mirror of https://github.com/vladmandic/human
459 lines
22 KiB
Markdown
459 lines
22 KiB
Markdown
[](https://github.com/sponsors/vladmandic)
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# Human Library
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**AI-powered 3D Face Detection & Rotation Tracking, Face Description & Recognition,**
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**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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## Highlights
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- Compatible with most server-side and client-side environments and frameworks
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- Combines multiple machine learning models which can be switched on-demand depending on the use-case
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- Related models are executed in an attention pipeline to provide details when needed
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- Optimized input pre-processing that can enhance image quality of any type of inputs
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- Detection of frame changes to trigger only required models for improved performance
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- Intelligent temporal interpolation to provide smooth results regardless of processing performance
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- Simple unified API
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- Built-in Image, Video and WebCam handling
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<br>
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## Compatibility
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- **Browser**:
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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
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Compatible with *WebView*
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- **NodeJS**:
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Compatibile with *WASM* backend for executions on architectures where *tensorflow* binaries are not available
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Compatible with *tfjs-node* using software execution via *tensorflow* shared libraries
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Compatible with *tfjs-node* using GPU-accelerated execution via *tensorflow* shared libraries and nVidia CUDA
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<br>
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## Releases
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- [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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*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))*
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*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*
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- To process images, simply drag & drop in your Browser window
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- 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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- [**List of all Demo applications**](https://github.com/vladmandic/human/wiki/Demos)
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- [**Live Examples galery**](https://vladmandic.github.io/human/samples/index.html)
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### Browser Demos
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*All browser demos are self-contained without any external dependencies*
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- **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
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- **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
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- **Embedded** [[*Live*]](https://vladmandic.github.io/human/demo/video/index.html) [[*Details*]](https://github.com/vladmandic/human/tree/main/video/index.html): Even simpler demo with tiny code embedded in HTML file
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- **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
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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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- **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
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- **ElectronJS** [[*Details*]](https://github.com/vladmandic/human-electron): Use Human with TypeScript and ElectonJS to create standalone cross-platform apps
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- **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
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- **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
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- **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
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### NodeJS Demos
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*NodeJS demos may require extra dependencies which are used to decode inputs*
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*See header of each demo to see its dependencies as they are not automatically installed with `Human`*
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- **Main** [[*Details*]](https://github.com/vladmandic/human/tree/main/demo/nodejs): Process images from files, folders or URLs using native methods
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- **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`
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- **Video** [[*Details*]](https://github.com/vladmandic/human/tree/main/demo/nodejs): Processing of video input using `ffmpeg`
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- **WebCam** [[*Details*]](https://github.com/vladmandic/human/tree/main/demo/nodejs): Processing of webcam screenshots using `fswebcam`
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- **Events** [[*Details*]](https://github.com/vladmandic/human/tree/main/demo/nodejs): Showcases usage of `Human` eventing to get notifications on processing
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- **Similarity** [[*Details*]](https://github.com/vladmandic/human/tree/main/demo/nodejs): Compares two input images for similarity of detected faces
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- **Face Match** [[*Details*]](https://github.com/vladmandic/human/tree/main/demo/facematch): Parallel processing of face **match** in multiple child worker threads
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- **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 - Main class**](https://vladmandic.github.io/human/typedoc/classes/Human.html)
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- [**TypeDoc API Specification - Full**](https://vladmandic.github.io/human/typedoc/)
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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)
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- [**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)
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- [**Result Details**](https://github.com/vladmandic/human/wiki/Result)
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- [**Customizing Draw Methods**](https://github.com/vladmandic/human/wiki/Draw)
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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)
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- [**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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## App Examples
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Visit [Examples gallery](https://vladmandic.github.io/human/samples/index.html) for more examples
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<https://vladmandic.github.io/human/samples/index.html>
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<br>
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## Options
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All options as presented in the demo application...
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> [demo/index.html](demo/index.html)
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<br>
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**Results Browser:**
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[ *Demo -> Display -> Show Results* ]<br>
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<br>
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## Advanced Examples
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1. **Face Similarity Matching:**
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Extracts all faces from provided input images,
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sorts them by similarity to selected face
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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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2. **Face ID:**
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Performs validation check on a webcam input to detect a real face and matches it to known faces stored in database
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> [demo/faceid](demo/faceid/index.html)
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<br>
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3. **3D Rendering:**
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> [human-motion](https://github.com/vladmandic/human-motion)
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<br>
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4. **VR Model Tracking:**
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> [human-three-vrm](https://github.com/vladmandic/human-three-vrm)
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> [human-bjs-vrm](https://github.com/vladmandic/human-bjs-vrm)
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5. **Human as OS native application:**
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> [human-electron](https://github.com/vladmandic/human-electron)
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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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[<img src="assets/facemesh.png" width="400"/>](assets/facemesh.png)
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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:
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(pick one: `jsdelirv`, `unpkg` or `cdnjs`)
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```html
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<!DOCTYPE HTML>
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<script src="https://cdn.jsdelivr.net/npm/@vladmandic/human/dist/human.js"></script>
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<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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```
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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)
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<br>
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## Inputs
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`Human` library can process all known input types:
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- `Image`, `ImageData`, `ImageBitmap`, `Canvas`, `OffscreenCanvas`, `Tensor`,
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- `HTMLImageElement`, `HTMLCanvasElement`, `HTMLVideoElement`, `HTMLMediaElement`
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Additionally, `HTMLVideoElement`, `HTMLMediaElement` can be a standard `<video>` tag that links to:
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- WebCam on user's system
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- Any supported video type
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e.g. `.mp4`, `.avi`, etc.
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- Additional video types supported via *HTML5 Media Source Extensions*
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e.g.: **HLS** (*HTTP Live Streaming*) using `hls.js` or **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><hr><br>
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## Code Examples
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Simple app that uses Human to process video input and
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draw output on screen using internal draw helper functions
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```js
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// 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
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const inputVideo = document.getElementById('video-id');
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const outputCanvas = document.getElementById('canvas-id');
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function detectVideo() {
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// perform processing using default configuration
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human.detect(inputVideo).then((result) => {
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// result object will contain detected details
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// as well as the processed canvas itself
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// so lets first draw processed frame on canvas
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human.draw.canvas(result.canvas, outputCanvas);
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// then draw results on the same canvas
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human.draw.face(outputCanvas, result.face);
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human.draw.body(outputCanvas, result.body);
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human.draw.hand(outputCanvas, result.hand);
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human.draw.gesture(outputCanvas, result.gesture);
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// and loop immediate to the next frame
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requestAnimationFrame(detectVideo);
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return result;
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});
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}
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detectVideo();
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```
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or using `async/await`:
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```js
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// 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); // create instance of Human
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const inputVideo = document.getElementById('video-id');
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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
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human.draw.all(outputCanvas, result); // draw all results
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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`:
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```js
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// 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); // create instance of Human
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const inputVideo = document.getElementById('video-id');
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const outputCanvas = document.getElementById('canvas-id');
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human.events.addEventListener('detect', () => { // event gets triggered when detect is complete
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human.draw.all(outputCanvas, human.result); // draw all results
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});
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function detectVideo() {
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human.detect(inputVideo) // run detection
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.then(() => requestAnimationFrame(detectVideo)); // upon detect complete start processing of the next frame
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}
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detectVideo(); // start loop
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```
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or using interpolated results for smooth video processing by separating detection and drawing loops:
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```js
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const human = new Human(); // create instance of Human
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const inputVideo = document.getElementById('video-id');
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const outputCanvas = document.getElementById('canvas-id');
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let result;
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async function detectVideo() {
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result = await human.detect(inputVideo); // run detection
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requestAnimationFrame(detectVideo); // run detect loop
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}
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async function drawVideo() {
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if (result) { // check if result is available
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const interpolated = human.next(result); // get smoothened result using last-known results
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human.draw.all(outputCanvas, interpolated); // draw the frame
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}
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requestAnimationFrame(drawVideo); // run draw loop
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}
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detectVideo(); // start detection loop
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drawVideo(); // start draw loop
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```
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or same, but using built-in full video processing instead of running manual frame-by-frame loop:
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```js
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const human = new Human(); // create instance of Human
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const inputVideo = document.getElementById('video-id');
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const outputCanvas = document.getElementById('canvas-id');
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async function drawResults() {
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const interpolated = human.next(); // get smoothened result using last-known results
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human.draw.all(outputCanvas, interpolated); // draw the frame
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requestAnimationFrame(drawResults); // run draw loop
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}
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human.video(inputVideo); // start detection loop which continously updates results
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drawResults(); // start draw loop
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```
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or using built-in webcam helper methods that take care of video handling completely:
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```js
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const human = new Human(); // create instance of Human
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const outputCanvas = document.getElementById('canvas-id');
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async function drawResults() {
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const interpolated = human.next(); // get smoothened result using last-known results
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human.draw.canvas(outputCanvas, human.webcam.element); // draw current webcam frame
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human.draw.all(outputCanvas, interpolated); // draw the frame detectgion results
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requestAnimationFrame(drawResults); // run draw loop
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}
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await human.webcam.start({ crop: true });
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human.video(human.webcam.element); // start detection loop which continously updates results
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drawResults(); // start draw loop
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```
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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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## Detailed Usage
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- [**Wiki Home**](https://github.com/vladmandic/human/wiki)
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- [**List of all available methods, properies and namespaces**](https://github.com/vladmandic/human/wiki/Usage)
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- [**TypeDoc API Specification - Main class**](https://vladmandic.github.io/human/typedoc/classes/Human.html)
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- [**TypeDoc API Specification - Full**](https://vladmandic.github.io/human/typedoc/)
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<br><hr><br>
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## TypeDefs
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`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
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*Note*: This does not include embedded `tfjs`
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If you want to use embedded `tfjs` inside `Human` (`human.tf` namespace) and still full **typedefs**, add this code:
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> import type * as tfjs from '@vladmandic/human/dist/tfjs.esm';
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> const tf = human.tf as typeof tfjs;
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This is not enabled by default as `Human` does not ship with full **TFJS TypeDefs** due to size considerations
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Enabling `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`:
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> @tensorflow/tfjs-core, @tensorflow/tfjs-converter, @tensorflow/tfjs-backend-wasm, @tensorflow/tfjs-backend-webgl
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<br><hr><br>
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## Default models
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Default models in Human library are:
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- **Face Detection**: *MediaPipe BlazeFace Back variation*
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- **Face Mesh**: *MediaPipe FaceMesh*
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- **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*
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- **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, 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
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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)
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<br><hr><br>
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## Diagnostics
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- [How to get diagnostic information or performance trace information](https://github.com/vladmandic/human/wiki/Diag)
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<br><hr><br>
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`Human` library is written in [TypeScript](https://www.typescriptlang.org/docs/handbook/intro.html) **4.9** using [TensorFlow/JS](https://www.tensorflow.org/js/) **4.0** and conforming to latest `JavaScript` [ECMAScript version 2022](https://262.ecma-international.org/) standard
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Build target for distributables is `JavaScript` [EMCAScript version 2018](https://262.ecma-international.org/9.0/)
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<br>
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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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[](https://github.com/sponsors/vladmandic)
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<br>
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