompt[None]
|
| 211 |
-
if prompt.dim() != 3:
|
| 212 |
-
raise ValueError("prompt should have 3 dimensions: [B, C, T] (C = 1).")
|
| 213 |
-
prompt = convert_audio(prompt, prompt_sample_rate, self.sample_rate, self.audio_channels)
|
| 214 |
-
if descriptions is None:
|
| 215 |
-
descriptions = [None] * len(prompt)
|
| 216 |
-
attributes, prompt_tokens = self._prepare_tokens_and_attributes(descriptions, prompt)
|
| 217 |
-
assert prompt_tokens is not None
|
| 218 |
-
return self._generate_tokens(attributes, prompt_tokens, progress)
|
| 219 |
-
|
| 220 |
-
@torch.no_grad()
|
| 221 |
-
def _prepare_tokens_and_attributes(
|
| 222 |
-
self,
|
| 223 |
-
descriptions: tp.Sequence[tp.Optional[str]],
|
| 224 |
-
prompt: tp.Optional[torch.Tensor],
|
| 225 |
-
melody_wavs: tp.Optional[MelodyList] = None,
|
| 226 |
-
) -> tp.Tuple[tp.List[ConditioningAttributes], tp.Optional[torch.Tensor]]:
|
| 227 |
-
"""Prepare model inputs.
|
| 228 |
-
|
| 229 |
-
Args:
|
| 230 |
-
descriptions (tp.List[str]): A list of strings used as text conditioning.
|
| 231 |
-
prompt (torch.Tensor): A batch of waveforms used for continuation.
|
| 232 |
-
melody_wavs (tp.Optional[torch.Tensor], optional): A batch of waveforms
|
| 233 |
-
used as melody conditioning. Defaults to None.
|
| 234 |
-
"""
|
| 235 |
-
attributes = [
|
| 236 |
-
ConditioningAttributes(text={'description': description})
|
| 237 |
-
for description in descriptions]
|
| 238 |
-
|
| 239 |
-
if melody_wavs is None:
|
| 240 |
-
for attr in attributes:
|
| 241 |
-
attr.wav['self_wav'] = WavCondition(
|
| 242 |
-
torch.zeros((1, 1), device=self.device),
|
| 243 |
-
torch.tensor([0], device=self.device),
|
| 244 |
-
path='null_wav') # type: ignore
|
| 245 |
-
else:
|
| 246 |
-
if self.name != "melody":
|
| 247 |
-
raise RuntimeError("This model doesn't support melody conditioning. "
|
| 248 |
-
"Use the `melody` model.")
|
| 249 |
-
assert len(melody_wavs) == len(descriptions), \
|
| 250 |
-
f"number of melody wavs must match number of descriptions! " \
|
| 251 |
-
f"got melody len={len(melody_wavs)}, and descriptions len={len(descriptions)}"
|
| 252 |
-
for attr, melody in zip(attributes, melody_wavs):
|
| 253 |
-
if melody is None:
|
| 254 |
-
attr.wav['self_wav'] = WavCondition(
|
| 255 |
-
torch.zeros((1, 1), device=self.device),
|
| 256 |
-
torch.tensor([0], device=self.device),
|
| 257 |
-
path='null_wav') # type: ignore
|
| 258 |
-
else:
|
| 259 |
-
attr.wav['self_wav'] = WavCondition(
|
| 260 |
-
melody.to(device=self.device),
|
| 261 |
-
torch.tensor([melody.shape[-1]], device=self.device))
|
| 262 |
-
|
| 263 |
-
if prompt is not None:
|
| 264 |
-
if descriptions is not None:
|
| 265 |
-
assert len(descriptions) == len(prompt), "Prompt and nb. descriptions doesn't match"
|
| 266 |
-
prompt = prompt.to(self.device)
|
| 267 |
-
prompt_tokens, scale = self.compression_model.encode(prompt)
|
| 268 |
-
assert scale is None
|
| 269 |
-
else:
|
| 270 |
-
prompt_tokens = None
|
| 271 |
-
return attributes, prompt_tokens
|
| 272 |
-
|
| 273 |
-
def _generate_tokens(self, attributes: tp.List[ConditioningAttributes],
|
| 274 |
-
prompt_tokens: tp.Optional[torch.Tensor], progress: bool = False) -> torch.Tensor:
|
| 275 |
-
"""Generate discrete audio tokens given audio prompt and/or conditions.
|
| 276 |
-
|
| 277 |
-
Args:
|
| 278 |
-
attributes (tp.List[ConditioningAttributes]): Conditions used for generation (text/melody).
|
| 279 |
-
prompt_tokens (tp.Optional[torch.Tensor]): Audio prompt used for continuation.
|
| 280 |
-
progress (bool, optional): Flag to display progress of the generation process. Defaults to False.
|
| 281 |
-
Returns:
|
| 282 |
-
torch.Tensor: Generated audio, of shape [B, C, T], T is defined by the generation params.
|
| 283 |
-
"""
|
| 284 |
-
total_gen_len = int(self.duration * self.frame_rate)
|
| 285 |
-
max_prompt_len = int(min(self.duration, self.max_duration) * self.frame_rate)
|
| 286 |
-
current_gen_offset: int = 0
|
| 287 |
-
|
| 288 |
-
def _progress_callback(generated_tokens: int, tokens_to_generate: int):
|
| 289 |
-
generated_tokens += current_gen_offset
|
| 290 |
-
if self._progress_callback is not None:
|
| 291 |
-
# Note that total_gen_len might be quite wrong depending on the
|
| 292 |
-
# codebook pattern used, but with delay it is almost accurate.
|
| 293 |
-
self._progress_callback(generated_tokens, total_gen_len)
|
| 294 |
-
else:
|
| 295 |
-
print(f'{generated_tokens: 6d} / {total_gen_len: 6d}', end='\r')
|
| 296 |
-
|
| 297 |
-
if prompt_tokens is not None:
|
| 298 |
-
assert max_prompt_len >= prompt_tokens.shape[-1], \
|
| 299 |
-
"Prompt is longer than audio to generate"
|
| 300 |
-
|
| 301 |
-
callback = None
|
| 302 |
-
if progress:
|
| 303 |
-
callback = _progress_callback
|
| 304 |
-
|
| 305 |
-
if self.duration <= self.max_duration:
|
| 306 |
-
# generate by sampling from LM, simple case.
|
| 307 |
-
with self.autocast:
|
| 308 |
-
gen_tokens = self.lm.generate(
|
| 309 |
-
prompt_tokens, attributes,
|
| 310 |
-
callback=callback, max_gen_len=total_gen_len, **self.generation_params)
|
| 311 |
-
|
| 312 |
-
else:
|
| 313 |
-
# now this gets a bit messier, we need to handle prompts,
|
| 314 |
-
# melody conditioning etc.
|
| 315 |
-
ref_wavs = [attr.wav['self_wav'] for attr in attributes]
|
| 316 |
-
all_tokens = []
|
| 317 |
-
if prompt_tokens is None:
|
| 318 |
-
prompt_length = 0
|
| 319 |
-
else:
|
| 320 |
-
all_tokens.append(prompt_tokens)
|
| 321 |
-
prompt_length = prompt_tokens.shape[-1]
|
| 322 |
-
|
| 323 |
-
stride_tokens = int(self.frame_rate * self.extend_stride)
|
| 324 |
-
|
| 325 |
-
while current_gen_offset + prompt_length < total_gen_len:
|
| 326 |
-
time_offset = current_gen_offset / self.frame_rate
|
| 327 |
-
chunk_duration = min(self.duration - time_offset, self.max_duration)
|
| 328 |
-
max_gen_len = int(chunk_duration * self.frame_rate)
|
| 329 |
-
for attr, ref_wav in zip(attributes, ref_wavs):
|
| 330 |
-
wav_length = ref_wav.length.item()
|
| 331 |
-
if wav_length == 0:
|
| 332 |
-
continue
|
| 333 |
-
# We will extend the wav periodically if it not long enough.
|
| 334 |
-
# we have to do it here rather than in conditioners.py as otherwise
|
| 335 |
-
# we wouldn't have the full wav.
|
| 336 |
-
initial_position = int(time_offset * self.sample_rate)
|
| 337 |
-
wav_target_length = int(self.max_duration * self.sample_rate)
|
| 338 |
-
print(initial_position / self.sample_rate, wav_target_length / self.sample_rate)
|
| 339 |
-
positions = torch.arange(initial_position,
|
| 340 |
-
initial_position + wav_target_length, device=self.device)
|
| 341 |
-
attr.wav['self_wav'] = WavCondition(
|
| 342 |
-
ref_wav[0][:, positions % wav_length],
|
| 343 |
-
torch.full_like(ref_wav[1], wav_target_length))
|
| 344 |
-
with self.autocast:
|
| 345 |
-
gen_tokens = self.lm.generate(
|
| 346 |
-
prompt_tokens, attributes,
|
| 347 |
-
callback=callback, max_gen_len=max_gen_len, **self.generation_params)
|
| 348 |
-
if prompt_tokens is None:
|
| 349 |
-
all_tokens.append(gen_tokens)
|
| 350 |
-
else:
|
| 351 |
-
all_tokens.append(gen_tokens[:, :, prompt_tokens.shape[-1]:])
|
| 352 |
-
prompt_tokens = gen_tokens[:, :, stride_tokens:]
|
| 353 |
-
prompt_length = prompt_tokens.shape[-1]
|
| 354 |
-
current_gen_offset += stride_tokens
|
| 355 |
-
|
| 356 |
-
gen_tokens = torch.cat(all_tokens, dim=-1)
|
| 357 |
-
|
| 358 |
-
# generate audio
|
| 359 |
-
assert gen_tokens.dim() == 3
|
| 360 |
-
with torch.no_grad():
|
| 361 |
-
gen_audio = self.compression_model.decode(gen_tokens, None)
|
| 362 |
-
return gen_audio
|
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|
spaces/AsakuraMizu/moe-tts/monotonic_align/__init__.py
DELETED
|
@@ -1,21 +0,0 @@
|
|
| 1 |
-
from numpy import zeros, int32, float32
|
| 2 |
-
from torch import from_numpy
|
| 3 |
-
|
| 4 |
-
from .core import maximum_path_jit
|
| 5 |
-
|
| 6 |
-
|
| 7 |
-
def maximum_path(neg_cent, mask):
|
| 8 |
-
""" numba optimized version.
|
| 9 |
-
neg_cent: [b, t_t, t_s]
|
| 10 |
-
mask: [b, t_t, t_s]
|
| 11 |
-
"""
|
| 12 |
-
device = neg_cent.device
|
| 13 |
-
dtype = neg_cent.dtype
|
| 14 |
-
neg_cent = neg_cent.data.cpu().numpy().astype(float32)
|
| 15 |
-
path = zeros(neg_cent.shape, dtype=int32)
|
| 16 |
-
|
| 17 |
-
t_t_max = mask.sum(1)[:, 0].data.cpu().numpy().astype(int32)
|
| 18 |
-
t_s_max = mask.sum(2)[:, 0].data.cpu().numpy().astype(int32)
|
| 19 |
-
maximum_path_jit(path, neg_cent, t_t_max, t_s_max)
|
| 20 |
-
return from_numpy(path).to(device=device, dtype=dtype)
|
| 21 |
-
|
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|
|
spaces/Bart92/RVC_HF/demucs/tasnet.py
DELETED
|
@@ -1,452 +0,0 @@
|
|
| 1 |
-
# Copyright (c) Facebook, Inc. and its affiliates.
|
| 2 |
-
# All rights reserved.
|
| 3 |
-
#
|
| 4 |
-
# This source code is licensed under the license found in the
|
| 5 |
-
# LICENSE file in the root directory of this source tree.
|
| 6 |
-
#
|
| 7 |
-
# Created on 2018/12
|
| 8 |
-
# Author: Kaituo XU
|
| 9 |
-
# Modified on 2019/11 by Alexandre Defossez, added support for multiple output channels
|
| 10 |
-
# Here is the original license:
|
| 11 |
-
# The MIT License (MIT)
|
| 12 |
-
#
|
| 13 |
-
# Copyright (c) 2018 Kaituo XU
|
| 14 |
-
#
|
| 15 |
-
# Permission is hereby granted, free of charge, to any person obtaining a copy
|
| 16 |
-
# of this software and associated documentation files (the "Software"), to deal
|
| 17 |
-
# in the Software without restriction, including without limitation the rights
|
| 18 |
-
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
|
| 19 |
-
# copies of the Software, and to permit persons to whom the Software is
|
| 20 |
-
# furnished to do so, subject to the following conditions:
|
| 21 |
-
#
|
| 22 |
-
# The above copyright notice and this permission notice shall be included in all
|
| 23 |
-
# copies or substantial portions of the Software.
|
| 24 |
-
#
|
| 25 |
-
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
|
| 26 |
-
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
|
| 27 |
-
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
|
| 28 |
-
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
|
| 29 |
-
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
|
| 30 |
-
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
|
| 31 |
-
# SOFTWARE.
|
| 32 |
-
|
| 33 |
-
import math
|
| 34 |
-
|
| 35 |
-
import torch
|
| 36 |
-
import torch.nn as nn
|
| 37 |
-
import torch.nn.functional as F
|
| 38 |
-
|
| 39 |
-
from .utils import capture_init
|
| 40 |
-
|
| 41 |
-
EPS = 1e-8
|
| 42 |
-
|
| 43 |
-
|
| 44 |
-
def overlap_and_add(signal, frame_step):
|
| 45 |
-
outer_dimensions = signal.size()[:-2]
|
| 46 |
-
frames, frame_length = signal.size()[-2:]
|
| 47 |
-
|
| 48 |
-
subframe_length = math.gcd(frame_length, frame_step) # gcd=Greatest Common Divisor
|
| 49 |
-
subframe_step = frame_step // subframe_length
|
| 50 |
-
subframes_per_frame = frame_length // subframe_length
|
| 51 |
-
output_size = frame_step * (frames - 1) + frame_length
|
| 52 |
-
output_subframes = output_size // subframe_length
|
| 53 |
-
|
| 54 |
-
subframe_signal = signal.view(*outer_dimensions, -1, subframe_length)
|
| 55 |
-
|
| 56 |
-
frame = torch.arange(0, output_subframes,
|
| 57 |
-
device=signal.device).unfold(0, subframes_per_frame, subframe_step)
|
| 58 |
-
frame = frame.long() # signal may in GPU or CPU
|
| 59 |
-
frame = frame.contiguous().view(-1)
|
| 60 |
-
|
| 61 |
-
result = signal.new_zeros(*outer_dimensions, output_subframes, subframe_length)
|
| 62 |
-
result.index_add_(-2, frame, subframe_signal)
|
| 63 |
-
result = result.view(*outer_dimensions, -1)
|
| 64 |
-
return result
|
| 65 |
-
|
| 66 |
-
|
| 67 |
-
class ConvTasNet(nn.Module):
|
| 68 |
-
@capture_init
|
| 69 |
-
def __init__(self,
|
| 70 |
-
sources,
|
| 71 |
-
N=256,
|
| 72 |
-
L=20,
|
| 73 |
-
B=256,
|
| 74 |
-
H=512,
|
| 75 |
-
P=3,
|
| 76 |
-
X=8,
|
| 77 |
-
R=4,
|
| 78 |
-
audio_channels=2,
|
| 79 |
-
norm_type="gLN",
|
| 80 |
-
causal=False,
|
| 81 |
-
mask_nonlinear='relu',
|
| 82 |
-
samplerate=44100,
|
| 83 |
-
segment_length=44100 * 2 * 4):
|
| 84 |
-
"""
|
| 85 |
-
Args:
|
| 86 |
-
sources: list of sources
|
| 87 |
-
N: Number of filters in autoencoder
|
| 88 |
-
L: Length of the filters (in samples)
|
| 89 |
-
B: Number of channels in bottleneck 1 × 1-conv block
|
| 90 |
-
H: Number of channels in convolutional blocks
|
| 91 |
-
P: Kernel size in convolutional blocks
|
| 92 |
-
X: Number of convolutional blocks in each repeat
|
| 93 |
-
R: Number of repeats
|
| 94 |
-
norm_type: BN, gLN, cLN
|
| 95 |
-
causal: causal or non-causal
|
| 96 |
-
mask_nonlinear: use which non-linear function to generate mask
|
| 97 |
-
"""
|
| 98 |
-
super(ConvTasNet, self).__init__()
|
| 99 |
-
# Hyper-parameter
|
| 100 |
-
self.sources = sources
|
| 101 |
-
self.C = len(sources)
|
| 102 |
-
self.N, self.L, self.B, self.H, self.P, self.X, self.R = N, L, B, H, P, X, R
|
| 103 |
-
self.norm_type = norm_type
|
| 104 |
-
self.causal = causal
|
| 105 |
-
self.mask_nonlinear = mask_nonlinear
|
| 106 |
-
self.audio_channels = audio_channels
|
| 107 |
-
self.samplerate = samplerate
|
| 108 |
-
self.segment_length = segment_length
|
| 109 |
-
# Components
|
| 110 |
-
self.encoder = Encoder(L, N, audio_channels)
|
| 111 |
-
self.separator = TemporalConvNet(
|
| 112 |
-
N, B, H, P, X, R, self.C, norm_type, causal, mask_nonlinear)
|
| 113 |
-
self.decoder = Decoder(N, L, audio_channels)
|
| 114 |
-
# init
|
| 115 |
-
for p in self.parameters():
|
| 116 |
-
if p.dim() > 1:
|
| 117 |
-
nn.init.xavier_normal_(p)
|
| 118 |
-
|
| 119 |
-
def valid_length(self, length):
|
| 120 |
-
return length
|
| 121 |
-
|
| 122 |
-
def forward(self, mixture):
|
| 123 |
-
"""
|
| 124 |
-
Args:
|
| 125 |
-
mixture: [M, T], M is batch size, T is #samples
|
| 126 |
-
Returns:
|
| 127 |
-
est_source: [M, C, T]
|
| 128 |
-
"""
|
| 129 |
-
mixture_w = self.encoder(mixture)
|
| 130 |
-
est_mask = self.separator(mixture_w)
|
| 131 |
-
est_source = self.decoder(mixture_w, est_mask)
|
| 132 |
-
|
| 133 |
-
# T changed after conv1d in encoder, fix it here
|
| 134 |
-
T_origin = mixture.size(-1)
|
| 135 |
-
T_conv = est_source.size(-1)
|
| 136 |
-
est_source = F.pad(est_source, (0, T_origin - T_conv))
|
| 137 |
-
return est_source
|
| 138 |
-
|
| 139 |
-
|
| 140 |
-
class Encoder(nn.Module):
|
| 141 |
-
"""Estimation of the nonnegative mixture weight by a 1-D conv layer.
|
| 142 |
-
"""
|
| 143 |
-
def __init__(self, L, N, audio_channels):
|
| 144 |
-
super(Encoder, self).__init__()
|
| 145 |
-
# Hyper-parameter
|
| 146 |
-
self.L, self.N = L, N
|
| 147 |
-
# Components
|
| 148 |
-
# 50% overlap
|
| 149 |
-
self.conv1d_U = nn.Conv1d(audio_channels, N, kernel_size=L, stride=L // 2, bias=False)
|
| 150 |
-
|
| 151 |
-
def forward(self, mixture):
|
| 152 |
-
"""
|
| 153 |
-
Args:
|
| 154 |
-
mixture: [M, T], M is batch size, T is #samples
|
| 155 |
-
Returns:
|
| 156 |
-
mixture_w: [M, N, K], where K = (T-L)/(L/2)+1 = 2T/L-1
|
| 157 |
-
"""
|
| 158 |
-
mixture_w = F.relu(self.conv1d_U(mixture)) # [M, N, K]
|
| 159 |
-
return mixture_w
|
| 160 |
-
|
| 161 |
-
|
| 162 |
-
class Decoder(nn.Module):
|
| 163 |
-
def __init__(self, N, L, audio_channels):
|
| 164 |
-
super(Decoder, self).__init__()
|
| 165 |
-
# Hyper-parameter
|
| 166 |
-
self.N, self.L = N, L
|
| 167 |
-
self.audio_channels = audio_channels
|
| 168 |
-
# Components
|
| 169 |
-
self.basis_signals = nn.Linear(N, audio_channels * L, bias=False)
|
| 170 |
-
|
| 171 |
-
def forward(self, mixture_w, est_mask):
|
| 172 |
-
"""
|
| 173 |
-
Args:
|
| 174 |
-
mixture_w: [M, N, K]
|
| 175 |
-
est_mask: [M, C, N, K]
|
| 176 |
-
Returns:
|
| 177 |
-
est_source: [M, C, T]
|
| 178 |
-
"""
|
| 179 |
-
# D = W * M
|
| 180 |
-
source_w = torch.unsqueeze(mixture_w, 1) * est_mask # [M, C, N, K]
|
| 181 |
-
source_w = torch.transpose(source_w, 2, 3) # [M, C, K, N]
|
| 182 |
-
# S = DV
|
| 183 |
-
est_source = self.basis_signals(source_w) # [M, C, K, ac * L]
|
| 184 |
-
m, c, k, _ = est_source.size()
|
| 185 |
-
est_source = est_source.view(m, c, k, self.audio_channels, -1).transpose(2, 3).contiguous()
|
| 186 |
-
est_source = overlap_and_add(est_source, self.L // 2) # M x C x ac x T
|
| 187 |
-
return est_source
|
| 188 |
-
|
| 189 |
-
|
| 190 |
-
class TemporalConvNet(nn.Module):
|
| 191 |
-
def __init__(self, N, B, H, P, X, R, C, norm_type="gLN", causal=False, mask_nonlinear='relu'):
|
| 192 |
-
"""
|
| 193 |
-
Args:
|
| 194 |
-
N: Number of filters in autoencoder
|
| 195 |
-
B: Number of channels in bottleneck 1 × 1-conv block
|
| 196 |
-
H: Number of channels in convolutional blocks
|
| 197 |
-
P: Kernel size in convolutional blocks
|
| 198 |
-
X: Number of convolutional blocks in each repeat
|
| 199 |
-
R: Number of repeats
|
| 200 |
-
C: Number of speakers
|
| 201 |
-
norm_type: BN, gLN, cLN
|
| 202 |
-
causal: causal or non-causal
|
| 203 |
-
mask_nonlinear: use which non-linear function to generate mask
|
| 204 |
-
"""
|
| 205 |
-
super(TemporalConvNet, self).__init__()
|
| 206 |
-
# Hyper-parameter
|
| 207 |
-
self.C = C
|
| 208 |
-
self.mask_nonlinear = mask_nonlinear
|
| 209 |
-
# Components
|
| 210 |
-
# [M, N, K] -> [M, N, K]
|
| 211 |
-
layer_norm = ChannelwiseLayerNorm(N)
|
| 212 |
-
# [M, N, K] -> [M, B, K]
|
| 213 |
-
bottleneck_conv1x1 = nn.Conv1d(N, B, 1, bias=False)
|
| 214 |
-
# [M, B, K] -> [M, B, K]
|
| 215 |
-
repeats = []
|
| 216 |
-
for r in range(R):
|
| 217 |
-
blocks = []
|
| 218 |
-
for x in range(X):
|
| 219 |
-
dilation = 2**x
|
| 220 |
-
padding = (P - 1) * dilation if causal else (P - 1) * dilation // 2
|
| 221 |
-
blocks += [
|
| 222 |
-
TemporalBlock(B,
|
| 223 |
-
H,
|
| 224 |
-
P,
|
| 225 |
-
stride=1,
|
| 226 |
-
padding=padding,
|
| 227 |
-
dilation=dilation,
|
| 228 |
-
norm_type=norm_type,
|
| 229 |
-
causal=causal)
|
| 230 |
-
]
|
| 231 |
-
repeats += [nn.Sequential(*blocks)]
|
| 232 |
-
temporal_conv_net = nn.Sequential(*repeats)
|
| 233 |
-
# [M, B, K] -> [M, C*N, K]
|
| 234 |
-
mask_conv1x1 = nn.Conv1d(B, C * N, 1, bias=False)
|
| 235 |
-
# Put together
|
| 236 |
-
self.network = nn.Sequential(layer_norm, bottleneck_conv1x1, temporal_conv_net,
|
| 237 |
-
mask_conv1x1)
|
| 238 |
-
|
| 239 |
-
def forward(self, mixture_w):
|
| 240 |
-
"""
|
| 241 |
-
Keep this API same with TasNet
|
| 242 |
-
Args:
|
| 243 |
-
mixture_w: [M, N, K], M is batch size
|
| 244 |
-
returns:
|
| 245 |
-
est_mask: [M, C, N, K]
|
| 246 |
-
"""
|
| 247 |
-
M, N, K = mixture_w.size()
|
| 248 |
-
score = self.network(mixture_w) # [M, N, K] -> [M, C*N, K]
|
| 249 |
-
score = score.view(M, self.C, N, K) # [M, C*N, K] -> [M, C, N, K]
|
| 250 |
-
if self.mask_nonlinear == 'softmax':
|
| 251 |
-
est_mask = F.softmax(score, dim=1)
|
| 252 |
-
elif self.mask_nonlinear == 'relu':
|
| 253 |
-
est_mask = F.relu(score)
|
| 254 |
-
else:
|
| 255 |
-
raise ValueError("Unsupported mask non-linear function")
|
| 256 |
-
return est_mask
|
| 257 |
-
|
| 258 |
-
|
| 259 |
-
class TemporalBlock(nn.Module):
|
| 260 |
-
def __init__(self,
|
| 261 |
-
in_channels,
|
| 262 |
-
out_channels,
|
| 263 |
-
kernel_size,
|
| 264 |
-
stride,
|
| 265 |
-
padding,
|
| 266 |
-
dilation,
|
| 267 |
-
norm_type="gLN",
|
| 268 |
-
causal=False):
|
| 269 |
-
super(TemporalBlock, self).__init__()
|
| 270 |
-
# [M, B, K] -> [M, H, K]
|
| 271 |
-
conv1x1 = nn.Conv1d(in_channels, out_channels, 1, bias=False)
|
| 272 |
-
prelu = nn.PReLU()
|
| 273 |
-
norm = chose_norm(norm_type, out_channels)
|
| 274 |
-
# [M, H, K] -> [M, B, K]
|
| 275 |
-
dsconv = DepthwiseSeparableConv(out_channels, in_channels, kernel_size, stride, padding,
|
| 276 |
-
dilation, norm_type, causal)
|
| 277 |
-
# Put together
|
| 278 |
-
self.net = nn.Sequential(conv1x1, prelu, norm, dsconv)
|
| 279 |
-
|
| 280 |
-
def forward(self, x):
|
| 281 |
-
"""
|
| 282 |
-
Args:
|
| 283 |
-
x: [M, B, K]
|
| 284 |
-
Returns:
|
| 285 |
-
[M, B, K]
|
| 286 |
-
"""
|
| 287 |
-
residual = x
|
| 288 |
-
out = self.net(x)
|
| 289 |
-
# TODO: when P = 3 here works fine, but when P = 2 maybe need to pad?
|
| 290 |
-
return out + residual # look like w/o F.relu is better than w/ F.relu
|
| 291 |
-
# return F.relu(out + residual)
|
| 292 |
-
|
| 293 |
-
|
| 294 |
-
class DepthwiseSeparableConv(nn.Module):
|
| 295 |
-
def __init__(self,
|
| 296 |
-
in_channels,
|
| 297 |
-
out_channels,
|
| 298 |
-
kernel_size,
|
| 299 |
-
stride,
|
| 300 |
-
padding,
|
| 301 |
-
dilation,
|
| 302 |
-
norm_type="gLN",
|
| 303 |
-
causal=False):
|
| 304 |
-
super(DepthwiseSeparableConv, self).__init__()
|
| 305 |
-
# Use `groups` option to implement depthwise convolution
|
| 306 |
-
# [M, H, K] -> [M, H, K]
|
| 307 |
-
depthwise_conv = nn.Conv1d(in_channels,
|
| 308 |
-
in_channels,
|
| 309 |
-
kernel_size,
|
| 310 |
-
stride=stride,
|
| 311 |
-
padding=padding,
|
| 312 |
-
dilation=dilation,
|
| 313 |
-
groups=in_channels,
|
| 314 |
-
bias=False)
|
| 315 |
-
if causal:
|
| 316 |
-
chomp = Chomp1d(padding)
|
| 317 |
-
prelu = nn.PReLU()
|
| 318 |
-
norm = chose_norm(norm_type, in_channels)
|
| 319 |
-
# [M, H, K] -> [M, B, K]
|
| 320 |
-
pointwise_conv = nn.Conv1d(in_channels, out_channels, 1, bias=False)
|
| 321 |
-
# Put together
|
| 322 |
-
if causal:
|
| 323 |
-
self.net = nn.Sequential(depthwise_conv, chomp, prelu, norm, pointwise_conv)
|
| 324 |
-
else:
|
| 325 |
-
self.net = nn.Sequential(depthwise_conv, prelu, norm, pointwise_conv)
|
| 326 |
-
|
| 327 |
-
def forward(self, x):
|
| 328 |
-
"""
|
| 329 |
-
Args:
|
| 330 |
-
x: [M, H, K]
|
| 331 |
-
Returns:
|
| 332 |
-
result: [M, B, K]
|
| 333 |
-
"""
|
| 334 |
-
return self.net(x)
|
| 335 |
-
|
| 336 |
-
|
| 337 |
-
class Chomp1d(nn.Module):
|
| 338 |
-
"""To ensure the output length is the same as the input.
|
| 339 |
-
"""
|
| 340 |
-
def __init__(self, chomp_size):
|
| 341 |
-
super(Chomp1d, self).__init__()
|
| 342 |
-
self.chomp_size = chomp_size
|
| 343 |
-
|
| 344 |
-
def forward(self, x):
|
| 345 |
-
"""
|
| 346 |
-
Args:
|
| 347 |
-
x: [M, H, Kpad]
|
| 348 |
-
Returns:
|
| 349 |
-
[M, H, K]
|
| 350 |
-
"""
|
| 351 |
-
return x[:, :, :-self.chomp_size].contiguous()
|
| 352 |
-
|
| 353 |
-
|
| 354 |
-
def chose_norm(norm_type, channel_size):
|
| 355 |
-
"""The input of normlization will be (M, C, K), where M is batch size,
|
| 356 |
-
C is channel size and K is sequence length.
|
| 357 |
-
"""
|
| 358 |
-
if norm_type == "gLN":
|
| 359 |
-
return GlobalLayerNorm(channel_size)
|
| 360 |
-
elif norm_type == "cLN":
|
| 361 |
-
return ChannelwiseLayerNorm(channel_size)
|
| 362 |
-
elif norm_type == "id":
|
| 363 |
-
return nn.Identity()
|
| 364 |
-
else: # norm_type == "BN":
|
| 365 |
-
# Given input (M, C, K), nn.BatchNorm1d(C) will accumulate statics
|
| 366 |
-
# along M and K, so this BN usage is right.
|
| 367 |
-
return nn.BatchNorm1d(channel_size)
|
| 368 |
-
|
| 369 |
-
|
| 370 |
-
# TODO: Use nn.LayerNorm to impl cLN to speed up
|
| 371 |
-
class ChannelwiseLayerNorm(nn.Module):
|
| 372 |
-
"""Channel-wise Layer Normalization (cLN)"""
|
| 373 |
-
def __init__(self, channel_size):
|
| 374 |
-
super(ChannelwiseLayerNorm, self).__init__()
|
| 375 |
-
self.gamma = nn.Parameter(torch.Tensor(1, channel_size, 1)) # [1, N, 1]
|
| 376 |
-
self.beta = nn.Parameter(torch.Tensor(1, channel_size, 1)) # [1, N, 1]
|
| 377 |
-
self.reset_parameters()
|
| 378 |
-
|
| 379 |
-
def reset_parameters(self):
|
| 380 |
-
self.gamma.data.fill_(1)
|
| 381 |
-
self.beta.data.zero_()
|
| 382 |
-
|
| 383 |
-
def forward(self, y):
|
| 384 |
-
"""
|
| 385 |
-
Args:
|
| 386 |
-
y: [M, N, K], M is batch size, N is channel size, K is length
|
| 387 |
-
Returns:
|
| 388 |
-
cLN_y: [M, N, K]
|
| 389 |
-
"""
|
| 390 |
-
mean = torch.mean(y, dim=1, keepdim=True) # [M, 1, K]
|
| 391 |
-
var = torch.var(y, dim=1, keepdim=True, unbiased=False) # [M, 1, K]
|
| 392 |
-
cLN_y = self.gamma * (y - mean) / torch.pow(var + EPS, 0.5) + self.beta
|
| 393 |
-
return cLN_y
|
| 394 |
-
|
| 395 |
-
|
| 396 |
-
class GlobalLayerNorm(nn.Module):
|
| 397 |
-
"""Global Layer Normalization (gLN)"""
|
| 398 |
-
def __init__(self, channel_size):
|
| 399 |
-
super(GlobalLayerNorm, self).__init__()
|
| 400 |
-
self.gamma = nn.Parameter(torch.Tensor(1, channel_size, 1)) # [1, N, 1]
|
| 401 |
-
self.beta = nn.Parameter(torch.Tensor(1, channel_size, 1)) # [1, N, 1]
|
| 402 |
-
self.reset_parameters()
|
| 403 |
-
|
| 404 |
-
def reset_parameters(self):
|
| 405 |
-
self.gamma.data.fill_(1)
|
| 406 |
-
self.beta.data.zero_()
|
| 407 |
-
|
| 408 |
-
def forward(self, y):
|
| 409 |
-
"""
|
| 410 |
-
Args:
|
| 411 |
-
y: [M, N, K], M is batch size, N is channel size, K is length
|
| 412 |
-
Returns:
|
| 413 |
-
gLN_y: [M, N, K]
|
| 414 |
-
"""
|
| 415 |
-
# TODO: in torch 1.0, torch.mean() support dim list
|
| 416 |
-
mean = y.mean(dim=1, keepdim=True).mean(dim=2, keepdim=True) # [M, 1, 1]
|
| 417 |
-
var = (torch.pow(y - mean, 2)).mean(dim=1, keepdim=True).mean(dim=2, keepdim=True)
|
| 418 |
-
gLN_y = self.gamma * (y - mean) / torch.pow(var + EPS, 0.5) + self.beta
|
| 419 |
-
return gLN_y
|
| 420 |
-
|
| 421 |
-
|
| 422 |
-
if __name__ == "__main__":
|
| 423 |
-
torch.manual_seed(123)
|
| 424 |
-
M, N, L, T = 2, 3, 4, 12
|
| 425 |
-
K = 2 * T // L - 1
|
| 426 |
-
B, H, P, X, R, C, norm_type, causal = 2, 3, 3, 3, 2, 2, "gLN", False
|
| 427 |
-
mixture = torch.randint(3, (M, T))
|
| 428 |
-
# test Encoder
|
| 429 |
-
encoder = Encoder(L, N)
|
| 430 |
-
encoder.conv1d_U.weight.data = torch.randint(2, encoder.conv1d_U.weight.size())
|
| 431 |
-
mixture_w = encoder(mixture)
|
| 432 |
-
print('mixture', mixture)
|
| 433 |
-
print('U', encoder.conv1d_U.weight)
|
| 434 |
-
print('mixture_w', mixture_w)
|
| 435 |
-
print('mixture_w size', mixture_w.size())
|
| 436 |
-
|
| 437 |
-
# test TemporalConvNet
|
| 438 |
-
separator = TemporalConvNet(N, B, H, P, X, R, C, norm_type=norm_type, causal=causal)
|
| 439 |
-
est_mask = separator(mixture_w)
|
| 440 |
-
print('est_mask', est_mask)
|
| 441 |
-
|
| 442 |
-
# test Decoder
|
| 443 |
-
decoder = Decoder(N, L)
|
| 444 |
-
est_mask = torch.randint(2, (B, K, C, N))
|
| 445 |
-
est_source = decoder(mixture_w, est_mask)
|
| 446 |
-
print('est_source', est_source)
|
| 447 |
-
|
| 448 |
-
# test Conv-TasNet
|
| 449 |
-
conv_tasnet = ConvTasNet(N, L, B, H, P, X, R, C, norm_type=norm_type)
|
| 450 |
-
est_source = conv_tasnet(mixture)
|
| 451 |
-
print('est_source', est_source)
|
| 452 |
-
print('est_source size', est_source.size())
|
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|
spaces/CVPR/CVPR2022_papers/paper_list.py
DELETED
|
@@ -1,102 +0,0 @@
|
|
| 1 |
-
from __future__ import annotations
|
| 2 |
-
|
| 3 |
-
import pandas as pd
|
| 4 |
-
|
| 5 |
-
|
| 6 |
-
class PaperList:
|
| 7 |
-
def __init__(self):
|
| 8 |
-
self.table = pd.read_csv('papers.csv')
|
| 9 |
-
self._preprcess_table()
|
| 10 |
-
|
| 11 |
-
self.table_header = '''
|
| 12 |
-
<tr>
|
| 13 |
-
<td width="50%">Paper</td>
|
| 14 |
-
<td width="22%">Authors</td>
|
| 15 |
-
<td width="4%">pdf</td>
|
| 16 |
-
<td width="4%">Supp</td>
|
| 17 |
-
<td width="4%">arXiv</td>
|
| 18 |
-
<td width="4%">GitHub</td>
|
| 19 |
-
<td width="4%">HF Spaces</td>
|
| 20 |
-
<td width="4%">HF Models</td>
|
| 21 |
-
<td width="4%">HF Datasets</td>
|
| 22 |
-
</tr>'''
|
| 23 |
-
|
| 24 |
-
def _preprcess_table(self) -> None:
|
| 25 |
-
self.table['title_lowercase'] = self.table.title.str.lower()
|
| 26 |
-
|
| 27 |
-
rows = []
|
| 28 |
-
for row in self.table.itertuples():
|
| 29 |
-
paper = f'<a href="{row.url}" target="_blank">{row.title}</a>'
|
| 30 |
-
pdf = f'<a href="{row.pdf}" target="_blank">pdf</a>'
|
| 31 |
-
supp = f'<a href="{row.supp}" target="_blank">supp</a>' if isinstance(
|
| 32 |
-
row.supp, str) else ''
|
| 33 |
-
arxiv = f'<a href="{row.arxiv}" target="_blank">arXiv</a>' if isinstance(
|
| 34 |
-
row.arxiv, str) else ''
|
| 35 |
-
github = f'<a href="{row.github}" target="_blank">GitHub</a>' if isinstance(
|
| 36 |
-
row.github, str) else ''
|
| 37 |
-
hf_space = f'<a href="{row.hf_space}" target="_blank">Space</a>' if isinstance(
|
| 38 |
-
row.hf_space, str) else ''
|
| 39 |
-
hf_model = f'<a href="{row.hf_model}" target="_blank">Model</a>' if isinstance(
|
| 40 |
-
row.hf_model, str) else ''
|
| 41 |
-
hf_dataset = f'<a href="{row.hf_dataset}" target="_blank">Dataset</a>' if isinstance(
|
| 42 |
-
row.hf_dataset, str) else ''
|
| 43 |
-
row = f'''
|
| 44 |
-
<tr>
|
| 45 |
-
<td>{paper}</td>
|
| 46 |
-
<td>{row.authors}</td>
|
| 47 |
-
<td>{pdf}</td>
|
| 48 |
-
<td>{supp}</td>
|
| 49 |
-
<td>{arxiv}</td>
|
| 50 |
-
<td>{github}</td>
|
| 51 |
-
<td>{hf_space}</td>
|
| 52 |
-
<td>{hf_model}</td>
|
| 53 |
-
<td>{hf_dataset}</td>
|
| 54 |
-
</tr>'''
|
| 55 |
-
rows.append(row)
|
| 56 |
-
self.table['html_table_content'] = rows
|
| 57 |
-
|
| 58 |
-
def render(self, search_query: str, case_sensitive: bool,
|
| 59 |
-
filter_names: list[str]) -> tuple[int, str]:
|
| 60 |
-
df = self.table
|
| 61 |
-
if search_query:
|
| 62 |
-
if case_sensitive:
|
| 63 |
-
df = df[df.title.str.contains(search_query)]
|
| 64 |
-
else:
|
| 65 |
-
df = df[df.title_lowercase.str.contains(search_query.lower())]
|
| 66 |
-
has_supp = 'Supp' in filter_names
|
| 67 |
-
has_arxiv = 'arXiv' in filter_names
|
| 68 |
-
has_github = 'GitHub' in filter_names
|
| 69 |
-
has_hf_space = 'HF Space' in filter_names
|
| 70 |
-
has_hf_model = 'HF Model' in filter_names
|
| 71 |
-
has_hf_dataset = 'HF Dataset' in filter_names
|
| 72 |
-
df = self.filter_table(df, has_supp, has_arxiv, has_github,
|
| 73 |
-
has_hf_space, has_hf_model, has_hf_dataset)
|
| 74 |
-
return len(df), self.to_html(df, self.table_header)
|
| 75 |
-
|
| 76 |
-
@staticmethod
|
| 77 |
-
def filter_table(df: pd.DataFrame, has_supp: bool, has_arxiv: bool,
|
| 78 |
-
has_github: bool, has_hf_space: bool, has_hf_model: bool,
|
| 79 |
-
has_hf_dataset: bool) -> pd.DataFrame:
|
| 80 |
-
if has_supp:
|
| 81 |
-
df = df[~df.supp.isna()]
|
| 82 |
-
if has_arxiv:
|
| 83 |
-
df = df[~df.arxiv.isna()]
|
| 84 |
-
if has_github:
|
| 85 |
-
df = df[~df.github.isna()]
|
| 86 |
-
if has_hf_space:
|
| 87 |
-
df = df[~df.hf_space.isna()]
|
| 88 |
-
if has_hf_model:
|
| 89 |
-
df = df[~df.hf_model.isna()]
|
| 90 |
-
if has_hf_dataset:
|
| 91 |
-
df = df[~df.hf_dataset.isna()]
|
| 92 |
-
return df
|
| 93 |
-
|
| 94 |
-
@staticmethod
|
| 95 |
-
def to_html(df: pd.DataFrame, table_header: str) -> str:
|
| 96 |
-
table_data = ''.join(df.html_table_content)
|
| 97 |
-
html = f'''
|
| 98 |
-
<table>
|
| 99 |
-
{table_header}
|
| 100 |
-
{table_data}
|
| 101 |
-
</table>'''
|
| 102 |
-
return html
|
|
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|
|
spaces/CVPR/LIVE/pybind11/tests/test_buffers.cpp
DELETED
|
@@ -1,195 +0,0 @@
|
|
| 1 |
-
/*
|
| 2 |
-
tests/test_buffers.cpp -- supporting Pythons' buffer protocol
|
| 3 |
-
|
| 4 |
-
Copyright (c) 2016 Wenzel Jakob <[email protected]>
|
| 5 |
-
|
| 6 |
-
All rights reserved. Use of this source code is governed by a
|
| 7 |
-
BSD-style license that can be found in the LICENSE file.
|
| 8 |
-
*/
|
| 9 |
-
|
| 10 |
-
#include "pybind11_tests.h"
|
| 11 |
-
#include "constructor_stats.h"
|
| 12 |
-
|
| 13 |
-
TEST_SUBMODULE(buffers, m) {
|
| 14 |
-
// test_from_python / test_to_python:
|
| 15 |
-
class Matrix {
|
| 16 |
-
public:
|
| 17 |
-
Matrix(ssize_t rows, ssize_t cols) : m_rows(rows), m_cols(cols) {
|
| 18 |
-
print_created(this, std::to_string(m_rows) + "x" + std::to_string(m_cols) + " matrix");
|
| 19 |
-
m_data = new float[(size_t) (rows*cols)];
|
| 20 |
-
memset(m_data, 0, sizeof(float) * (size_t) (rows * cols));
|
| 21 |
-
}
|
| 22 |
-
|
| 23 |
-
Matrix(const Matrix &s) : m_rows(s.m_rows), m_cols(s.m_cols) {
|
| 24 |
-
print_copy_created(this, std::to_string(m_rows) + "x" + std::to_string(m_cols) + " matrix");
|
| 25 |
-
m_data = new float[(size_t) (m_rows * m_cols)];
|
| 26 |
-
memcpy(m_data, s.m_data, sizeof(float) * (size_t) (m_rows * m_cols));
|
| 27 |
-
}
|
| 28 |
-
|
| 29 |
-
Matrix(Matrix &&s) : m_rows(s.m_rows), m_cols(s.m_cols), m_data(s.m_data) {
|
| 30 |
-
print_move_created(this);
|
| 31 |
-
s.m_rows = 0;
|
| 32 |
-
s.m_cols = 0;
|
| 33 |
-
s.m_data = nullptr;
|
| 34 |
-
}
|
| 35 |
-
|
| 36 |
-
~Matrix() {
|
| 37 |
-
print_destroyed(this, std::to_string(m_rows) + "x" + std::to_string(m_cols) + " matrix");
|
| 38 |
-
delete[] m_data;
|
| 39 |
-
}
|
| 40 |
-
|
| 41 |
-
Matrix &operator=(const Matrix &s) {
|
| 42 |
-
print_copy_assigned(this, std::to_string(m_rows) + "x" + std::to_string(m_cols) + " matrix");
|
| 43 |
-
delete[] m_data;
|
| 44 |
-
m_rows = s.m_rows;
|
| 45 |
-
m_cols = s.m_cols;
|
| 46 |
-
m_data = new float[(size_t) (m_rows * m_cols)];
|
| 47 |
-
memcpy(m_data, s.m_data, sizeof(float) * (size_t) (m_rows * m_cols));
|
| 48 |
-
return *this;
|
| 49 |
-
}
|
| 50 |
-
|
| 51 |
-
Matrix &operator=(Matrix &&s) {
|
| 52 |
-
print_move_assigned(this, std::to_string(m_rows) + "x" + std::to_string(m_cols) + " matrix");
|
| 53 |
-
if (&s != this) {
|
| 54 |
-
delete[] m_data;
|
| 55 |
-
m_rows = s.m_rows; m_cols = s.m_cols; m_data = s.m_data;
|
| 56 |
-
s.m_rows = 0; s.m_cols = 0; s.m_data = nullptr;
|
| 57 |
-
}
|
| 58 |
-
return *this;
|
| 59 |
-
}
|
| 60 |
-
|
| 61 |
-
float operator()(ssize_t i, ssize_t j) const {
|
| 62 |
-
return m_data[(size_t) (i*m_cols + j)];
|
| 63 |
-
}
|
| 64 |
-
|
| 65 |
-
float &operator()(ssize_t i, ssize_t j) {
|
| 66 |
-
return m_data[(size_t) (i*m_cols + j)];
|
| 67 |
-
}
|
| 68 |
-
|
| 69 |
-
float *data() { return m_data; }
|
| 70 |
-
|
| 71 |
-
ssize_t rows() const { return m_rows; }
|
| 72 |
-
ssize_t cols() const { return m_cols; }
|
| 73 |
-
private:
|
| 74 |
-
ssize_t m_rows;
|
| 75 |
-
ssize_t m_cols;
|
| 76 |
-
float *m_data;
|
| 77 |
-
};
|
| 78 |
-
py::class_<Matrix>(m, "Matrix", py::buffer_protocol())
|
| 79 |
-
.def(py::init<ssize_t, ssize_t>())
|
| 80 |
-
/// Construct from a buffer
|
| 81 |
-
.def(py::init([](py::buffer const b) {
|
| 82 |
-
py::buffer_info info = b.request();
|
| 83 |
-
if (info.format != py::format_descriptor<float>::format() || info.ndim != 2)
|
| 84 |
-
throw std::runtime_error("Incompatible buffer format!");
|
| 85 |
-
|
| 86 |
-
auto v = new Matrix(info.shape[0], info.shape[1]);
|
| 87 |
-
memcpy(v->data(), info.ptr, sizeof(float) * (size_t) (v->rows() * v->cols()));
|
| 88 |
-
return v;
|
| 89 |
-
}))
|
| 90 |
-
|
| 91 |
-
.def("rows", &Matrix::rows)
|
| 92 |
-
.def("cols", &Matrix::cols)
|
| 93 |
-
|
| 94 |
-
/// Bare bones interface
|
| 95 |
-
.def("__getitem__", [](const Matrix &m, std::pair<ssize_t, ssize_t> i) {
|
| 96 |
-
if (i.first >= m.rows() || i.second >= m.cols())
|
| 97 |
-
throw py::index_error();
|
| 98 |
-
return m(i.first, i.second);
|
| 99 |
-
})
|
| 100 |
-
.def("__setitem__", [](Matrix &m, std::pair<ssize_t, ssize_t> i, float v) {
|
| 101 |
-
if (i.first >= m.rows() || i.second >= m.cols())
|
| 102 |
-
throw py::index_error();
|
| 103 |
-
m(i.first, i.second) = v;
|
| 104 |
-
})
|
| 105 |
-
/// Provide buffer access
|
| 106 |
-
.def_buffer([](Matrix &m) -> py::buffer_info {
|
| 107 |
-
return py::buffer_info(
|
| 108 |
-
m.data(), /* Pointer to buffer */
|
| 109 |
-
{ m.rows(), m.cols() }, /* Buffer dimensions */
|
| 110 |
-
{ sizeof(float) * size_t(m.cols()), /* Strides (in bytes) for each index */
|
| 111 |
-
sizeof(float) }
|
| 112 |
-
);
|
| 113 |
-
})
|
| 114 |
-
;
|
| 115 |
-
|
| 116 |
-
|
| 117 |
-
// test_inherited_protocol
|
| 118 |
-
class SquareMatrix : public Matrix {
|
| 119 |
-
public:
|
| 120 |
-
SquareMatrix(ssize_t n) : Matrix(n, n) { }
|
| 121 |
-
};
|
| 122 |
-
// Derived classes inherit the buffer protocol and the buffer access function
|
| 123 |
-
py::class_<SquareMatrix, Matrix>(m, "SquareMatrix")
|
| 124 |
-
.def(py::init<ssize_t>());
|
| 125 |
-
|
| 126 |
-
|
| 127 |
-
// test_pointer_to_member_fn
|
| 128 |
-
// Tests that passing a pointer to member to the base class works in
|
| 129 |
-
// the derived class.
|
| 130 |
-
struct Buffer {
|
| 131 |
-
int32_t value = 0;
|
| 132 |
-
|
| 133 |
-
py::buffer_info get_buffer_info() {
|
| 134 |
-
return py::buffer_info(&value, sizeof(value),
|
| 135 |
-
py::format_descriptor<int32_t>::format(), 1);
|
| 136 |
-
}
|
| 137 |
-
};
|
| 138 |
-
py::class_<Buffer>(m, "Buffer", py::buffer_protocol())
|
| 139 |
-
.def(py::init<>())
|
| 140 |
-
.def_readwrite("value", &Buffer::value)
|
| 141 |
-
.def_buffer(&Buffer::get_buffer_info);
|
| 142 |
-
|
| 143 |
-
|
| 144 |
-
class ConstBuffer {
|
| 145 |
-
std::unique_ptr<int32_t> value;
|
| 146 |
-
|
| 147 |
-
public:
|
| 148 |
-
int32_t get_value() const { return *value; }
|
| 149 |
-
void set_value(int32_t v) { *value = v; }
|
| 150 |
-
|
| 151 |
-
py::buffer_info get_buffer_info() const {
|
| 152 |
-
return py::buffer_info(value.get(), sizeof(*value),
|
| 153 |
-
py::format_descriptor<int32_t>::format(), 1);
|
| 154 |
-
}
|
| 155 |
-
|
| 156 |
-
ConstBuffer() : value(new int32_t{0}) { };
|
| 157 |
-
};
|
| 158 |
-
py::class_<ConstBuffer>(m, "ConstBuffer", py::buffer_protocol())
|
| 159 |
-
.def(py::init<>())
|
| 160 |
-
.def_property("value", &ConstBuffer::get_value, &ConstBuffer::set_value)
|
| 161 |
-
.def_buffer(&ConstBuffer::get_buffer_info);
|
| 162 |
-
|
| 163 |
-
struct DerivedBuffer : public Buffer { };
|
| 164 |
-
py::class_<DerivedBuffer>(m, "DerivedBuffer", py::buffer_protocol())
|
| 165 |
-
.def(py::init<>())
|
| 166 |
-
.def_readwrite("value", (int32_t DerivedBuffer::*) &DerivedBuffer::value)
|
| 167 |
-
.def_buffer(&DerivedBuffer::get_buffer_info);
|
| 168 |
-
|
| 169 |
-
struct BufferReadOnly {
|
| 170 |
-
const uint8_t value = 0;
|
| 171 |
-
BufferReadOnly(uint8_t value): value(value) {}
|
| 172 |
-
|
| 173 |
-
py::buffer_info get_buffer_info() {
|
| 174 |
-
return py::buffer_info(&value, 1);
|
| 175 |
-
}
|
| 176 |
-
};
|
| 177 |
-
py::class_<BufferReadOnly>(m, "BufferReadOnly", py::buffer_protocol())
|
| 178 |
-
.def(py::init<uint8_t>())
|
| 179 |
-
.def_buffer(&BufferReadOnly::get_buffer_info);
|
| 180 |
-
|
| 181 |
-
struct BufferReadOnlySelect {
|
| 182 |
-
uint8_t value = 0;
|
| 183 |
-
bool readonly = false;
|
| 184 |
-
|
| 185 |
-
py::buffer_info get_buffer_info() {
|
| 186 |
-
return py::buffer_info(&value, 1, readonly);
|
| 187 |
-
}
|
| 188 |
-
};
|
| 189 |
-
py::class_<BufferReadOnlySelect>(m, "BufferReadOnlySelect", py::buffer_protocol())
|
| 190 |
-
.def(py::init<>())
|
| 191 |
-
.def_readwrite("value", &BufferReadOnlySelect::value)
|
| 192 |
-
.def_readwrite("readonly", &BufferReadOnlySelect::readonly)
|
| 193 |
-
.def_buffer(&BufferReadOnlySelect::get_buffer_info);
|
| 194 |
-
|
| 195 |
-
}
|
|
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|
spaces/CVPR/LIVE/pydiffvg/device.py
DELETED
|
@@ -1,25 +0,0 @@
|
|
| 1 |
-
import torch
|
| 2 |
-
|
| 3 |
-
use_gpu = torch.cuda.is_available()
|
| 4 |
-
device = torch.device('cuda') if use_gpu else torch.device('cpu')
|
| 5 |
-
|
| 6 |
-
def set_use_gpu(v):
|
| 7 |
-
global use_gpu
|
| 8 |
-
global device
|
| 9 |
-
use_gpu = v
|
| 10 |
-
if not use_gpu:
|
| 11 |
-
device = torch.device('cpu')
|
| 12 |
-
|
| 13 |
-
def get_use_gpu():
|
| 14 |
-
global use_gpu
|
| 15 |
-
return use_gpu
|
| 16 |
-
|
| 17 |
-
def set_device(d):
|
| 18 |
-
global device
|
| 19 |
-
global use_gpu
|
| 20 |
-
device = d
|
| 21 |
-
use_gpu = device.type == 'cuda'
|
| 22 |
-
|
| 23 |
-
def get_device():
|
| 24 |
-
global device
|
| 25 |
-
return device
|
|
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|
spaces/CVPR/LIVE/thrust/thrust/system/omp/detail/uninitialized_fill.h
DELETED
|
@@ -1,23 +0,0 @@
|
|
| 1 |
-
/*
|
| 2 |
-
* Copyright 2008-2013 NVIDIA Corporation
|
| 3 |
-
*
|
| 4 |
-
* Licensed under the Apache License, Version 2.0 (the "License");
|
| 5 |
-
* you may not use this file except in compliance with the License.
|
| 6 |
-
* You may obtain a copy of the License at
|
| 7 |
-
*
|
| 8 |
-
* http://www.apache.org/licenses/LICENSE-2.0
|
| 9 |
-
*
|
| 10 |
-
* Unless required by applicable law or agreed to in writing, software
|
| 11 |
-
* distributed under the License is distributed on an "AS IS" BASIS,
|
| 12 |
-
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
| 13 |
-
* See the License for the specific language governing permissions and
|
| 14 |
-
* limitations under the License.
|
| 15 |
-
*/
|
| 16 |
-
|
| 17 |
-
#pragma once
|
| 18 |
-
|
| 19 |
-
#include <thrust/detail/config.h>
|
| 20 |
-
|
| 21 |
-
// this system inherits uninitialized_fill
|
| 22 |
-
#include <thrust/system/cpp/detail/uninitialized_fill.h>
|
| 23 |
-
|
|
|
|
|
|
|
|
|
|
|
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|
|
spaces/CVPR/WALT/mmdet/models/roi_heads/mask_heads/scnet_mask_head.py
DELETED
|
@@ -1,27 +0,0 @@
|
|
| 1 |
-
from mmdet.models.builder import HEADS
|
| 2 |
-
from mmdet.models.utils import ResLayer, SimplifiedBasicBlock
|
| 3 |
-
from .fcn_mask_head import FCNMaskHead
|
| 4 |
-
|
| 5 |
-
|
| 6 |
-
@HEADS.register_module()
|
| 7 |
-
class SCNetMaskHead(FCNMaskHead):
|
| 8 |
-
"""Mask head for `SCNet <https://arxiv.org/abs/2012.10150>`_.
|
| 9 |
-
|
| 10 |
-
Args:
|
| 11 |
-
conv_to_res (bool, optional): if True, change the conv layers to
|
| 12 |
-
``SimplifiedBasicBlock``.
|
| 13 |
-
"""
|
| 14 |
-
|
| 15 |
-
def __init__(self, conv_to_res=True, **kwargs):
|
| 16 |
-
super(SCNetMaskHead, self).__init__(**kwargs)
|
| 17 |
-
self.conv_to_res = conv_to_res
|
| 18 |
-
if conv_to_res:
|
| 19 |
-
assert self.conv_kernel_size == 3
|
| 20 |
-
self.num_res_blocks = self.num_convs // 2
|
| 21 |
-
self.convs = ResLayer(
|
| 22 |
-
SimplifiedBasicBlock,
|
| 23 |
-
self.in_channels,
|
| 24 |
-
self.conv_out_channels,
|
| 25 |
-
self.num_res_blocks,
|
| 26 |
-
conv_cfg=self.conv_cfg,
|
| 27 |
-
norm_cfg=self.norm_cfg)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
spaces/CognitiveLabs/Research-Assistant/agent/research_agent.py
DELETED
|
@@ -1,109 +0,0 @@
|
|
| 1 |
-
import json
|
| 2 |
-
from actions.duck_search import duckduckgo_search
|
| 3 |
-
from processing.text import read_txt_files
|
| 4 |
-
from agent.llm_utils import llm_response, llm_stream_response
|
| 5 |
-
from config import Config
|
| 6 |
-
from agent import prompts
|
| 7 |
-
import os
|
| 8 |
-
import string
|
| 9 |
-
|
| 10 |
-
CFG = Config()
|
| 11 |
-
|
| 12 |
-
|
| 13 |
-
class ResearchAgent:
|
| 14 |
-
def __init__(self, question, agent):
|
| 15 |
-
""" Initializes the research assistant with the given question.
|
| 16 |
-
Args: question (str): The question to research
|
| 17 |
-
Returns: None
|
| 18 |
-
"""
|
| 19 |
-
|
| 20 |
-
self.question = question
|
| 21 |
-
self.agent = agent
|
| 22 |
-
self.visited_urls = set()
|
| 23 |
-
self.search_summary = ""
|
| 24 |
-
self.directory_name = ''.join(c for c in question if c.isascii() and c not in string.punctuation)[:100]
|
| 25 |
-
self.dir_path = os.path.dirname(f"./outputs/{self.directory_name}/")
|
| 26 |
-
|
| 27 |
-
def call_agent(self, action):
|
| 28 |
-
messages = [{
|
| 29 |
-
"role": "system",
|
| 30 |
-
"content": prompts.generate_agent_role_prompt(self.agent),
|
| 31 |
-
}, {
|
| 32 |
-
"role": "user",
|
| 33 |
-
"content": action,
|
| 34 |
-
}]
|
| 35 |
-
return llm_response(
|
| 36 |
-
model=CFG.fast_llm_model,
|
| 37 |
-
messages=messages,
|
| 38 |
-
)
|
| 39 |
-
|
| 40 |
-
def call_agent_stream(self, action):
|
| 41 |
-
messages = [{
|
| 42 |
-
"role": "system",
|
| 43 |
-
"content": prompts.generate_agent_role_prompt(self.agent),
|
| 44 |
-
}, {
|
| 45 |
-
"role": "user",
|
| 46 |
-
"content": action,
|
| 47 |
-
}]
|
| 48 |
-
yield from llm_stream_response(
|
| 49 |
-
model=CFG.fast_llm_model,
|
| 50 |
-
messages=messages
|
| 51 |
-
)
|
| 52 |
-
|
| 53 |
-
def create_search_queries(self):
|
| 54 |
-
""" Creates the search queries for the given question.
|
| 55 |
-
Args: None
|
| 56 |
-
Returns: list[str]: The search queries for the given question
|
| 57 |
-
"""
|
| 58 |
-
result = self.call_agent(prompts.generate_search_queries_prompt(self.question))
|
| 59 |
-
return json.loads(result)
|
| 60 |
-
|
| 61 |
-
def search_single_query(self, query):
|
| 62 |
-
""" Runs the async search for the given query.
|
| 63 |
-
Args: query (str): The query to run the async search for
|
| 64 |
-
Returns: list[str]: The async search for the given query
|
| 65 |
-
"""
|
| 66 |
-
return duckduckgo_search(query, max_search_result=3)
|
| 67 |
-
|
| 68 |
-
def run_search_summary(self, query):
|
| 69 |
-
""" Runs the search summary for the given query.
|
| 70 |
-
Args: query (str): The query to run the search summary for
|
| 71 |
-
Returns: str: The search summary for the given query
|
| 72 |
-
"""
|
| 73 |
-
responses = self.search_single_query(query)
|
| 74 |
-
|
| 75 |
-
print(f"Searching for {query}")
|
| 76 |
-
query = hash(query)
|
| 77 |
-
file_path = f"./outputs/{self.directory_name}/research-{query}.txt"
|
| 78 |
-
os.makedirs(os.path.dirname(file_path), exist_ok=True)
|
| 79 |
-
with open(file_path, "w") as f:
|
| 80 |
-
json.dump(responses, f)
|
| 81 |
-
print(f"Saved {query} to {file_path}")
|
| 82 |
-
return responses
|
| 83 |
-
|
| 84 |
-
def search_online(self):
|
| 85 |
-
""" Conducts the search for the given question.
|
| 86 |
-
Args: None
|
| 87 |
-
Returns: str: The search results for the given question
|
| 88 |
-
"""
|
| 89 |
-
|
| 90 |
-
self.search_summary = read_txt_files(self.dir_path) if os.path.isdir(self.dir_path) else ""
|
| 91 |
-
|
| 92 |
-
if not self.search_summary:
|
| 93 |
-
search_queries = self.create_search_queries()
|
| 94 |
-
for _, query in search_queries.items():
|
| 95 |
-
search_result = self.run_search_summary(query)
|
| 96 |
-
self.search_summary += f"=Query=:\n{query}\n=Search Result=:\n{search_result}\n================\n"
|
| 97 |
-
|
| 98 |
-
return self.search_summary
|
| 99 |
-
|
| 100 |
-
def write_report(self, report_type):
|
| 101 |
-
""" Writes the report for the given question.
|
| 102 |
-
Args: None
|
| 103 |
-
Returns: str: The report for the given question
|
| 104 |
-
"""
|
| 105 |
-
# yield "Searching online..."
|
| 106 |
-
|
| 107 |
-
report_type_func = prompts.get_report_by_type(report_type)
|
| 108 |
-
|
| 109 |
-
yield from self.call_agent_stream(report_type_func(self.question, self.search_online()))
|
|
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|
spaces/CrucibleAI/ControlNetMediaPipeFaceSD21/ldm/modules/midas/midas/transforms.py
DELETED
|
@@ -1,234 +0,0 @@
|
|
| 1 |
-
import numpy as np
|
| 2 |
-
import cv2
|
| 3 |
-
import math
|
| 4 |
-
|
| 5 |
-
|
| 6 |
-
def apply_min_size(sample, size, image_interpolation_method=cv2.INTER_AREA):
|
| 7 |
-
"""Rezise the sample to ensure the given size. Keeps aspect ratio.
|
| 8 |
-
|
| 9 |
-
Args:
|
| 10 |
-
sample (dict): sample
|
| 11 |
-
size (tuple): image size
|
| 12 |
-
|
| 13 |
-
Returns:
|
| 14 |
-
tuple: new size
|
| 15 |
-
"""
|
| 16 |
-
shape = list(sample["disparity"].shape)
|
| 17 |
-
|
| 18 |
-
if shape[0] >= size[0] and shape[1] >= size[1]:
|
| 19 |
-
return sample
|
| 20 |
-
|
| 21 |
-
scale = [0, 0]
|
| 22 |
-
scale[0] = size[0] / shape[0]
|
| 23 |
-
scale[1] = size[1] / shape[1]
|
| 24 |
-
|
| 25 |
-
scale = max(scale)
|
| 26 |
-
|
| 27 |
-
shape[0] = math.ceil(scale * shape[0])
|
| 28 |
-
shape[1] = math.ceil(scale * shape[1])
|
| 29 |
-
|
| 30 |
-
# resize
|
| 31 |
-
sample["image"] = cv2.resize(
|
| 32 |
-
sample["image"], tuple(shape[::-1]), interpolation=image_interpolation_method
|
| 33 |
-
)
|
| 34 |
-
|
| 35 |
-
sample["disparity"] = cv2.resize(
|
| 36 |
-
sample["disparity"], tuple(shape[::-1]), interpolation=cv2.INTER_NEAREST
|
| 37 |
-
)
|
| 38 |
-
sample["mask"] = cv2.resize(
|
| 39 |
-
sample["mask"].astype(np.float32),
|
| 40 |
-
tuple(shape[::-1]),
|
| 41 |
-
interpolation=cv2.INTER_NEAREST,
|
| 42 |
-
)
|
| 43 |
-
sample["mask"] = sample["mask"].astype(bool)
|
| 44 |
-
|
| 45 |
-
return tuple(shape)
|
| 46 |
-
|
| 47 |
-
|
| 48 |
-
class Resize(object):
|
| 49 |
-
"""Resize sample to given size (width, height).
|
| 50 |
-
"""
|
| 51 |
-
|
| 52 |
-
def __init__(
|
| 53 |
-
self,
|
| 54 |
-
width,
|
| 55 |
-
height,
|
| 56 |
-
resize_target=True,
|
| 57 |
-
keep_aspect_ratio=False,
|
| 58 |
-
ensure_multiple_of=1,
|
| 59 |
-
resize_method="lower_bound",
|
| 60 |
-
image_interpolation_method=cv2.INTER_AREA,
|
| 61 |
-
):
|
| 62 |
-
"""Init.
|
| 63 |
-
|
| 64 |
-
Args:
|
| 65 |
-
width (int): desired output width
|
| 66 |
-
height (int): desired output height
|
| 67 |
-
resize_target (bool, optional):
|
| 68 |
-
True: Resize the full sample (image, mask, target).
|
| 69 |
-
False: Resize image only.
|
| 70 |
-
Defaults to True.
|
| 71 |
-
keep_aspect_ratio (bool, optional):
|
| 72 |
-
True: Keep the aspect ratio of the input sample.
|
| 73 |
-
Output sample might not have the given width and height, and
|
| 74 |
-
resize behaviour depends on the parameter 'resize_method'.
|
| 75 |
-
Defaults to False.
|
| 76 |
-
ensure_multiple_of (int, optional):
|
| 77 |
-
Output width and height is constrained to be multiple of this parameter.
|
| 78 |
-
Defaults to 1.
|
| 79 |
-
resize_method (str, optional):
|
| 80 |
-
"lower_bound": Output will be at least as large as the given size.
|
| 81 |
-
"upper_bound": Output will be at max as large as the given size. (Output size might be smaller than given size.)
|
| 82 |
-
"minimal": Scale as least as possible. (Output size might be smaller than given size.)
|
| 83 |
-
Defaults to "lower_bound".
|
| 84 |
-
"""
|
| 85 |
-
self.__width = width
|
| 86 |
-
self.__height = height
|
| 87 |
-
|
| 88 |
-
self.__resize_target = resize_target
|
| 89 |
-
self.__keep_aspect_ratio = keep_aspect_ratio
|
| 90 |
-
self.__multiple_of = ensure_multiple_of
|
| 91 |
-
self.__resize_method = resize_method
|
| 92 |
-
self.__image_interpolation_method = image_interpolation_method
|
| 93 |
-
|
| 94 |
-
def constrain_to_multiple_of(self, x, min_val=0, max_val=None):
|
| 95 |
-
y = (np.round(x / self.__multiple_of) * self.__multiple_of).astype(int)
|
| 96 |
-
|
| 97 |
-
if max_val is not None and y > max_val:
|
| 98 |
-
y = (np.floor(x / self.__multiple_of) * self.__multiple_of).astype(int)
|
| 99 |
-
|
| 100 |
-
if y < min_val:
|
| 101 |
-
y = (np.ceil(x / self.__multiple_of) * self.__multiple_of).astype(int)
|
| 102 |
-
|
| 103 |
-
return y
|
| 104 |
-
|
| 105 |
-
def get_size(self, width, height):
|
| 106 |
-
# determine new height and width
|
| 107 |
-
scale_height = self.__height / height
|
| 108 |
-
scale_width = self.__width / width
|
| 109 |
-
|
| 110 |
-
if self.__keep_aspect_ratio:
|
| 111 |
-
if self.__resize_method == "lower_bound":
|
| 112 |
-
# scale such that output size is lower bound
|
| 113 |
-
if scale_width > scale_height:
|
| 114 |
-
# fit width
|
| 115 |
-
scale_height = scale_width
|
| 116 |
-
else:
|
| 117 |
-
# fit height
|
| 118 |
-
scale_width = scale_height
|
| 119 |
-
elif self.__resize_method == "upper_bound":
|
| 120 |
-
# scale such that output size is upper bound
|
| 121 |
-
if scale_width < scale_height:
|
| 122 |
-
# fit width
|
| 123 |
-
scale_height = scale_width
|
| 124 |
-
else:
|
| 125 |
-
# fit height
|
| 126 |
-
scale_width = scale_height
|
| 127 |
-
elif self.__resize_method == "minimal":
|
| 128 |
-
# scale as least as possbile
|
| 129 |
-
if abs(1 - scale_width) < abs(1 - scale_height):
|
| 130 |
-
# fit width
|
| 131 |
-
scale_height = scale_width
|
| 132 |
-
else:
|
| 133 |
-
# fit height
|
| 134 |
-
scale_width = scale_height
|
| 135 |
-
else:
|
| 136 |
-
raise ValueError(
|
| 137 |
-
f"resize_method {self.__resize_method} not implemented"
|
| 138 |
-
)
|
| 139 |
-
|
| 140 |
-
if self.__resize_method == "lower_bound":
|
| 141 |
-
new_height = self.constrain_to_multiple_of(
|
| 142 |
-
scale_height * height, min_val=self.__height
|
| 143 |
-
)
|
| 144 |
-
new_width = self.constrain_to_multiple_of(
|
| 145 |
-
scale_width * width, min_val=self.__width
|
| 146 |
-
)
|
| 147 |
-
elif self.__resize_method == "upper_bound":
|
| 148 |
-
new_height = self.constrain_to_multiple_of(
|
| 149 |
-
scale_height * height, max_val=self.__height
|
| 150 |
-
)
|
| 151 |
-
new_width = self.constrain_to_multiple_of(
|
| 152 |
-
scale_width * width, max_val=self.__width
|
| 153 |
-
)
|
| 154 |
-
elif self.__resize_method == "minimal":
|
| 155 |
-
new_height = self.constrain_to_multiple_of(scale_height * height)
|
| 156 |
-
new_width = self.constrain_to_multiple_of(scale_width * width)
|
| 157 |
-
else:
|
| 158 |
-
raise ValueError(f"resize_method {self.__resize_method} not implemented")
|
| 159 |
-
|
| 160 |
-
return (new_width, new_height)
|
| 161 |
-
|
| 162 |
-
def __call__(self, sample):
|
| 163 |
-
width, height = self.get_size(
|
| 164 |
-
sample["image"].shape[1], sample["image"].shape[0]
|
| 165 |
-
)
|
| 166 |
-
|
| 167 |
-
# resize sample
|
| 168 |
-
sample["image"] = cv2.resize(
|
| 169 |
-
sample["image"],
|
| 170 |
-
(width, height),
|
| 171 |
-
interpolation=self.__image_interpolation_method,
|
| 172 |
-
)
|
| 173 |
-
|
| 174 |
-
if self.__resize_target:
|
| 175 |
-
if "disparity" in sample:
|
| 176 |
-
sample["disparity"] = cv2.resize(
|
| 177 |
-
sample["disparity"],
|
| 178 |
-
(width, height),
|
| 179 |
-
interpolation=cv2.INTER_NEAREST,
|
| 180 |
-
)
|
| 181 |
-
|
| 182 |
-
if "depth" in sample:
|
| 183 |
-
sample["depth"] = cv2.resize(
|
| 184 |
-
sample["depth"], (width, height), interpolation=cv2.INTER_NEAREST
|
| 185 |
-
)
|
| 186 |
-
|
| 187 |
-
sample["mask"] = cv2.resize(
|
| 188 |
-
sample["mask"].astype(np.float32),
|
| 189 |
-
(width, height),
|
| 190 |
-
interpolation=cv2.INTER_NEAREST,
|
| 191 |
-
)
|
| 192 |
-
sample["mask"] = sample["mask"].astype(bool)
|
| 193 |
-
|
| 194 |
-
return sample
|
| 195 |
-
|
| 196 |
-
|
| 197 |
-
class NormalizeImage(object):
|
| 198 |
-
"""Normlize image by given mean and std.
|
| 199 |
-
"""
|
| 200 |
-
|
| 201 |
-
def __init__(self, mean, std):
|
| 202 |
-
self.__mean = mean
|
| 203 |
-
self.__std = std
|
| 204 |
-
|
| 205 |
-
def __call__(self, sample):
|
| 206 |
-
sample["image"] = (sample["image"] - self.__mean) / self.__std
|
| 207 |
-
|
| 208 |
-
return sample
|
| 209 |
-
|
| 210 |
-
|
| 211 |
-
class PrepareForNet(object):
|
| 212 |
-
"""Prepare sample for usage as network input.
|
| 213 |
-
"""
|
| 214 |
-
|
| 215 |
-
def __init__(self):
|
| 216 |
-
pass
|
| 217 |
-
|
| 218 |
-
def __call__(self, sample):
|
| 219 |
-
image = np.transpose(sample["image"], (2, 0, 1))
|
| 220 |
-
sample["image"] = np.ascontiguousarray(image).astype(np.float32)
|
| 221 |
-
|
| 222 |
-
if "mask" in sample:
|
| 223 |
-
sample["mask"] = sample["mask"].astype(np.float32)
|
| 224 |
-
sample["mask"] = np.ascontiguousarray(sample["mask"])
|
| 225 |
-
|
| 226 |
-
if "disparity" in sample:
|
| 227 |
-
disparity = sample["disparity"].astype(np.float32)
|
| 228 |
-
sample["disparity"] = np.ascontiguousarray(disparity)
|
| 229 |
-
|
| 230 |
-
if "depth" in sample:
|
| 231 |
-
depth = sample["depth"].astype(np.float32)
|
| 232 |
-
sample["depth"] = np.ascontiguousarray(depth)
|
| 233 |
-
|
| 234 |
-
return sample
|
|
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spaces/Cyril666/ContourNet-ABI/maskrcnn_benchmark/csrc/cuda/dcn_v2_im2col_cuda.h
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/*!
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******************* BEGIN Caffe Copyright Notice and Disclaimer ****************
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*
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* COPYRIGHT
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*
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* All contributions by the University of California:
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* Copyright (c) 2014-2017 The Regents of the University of California (Regents)
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* All rights reserved.
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*
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* All other contributions:
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* Copyright (c) 2014-2017, the respective contributors
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* All rights reserved.
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*
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* Caffe uses a shared copyright model: each contributor holds copyright over
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* their contributions to Caffe. The project versioning records all such
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* contribution and copyright details. If a contributor wants to further mark
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* their specific copyright on a particular contribution, they should indicate
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* their copyright solely in the commit message of the change when it is
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* committed.
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*
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* LICENSE
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions are met:
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*
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* 1. Redistributions of source code must retain the above copyright notice, this
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* list of conditions and the following disclaimer.
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* 2. Redistributions in binary form must reproduce the above copyright notice,
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* this list of conditions and the following disclaimer in the documentation
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* and/or other materials provided with the distribution.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
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* ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
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* WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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* DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
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* ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
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* (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
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* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
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* ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
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* SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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*
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* CONTRIBUTION AGREEMENT
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*
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* By contributing to the BVLC/caffe repository through pull-request, comment,
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* or otherwise, the contributor releases their content to the
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* license and copyright terms herein.
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*
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***************** END Caffe Copyright Notice and Disclaimer ********************
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*
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* Copyright (c) 2018 Microsoft
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* Licensed under The MIT License [see LICENSE for details]
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* \file modulated_deformable_im2col.h
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* \brief Function definitions of converting an image to
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* column matrix based on kernel, padding, dilation, and offset.
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* These functions are mainly used in deformable convolution operators.
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* \ref: https://arxiv.org/abs/1811.11168
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* \author Yuwen Xiong, Haozhi Qi, Jifeng Dai, Xizhou Zhu, Han Hu
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*/
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/***************** Adapted by Charles Shang *********************/
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#ifndef DCN_V2_IM2COL_CUDA
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#define DCN_V2_IM2COL_CUDA
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#ifdef __cplusplus
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extern "C"
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{
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#endif
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void modulated_deformable_im2col_cuda(cudaStream_t stream,
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const float *data_im, const float *data_offset, const float *data_mask,
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const int batch_size, const int channels, const int height_im, const int width_im,
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const int height_col, const int width_col, const int kernel_h, const int kenerl_w,
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const int pad_h, const int pad_w, const int stride_h, const int stride_w,
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const int dilation_h, const int dilation_w,
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const int deformable_group, float *data_col);
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void modulated_deformable_col2im_cuda(cudaStream_t stream,
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const float *data_col, const float *data_offset, const float *data_mask,
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const int batch_size, const int channels, const int height_im, const int width_im,
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const int height_col, const int width_col, const int kernel_h, const int kenerl_w,
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const int pad_h, const int pad_w, const int stride_h, const int stride_w,
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const int dilation_h, const int dilation_w,
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const int deformable_group, float *grad_im);
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void modulated_deformable_col2im_coord_cuda(cudaStream_t stream,
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const float *data_col, const float *data_im, const float *data_offset, const float *data_mask,
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const int batch_size, const int channels, const int height_im, const int width_im,
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const int height_col, const int width_col, const int kernel_h, const int kenerl_w,
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const int pad_h, const int pad_w, const int stride_h, const int stride_w,
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const int dilation_h, const int dilation_w,
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const int deformable_group,
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float *grad_offset, float *grad_mask);
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#ifdef __cplusplus
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}
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#endif
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#endif
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spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/attrs/converters.py
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# SPDX-License-Identifier: MIT
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from attr.converters import * # noqa
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spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/gradio/templates/cdn/assets/Blocks-c9e1499d.js
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spaces/DaCuteRaccoon/dalle-mini/html2canvas.js
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