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thub.com/sponsors/vladmandic)\n![Git Version](https://img.shields.io/github/package-json/v/vladmandic/human?style=flat-square&svg=true&label=git)\n![NPM Version](https://img.shields.io/npm/v/@vladmandic/human.png?style=flat-square)\n![Last Commit](https://img.shields.io/github/last-commit/vladmandic/human?style=flat-square&svg=true)\n![License](https://img.shields.io/github/license/vladmandic/human?style=flat-square&svg=true)\n![GitHub Status Checks](https://img.shields.io/github/checks-status/vladmandic/human/main?style=flat-square&svg=true)\n\n# Human Library\n\n**AI-powered 3D Face Detection & Rotation Tracking, Face Description & Recognition,**  \n**Body Pose Tracking, 3D Hand & Finger Tracking, Iris Analysis,**  \n**Age & Gender & Emotion Prediction, Gaze Tracking, Gesture Recognition, Body Segmentation**  \n\n<br>\n\n## Highlights\n\n- Compatible with most server-side and client-side environments and frameworks  \n- Combines multiple machine learning models which can be switched on-demand depending on the use-case  \n- Related models are executed in an attention pipeline to provide details when needed  \n- Optimized input pre-processing that can enhance image quality of any type of inputs  \n- Detection of frame changes to trigger only required models for improved performance  \n- Intelligent temporal interpolation to provide smooth results regardless of processing performance  \n- Simple unified API  \n- Built-in Image, Video and WebCam handling\n\n[*Jump to Quick Start*](#quick-start)\n\n<br>\n\n## Compatibility\n\n**Browser**:  \n  - Compatible with both desktop and mobile platforms  \n  - Compatible with *WebGPU*, *WebGL*, *WASM*, *CPU* backends  \n  - Compatible with *WebWorker* execution  \n  - Compatible with *WebView*  \n  - Primary platform: *Chromium*-based browsers  \n  - Secondary platform: *Firefox*, *Safari*\n\n**NodeJS**:  \n  - Compatibile with *WASM* backend for executions on architectures where *tensorflow* binaries are not available  \n  - Compatible with *tfjs-node* using software execution via *tensorflow* shared libraries  \n  - Compatible with *tfjs-node* using GPU-accelerated execution via *tensorflow* shared libraries and nVidia CUDA  \n  - Supported versions are from **14.x** to **22.x**  \n  - NodeJS version **23.x** is not supported due to breaking changes and issues with `@tensorflow/tfjs`  \n\n<br>\n\n## Releases\n- [Release Notes](https://github.com/vladmandic/human/releases)\n- [NPM Link](https://www.npmjs.com/package/@vladmandic/human)\n## Demos\n\n*Check out [**Simple Live Demo**](https://vladmandic.github.io/human/demo/typescript/index.html) fully annotated app as a good start starting point ([html](https://github.com/vladmandic/human/blob/main/demo/typescript/index.html))([code](https://github.com/vladmandic/human/blob/main/demo/typescript/index.ts))*  \n\n*Check out [**Main Live Demo**](https://vladmandic.github.io/human/demo/index.html) app for advanced processing of of webcam, video stream or images static images with all possible tunable options*  \n\n- To start video detection, simply press *Play*  \n- To process images, simply drag & drop in your Browser window  \n- Note: For optimal performance, select only models you'd like to use\n- Note: If you have modern GPU, *WebGL* (default) backend is preferred, otherwise select *WASM* backend\n\n<br>\n\n\n- [**List of all Demo applications**](https://github.com/vladmandic/human/wiki/Demos)\n- [**Live Examples galery**](https://vladmandic.github.io/human/samples/index.html)\n\n### Browser Demos\n\n*All browser demos are self-contained without any external dependencies*\n\n- **Full** [[*Live*]](https://vladmandic.github.io/human/demo/index.html) [[*Details*]](https://github.com/vladmandic/human/tree/main/demo): Main browser demo app that showcases all Human capabilities\n- **Simple** [[*Live*]](https://vladmandic.github.io/human/demo/typescript/index.html) [[*Details*]](https://github.com/vladmandic/human/tree/main/demo/typescript): Simple demo in WebCam processing demo in TypeScript\n- **Embedded** [[*Live*]](https://vladmandic.github.io/human/demo/video/index.html) [[*Details*]](https://github.com/vladmandic/human/tree/main/demo/video/index.html): Even simpler demo with tiny code embedded in HTML file\n- **Face Detect** [[*Live*]](https://vladmandic.github.io/human/demo/facedetect/index.html) [[*Details*]](https://github.com/vladmandic/human/tree/main/demo/facedetect): Extract faces from images and processes details\n- **Face Match** [[*Live*]](https://vladmandic.github.io/human/demo/facematch/index.html) [[*Details*]](https://github.com/vladmandic/human/tree/main/demo/facematch): Extract faces from images, calculates face descriptors and similarities and matches them to known database\n- **Face ID** [[*Live*]](https://vladmandic.github.io/human/demo/faceid/index.html) [[*Details*]](https://github.com/vladmandic/human/tree/main/demo/faceid): Runs multiple checks to validate webcam input before performing face match to faces in IndexDB\n- **Multi-thread** [[*Live*]](https://vladmandic.github.io/human/demo/multithread/index.html) [[*Details*]](https://github.com/vladmandic/human/tree/main/demo/multithread): Runs each Human module in a separate web worker for highest possible performance  \n- **NextJS** [[*Live*]](https://vladmandic.github.io/human-next/out/index.html) [[*Details*]](https://github.com/vladmandic/human-next): Use Human with TypeScript, NextJS and ReactJS\n- **ElectronJS** [[*Details*]](https://github.com/vladmandic/human-electron): Use Human with TypeScript and ElectonJS to create standalone cross-platform apps\n- **3D Analysis with BabylonJS** [[*Live*]](https://vladmandic.github.io/human-motion/src/index.html) [[*Details*]](https://github.com/vladmandic/human-motion): 3D tracking and visualization of heead, face, eye, body and hand\n- **VRM Virtual Model Tracking with Three.JS** [[*Live*]](https://vladmandic.github.io/human-three-vrm/src/human-vrm.html) [[*Details*]](https://github.com/vladmandic/human-three-vrm): VR model with head, face, eye, body and hand tracking  \n- **VRM Virtual Model Tracking with BabylonJS** [[*Live*]](https://vladmandic.github.io/human-bjs-vrm/src/index.html) [[*Details*]](https://github.com/vladmandic/human-bjs-vrm): VR model with head, face, eye, body and hand tracking  \n\n### NodeJS Demos\n\n*NodeJS demos may require extra dependencies which are used to decode inputs*  \n*See header of each demo to see its dependencies as they are not automatically installed with `Human`*\n\n- **Main** [[*Details*]](https://github.com/vladmandic/human/tree/main/demo/nodejs/node.js): Process images from files, folders or URLs using native methods  \n- **Canvas** [[*Details*]](https://github.com/vladmandic/human/tree/main/demo/nodejs/node-canvas.js): Process image from file or URL and draw results to a new image file using `node-canvas`  \n- **Video** [[*Details*]](https://github.com/vladmandic/human/tree/main/demo/nodejs/node-video.js): Processing of video input using `ffmpeg`  \n- **WebCam** [[*Details*]](https://github.com/vladmandic/human/tree/main/demo/nodejs/node-webcam.js): Processing of webcam screenshots using `fswebcam`  \n- **Events** [[*Details*]](https://github.com/vladmandic/human/tree/main/demo/nodejs/node-event.js): Showcases usage of `Human` eventing to get notifications on processing\n- **Similarity** [[*Details*]](https://github.com/vladmandic/human/tree/main/demo/nodejs/node-similarity.js): Compares two input images for similarity of detected faces\n- **Face Match** [[*Details*]](https://github.com/vladmandic/human/tree/main/demo/facematch/node-match.js): Parallel processing of face **match** in multiple child worker threads\n- **Multiple Workers** [[*Details*]](https://github.com/vladmandic/human/tree/main/demo/multithread/node-multiprocess.js): Runs multiple parallel `human` by dispaching them to pool of pre-created worker processes  \n- **Dynamic Load** [[*Details*]](https://github.com/vladmandic/human/tree/main/demo/nodejs): Loads Human dynamically with multiple different desired backends  \n\n## Project pages\n\n- [**Code Repository**](https://github.com/vladmandic/human)\n- [**NPM Package**](https://www.npmjs.com/package/@vladmandic/human)\n- [**Issues Tracker**](https://github.com/vladmandic/human/issues)\n- [**TypeDoc API Specification - Main class**](https://vladmandic.github.io/human/typedoc/classes/Human.html)\n- [**TypeDoc API Specification - Full**](https://vladmandic.github.io/human/typedoc/)\n- [**Change Log**](https://github.com/vladmandic/human/blob/main/CHANGELOG.md)\n- [**Current To-do List**](https://github.com/vladmandic/human/blob/main/TODO.md)\n\n## Wiki pages\n\n- [**Home**](https://github.com/vladmandic/human/wiki)\n- [**Installation**](https://github.com/vladmandic/human/wiki/Install)\n- [**Usage & Functions**](https://github.com/vladmandic/human/wiki/Usage)\n- [**Configuration Details**](https://github.com/vladmandic/human/wiki/Config)\n- [**Result Details**](https://github.com/vladmandic/human/wiki/Result)\n- [**Customizing Draw Methods**](https://github.com/vladmandic/human/wiki/Draw)\n- [**Caching & Smoothing**](https://github.com/vladmandic/human/wiki/Caching)\n- [**Input Processing**](https://github.com/vladmandic/human/wiki/Image)\n- [**Face Recognition & Face Description**](https://github.com/vladmandic/human/wiki/Embedding)\n- [**Gesture Recognition**](https://github.com/vladmandic/human/wiki/Gesture)\n- [**Common Issues**](https://github.com/vladmandic/human/wiki/Issues)\n- [**Background and Benchmarks**](https://github.com/vladmandic/human/wiki/Background)\n\n## Additional notes\n\n- [**Comparing Backends**](https://github.com/vladmandic/human/wiki/Backends)\n- [**Development Server**](https://github.com/vladmandic/human/wiki/Development-Server)\n- [**Build Process**](https://github.com/vladmandic/human/wiki/Build-Process)\n- [**Adding Custom Modules**](https://github.com/vladmandic/human/wiki/Module)\n- [**Performance Notes**](https://github.com/vladmandic/human/wiki/Performance)\n- [**Performance Profiling**](https://github.com/vladmandic/human/wiki/Profiling)\n- [**Platform Support**](https://github.com/vladmandic/human/wiki/Platforms)\n- [**Diagnostic and Performance trace information**](https://github.com/vladmandic/human/wiki/Diag)\n- [**Dockerize Human applications**](https://github.com/vladmandic/human/wiki/Docker)\n- [**List of Models & Credits**](https://github.com/vladmandic/human/wiki/Models)\n- [**Models Download Repository**](https://github.com/vladmandic/human-models)\n- [**Security & Privacy Policy**](https://github.com/vladmandic/human/blob/main/SECURITY.md)\n- [**License & Usage Restrictions**](https://github.com/vladmandic/human/blob/main/LICENSE)\n\n<br>\n\n*See [**issues**](https://github.com/vladmandic/human/issues?q=) and [**discussions**](https://github.com/vladmandic/human/discussions) for list of known limitations and planned enhancements*  \n\n*Suggestions are welcome!*  \n\n<hr><br>\n\n## App Examples\n\nVisit [Examples gallery](https://vladmandic.github.io/human/samples/index.html) for more examples  \n[<img src=\"assets/samples.jpg\" width=\"640\"/>](assets/samples.jpg)\n\n<br>\n\n## Options\n\nAll options as presented in the demo application...  \n[demo/index.html](demo/index.html)  \n[<img src=\"assets/screenshot-menu.png\"/>](assets/screenshot-menu.png)\n\n<br>\n\n**Results Browser:**  \n[ *Demo -> Display -> Show Results* ]<br>\n[<img src=\"assets/screenshot-results.png\"/>](assets/screenshot-results.png)\n\n<br>\n\n## Advanced Examples\n\n1. **Face Similarity Matching:**  \nExtracts all faces from provided input images,  \nsorts them by similarity to selected face  \nand optionally matches detected face with database of known people to guess their names\n> [demo/facematch](demo/facematch/index.html)  \n\n[<img src=\"assets/screenshot-facematch.jpg\" width=\"640\"/>](assets/screenshot-facematch.jpg)\n\n2. **Face Detect:**  \nExtracts all detect faces from loaded images on-demand and highlights face details on a selected face  \n> [demo/facedetect](demo/facedetect/index.html)  \n\n[<img src=\"assets/screenshot-facedetect.jpg\" width=\"640\"/>](assets/screenshot-facedetect.jpg)\n\n3. **Face ID:**  \nPerforms validation check on a webcam input to detect a real face and matches it to known faces stored in database\n> [demo/faceid](demo/faceid/index.html)  \n\n[<img src=\"assets/screenshot-faceid.jpg\" width=\"640\"/>](assets/screenshot-faceid.jpg)\n\n<br>\n\n4. **3D Rendering:**  \n> [human-motion](https://github.com/vladmandic/human-motion)\n\n[<img src=\"https://github.com/vladmandic/human-motion/raw/main/assets/screenshot-face.jpg\" width=\"640\"/>](https://github.com/vladmandic/human-motion/raw/main/assets/screenshot-face.jpg)\n[<img src=\"https://github.com/vladmandic/human-motion/raw/main/assets/screenshot-body.jpg\" width=\"640\"/>](https://github.com/vladmandic/human-motion/raw/main/assets/screenshot-body.jpg)\n[<img src=\"https://github.com/vladmandic/human-motion/raw/main/assets/screenshot-hand.jpg\" width=\"640\"/>](https://github.com/vladmandic/human-motion/raw/main/assets/screenshot-hand.jpg)\n\n<br>\n\n5. **VR Model Tracking:**  \n> [human-three-vrm](https://github.com/vladmandic/human-three-vrm)  \n> [human-bjs-vrm](https://github.com/vladmandic/human-bjs-vrm)  \n\n[<img src=\"https://github.com/vladmandic/human-three-vrm/raw/main/assets/human-vrm-screenshot.jpg\" width=\"640\"/>](https://github.com/vladmandic/human-three-vrm/raw/main/assets/human-vrm-screenshot.jpg)\n\n\n6. **Human as OS native application:**\n> [human-electron](https://github.com/vladmandic/human-electron)\n\n<br>\n\n**468-Point Face Mesh Defails:**  \n(view in full resolution to see keypoints)  \n\n[<img src=\"assets/facemesh.png\" width=\"400\"/>](assets/facemesh.png)\n\n<br><hr><br>\n\n## Quick Start\n\nSimply load `Human` (*IIFE version*) directly from a cloud CDN in your HTML file:  \n(pick one: `jsdelirv`, `unpkg` or `cdnjs`)\n\n```html\n<!DOCTYPE HTML>\n<script src=\"https://cdn.jsdelivr.net/npm/@vladmandic/human/dist/human.js\"></script>\n<script src=\"https://unpkg.dev/@vladmandic/human/dist/human.js\"></script>\n<script src=\"https://cdnjs.cloudflare.com/ajax/libs/human/3.0.0/human.js\"></script>\n```\n\nFor details, including how to use `Browser ESM` version or `NodeJS` version of `Human`, see [**Installation**](https://github.com/vladmandic/human/wiki/Install)\n\n<br>\n\n## Code Examples\n\nSimple app that uses Human to process video input and  \ndraw output on screen using internal draw helper functions\n\n```js\n// create instance of human with simple configuration using default values\nconst config = { backend: 'webgl' };\nconst human = new Human.Human(config);\n// select input HTMLVideoElement and output HTMLCanvasElement from page\nconst inputVideo = document.getElementById('video-id');\nconst outputCanvas = document.getElementById('canvas-id');\n\nfunction detectVideo() {\n  // perform processing using default configuration\n  human.detect(inputVideo).then((result) => {\n    // result object will contain detected details\n    // as well as the processed canvas itself\n    // so lets first draw processed frame on canvas\n    human.draw.canvas(result.canvas, outputCanvas);\n    // then draw results on the same canvas\n    human.draw.face(outputCanvas, result.face);\n    human.draw.body(outputCanvas, result.body);\n    human.draw.hand(outputCanvas, result.hand);\n    human.draw.gesture(outputCanvas, result.gesture);\n    // and loop immediate to the next frame\n    requestAnimationFrame(detectVideo);\n    return result;\n  });\n}\n\ndetectVideo();\n```\n\nor using `async/await`:\n\n```js\n// create instance of human with simple configuration using default values\nconst config = { backend: 'webgl' };\nconst human = new Human(config); // create instance of Human\nconst inputVideo = document.getElementById('video-id');\nconst outputCanvas = document.getElementById('canvas-id');\n\nasync function detectVideo() {\n  const result = await human.detect(inputVideo); // run detection\n  human.draw.all(outputCanvas, result); // draw all results\n  requestAnimationFrame(detectVideo); // run loop\n}\n\ndetectVideo(); // start loop\n```\n\nor using `Events`:\n\n```js\n// create instance of human with simple configuration using default values\nconst config = { backend: 'webgl' };\nconst human = new Human(config); // create instance of Human\nconst inputVideo = document.getElementById('video-id');\nconst outputCanvas = document.getElementById('canvas-id');\n\nhuman.events.addEventListener('detect', () => { // event gets triggered when detect is complete\n  human.draw.all(outputCanvas, human.result); // draw all results\n});\n\nfunction detectVideo() {\n  human.detect(inputVideo) // run detection\n    .then(() => requestAnimationFrame(detectVideo)); // upon detect complete start processing of the next frame\n}\n\ndetectVideo(); // start loop\n```\n\nor using interpolated results for smooth video processing by separating detection and drawing loops:\n\n```js\nconst human = new Human(); // create instance of Human\nconst inputVideo = document.getElementById('video-id');\nconst outputCanvas = document.getElementById('canvas-id');\nlet result;\n\nasync function detectVideo() {\n  result = await human.detect(inputVideo); // run detection\n  requestAnimationFrame(detectVideo); // run detect loop\n}\n\nasync function drawVideo() {\n  if (result) { // check if result is available\n    const interpolated = human.next(result); // get smoothened result using last-known results\n    human.draw.all(outputCanvas, interpolated); // draw the frame\n  }\n  requestAnimationFrame(drawVideo); // run draw loop\n}\n\ndetectVideo(); // start detection loop\ndrawVideo(); // start draw loop\n```\n\nor same, but using built-in full video processing instead of running manual frame-by-frame loop:\n\n```js\nconst human = new Human(); // create instance of Human\nconst inputVideo = document.getElementById('video-id');\nconst outputCanvas = document.getElementById('canvas-id');\n\nasync function drawResults() {\n  const interpolated = human.next(); // get smoothened result using last-known results\n  human.draw.all(outputCanvas, interpolated); // draw the frame\n  requestAnimationFrame(drawResults); // run draw loop\n}\n\nhuman.video(inputVideo); // start detection loop which continously updates results\ndrawResults(); // start draw loop\n```\n\nor using built-in webcam helper methods that take care of video handling completely:\n\n```js\nconst human = new Human(); // create instance of Human\nconst outputCanvas = document.getElementById('canvas-id');\n\nasync function drawResults() {\n  const interpolated = human.next(); // get smoothened result using last-known results\n  human.draw.canvas(outputCanvas, human.webcam.element); // draw current webcam frame\n  human.draw.all(outputCanvas, interpolated); // draw the frame detectgion results\n  requestAnimationFrame(drawResults); // run draw loop\n}\n\nawait human.webcam.start({ crop: true });\nhuman.video(human.webcam.element); // start detection loop which continously updates results\ndrawResults(); // start draw loop\n```\n\nAnd for even better results, you can run detection in a separate web worker thread\n\n<br><hr><br>\n\n## Inputs\n\n`Human` library can process all known input types:  \n\n- `Image`, `ImageData`, `ImageBitmap`, `Canvas`, `OffscreenCanvas`, `Tensor`,  \n- `HTMLImageElement`, `HTMLCanvasElement`, `HTMLVideoElement`, `HTMLMediaElement`\n\nAdditionally, `HTMLVideoElement`, `HTMLMediaElement` can be a standard `<video>` tag that links to:\n\n- WebCam on user's system\n- Any supported video type  \n  e.g. `.mp4`, `.avi`, etc.\n- Additional video types supported via *HTML5 Media Source Extensions*  \n  e.g.: **HLS** (*HTTP Live Streaming*) using `hls.js` or **DASH** (*Dynamic Adaptive Streaming over HTTP*) using `dash.js`\n- **WebRTC** media track using built-in support  \n\n<br><hr><br>\n\n## Detailed Usage\n\n- [**Wiki Home**](https://github.com/vladmandic/human/wiki)\n- [**List of all available methods, properies and namespaces**](https://github.com/vladmandic/human/wiki/Usage)\n- [**TypeDoc API Specification - Main class**](https://vladmandic.github.io/human/typedoc/classes/Human.html)\n- [**TypeDoc API Specification - Full**](https://vladmandic.github.io/human/typedoc/)\n\n    ![typedoc](assets/screenshot-typedoc.png)\n\n<br><hr><br>\n\n## TypeDefs\n\n`Human` is written using TypeScript strong typing and ships with full **TypeDefs** for all classes defined by the library bundled in `types/human.d.ts` and enabled by default  \n\n*Note*: This does not include embedded `tfjs`  \nIf you want to use embedded `tfjs` inside `Human` (`human.tf` namespace) and still full **typedefs**, add this code:\n\n> import type * as tfjs from '@vladmandic/human/dist/tfjs.esm';  \n> const tf = human.tf as typeof tfjs;\n\nThis is not enabled by default as `Human` does not ship with full **TFJS TypeDefs** due to size considerations  \nEnabling `tfjs` TypeDefs as above creates additional project (dev-only as only types are required) dependencies as defined in `@vladmandic/human/dist/tfjs.esm.d.ts`:\n\n> @tensorflow/tfjs-core, @tensorflow/tfjs-converter, @tensorflow/tfjs-backend-wasm, @tensorflow/tfjs-backend-webgl\n\n\n<br><hr><br>\n\n## Default models\n\nDefault models in Human library are:\n\n- **Face Detection**: *MediaPipe BlazeFace Back variation*\n- **Face Mesh**: *MediaPipe FaceMesh*\n- **Face Iris Analysis**: *MediaPipe Iris*\n- **Face Description**: *HSE FaceRes*\n- **Emotion Detection**: *Oarriaga Emotion*\n- **Body Analysis**: *MoveNet Lightning variation*\n- **Hand Analysis**: *HandTrack & MediaPipe HandLandmarks*\n- **Body Segmentation**: *Google Selfie*\n- **Object Detection**: *CenterNet with MobileNet v3*\n\nNote that alternative models are provided and can be enabled via configuration  \nFor example, body pose detection by default uses *MoveNet Lightning*, but can be switched to *MultiNet Thunder* for higher precision or *Multinet MultiPose* for multi-person detection or even *PoseNet*, *BlazePose* or *EfficientPose* depending on the use case  \n\nFor more info, see [**Configuration Details**](https://github.com/vladmandic/human/wiki/Configuration) and [**List of Models**](https://github.com/vladmandic/human/wiki/Models)\n\n<br><hr><br>\n\n## Diagnostics\n\n- [How to get diagnostic information or performance trace information](https://github.com/vladmandic/human/wiki/Diag)\n\n<br><hr><br>\n\n`Human` library is written in [TypeScript](https://www.typescriptlang.org/docs/handbook/intro.html) **5.1** using [TensorFlow/JS](https://www.tensorflow.org/js/) **4.10** and conforming to latest `JavaScript` [ECMAScript version 2022](https://262.ecma-international.org/) standard  \n\nBuild target for distributables is `JavaScript` [EMCAScript version 2018](https://262.ecma-international.org/9.0/)  \n\n<br>\n\nFor details see [**Wiki Pages**](https://github.com/vladmandic/human/wiki)  \nand [**API Specification**](https://vladmandic.github.io/human/typedoc/classes/Human.html)\n\n<br>\n\n[![](https://img.shields.io/static/v1?label=Sponsor&message=%E2%9D%A4&logo=GitHub&color=%23fe8e86)](https://github.com/sponsors/vladmandic)\n![Stars](https://img.shields.io/github/stars/vladmandic/human?style=flat-square&svg=true)\n![Forks](https://badgen.net/github/forks/vladmandic/human)\n![Code Size](https://img.shields.io/github/languages/code-size/vladmandic/human?style=flat-square&svg=true)\n![CDN](https://data.jsdelivr.com/v1/package/npm/@vladmandic/human/badge)<br>\n![Downloads](https://img.shields.io/npm/dw/@vladmandic/human.png?style=flat-square)\n![Downloads](https://img.shields.io/npm/dm/@vladmandic/human.png?style=flat-square)\n![Downloads](https://img.shields.io/npm/dy/@vladmandic/human.png?style=flat-square)","users":{}}