# Human Library
**3D Face Detection & Rotation Tracking, Face Description & Recognition,**
**Body Pose Tracking, 3D Hand & Finger Tracking,**
**Iris Analysis, Age & Gender & Emotion Prediction,**
**Gesture Recognition**
JavaScript module using TensorFlow/JS Machine Learning library
- **Browser**:
Compatible with both desktop and mobile platforms
Compatible with *CPU*, *WebGL*, *WASM* backends
Compatible with *WebWorker* execution
- **NodeJS**:
Compatible with both software *tfjs-node* and
GPU accelerated backends *tfjs-node-gpu* using CUDA libraries
Check out [**Live Demo**](https://vladmandic.github.io/human/demo/index.html) for processing of live WebCam video or static images
## Demos
- [**Demo Application**](https://vladmandic.github.io/human/demo/index.html)
- [**Face Extraction, Description, Identification and Matching**](https://vladmandic.github.io/human/demo/facematch.html)
- [**Face Extraction and 3D Rendering**](https://vladmandic.github.io/human/demo/face3d.html)
## Project pages
- [**Code Repository**](https://github.com/vladmandic/human)
- [**NPM Package**](https://www.npmjs.com/package/@vladmandic/human)
- [**Issues Tracker**](https://github.com/vladmandic/human/issues)
- [**API Specification**](https://vladmandic.github.io/human/typedoc/classes/human.html)
- [**Change Log**](https://github.com/vladmandic/human/blob/main/CHANGELOG.md)
## Wiki pages
- [**Home**](https://github.com/vladmandic/human/wiki)
- [**Demos**](https://github.com/vladmandic/human/wiki/Demos)
- [**Installation**](https://github.com/vladmandic/human/wiki/Install)
- [**Usage & Functions**](https://github.com/vladmandic/human/wiki/Usage)
- [**Configuration Details**](https://github.com/vladmandic/human/wiki/Configuration)
- [**Output Details**](https://github.com/vladmandic/human/wiki/Outputs)
- [**Face Recognition & Face Description**](https://github.com/vladmandic/human/wiki/Embedding)
- [**Gesture Recognition**](https://github.com/vladmandic/human/wiki/Gesture)
- [**Common Issues**](https://github.com/vladmandic/human/wiki/Issues)
## Additional notes
- [**Notes on Backends**](https://github.com/vladmandic/human/wiki/Backends)
- [**Development Server**](https://github.com/vladmandic/human/wiki/Development-Server)
- [**Build Process**](https://github.com/vladmandic/human/wiki/Build-Process)
- [**Performance Notes**](https://github.com/vladmandic/human/wiki/Performance)
- [**Performance Profiling**](https://github.com/vladmandic/human/wiki/Profiling)
- [**Platform Support**](https://github.com/vladmandic/human/wiki/Platforms)
- [**List of Models & Credits**](https://github.com/vladmandic/human/wiki/Models)
*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*
*Suggestions are welcome!*
## Options
As presented in the demo application...
## Examples
**Training image:**
**Using static images:**
**Live WebCam view:**
**Face Similarity Matching:**
**Face3D OpenGL Rendering:**
**468-Point Face Mesh Defails:**
Example simple app that uses Human to process video input and
draw output on screen using internal draw helper functions
```js
import Human from '@vladmandic/human';
// create instance of human with simple configuration using default values
const config = { backend: 'webgl' };
const human = new Human(config);
function detectVideo() {
// select input HTMLVideoElement and output HTMLCanvasElement from page
const inputVideo = document.getElementById('video-id');
const outputCanvas = document.getElementById('canvas-id');
// perform processing using default configuration
human.detect(inputVideo).then((result) => {
// result object will contain detected details
// as well as the processed canvas itself
// so lets first draw processed frame on canvas
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);
// loop immediate to next frame
requestAnimationFrame(detectVideo);
});
}
detectVideo();
```
## Default models
Default models in Human library are:
- **Face Detection**: MediaPipe BlazeFace-Back
- **Face Mesh**: MediaPipe FaceMesh
- **Face Description**: HSE FaceRes
- **Face Iris Analysis**: MediaPipe Iris
- **Emotion Detection**: Oarriaga Emotion
- **Body Analysis**: PoseNet
Note that alternative models are provided and can be enabled via configuration
For example, `PoseNet` model can be switched for `BlazePose` model depending on the use case
For more info, see [**Configuration Details**](https://github.com/vladmandic/human/wiki/Configuration) and [**List of Models**](https://github.com/vladmandic/human/wiki/Models)
`Human` library is written in `TypeScript` [4.3](https://www.typescriptlang.org/docs/handbook/intro.html)
Conforming to `JavaScript` [ECMAScript version 2020](https://www.ecma-international.org/ecma-262/11.0/index.html) standard
Build target is `JavaScript` **EMCAScript version 2018**
For details see [**Wiki Pages**](https://github.com/vladmandic/human/wiki)
and [**API Specification**](https://vladmandic.github.io/human/typedoc/classes/human.html)
