update docs

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`
+
 <br>

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**
 
 <br>
 
-### 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*  
+
+<br>
+
+## 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
+<br>
+
+## 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
+<br>
+
+## 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 @@
 
 <br>
 
-Compatible with *Browser*, *WebWorker* and *NodeJS* execution on both Windows and Linux
+## Default models
 
-- Browser/WebWorker: Compatible with *CPU*, *WebGL*, *WASM* and *WebGPU* backends  
+Default models in Human library are:
-- 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)  
+- **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)
 
 <br>
 
-*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!*  
+
+<br><hr><br>

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:
 

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.version       // string containing version of human library
-  human.defaults      // read-only view of default configuration object
-  human.models        // dynamically maintained list of object of any loaded models
   human.tf            // instance of tfjs used by human
+  human.config        // access to configuration object, normally set as parameter to detect()
   human.state         // <string> describing current operation in progress
                       // progresses through: 'config', 'check', 'backend', 'load', 'run:<model>', '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`: