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# Human Library
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**AI-powered 3D Face Detection & Rotation Tracking, Face Description & Recognition,**
**Body Pose Tracking, 3D Hand & Finger Tracking, Iris Analysis,**
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**Age & Gender & Emotion Prediction, Gaze Tracking, Gesture Recognition, Body Segmentation**
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< br >
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JavaScript module using TensorFlow/JS Machine Learning library
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- **Browser**:
Compatible with both desktop and mobile platforms
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Compatible with *CPU* , *WebGL* , *WASM* backends
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Compatible with *WebWorker* execution
- **NodeJS**:
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Compatible with both software *tfjs-node* and
GPU accelerated backends *tfjs-node-gpu* using CUDA libraries
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< br >
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*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))*
*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*
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- To start video detection, simply press *Play*
- To process images, simply drag & drop in your Browser window
- Note: For optimal performance, select only models you'd like to use
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- Note: If you have modern GPU, WebGL (default) backend is preferred, otherwise select WASM backend
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< br >
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## Releases
- [Release Notes ](https://github.com/vladmandic/human/releases )
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- [NPM Link ](https://www.npmjs.com/package/@vladmandic/human )
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## Demos
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- [**List of all Demo applications** ](https://github.com/vladmandic/human/wiki/Demos )
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- [**Examples galery** ](https://vladmandic.github.io/human/samples/samples.html )
### Browser Demos
- **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
- **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
- **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 simmilarities and matches them to known database
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- **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
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- **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
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- **3D Analysis** [[*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
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- **Virtual Avatar** [[*Live*]](https://vladmandic.github.io/human-vrm/src/human-vrm.html) [[*Details*]](https://github.com/vladmandic/human-vrm): VR model with head, face, eye, body and hand tracking
### NodeJS Demos
- **Main** [[*Details*]](https://github.com/vladmandic/human/tree/main/demo/nodejs): Process images from files, folders or URLs using native methods
- **Canvas** [[*Details*]](https://github.com/vladmandic/human/tree/main/demo/nodejs): Process image from file or URL and draw results to a new image file using `node-canvas`
- **Video** [[*Details*]](https://github.com/vladmandic/human/tree/main/demo/nodejs): Processing of video input using `ffmpeg`
- **WebCam** [[*Details*]](https://github.com/vladmandic/human/tree/main/demo/nodejs): Processing of webcam screenshots using `fswebcam`
- **Events** [[*Details*]](https://github.com/vladmandic/human/tree/main/demo/nodejs): Showcases usage of `Human` eventing to get notifications on processing
- **Similarity** [[*Details*]](https://github.com/vladmandic/human/tree/main/demo/nodejs): Compares two input images for similarity of detected faces
- **Face Match** [[*Details*]](https://github.com/vladmandic/human/tree/main/demo/facematch): Parallel processing of face **match** in multiple child worker threads
- **Multiple Workers** [[*Details*]](https://github.com/vladmandic/human/tree/main/demo/nodejs): Runs multiple parallel `human` by dispaching them to pool of pre-created worker processes
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## Project pages
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- [**Code Repository** ](https://github.com/vladmandic/human )
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- [**NPM Package** ](https://www.npmjs.com/package/@vladmandic/human )
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- [**Issues Tracker** ](https://github.com/vladmandic/human/issues )
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- [**TypeDoc API Specification** ](https://vladmandic.github.io/human/typedoc/classes/Human.html )
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- [**Change Log** ](https://github.com/vladmandic/human/blob/main/CHANGELOG.md )
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- [**Current To-do List** ](https://github.com/vladmandic/human/blob/main/TODO.md )
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## Wiki pages
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- [**Home** ](https://github.com/vladmandic/human/wiki )
- [**Installation** ](https://github.com/vladmandic/human/wiki/Install )
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- [**Usage & Functions** ](https://github.com/vladmandic/human/wiki/Usage )
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- [**Configuration Details** ](https://github.com/vladmandic/human/wiki/Config )
- [**Result Details** ](https://github.com/vladmandic/human/wiki/Result )
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- [**Caching & Smoothing** ](https://github.com/vladmandic/human/wiki/Caching )
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- [**Input Processing** ](https://github.com/vladmandic/human/wiki/Image )
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- [**Face Recognition & Face Description** ](https://github.com/vladmandic/human/wiki/Embedding )
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- [**Gesture Recognition** ](https://github.com/vladmandic/human/wiki/Gesture )
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- [**Common Issues** ](https://github.com/vladmandic/human/wiki/Issues )
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- [**Background and Benchmarks** ](https://github.com/vladmandic/human/wiki/Background )
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## Additional notes
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- [**Comparing Backends** ](https://github.com/vladmandic/human/wiki/Backends )
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- [**Development Server** ](https://github.com/vladmandic/human/wiki/Development-Server )
- [**Build Process** ](https://github.com/vladmandic/human/wiki/Build-Process )
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- [**Adding Custom Modules** ](https://github.com/vladmandic/human/wiki/Module )
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- [**Performance Notes** ](https://github.com/vladmandic/human/wiki/Performance )
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- [**Performance Profiling** ](https://github.com/vladmandic/human/wiki/Profiling )
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- [**Platform Support** ](https://github.com/vladmandic/human/wiki/Platforms )
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- [**Diagnostic and Performance trace information** ](https://github.com/vladmandic/human/wiki/Diag )
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- [**Dockerize Human applications** ](https://github.com/vladmandic/human/wiki/Docker )
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- [**List of Models & Credits** ](https://github.com/vladmandic/human/wiki/Models )
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- [**Models Download Repository** ](https://github.com/vladmandic/human-models )
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- [**Security & Privacy Policy** ](https://github.com/vladmandic/human/blob/main/SECURITY.md )
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- [**License & Usage Restrictions** ](https://github.com/vladmandic/human/blob/main/LICENSE )
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< br >
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*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*
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*Suggestions are welcome!*
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< hr > < br >
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## Examples
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Visit [Examples galery ](https://vladmandic.github.io/human/samples/samples.html ) for more examples
< https: / / vladmandic . github . io / human / samples / samples . html >
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< br >
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## Options
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All options as presented in the demo application...
> [demo/index.html](demo/index.html)
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< br >
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**Results Browser:**
[ *Demo -> Display -> Show Results* ]< br >

< br >
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## Advanced Examples
1. **Face Similarity Matching:**
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Extracts all faces from provided input images,
sorts them by similarity to selected face
and optionally matches detected face with database of known people to guess their names
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> [demo/facematch](demo/facematch/index.html)
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< br >
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2. **Face3D OpenGL Rendering:**
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> [human-motion](https://github.com/vladmandic/human-motion)
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< br >
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3. **VR Model Tracking:**
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> [human-vrmmotion](https://github.com/vladmandic/human-vrm)

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< br >
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**468-Point Face Mesh Defails:**
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(view in full resolution to see keypoints)
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< br > < hr > < br >
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## Quick Start
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Simply load `Human` (*IIFE version*) directly from a cloud CDN in your HTML file:
(pick one: `jsdelirv` , `unpkg` or `cdnjs` )
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```html
< script src = "https://cdn.jsdelivr.net/npm/@vladmandic/human/dist/human.js" > < / script >
< script src = "https://unpkg.dev/@vladmandic/human/dist/human.js" > < / script >
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< script src = "https://cdnjs.cloudflare.com/ajax/libs/human/2.1.5/human.js" > < / script >
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```
For details, including how to use `Browser ESM` version or `NodeJS` version of `Human` , see [**Installation** ](https://github.com/vladmandic/human/wiki/Install )
< br >
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## Inputs
`Human` library can process all known input types:
- `Image` , `ImageData` , `ImageBitmap` , `Canvas` , `OffscreenCanvas` , `Tensor` ,
- `HTMLImageElement` , `HTMLCanvasElement` , `HTMLVideoElement` , `HTMLMediaElement`
Additionally, `HTMLVideoElement` , `HTMLMediaElement` can be a standard `<video>` tag that links to:
- WebCam on user's system
- Any supported video type
For example: `.mp4` , `.avi` , etc.
- Additional video types supported via *HTML5 Media Source Extensions*
Live streaming examples:
- **HLS** (*HTTP Live Streaming*) using `hls.js`
- **DASH** (Dynamic Adaptive Streaming over HTTP) using `dash.js`
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- **WebRTC** media track using built-in support
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< br >
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## Example
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Example simple app that uses Human to process video input and
draw output on screen using internal draw helper functions
```js
// create instance of human with simple configuration using default values
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const config = { backend: 'webgl' };
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const human = new Human(config);
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// select input HTMLVideoElement and output HTMLCanvasElement from page
const inputVideo = document.getElementById('video-id');
const outputCanvas = document.getElementById('canvas-id');
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function detectVideo() {
// perform processing using default configuration
human.detect(inputVideo).then((result) => {
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// result object will contain detected details
// as well as the processed canvas itself
// so lets first draw processed frame on canvas
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human.draw.canvas(result.canvas, outputCanvas);
// then draw results on the same canvas
human.draw.face(outputCanvas, result.face);
human.draw.body(outputCanvas, result.body);
human.draw.hand(outputCanvas, result.hand);
human.draw.gesture(outputCanvas, result.gesture);
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// and loop immediate to the next frame
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requestAnimationFrame(detectVideo);
});
}
detectVideo();
```
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or using `async/await` :
```js
// create instance of human with simple configuration using default values
const config = { backend: 'webgl' };
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const human = new Human(config); // create instance of Human
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const inputVideo = document.getElementById('video-id');
const outputCanvas = document.getElementById('canvas-id');
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async function detectVideo() {
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const result = await human.detect(inputVideo); // run detection
human.draw.all(outputCanvas, result); // draw all results
requestAnimationFrame(detectVideo); // run loop
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}
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detectVideo(); // start loop
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```
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or using `Events` :
```js
// create instance of human with simple configuration using default values
const config = { backend: 'webgl' };
const human = new Human(config); // create instance of Human
const inputVideo = document.getElementById('video-id');
const outputCanvas = document.getElementById('canvas-id');
human.events.addEventListener('detect', () => { // event gets triggered when detect is complete
human.draw.all(outputCanvas, human.result); // draw all results
});
function detectVideo() {
human.detect(inputVideo) // run detection
.then(() => requestAnimationFrame(detectVideo)); // upon detect complete start processing of the next frame
}
detectVideo(); // start loop
```
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or using interpolated results for smooth video processing by separating detection and drawing loops:
```js
const human = new Human(); // create instance of Human
const inputVideo = document.getElementById('video-id');
const outputCanvas = document.getElementById('canvas-id');
let result;
async function detectVideo() {
result = await human.detect(inputVideo); // run detection
requestAnimationFrame(detectVideo); // run detect loop
}
async function drawVideo() {
if (result) { // check if result is available
const interpolated = human.next(result); // calculate next interpolated frame
human.draw.all(outputCanvas, interpolated); // draw the frame
}
requestAnimationFrame(drawVideo); // run draw loop
}
detectVideo(); // start detection loop
drawVideo(); // start draw loop
```
And for even better results, you can run detection in a separate web worker thread
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< br > < hr > < br >
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## Default models
Default models in Human library are:
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- **Face Detection**: MediaPipe BlazeFace Back variation
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- **Face Mesh**: MediaPipe FaceMesh
- **Face Iris Analysis**: MediaPipe Iris
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- **Face Description**: HSE FaceRes
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- **Emotion Detection**: Oarriaga Emotion
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- **Body Analysis**: MoveNet Lightning variation
- **Hand Analysis**: HandTrack & MediaPipe HandLandmarks
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- **Body Segmentation**: Google Selfie
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- **Object Detection**: CenterNet with MobileNet v3
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Note that alternative models are provided and can be enabled via configuration
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For example, `PoseNet` model can be switched for `BlazePose` , `EfficientPose` or `MoveNet` model depending on the use case
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For more info, see [**Configuration Details** ](https://github.com/vladmandic/human/wiki/Configuration ) and [**List of Models** ](https://github.com/vladmandic/human/wiki/Models )
< br > < hr > < br >
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## Diagnostics
- [How to get diagnostic information or performance trace information ](https://github.com/vladmandic/human/wiki/Diag )
< br > < hr > < br >
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`Human` library is written in `TypeScript` [4.5 ](https://www.typescriptlang.org/docs/handbook/intro.html )
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Conforming to latest `JavaScript` [ECMAScript version 2021 ](https://262.ecma-international.org/ ) standard
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Build target is `JavaScript` [EMCAScript version 2018 ](https://262.ecma-international.org/11.0/ )
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< br >
For details see [**Wiki Pages** ](https://github.com/vladmandic/human/wiki )
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and [**API Specification** ](https://vladmandic.github.io/human/typedoc/classes/Human.html )
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< br >
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< br >
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