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2 : Detect","目录","Machine Learning and AI","Uncategorized","有趣","Multimedia","🤖 AI \u0026 Machine Learning","📖 Learn"],"sub_categories":["Code Repositories","Computer Vision","Uncategorized","zsh 插件","Image","🤩 Powered by TensorFlow.js"],"readme":"\u003cp align=\"center\"\u003e\n  \u003cimg src=\"https://github.com/infinitered/nsfwjs/raw/master/_art/nsfwjs_logo.jpg\" alt=\"NSFWJS Logo\" width=\"400\" /\u003e\n  \u003ch2 align=\"center\"\u003eClient-side indecent content checking\u003c/h2\u003e\n\u003c/p\u003e\n\n[![All Contributors](https://img.shields.io/badge/all_contributors-25-green.svg?style=flat-square)](#contributors)\n[![CircleCI](https://dl.circleci.com/status-badge/img/gh/infinitered/nsfwjs/tree/master.svg?style=svg)](https://dl.circleci.com/status-badge/redirect/gh/infinitered/nsfwjs/tree/master)\n[![Netlify Status](https://api.netlify.com/api/v1/badges/72d19dc0-d316-4f75-9904-a33d833ff628/deploy-status)](https://app.netlify.com/sites/nsfwjs/deploys)\n\nA simple JavaScript library to help you quickly identify unseemly images; all in the client's browser. NSFWJS isn't perfect, but it's pretty accurate (~90% with small and ~93% with midsized model)... and it's getting more accurate all the time.\n\nWhy would this be useful? [Check out the announcement blog post](https://shift.infinite.red/avoid-nightmares-nsfw-js-ab7b176978b1).\n\n\u003cp align=\"center\"\u003e\n\u003cimg src=\"https://github.com/infinitered/nsfwjs/raw/master/_art/nsfw_demo.gif\" alt=\"demo example\" width=\"800\" align=\"center\" /\u003e\n\u003c/p\u003e\n\n## NOTE\n\nIf you're trying to access the Cloudfront hosted model and are running into an error, it's likely due to the fact that the model has been moved to a new location. Please take a look at our [Host your own model](#host-your-own-model) section. We will be returning the model after some hotlinkers have been dealt with.\n\n## **Table of Contents**\n\n\u003c!-- START doctoc generated TOC please keep comment here to allow auto update --\u003e\n\u003c!-- DON'T EDIT THIS SECTION, INSTEAD RE-RUN doctoc TO UPDATE --\u003e\n\n\n- [QUICK: How to use the module](#quick-how-to-use-the-module)\n  - [Selective model bundles (tree-shaking)](#selective-model-bundles-tree-shaking)\n- [Library API](#library-api)\n  - [`load` the model](#load-the-model)\n  - [Caching](#caching)\n  - [`classify` an image](#classify-an-image)\n  - [`dispose` a loaded model](#dispose-a-loaded-model)\n- [Production](#production)\n- [Backend selection](#backend-selection)\n  - [WASM backend (optional)](#wasm-backend-optional)\n  - [WebGPU backend (optional)](#webgpu-backend-optional)\n  - [Node.js backend](#nodejs-backend)\n- [Install](#install)\n  - [Host your own model](#host-your-own-model)\n- [Run the Examples](#run-the-examples)\n  - [Tensorflow.js in the browser](#tensorflowjs-in-the-browser)\n  - [Browserify](#browserify)\n  - [React Native](#react-native)\n  - [Node JS App](#node-js-app)\n  - [NSFW Filter](#nsfw-filter)\n- [Learn TensorFlow.js](#learn-tensorflowjs)\n- [More!](#more)\n  - [Open Source](#open-source)\n  - [Need the experts? Hire Infinite Red for your next project](#need-the-experts-hire-infinite-red-for-your-next-project)\n- [Contributors](#contributors)\n\n\u003c!-- END doctoc generated TOC please keep comment here to allow auto update --\u003e\n\nThe library categorizes image probabilities in the following 5 classes:\n\n- `Drawing` - safe for work drawings (including anime)\n- `Hentai` - hentai and pornographic drawings\n- `Neutral` - safe for work neutral images\n- `Porn` - pornographic images, sexual acts\n- `Sexy` - sexually explicit images, not pornography\n\n\u003e _The demo is a continuous deployment source - Give it a go: http://nsfwjs.com_\n\n## QUICK: How to use the module\n\n```js\nimport * as nsfwjs from \"nsfwjs\";\n\nconst img = document.getElementById(\"img\");\n\n// If you want to host models on your own or use different model from the ones available, see the section \"Host your own model\".\nconst model = await nsfwjs.load();\n\n// Classify the image\nconst predictions = await model.classify(img);\nconsole.log(\"Predictions: \", predictions);\n```\n\n### Selective model bundles (tree-shaking)\n\n`nsfwjs` keeps the default behavior and includes built-in model definitions. For selective bundling, import from `nsfwjs/core` and pass only the models you want in `modelDefinitions`.\n\n```js\nimport { load } from \"nsfwjs/core\";\nimport { MobileNetV2Model } from \"nsfwjs/models/mobilenet_v2\";\nimport { MobileNetV2MidModel } from \"nsfwjs/models/mobilenet_v2_mid\";\n\nconst model = await load(\"MobileNetV2\", {\n  modelDefinitions: [MobileNetV2Model, MobileNetV2MidModel],\n});\n```\n\nIf you pass an empty model registry, named bundled model loads will fail:\n\n```js\nawait load(\"MobileNetV2\", { modelDefinitions: [] }); // throws\n```\n\n## Library API\n\n### `load` the model\n\nBefore you can classify any image, you'll need to load the model.\n\n```js\nconst model = nsfwjs.load(); // Default: \"MobileNetV2\"\n```\n\nYou can use the optional first parameter to specify which model you want to use from the three built-in bundled models. Defaults to: `\"MobileNetV2\"`.\n\nFor tree-shaken selective model bundling, use `nsfwjs/core` and pass `modelDefinitions` as shown above.\n\n```js\nconst model = nsfwjs.load(\"MobileNetV2Mid\"); // \"MobileNetV2\" | \"MobileNetV2Mid\" | \"InceptionV3\"\n```\n\nYou can also use same parameter and load the model from your website/server, as explained in the [Host your own model](#host-your-own-model) section. Doing so could reduce the bundle size for loading the model by approximately 1.33 times (33%) since you can directly use the binary files instead of the base64 that are bundled with the package. i.e. The `\"MobileNetV2\"` model bundled into the package is 3.5MB instead of 2.6MB for hosted binary files. This would only make a difference if you are loading the model every time (without [Caching](#caching)) on the client-side browser since on the server-side, you'd only be loading the model once at the server start.\n\nIf you are hosting your own model via URL and want the smallest app bundle, import `load` from `nsfwjs/core` instead of `nsfwjs`. The core entrypoint does not include built-in model definitions by default, so bundlers do not pull those model assets into your app bundle.\n\n```js\nimport { load } from \"nsfwjs/core\";\n\nconst model = await load(\"/path/to/mobilenet_v2/model.json\");\n```\n\nModel MobileNetV2 - [224x224](https://github.com/infinitered/nsfwjs/blob/master/models/mobilenet_v2/)\n\n```js\nconst model = nsfwjs.load(\"/path/to/mobilenet_v2/\");\n```\n\nIf you're using a model that needs an image of dimension other than 224x224, you can pass the size in the options parameter.\n\nModel MobileNetV2Mid - [Graph](https://github.com/infinitered/nsfwjs/tree/master/models/mobilenet_v2_mid)\n\n```js\n/* You may need to load this model with graph type */\nconst model = nsfwjs.load(\"/path/to/mobilenet_v2_mid/\", { type: 'graph' });\n```\n\nIf you're using a graph model, you cannot use the infer method, and you'll need to tell model load that you're dealing with a graph model in options.\n\nModel InceptionV3 - [299x299](https://github.com/infinitered/nsfwjs/tree/master/models/inception_v3)\n\n```js\nconst model = nsfwjs.load(\"/path/to/inception_v3/\", { size: 299 });\n```\n\n### Caching\n\nIf you're using in the browser and you'd like to subsequently load from indexed db or local storage (NOTE: model size may be too large for local storage!) you can save the underlying model using the appropriate scheme and load from there.\n\n```js\nconst initialLoad = await nsfwjs.load(\n  \"/path/to/different/model/\" /*, { ...options }*/\n);\nawait initialLoad.model.save(\"indexeddb://exampleModel\");\nconst model = await nsfwjs.load(\"indexeddb://exampleModel\" /*, { ...options }*/);\n```\n\n**Parameters**\n\nInitial Load:\n1. URL or path to folder containing `model.json`.\n2. Optional object with size or type property that your model expects.\n\nSubsequent Load:\n1. IndexedDB path.\n2. Optional object with size or type property that your model expects.\n\n\n**Returns**\n\n- Ready to use NSFWJS model object\n  \n\n**Troubleshooting**\n\n- On the tab where the model is being loaded, inspect element and navigate to the the \"Application\" tab. On the left pane under the \"Storage\" section, there is a subsection named \"IndexedDB\". Here you can view if the model is being saved.\n\nFor a complete browser worker implementation (including backend initialization, IndexedDB-first load, and save-on-miss caching), see [`examples/nsfw_demo/src/nsfwjs.worker.ts`](./examples/nsfw_demo/src/nsfwjs.worker.ts).\n\n### `classify` an image\n\nThis function can take any browser-based image elements (`\u003cimg\u003e`, `\u003cvideo\u003e`, `\u003ccanvas\u003e`) and returns an array of most likely predictions and their confidence levels.\n\n```js\n// Return top 3 guesses (instead of all 5)\nconst predictions = await model.classify(img, 3);\n```\n\n**Parameters**\n\n- Tensor, Image data, Image element, video element, or canvas element to check\n- Number of results to return (default all 5)\n\n**Returns**\n\n- Array of objects that contain `className` and `probability`. Array size is determined by the second parameter in the `classify` function.\n\n### `dispose` a loaded model\n\nIf you are done with a model instance, call `dispose()` to release held tensors and model resources.\n\n```js\nconst model = await nsfwjs.load();\n// ... classify/infer\nmodel.dispose();\n```\n\n## Production\n\nTensorflow.js offers two flags, `enableProdMode` and `enableDebugMode`. If you're going to use NSFWJS in production, be sure to enable prod mode before loading the NSFWJS model.\n\n```js\nimport * as tf from \"@tensorflow/tfjs\";\nimport * as nsfwjs from \"nsfwjs\";\ntf.enableProdMode();\n//...\nlet model = await nsfwjs.load(`${urlToNSFWJSModel}`);\n```\n\n**NOTE:** Consider downloading and hosting the model yourself before moving to production as explained in the [Host your own model](#host-your-own-model) section. This could potentially improve the initial load time of the model. Furthermore, consider [Caching](#caching) the model, if you are using it in the browser.\n\n## Backend selection\n\nNSFWJS uses whichever TensorFlow.js backend is active.\n\nSetting a backend explicitly is optional. If you import one or more backends and call `await tf.ready()`, TensorFlow.js will pick the best available backend.\n\nUse `tf.setBackend(...)` only when you want deterministic behavior across devices.\n\nAutomatic backend selection:\n\n```js\nimport * as tf from \"@tensorflow/tfjs\";\nimport \"@tensorflow/tfjs-backend-webgpu\";\nimport \"@tensorflow/tfjs-backend-wasm\";\nimport * as nsfwjs from \"nsfwjs\";\n\nawait tf.ready();\n\nconst model = await nsfwjs.load();\n```\n\nPinned backend selection:\n\n```js\nimport * as tf from \"@tensorflow/tfjs\";\nimport \"@tensorflow/tfjs-backend-webgpu\";\n\nawait tf.setBackend(\"webgpu\");\nawait tf.ready();\n```\n\n### WASM backend (optional)\n\n```bash\nyarn add @tensorflow/tfjs-backend-wasm\n```\n\n```js\nimport * as tf from \"@tensorflow/tfjs\";\nimport {\n  setWasmPaths,\n} from \"@tensorflow/tfjs-backend-wasm\";\nimport \"@tensorflow/tfjs-backend-wasm\";\n\n// If you aren't using a standard bundler, set the path to the .wasm binaries.\nsetWasmPaths(\"https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm/dist/\");\n\nawait tf.setBackend(\"wasm\");\nawait tf.ready();\n```\n\n### WebGPU backend (optional)\n\n```bash\nyarn add @tensorflow/tfjs-backend-webgpu\n```\n\n```js\nimport * as tf from \"@tensorflow/tfjs\";\nimport \"@tensorflow/tfjs-backend-webgpu\";\n\nawait tf.setBackend(\"webgpu\");\nawait tf.ready();\n```\n\nBackend guidance:\n\n- `webgpu`: often fastest on supported browsers/hardware.\n- `webgl`: strong default in modern desktop/mobile browsers.\n- `wasm`: useful fallback for environments where WebGL is unavailable/restricted.\n- `cpu`: broad compatibility but typically slower.\n\n### Node.js backend\n\nFor Node.js workloads, consider using `@tensorflow/tfjs-node` (or `@tensorflow/tfjs-node-gpu` where applicable) for better performance. See the [Node JS App](#node-js-app) section for examples.\n\nAlways benchmark in your target browser/device set.\n\n## Install\n\nNSFWJS is powered by TensorFlow.js as a peer dependency. If your project does not already have TFJS you'll may want to add it.\n\n```bash\n# peer dependency\n$ yarn add @tensorflow/tfjs\n# install NSFWJS\n$ yarn add nsfwjs\n```\n\nFor script tags include all the bundles as shown [here](#browserify). Then simply access the nsfwjs global variable. This requires that you've already imported TensorFlow.js as well.\n\n### Host your own model\n\nThe magic that powers NSFWJS is the [NSFW detection model](https://github.com/gantman/nsfw_model). By default, the models are bundled into this package. But you may want to host the models on your own server to reduce bundle size by loading them as raw binary files or to host your own custom model. If you want to host your own version of [the model files](https://github.com/infinitered/nsfwjs/tree/master/models), you can do so by following the steps below. You can then pass the relative URL to your hosted files in the `load` function along with the `options` if necessary.\n\nIf you are loading a hosted model URL, prefer `nsfwjs/core` so your app does not bundle built-in model definitions. See [Selective model bundles (tree-shaking)](#selective-model-bundles-tree-shaking).\n\nHere is how to install the default model on a website:\n\n1. Download the project by either downloading as zip or cloning `git clone https://github.com/infinitered/nsfwjs.git`.\n2. Extract the `models` folder from the root of the project and drop it in the `public` directory of your web application to serve them as static files along side your website. (You can host it anywhere such as on a s3 bucket as long as you can access it via URL).\n3. Retrieve the URL and put it into `nsfwjs.load()`. For example: `nsfwjs.load(https://yourwebsite.com/models/mobilenet_v2/model.json)`.\n\n## Run the Examples\n\n### Tensorflow.js in the browser\n\nThe demo that powers https://nsfwjs.com/ is available in the [`examples/nsfw_demo`](https://github.com/infinitered/nsfwjs/tree/master/examples/nsfw_demo) folder.\n\nTo run the demo, run `yarn demo` which will copy the latest code into the demo and start the dev server.\n\n### Browserify\n\nA browserified version using nothing but promises and script tags is available in the [`minimal_demo`](https://github.com/infinitered/nsfwjs/tree/master/examples/minimal_demo) folder.\n\n```js\n\u003cscript src=\"/path/to/model/directory/model.min.js\"\u003e\u003c/script\u003e\n\u003cscript src=\"/path/to/model/directory/group1-shard1of2.min.js\"\u003e\u003c/script\u003e\n\u003cscript src=\"/path/to/model/directory/group1-shard2of2.min.js\"\u003e\u003c/script\u003e\n\u003cscript src=\"/path/to/bundle/nsfwjs.min.js\"\u003e\u003c/script\u003e\n```\n\nYou should host the `nsfwjs.min.js` file and all the model bundles that you want to use alongside your project, and reference them using the `src` attribute in the script tags.\n\n### React Native\n\nThe [NSFWJS React Native app](https://github.com/infinitered/nsfwjs-mobile)\n\n![React Native Demo](./_art/nsfwjs-mobile.jpg)\n\nLoads a local copy of the model to reduce network load and utilizes TFJS-React-Native. [Blog Post](https://shift.infinite.red/nsfw-js-for-react-native-a37c9ba45fe9)\n\n### Node JS App\n\nUsing NPM, you can also use the model on the server side.\n\n```bash\n$ npm install nsfwjs\n$ npm install @tensorflow/tfjs-node\n```\n\n```javascript\nconst axios = require(\"axios\"); //you can use any http client\nconst tf = require(\"@tensorflow/tfjs-node\");\nconst nsfw = require(\"nsfwjs\");\nasync function fn() {\n  const pic = await axios.get(`link-to-picture`, {\n    responseType: \"arraybuffer\",\n  });\n  const model = await nsfw.load(); // To load a local model, nsfw.load('file://./path/to/model/')\n  // Image must be in tf.tensor3d format\n  // you can convert image to tf.tensor3d with tf.node.decodeImage(Uint8Array,channels)\n  const image = await tf.node.decodeImage(pic.data, 3);\n  const predictions = await model.classify(image);\n  image.dispose(); // Tensor memory must be managed explicitly (it is not sufficient to let a tf.Tensor go out of scope for its memory to be released).\n  console.log(predictions);\n}\nfn();\n```\n\nHere is another full example of a [multipart/form-data POST using Express](examples/node_demo), supposing you are using JPG format.\n\n```javascript\nconst express = require(\"express\");\nconst multer = require(\"multer\");\nconst jpeg = require(\"jpeg-js\");\n\nconst tf = require(\"@tensorflow/tfjs-node\");\nconst nsfw = require(\"nsfwjs\");\n\nconst app = express();\nconst upload = multer();\n\nlet _model;\n\nconst convert = async (img) =\u003e {\n  // Decoded image in UInt8 Byte array\n  const image = await jpeg.decode(img, { useTArray: true });\n\n  const numChannels = 3;\n  const numPixels = image.width * image.height;\n  const values = new Int32Array(numPixels * numChannels);\n\n  for (let i = 0; i \u003c numPixels; i++)\n    for (let c = 0; c \u003c numChannels; ++c)\n      values[i * numChannels + c] = image.data[i * 4 + c];\n\n  return tf.tensor3d(values, [image.height, image.width, numChannels], \"int32\");\n};\n\napp.post(\"/nsfw\", upload.single(\"image\"), async (req, res) =\u003e {\n  if (!req.file) res.status(400).send(\"Missing image multipart/form-data\");\n  else {\n    const image = await convert(req.file.buffer);\n    const predictions = await _model.classify(image);\n    image.dispose();\n    res.json(predictions);\n  }\n});\n\nconst load_model = async () =\u003e {\n  _model = await nsfw.load();\n};\n\n// Keep the model in memory, make sure it's loaded only once\nload_model().then(() =\u003e app.listen(8080));\n\n// curl --request POST localhost:8080/nsfw --header 'Content-Type: multipart/form-data' --data-binary 'image=@/full/path/to/picture.jpg'\n```\n\nYou can also use [`lovell/sharp`](https://github.com/lovell/sharp) for preprocessing tasks and more file formats.\n\n### NSFW Filter\n\n[**NSFW Filter**](https://github.com/navendu-pottekkat/nsfw-filter) is an open source web extension for Google Chrome that uses NSFWJS for filtering out NSFW images.\n\nCheck out the project [here](https://github.com/navendu-pottekkat/nsfw-filter).\n\n## Learn TensorFlow.js\n\nLearn how to write your own library like NSFWJS with my O'Reilly book \"Learning TensorFlow.js\" available on [O'Reilly](https://learning.oreilly.com/library/view/learning-tensorflowjs/9781492090786/) and [Amazon](https://amzn.to/3dR3vpY).\n\n[![Learning TensorFlow.js JavaScript Book Red](_art/red_mockup_top.jpg)](https://amzn.to/3dR3vpY)\n\n## More!\n\nAn [FAQ](https://github.com/infinitered/nsfwjs/wiki/FAQ:-NSFW-JS) page is available.\n\nMore about NSFWJS and TensorFlow.js - https://youtu.be/uzQwmZwy3yw\n\nThe [model was trained in Keras over several days](https://medium.freecodecamp.org/how-to-set-up-nsfw-content-detection-with-machine-learning-229a9725829c) and 60+ Gigs of data. Be sure to [check out the model code](https://github.com/GantMan/nsfw_model) which was trained on data provided by [Alexander Kim's](https://github.com/alexkimxyz) [nsfw_data_scraper](https://github.com/alexkimxyz/nsfw_data_scraper).\n\n### Open Source\n\nNSFWJS, as open source, is free to use and always will be :heart:. It's MIT licensed, and we'll always do our best to help and quickly answer issues. If you'd like to get a hold of us, join our [community slack](http://community.infinite.red).\n\n### Need the experts? Hire Infinite Red for your next project\n\nIf your project's calling for the experts in all things React Native, Infinite Red’s here to help! Our experienced team of software engineers have worked with companies like Microsoft, Zoom, and Mercari to bring even some of the most complex projects to life.\n\nWhether it’s running a full project or training a team on React Native, we can help you solve your company’s toughest engineering challenges – and make it a great experience at the same time.\nReady to see how we can work together? [Send us a message](mailto:hello@infinite.red)\n\n## Contributors\n\nThanks goes to these wonderful people ([emoji key](https://allcontributors.org/docs/en/emoji-key)):\n\n\u003c!-- ALL-CONTRIBUTORS-LIST:START - Do not remove or modify this section --\u003e\n\u003c!-- prettier-ignore-start --\u003e\n\u003c!-- markdownlint-disable --\u003e\n\u003ctable\u003e\n  \u003ctbody\u003e\n    \u003ctr\u003e\n      \u003ctd align=\"center\" valign=\"top\" width=\"14.28%\"\u003e\u003ca href=\"http://gantlaborde.com/\"\u003e\u003cimg src=\"https://avatars0.githubusercontent.com/u/997157?v=4?s=100\" width=\"100px;\" alt=\"Gant Laborde\"/\u003e\u003cbr /\u003e\u003csub\u003e\u003cb\u003eGant Laborde\u003c/b\u003e\u003c/sub\u003e\u003c/a\u003e\u003cbr /\u003e\u003ca href=\"#question-GantMan\" title=\"Answering Questions\"\u003e💬\u003c/a\u003e \u003ca href=\"#blog-GantMan\" title=\"Blogposts\"\u003e📝\u003c/a\u003e \u003ca href=\"https://github.com/infinitered/nsfwjs/commits?author=GantMan\" title=\"Code\"\u003e💻\u003c/a\u003e \u003ca href=\"#example-GantMan\" title=\"Examples\"\u003e💡\u003c/a\u003e \u003ca href=\"#ideas-GantMan\" title=\"Ideas, Planning, \u0026 Feedback\"\u003e🤔\u003c/a\u003e \u003ca href=\"#infra-GantMan\" title=\"Infrastructure (Hosting, Build-Tools, etc)\"\u003e🚇\u003c/a\u003e \u003ca href=\"https://github.com/infinitered/nsfwjs/pulls?q=is%3Apr+reviewed-by%3AGantMan\" title=\"Reviewed Pull Requests\"\u003e👀\u003c/a\u003e \u003ca href=\"https://github.com/infinitered/nsfwjs/commits?author=GantMan\" title=\"Tests\"\u003e⚠️\u003c/a\u003e\u003c/td\u003e\n      \u003ctd align=\"center\" valign=\"top\" width=\"14.28%\"\u003e\u003ca href=\"https://jamonholmgren.com\"\u003e\u003cimg src=\"https://avatars3.githubusercontent.com/u/1479215?v=4?s=100\" width=\"100px;\" alt=\"Jamon Holmgren\"/\u003e\u003cbr /\u003e\u003csub\u003e\u003cb\u003eJamon Holmgren\u003c/b\u003e\u003c/sub\u003e\u003c/a\u003e\u003cbr /\u003e\u003ca href=\"https://github.com/infinitered/nsfwjs/commits?author=jamonholmgren\" title=\"Documentation\"\u003e📖\u003c/a\u003e \u003ca href=\"#ideas-jamonholmgren\" title=\"Ideas, Planning, \u0026 Feedback\"\u003e🤔\u003c/a\u003e \u003ca href=\"https://github.com/infinitered/nsfwjs/commits?author=jamonholmgren\" title=\"Code\"\u003e💻\u003c/a\u003e \u003ca href=\"#content-jamonholmgren\" title=\"Content\"\u003e🖋\u003c/a\u003e\u003c/td\u003e\n      \u003ctd align=\"center\" valign=\"top\" width=\"14.28%\"\u003e\u003ca href=\"https://github.com/mazenchami\"\u003e\u003cimg src=\"https://avatars.githubusercontent.com/u/9324607?v=4?s=100\" width=\"100px;\" alt=\"Mazen Chami\"/\u003e\u003cbr /\u003e\u003csub\u003e\u003cb\u003eMazen Chami\u003c/b\u003e\u003c/sub\u003e\u003c/a\u003e\u003cbr /\u003e\u003ca href=\"https://github.com/infinitered/nsfwjs/commits?author=mazenchami\" title=\"Documentation\"\u003e📖\u003c/a\u003e \u003ca href=\"https://github.com/infinitered/nsfwjs/commits?author=mazenchami\" title=\"Code\"\u003e💻\u003c/a\u003e \u003ca href=\"https://github.com/infinitered/nsfwjs/pulls?q=is%3Apr+reviewed-by%3Amazenchami\" title=\"Reviewed Pull Requests\"\u003e👀\u003c/a\u003e \u003ca href=\"https://github.com/infinitered/nsfwjs/commits?author=mazenchami\" title=\"Tests\"\u003e⚠️\u003c/a\u003e\u003c/td\u003e\n      \u003ctd align=\"center\" valign=\"top\" width=\"14.28%\"\u003e\u003ca href=\"https://github.com/jstudenski\"\u003e\u003cimg src=\"https://avatars0.githubusercontent.com/u/7350279?v=4?s=100\" width=\"100px;\" alt=\"Jeff Studenski\"/\u003e\u003cbr /\u003e\u003csub\u003e\u003cb\u003eJeff Studenski\u003c/b\u003e\u003c/sub\u003e\u003c/a\u003e\u003cbr /\u003e\u003ca href=\"#design-jstudenski\" title=\"Design\"\u003e🎨\u003c/a\u003e\u003c/td\u003e\n      \u003ctd align=\"center\" valign=\"top\" width=\"14.28%\"\u003e\u003ca href=\"https://github.com/fvonhoven\"\u003e\u003cimg src=\"https://avatars2.githubusercontent.com/u/10098988?v=4?s=100\" width=\"100px;\" alt=\"Frank von Hoven III\"/\u003e\u003cbr /\u003e\u003csub\u003e\u003cb\u003eFrank von Hoven III\u003c/b\u003e\u003c/sub\u003e\u003c/a\u003e\u003cbr /\u003e\u003ca href=\"https://github.com/infinitered/nsfwjs/commits?author=fvonhoven\" title=\"Documentation\"\u003e📖\u003c/a\u003e \u003ca href=\"#ideas-fvonhoven\" title=\"Ideas, Planning, \u0026 Feedback\"\u003e🤔\u003c/a\u003e\u003c/td\u003e\n      \u003ctd align=\"center\" valign=\"top\" width=\"14.28%\"\u003e\u003ca href=\"https://github.com/sandeshsoni\"\u003e\u003cimg src=\"https://avatars3.githubusercontent.com/u/3761745?v=4?s=100\" width=\"100px;\" alt=\"Sandesh Soni\"/\u003e\u003cbr /\u003e\u003csub\u003e\u003cb\u003eSandesh Soni\u003c/b\u003e\u003c/sub\u003e\u003c/a\u003e\u003cbr /\u003e\u003ca href=\"https://github.com/infinitered/nsfwjs/commits?author=sandeshsoni\" title=\"Code\"\u003e💻\u003c/a\u003e\u003c/td\u003e\n      \u003ctd align=\"center\" valign=\"top\" width=\"14.28%\"\u003e\u003ca href=\"https://github.com/seannam1218\"\u003e\u003cimg src=\"https://avatars1.githubusercontent.com/u/24437898?v=4?s=100\" width=\"100px;\" alt=\"Sean Nam\"/\u003e\u003cbr /\u003e\u003csub\u003e\u003cb\u003eSean Nam\u003c/b\u003e\u003c/sub\u003e\u003c/a\u003e\u003cbr /\u003e\u003ca href=\"https://github.com/infinitered/nsfwjs/commits?author=seannam1218\" title=\"Documentation\"\u003e📖\u003c/a\u003e\u003c/td\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd align=\"center\" valign=\"top\" width=\"14.28%\"\u003e\u003ca href=\"https://github.com/emer7\"\u003e\u003cimg src=\"https://avatars1.githubusercontent.com/u/21377166?v=4?s=100\" width=\"100px;\" alt=\"Gilbert Emerson\"/\u003e\u003cbr /\u003e\u003csub\u003e\u003cb\u003eGilbert Emerson\u003c/b\u003e\u003c/sub\u003e\u003c/a\u003e\u003cbr /\u003e\u003ca href=\"https://github.com/infinitered/nsfwjs/commits?author=emer7\" title=\"Code\"\u003e💻\u003c/a\u003e\u003c/td\u003e\n      \u003ctd align=\"center\" valign=\"top\" width=\"14.28%\"\u003e\u003ca href=\"https://github.com/xilaraux\"\u003e\u003cimg src=\"https://avatars2.githubusercontent.com/u/17703730?v=4?s=100\" width=\"100px;\" alt=\"Oleksandr Kozlov\"/\u003e\u003cbr /\u003e\u003csub\u003e\u003cb\u003eOleksandr Kozlov\u003c/b\u003e\u003c/sub\u003e\u003c/a\u003e\u003cbr /\u003e\u003ca href=\"#infra-xilaraux\" title=\"Infrastructure (Hosting, Build-Tools, etc)\"\u003e🚇\u003c/a\u003e \u003ca href=\"https://github.com/infinitered/nsfwjs/commits?author=xilaraux\" title=\"Tests\"\u003e⚠️\u003c/a\u003e \u003ca href=\"https://github.com/infinitered/nsfwjs/commits?author=xilaraux\" title=\"Code\"\u003e💻\u003c/a\u003e\u003c/td\u003e\n      \u003ctd align=\"center\" valign=\"top\" width=\"14.28%\"\u003e\u003ca href=\"http://morganlaco.com\"\u003e\u003cimg src=\"https://avatars2.githubusercontent.com/u/4466642?v=4?s=100\" width=\"100px;\" alt=\"Morgan\"/\u003e\u003cbr /\u003e\u003csub\u003e\u003cb\u003eMorgan\u003c/b\u003e\u003c/sub\u003e\u003c/a\u003e\u003cbr /\u003e\u003ca href=\"https://github.com/infinitered/nsfwjs/commits?author=mlaco\" title=\"Code\"\u003e💻\u003c/a\u003e \u003ca href=\"#ideas-mlaco\" title=\"Ideas, Planning, \u0026 Feedback\"\u003e🤔\u003c/a\u003e\u003c/td\u003e\n      \u003ctd align=\"center\" valign=\"top\" width=\"14.28%\"\u003e\u003ca href=\"http://mycaule.github.io/\"\u003e\u003cimg src=\"https://avatars2.githubusercontent.com/u/6161385?v=4?s=100\" width=\"100px;\" alt=\"Michel Hua\"/\u003e\u003cbr /\u003e\u003csub\u003e\u003cb\u003eMichel Hua\u003c/b\u003e\u003c/sub\u003e\u003c/a\u003e\u003cbr /\u003e\u003ca href=\"https://github.com/infinitered/nsfwjs/commits?author=mycaule\" title=\"Code\"\u003e💻\u003c/a\u003e \u003ca href=\"https://github.com/infinitered/nsfwjs/commits?author=mycaule\" title=\"Documentation\"\u003e📖\u003c/a\u003e\u003c/td\u003e\n      \u003ctd align=\"center\" valign=\"top\" width=\"14.28%\"\u003e\u003ca href=\"https://www.infinite.red\"\u003e\u003cimg src=\"https://avatars2.githubusercontent.com/u/1771152?v=4?s=100\" width=\"100px;\" alt=\"Kevin VanGelder\"/\u003e\u003cbr /\u003e\u003csub\u003e\u003cb\u003eKevin VanGelder\u003c/b\u003e\u003c/sub\u003e\u003c/a\u003e\u003cbr /\u003e\u003ca href=\"https://github.com/infinitered/nsfwjs/commits?author=kevinvangelder\" title=\"Code\"\u003e💻\u003c/a\u003e \u003ca href=\"https://github.com/infinitered/nsfwjs/commits?author=kevinvangelder\" title=\"Documentation\"\u003e📖\u003c/a\u003e\u003c/td\u003e\n      \u003ctd align=\"center\" valign=\"top\" width=\"14.28%\"\u003e\u003ca href=\"http://technikempire.com\"\u003e\u003cimg src=\"https://avatars2.githubusercontent.com/u/11234763?v=4?s=100\" width=\"100px;\" alt=\"Jesse Nicholson\"/\u003e\u003cbr /\u003e\u003csub\u003e\u003cb\u003eJesse Nicholson\u003c/b\u003e\u003c/sub\u003e\u003c/a\u003e\u003cbr /\u003e\u003ca href=\"#data-TechnikEmpire\" title=\"Data\"\u003e🔣\u003c/a\u003e \u003ca href=\"#ideas-TechnikEmpire\" title=\"Ideas, Planning, \u0026 Feedback\"\u003e🤔\u003c/a\u003e\u003c/td\u003e\n      \u003ctd align=\"center\" valign=\"top\" width=\"14.28%\"\u003e\u003ca href=\"https://github.com/camhart\"\u003e\u003cimg src=\"https://avatars0.githubusercontent.com/u/3038809?v=4?s=100\" width=\"100px;\" alt=\"camhart\"/\u003e\u003cbr /\u003e\u003csub\u003e\u003cb\u003ecamhart\u003c/b\u003e\u003c/sub\u003e\u003c/a\u003e\u003cbr /\u003e\u003ca href=\"https://github.com/infinitered/nsfwjs/commits?author=camhart\" title=\"Documentation\"\u003e📖\u003c/a\u003e\u003c/td\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd align=\"center\" valign=\"top\" width=\"14.28%\"\u003e\u003ca href=\"https://github.com/Cameron-Burkholder\"\u003e\u003cimg src=\"https://avatars2.githubusercontent.com/u/13265710?v=4?s=100\" width=\"100px;\" alt=\"Cameron Burkholder\"/\u003e\u003cbr /\u003e\u003csub\u003e\u003cb\u003eCameron Burkholder\u003c/b\u003e\u003c/sub\u003e\u003c/a\u003e\u003cbr /\u003e\u003ca href=\"#design-Cameron-Burkholder\" title=\"Design\"\u003e🎨\u003c/a\u003e\u003c/td\u003e\n      \u003ctd align=\"center\" valign=\"top\" width=\"14.28%\"\u003e\u003ca href=\"https://qwertyforce.ru\"\u003e\u003cimg src=\"https://avatars0.githubusercontent.com/u/44163887?v=4?s=100\" width=\"100px;\" alt=\"qwertyforce\"/\u003e\u003cbr /\u003e\u003csub\u003e\u003cb\u003eqwertyforce\u003c/b\u003e\u003c/sub\u003e\u003c/a\u003e\u003cbr /\u003e\u003ca href=\"https://github.com/infinitered/nsfwjs/commits?author=qwertyforce\" title=\"Documentation\"\u003e📖\u003c/a\u003e\u003c/td\u003e\n      \u003ctd align=\"center\" valign=\"top\" width=\"14.28%\"\u003e\u003ca href=\"https://github.com/YegorZaremba\"\u003e\u003cimg src=\"https://avatars3.githubusercontent.com/u/31797554?v=4?s=100\" width=\"100px;\" alt=\"Yegor \u003c3\"/\u003e\u003cbr /\u003e\u003csub\u003e\u003cb\u003eYegor \u003c3\u003c/b\u003e\u003c/sub\u003e\u003c/a\u003e\u003cbr /\u003e\u003ca href=\"https://github.com/infinitered/nsfwjs/commits?author=YegorZaremba\" title=\"Code\"\u003e💻\u003c/a\u003e \u003ca href=\"https://github.com/infinitered/nsfwjs/commits?author=YegorZaremba\" title=\"Tests\"\u003e⚠️\u003c/a\u003e\u003c/td\u003e\n      \u003ctd align=\"center\" valign=\"top\" width=\"14.28%\"\u003e\u003ca href=\"http://navendu.me\"\u003e\u003cimg src=\"https://avatars1.githubusercontent.com/u/49474499?v=4?s=100\" width=\"100px;\" alt=\"Navendu Pottekkat\"/\u003e\u003cbr /\u003e\u003csub\u003e\u003cb\u003eNavendu Pottekkat\u003c/b\u003e\u003c/sub\u003e\u003c/a\u003e\u003cbr /\u003e\u003ca href=\"https://github.com/infinitered/nsfwjs/commits?author=navendu-pottekkat\" title=\"Documentation\"\u003e📖\u003c/a\u003e\u003c/td\u003e\n      \u003ctd align=\"center\" valign=\"top\" width=\"14.28%\"\u003e\u003ca href=\"https://github.com/VladStepanov\"\u003e\u003cimg src=\"https://avatars0.githubusercontent.com/u/49880862?v=4?s=100\" width=\"100px;\" alt=\"Vladislav\"/\u003e\u003cbr /\u003e\u003csub\u003e\u003cb\u003eVladislav\u003c/b\u003e\u003c/sub\u003e\u003c/a\u003e\u003cbr /\u003e\u003ca href=\"https://github.com/infinitered/nsfwjs/commits?author=VladStepanov\" title=\"Code\"\u003e💻\u003c/a\u003e \u003ca href=\"https://github.com/infinitered/nsfwjs/commits?author=VladStepanov\" title=\"Documentation\"\u003e📖\u003c/a\u003e\u003c/td\u003e\n      \u003ctd align=\"center\" valign=\"top\" width=\"14.28%\"\u003e\u003ca href=\"https://github.com/nacht42\"\u003e\u003cimg src=\"https://avatars1.githubusercontent.com/u/37903575?v=4?s=100\" width=\"100px;\" alt=\"Nacht\"/\u003e\u003cbr /\u003e\u003csub\u003e\u003cb\u003eNacht\u003c/b\u003e\u003c/sub\u003e\u003c/a\u003e\u003cbr /\u003e\u003ca href=\"https://github.com/infinitered/nsfwjs/commits?author=nacht42\" title=\"Code\"\u003e💻\u003c/a\u003e\u003c/td\u003e\n      \u003ctd align=\"center\" valign=\"top\" width=\"14.28%\"\u003e\u003ca href=\"https://github.com/kateinkim\"\u003e\u003cimg src=\"https://avatars.githubusercontent.com/u/53795920?v=4?s=100\" width=\"100px;\" alt=\"kateinkim\"/\u003e\u003cbr /\u003e\u003csub\u003e\u003cb\u003ekateinkim\u003c/b\u003e\u003c/sub\u003e\u003c/a\u003e\u003cbr /\u003e\u003ca href=\"https://github.com/infinitered/nsfwjs/commits?author=kateinkim\" title=\"Code\"\u003e💻\u003c/a\u003e \u003ca href=\"https://github.com/infinitered/nsfwjs/commits?author=kateinkim\" title=\"Documentation\"\u003e📖\u003c/a\u003e\u003c/td\u003e\n    \u003c/tr\u003e\n    \u003ctr\u003e\n      \u003ctd align=\"center\" valign=\"top\" width=\"14.28%\"\u003e\u003ca href=\"https://janpoonthong.github.io/portfolio/\"\u003e\u003cimg src=\"https://avatars.githubusercontent.com/u/56725335?v=4?s=100\" width=\"100px;\" alt=\"jan\"/\u003e\u003cbr /\u003e\u003csub\u003e\u003cb\u003ejan\u003c/b\u003e\u003c/sub\u003e\u003c/a\u003e\u003cbr /\u003e\u003ca href=\"https://github.com/infinitered/nsfwjs/commits?author=JanPoonthong\" title=\"Documentation\"\u003e📖\u003c/a\u003e\u003c/td\u003e\n      \u003ctd align=\"center\" valign=\"top\" width=\"14.28%\"\u003e\u003ca href=\"https://github.com/roerohan\"\u003e\u003cimg src=\"https://avatars.githubusercontent.com/u/42958812?v=4?s=100\" width=\"100px;\" alt=\"Rohan Mukherjee\"/\u003e\u003cbr /\u003e\u003csub\u003e\u003cb\u003eRohan Mukherjee\u003c/b\u003e\u003c/sub\u003e\u003c/a\u003e\u003cbr /\u003e\u003ca href=\"#question-roerohan\" title=\"Answering Questions\"\u003e💬\u003c/a\u003e \u003ca href=\"#infra-roerohan\" title=\"Infrastructure (Hosting, Build-Tools, etc)\"\u003e🚇\u003c/a\u003e \u003ca href=\"#maintenance-roerohan\" title=\"Maintenance\"\u003e🚧\u003c/a\u003e \u003ca href=\"https://github.com/infinitered/nsfwjs/commits?author=roerohan\" title=\"Code\"\u003e💻\u003c/a\u003e\u003c/td\u003e\n      \u003ctd align=\"center\" valign=\"top\" width=\"14.28%\"\u003e\u003ca href=\"https://hazya.dev\"\u003e\u003cimg src=\"https://avatars.githubusercontent.com/u/63403456?v=4?s=100\" width=\"100px;\" alt=\"Hasitha Wickramasinghe\"/\u003e\u003cbr /\u003e\u003csub\u003e\u003cb\u003eHasitha Wickramasinghe\u003c/b\u003e\u003c/sub\u003e\u003c/a\u003e\u003cbr /\u003e\u003ca href=\"https://github.com/infinitered/nsfwjs/commits?author=haZya\" title=\"Code\"\u003e💻\u003c/a\u003e \u003ca href=\"https://github.com/infinitered/nsfwjs/commits?author=haZya\" title=\"Documentation\"\u003e📖\u003c/a\u003e \u003ca href=\"#example-haZya\" title=\"Examples\"\u003e💡\u003c/a\u003e \u003ca href=\"#ideas-haZya\" title=\"Ideas, Planning, \u0026 Feedback\"\u003e🤔\u003c/a\u003e \u003ca href=\"#infra-haZya\" title=\"Infrastructure (Hosting, Build-Tools, etc)\"\u003e🚇\u003c/a\u003e \u003ca href=\"https://github.com/infinitered/nsfwjs/commits?author=haZya\" title=\"Tests\"\u003e⚠️\u003c/a\u003e\u003c/td\u003e\n      \u003ctd align=\"center\" valign=\"top\" width=\"14.28%\"\u003e\u003ca href=\"https://github.com/jonmajorc\"\u003e\u003cimg src=\"https://avatars.githubusercontent.com/u/7799266?v=4?s=100\" width=\"100px;\" alt=\"Jon Major Condon\"/\u003e\u003cbr /\u003e\u003csub\u003e\u003cb\u003eJon Major Condon\u003c/b\u003e\u003c/sub\u003e\u003c/a\u003e\u003cbr /\u003e\u003ca href=\"https://github.com/infinitered/nsfwjs/commits?author=jonmajorc\" title=\"Code\"\u003e💻\u003c/a\u003e \u003ca href=\"#infra-jonmajorc\" title=\"Infrastructure (Hosting, Build-Tools, etc)\"\u003e🚇\u003c/a\u003e \u003ca href=\"https://github.com/infinitered/nsfwjs/pulls?q=is%3Apr+reviewed-by%3Ajonmajorc\" title=\"Reviewed Pull Requests\"\u003e👀\u003c/a\u003e\u003c/td\u003e\n    \u003c/tr\u003e\n  \u003c/tbody\u003e\n\u003c/table\u003e\n\n\u003c!-- markdownlint-restore --\u003e\n\u003c!-- prettier-ignore-end --\u003e\n\n\u003c!-- ALL-CONTRIBUTORS-LIST:END --\u003e\n\nThis project follows the [all-contributors](https://github.com/all-contributors/all-contributors) specification. Contributions of any kind welcome!\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Finfinitered%2Fnsfwjs","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Finfinitered%2Fnsfwjs","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Finfinitered%2Fnsfwjs/lists"}