diff --git a/Demos.md b/Demos.md index be443e0..5b15013 100644 --- a/Demos.md +++ b/Demos.md @@ -194,4 +194,41 @@ found 0 vulnerabilities ... ``` +## Human as a Daemon + +If you want to run `Human` as a `systemd` service on `Linux`, +take a look at included sample `human.service` file and +modify NodeJS path in `ExecStart` and your working folder in `WorkingDirectory` + +```text +[Unit] +Description=human +After=network.target network-online.target + +[Service] +Type=simple +Environment="NODE_ENV=production" +ExecStart=/home/vlado/.nvm/versions/node/v15.7.0/bin/node server/serve.js +WorkingDirectory=/home/vlado/dev/human +StandardOutput=inherit +StandardError=inherit +Restart=always +RestartSec=300 +User=vlado +StandardOutput=null + +[Install] +WantedBy=multi-user.target +``` + +To activate service: + +- copy the content to your `/etc/systemd/system` folder +- reload service configuration: `sudo systemctl daemon-reload` +- start service with: `sudo systemctl start human` +- stop service with: `sudo systemctl stop human` +- check status with: `sudo systemctl status human` +- to run service on system startup: `sudo systemctl enable human` +- to disable running service on system startup: `sudo systemctl disable human` +
diff --git a/Home.md b/Home.md index a5ca7bd..2835cd9 100644 --- a/Home.md +++ b/Home.md @@ -1,18 +1,31 @@ # Human Library -## 3D Face Detection, Face Embedding & Recognition, Body Pose Tracking, Hand & Finger Tracking, Iris Analysis, Age & Gender & Emotion Prediction & Gesture Recognition +**3D Face Detection & Rotation Tracking, Face Embedding & Recognition,** +**Body Pose Tracking, Hand & Finger Tracking,** +**Iris Analysis, Age & Gender & Emotion Prediction** +**& Gesture Recognition**
-### Project pages +Native JavaScript module using TensorFlow/JS Machine Learning library +Compatible with *Browser*, *WebWorker* and *NodeJS* execution on both Windows and Linux -- [**Live Demo**](https://vladmandic.github.io/human/demo/index.html) +- Browser/WebWorker: Compatible with *CPU*, *WebGL*, *WASM* and *WebGPU* backends +- NodeJS: Compatible with software *tfjs-node* and CUDA accelerated backends *tfjs-node-gpu* + +
+ +## Project pages + +- [**Live Demo**](https://vladmandic.github.io/human/demo/index.html) - [**Code Repository**](https://github.com/vladmandic/human) - [**NPM Package**](https://www.npmjs.com/package/@vladmandic/human) - [**Issues Tracker**](https://github.com/vladmandic/human/issues) - [**Change Log**](https://github.com/vladmandic/human/CHANGELOG.md) -### Wiki pages +
+ +## Wiki pages - [**Home**](https://github.com/vladmandic/human/wiki) - [**Demos**](https://github.com/vladmandic/human/wiki/Demos) @@ -23,7 +36,9 @@ - [**Face Embedding and Recognition**](https://github.com/vladmandic/human/wiki/Embedding) - [**Gesture Recognition**](https://github.com/vladmandic/human/wiki/Gesture) -### Additional notes +
+ +## Additional notes - [**Notes on Backends**](https://github.com/vladmandic/human/wiki/Backends) - [**Development Server**](https://github.com/vladmandic/human/wiki/Development-Server) @@ -35,14 +50,28 @@
-Compatible with *Browser*, *WebWorker* and *NodeJS* execution on both Windows and Linux +## Default models -- Browser/WebWorker: Compatible with *CPU*, *WebGL*, *WASM* and *WebGPU* backends -- NodeJS: Compatible with software *tfjs-node* and CUDA accelerated backends *tfjs-node-gpu* -- (and maybe with React-Native as it doesn't use any DOM objects) +Default models in Human library are: + +- **Face Detection**: MediaPipe BlazeFace-Back +- **Face Mesh**: MediaPipe FaceMesh +- **Face Iris Analysis**: MediaPipe Iris +- **Emotion Detection**: Oarriaga Emotion +- **Gender Detection**: Oarriaga Gender +- **Age Detection**: SSR-Net Age IMDB +- **Body Analysis**: PoseNet +- **Face Embedding**: Sirius-AI MobileFaceNet Embedding + +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)
-*This is a pre-release project, see [issues](https://github.com/vladmandic/human/issues) for list of known limitations and planned enhancements* +*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!* + +

diff --git a/Profiling.md b/Profiling.md index 945459a..c0064c5 100644 --- a/Profiling.md +++ b/Profiling.md @@ -1,6 +1,6 @@ # Profiling -If `config.profile` is enabled, call to `human.profile()` will return detailed profiling data from the last detect invokation. +If `config.profile` is enabled, call to `human.profileData()` will return detailed profiling data from the last detect invokation. example: diff --git a/Usage.md b/Usage.md index cc9bda5..08e787a 100644 --- a/Usage.md +++ b/Usage.md @@ -26,12 +26,12 @@ or if you want to use promises Additionally, `Human` library exposes several objects and methods: ```js - human.config // access to configuration object, normally set as parameter to detect() - human.defaults // read-only view of default configuration object - human.models // dynamically maintained list of object of any loaded models + human.version // string containing version of human library human.tf // instance of tfjs used by human + human.config // access to configuration object, normally set as parameter to detect() human.state // describing current operation in progress // progresses through: 'config', 'check', 'backend', 'load', 'run:', 'idle' + human.sysinfo // object containing current client platform and agent human.load(config) // explicitly call load method that loads configured models // if you want to pre-load them instead of on-demand loading during 'human.detect()' human.image(image, config?) // runs image processing without detection and returns canvas @@ -40,6 +40,8 @@ Additionally, `Human` library exposes several objects and methods: human.simmilarity(embedding1, embedding2) // runs simmilarity calculation between two provided embedding vectors // vectors for source and target must be previously detected using // face.embedding module + human.models // dynamically maintained list of object of any loaded models + human.classes // dynamically maintained list of classes that perform detection on each model ``` Plus additional helper functions inside `human.draw`: