From c7ad6efe38e79ab1118c42e72e42af9c20c2d751 Mon Sep 17 00:00:00 2001
From: Vladimir Mandic <mandic00@live.com>
Date: Sat, 7 Nov 2020 09:39:54 -0500
Subject: [PATCH] created wiki

---
 CHANGELOG.md | 170 ---------------
 README.md    | 585 ++-------------------------------------------------
 changelog.js |   2 +-
 package.json |   1 +
 wiki         |   1 +
 5 files changed, 26 insertions(+), 733 deletions(-)
 delete mode 100644 CHANGELOG.md
 create mode 160000 wiki

diff --git a/CHANGELOG.md b/CHANGELOG.md
deleted file mode 100644
index 7924105f..00000000
--- a/CHANGELOG.md
+++ /dev/null
@@ -1,170 +0,0 @@
-
-# @vladmandic/human  
-
-Version: **0.7.3**  
-Description: **human: 3D Face Detection, Body Pose, Hand & Finger Tracking, Iris Tracking, Age & Gender Prediction, Emotion Prediction & Gesture Recognition**  
-
-Author: **Vladimir Mandic <mandic00@live.com>**  
-License: **MIT** </LICENSE>  
-Repository: **<git+https://github.com/vladmandic/human.git>**  
-
-## Changelog
-
-### **HEAD -> main** 2020/11/05 mandic00@live.com
-
-### **0.7.3** 2020/11/05 mandic00@live.com
-- optimized camera and mobile layout
-- fixed worker and filter compatibility
-- removed test code
-
-### **0.7.2** 2020/11/04 mandic00@live.com
-- major work on handpose model
-
-### **0.7.1** 2020/11/04 mandic00@live.com
-- changed demo build process
-
-### **0.6.7** 2020/11/04 mandic00@live.com
-- implemented simple gesture recognition
-
-### **0.6.6** 2020/11/04 mandic00@live.com
-- remove debug code
-
-### **0.6.5** 2020/11/04 mandic00@live.com
-- redo hand detection
-
-### **0.6.4** 2020/11/03 mandic00@live.com
-- added manifest
-
-### **0.6.3** 2020/11/03 mandic00@live.com
-- enhanced processing resolution
-- fix pause restart
-- complete model refactoring
-- fixed typo
-
-### **0.6.2** 2020/11/02 mandic00@live.com
-- optimized demo
-- package update
-
-### **0.6.1** 2020/11/02 mandic00@live.com
-- major performance improvements for all models
-- revert "optimized canvas handling"
-- optimized canvas handling
-- minor optimization to imagefx
-- fix demo image sample
-- added tfjs-vis to distribution
-
-### **0.5.5** 2020/11/01 mandic00@live.com
-- changed defaults
-
-### **0.5.4** 2020/11/01 mandic00@live.com
-- implemented memory profiler
-
-### **0.5.3** 2020/10/30 mandic00@live.com
-- improved debug logging
-
-### **0.5.2** 2020/10/30 mandic00@live.com
-- added wasm and webgpu backends
-
-### **0.5.1** 2020/10/30 mandic00@live.com
-- improve demo line continous draws
-
-### **0.4.10** 2020/10/30 mandic00@live.com
-- fix for seedrandom
-
-### **0.4.9** 2020/10/29 mandic00@live.com
-
-### **0.4.8** 2020/10/28 mandic00@live.com
-- revert "updated menu handler"
-- fix webpack compatibility issue
-
-### **0.4.7** 2020/10/27 mandic00@live.com
-
-### **0.4.6** 2020/10/27 mandic00@live.com
-- fix firefox compatibility bug
-
-### **0.4.5** 2020/10/27 mandic00@live.com
-
-### **0.4.4** 2020/10/27 mandic00@live.com
-- implelented input resizing
-
-### **0.4.3** 2020/10/22 mandic00@live.com
-
-### **0.4.2** 2020/10/20 mandic00@live.com
-- log initialization
-
-### **0.4.1** 2020/10/19 mandic00@live.com
-- breaking change: convert to object class
-- compatibility notes
-
-### **0.3.9** 2020/10/18 mandic00@live.com
-- implemented image filters
-- pure tensor pipeline without image converts
-- autodetect skipframes
-
-### **0.3.8** 2020/10/17 mandic00@live.com
-- new menu layout
-
-### **0.3.7** 2020/10/17 mandic00@live.com
-- added diagnostics output
-- parallelized agegender operations
-
-### **0.3.6** 2020/10/17 mandic00@live.com
-- fixed webcam initialization
-- fixed memory leaks and added scoped runs
-- modularized draw
-- added state handling
-- refactored package file layout
-
-### **0.3.5** 2020/10/16 mandic00@live.com
-- added auto-generated changelog
-
-### **0.3.4** 2020/10/16 mandic00@live.com
-- added camera selection
-- optimized blazeface anchors
-- added error handling
-
-### **0.3.3** 2020/10/15 mandic00@live.com
-- added blazeface back and front models
-
-### **0.3.2** 2020/10/15 mandic00@live.com
-- reduced web worker latency
-- added debugging and versioning
-- optimized demos and added scoped runs
-- added multi backend support
-
-### **0.3.1** 2020/10/14 mandic00@live.com
-
-### **0.2.10** 2020/10/14 mandic00@live.com
-- added emotion backend
-- module parametrization and performance monitoring
-- implemented multi-hand support
-- fixed documentation typos
-
-### **0.2.9** 2020/10/13 mandic00@live.com
-- added node build and demo
-
-### **0.2.8** 2020/10/13 mandic00@live.com
-- added example image
-
-### **0.2.7** 2020/10/13 mandic00@live.com
-- new examples
-
-### **0.2.6** 2020/10/13 mandic00@live.com
-- enable all models by default
-
-### **0.2.5** 2020/10/12 mandic00@live.com
-- fixed memory leak
-
-### **0.2.4** 2020/10/12 mandic00@live.com
-- removed extra files
-
-### **0.2.3** 2020/10/12 mandic00@live.com
-
-### **0.2.2** 2020/10/12 mandic00@live.com
-
-### **tag: 1.0** 2020/10/12 mandic00@live.com
-
-### **0.2.1** 2020/10/12 mandic00@live.com
-- added sample image
-- initial public commit
-- initial commit
diff --git a/README.md b/README.md
index 5597d93d..ac5ee664 100644
--- a/README.md
+++ b/README.md
@@ -2,69 +2,39 @@
 
 ## 3D Face Detection, Body Pose, Hand & Finger Tracking, Iris Tracking, Age & Gender Prediction, Emotion Prediction & Gesture Recognition
 
-- [**Documentation**](https://github.com/vladmandic/human#readme)
+### 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**](./CHANGELOG.md)
-- [**Live Demo**](https://vladmandic.github.io/human/demo/index.html)
+- [**Change Log**](https://github.com/vladmandic/human/wiki/Change-Log)
+
+### Wiki pages:
+
+- [**Home**](wiki)
+- [**Installation**](wiki/Install)
+- [**Usage**](wiki/Usage)
+- [**Configuration**](wiki/Configuration)
+- [**Outputs**](wiki/Outputs)
+- [**Demos**](wiki/Demos)
+- [**Development Server**](wiki/Development-Server)
+- [**Build Process**](wiki/Build-Process)
+- [**Profiling**](wiki/Profiling)
+- [**Performance Notes**](wiki/Performance)
+- [**Credits**](wiki/Credits)
 
 Compatible with *Browser*, *WebWorker* and *NodeJS* execution  
-Compatible with *CPU*, *WebGL*, *WASM* and *WebGPU* backends  
+- Browser/WebWorker: Compatible with *CPU*, *WebGL*, *WASM* and *WebGPU* backends  
+- NodeJS: Compatible with software *tfjs-node* and CUSA accelerated backends *tfjs-node-gpu*  
+
 (and maybe with React-Native as it doesn't use any DOM objects)  
 
 *This is a pre-release project, see [issues](https://github.com/vladmandic/human/issues) for list of known limitations and planned enhancements*  
 
-*Suggestions are welcome!*
+*Suggestions are welcome!*  
 
-<hr>
-
-## Demo
-
-Demos are included in `/demo`:
-
-**Browser**:
-- `index.html`: Full demo using Browser with ESM module, includes selectable backends and webworkers  
-  it loads `dist/demo-browser-index.js` which is built from sources in `demo`, starting with `demo/browser`  
-  alternatively you can load `demo/browser.js` directly  
-
-*You can run browser demo either live from git pages, by serving demo folder from your web server or use  
-included micro http2 server with source file monitoring and dynamic rebuild*
-
-### Dev Server
-
-To start micro http2 dev server, you must provide your own SSL certificate (production or self-signed)  
-and place them in `dev-server.js`  
-
-Once SSL certificates have been provided, simply run  
-```shell
-npm run dev
-```  
-On first start, it will install all development dependencies required to rebuild `Human` library  
-
-```log
-> @vladmandic/human@0.7.5 dev /home/vlado/dev/human
-> npm install && node --trace-warnings --unhandled-rejections=strict --trace-uncaught --no-deprecation dev-server.js
-
-audited 321 packages in 2.506s
-found 0 vulnerabilities
-
-2020-11-06 16:19:09 INFO:  @vladmandic/human version 0.7.5
-2020-11-06 16:19:09 INFO:  User: vlado Platform: linux Arch: x64 Node: v15.0.1
-2020-11-06 16:19:09 STATE:  HTTP2 server listening: 8000
-2020-11-06 16:19:09 STATE:  Monitoring: [ 'package.json', 'config.js', 'demo', 'src', [length]: 4 ]
-2020-11-06 16:19:16 DATA:  GET/2.0 200 text/html 4866 / ::ffff:192.168.0.200
-2020-11-06 16:19:16 DATA:  GET/2.0 200 text/javascript 1708910 /dist/demo-browser-index.js ::ffff:192.168.0.200
-```
-
-*If you want to test `wasm` or `webgpu` backends, enable loading in `index.html`*
-
-**NodeJS**:
-- `node.js`: Demo using NodeJS with CommonJS module  
-  This is a very simple demo as althought `Human` library is compatible with NodeJS execution  
-  and is able to load images and models from local filesystem,  
-
-<hr>
+<hr>  
 
 ## Examples
 
@@ -74,512 +44,3 @@ found 0 vulnerabilities
 **Using webcam:**  
 ![Example Using WebCam](assets/screenshot2.jpg)
 
-<hr>
-
-## Installation
-
-**Important**  
-*The packaged (IIFE and ESM) version of `Human` includes `TensorFlow/JS (TFJS) 2.7.0` library which can be accessed via `human.tf`*  
-*You should NOT manually load another instance of `tfjs`, but if you do, be aware of possible version conflicts*  
-
-There are multiple ways to use `Human` library, pick one that suits you:
-
-### Included
-
-- `dist/human.js`: IIFE format bundle with TFJS for Browsers
-- `dist/human.esm.js`: ESM format bundle with TFJS for Browsers
-- `dist/human.esm-nobundle.js`: ESM format bundle without TFJS for Browsers
-- `dist/human.node.js`: CommonJS format bundle with TFJS for NodeJS
-- `dist/human.node-nobundle.js`: CommonJS format bundle without TFJS for NodeJS
-
-All versions include `sourcemap` *(.map)* and build `manifest` *(.json)*  
-While `Human` is in pre-release mode, all bundles are non-minified  
-
-Defaults:
-```json
-  {
-    "main": "dist/human.node.js",
-    "module": "dist/human.esm.js",
-    "browser": "dist/human.esm.js",
-  }
-```
-
-### 1. [IIFE](https://developer.mozilla.org/en-US/docs/Glossary/IIFE) script
-
-*Simplest way for usage within Browser*
-
-Simply download `dist/human.js`, include it in your `HTML` file & it's ready to use.
-
-```html
-  <script src="dist/human.js"><script>
-``` 
-
-IIFE script auto-registers global namespace `Human` within global `Window` object  
-Which you can use to create instance of `human` library: 
-
-```js
-  const human = new Human();
-```
-
-This way you can also use `Human` library within embbedded `<script>` tag within your `html` page for all-in-one approach  
-
-### 2. [ESM](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Statements/import) module
-
-*Recommended for usage within `Browser`*  
-
-#### **2.1 Using Script Module**
-You could use same syntax within your main `JS` file if it's imported with `<script type="module">`  
-
-```html
-  <script src="./index.js" type="module">
-```
-and then in your `index.js`
-
-```js
-  import Human from 'dist/human.esm.js'; // for direct import must use path to module, not package name
-  const human = new Human();
-```
-
-#### **2.2 With Bundler**
-
-If you're using bundler *(such as rollup, webpack, parcel, browserify, esbuild)*  to package your client application,  
-you can import ESM version of `Human` library which supports full tree shaking  
-
-Install with:
-```shell
-  npm install @vladmandic/human
-```
-```js
-  import Human from '@vladmandic/human'; // points to @vladmandic/human/dist/human.esm.js
-                                         // you can also force-load specific version
-                                         // for example: `@vladmandic/human/dist/human.esm-nobundle.js`
-  const human = new Human();
-```
-
-Or if you prefer to package your version of `tfjs`, you can use `nobundle` version
-
-Install with:
-```shell
-  npm install @vladmandic/human @tensorflow/tfjs-node
-```
-```js
-  import tf from '@tensorflow/tfjs'
-  import Human from '@vladmandic/human/dist/human.esm-nobundle.js'; // same functionality as default import, but without tfjs bundled
-  const human = new Human();
-```
-
-### 3. [NPM](https://www.npmjs.com/) module
-
-*Recommended for `NodeJS` projects that will execute in the backend*  
-
-Entry point is bundle in CommonJS format `dist/human.node.js`  
-You also need to install and include `tfjs-node` or `tfjs-node-gpu` in your project so it can register an optimized backend  
-
-Install with:
-```shell
-  npm install @vladmandic/human @tensorflow/tfjs-node
-```
-And then use with:
-```js
-  const tf = require('@tensorflow/tfjs-node'); // can also use '@tensorflow/tfjs-node-gpu' if you have environment with CUDA extensions
-  const Human = require('@vladmandic/human').default; // points to @vladmandic/human/dist/human.node.js
-  const human = new Human();
-```
-
-Since NodeJS projects load `weights` from local filesystem instead of using `http` calls, you must modify default configuration to include correct paths with `file://` prefix  
-
-For example:
-```js
-const config = {
-  body: { enabled: true, modelPath: 'file://models/posenet/model.json' },
-}
-```
-
-### Weights
-
-Pretrained model weights are includes in `./models`  
-Default configuration uses relative paths to you entry script pointing to `../models`  
-If your application resides in a different folder, modify `modelPath` property in configuration of each module  
-
-<hr>
-
-## Usage
-
-`Human` library does not require special initialization.
-All configuration is done in a single JSON object and all model weights will be dynamically loaded upon their first usage  
-(and only then, `Human` will not load weights that it doesn't need according to configuration).
-
-There is only *ONE* method you need:
-
-```js
-  // 'image': can be of any type of an image object: HTMLImage, HTMLVideo, HTMLMedia, Canvas, Tensor4D  
-  // 'config': optional parameter used to override any options present in default configuration  
-  // configuration is fully dynamic and can change between different calls to 'detect()'  
-  const result = await human.detect(image, config?)
-```
-
-or if you want to use promises
-
-```js
-  human.detect(image, config?).then((result) => {
-    // your code
-  })
-```
-
-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.tf            // instance of tfjs used by human
-  human.state         // <string> describing current operation in progress
-                      // progresses through: 'config', 'check', 'backend', 'load', 'run:<model>', 'idle'
-  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()'
-```
-
-Note that when using `Human` library in `NodeJS`, you must load and parse the image *before* you pass it for detection and dispose it afterwards  
-Input format is `Tensor4D[1, width, height, 3]` of type `float32` 
-
-For example:
-```js
-  const imageFile = '../assets/sample1.jpg';
-  const buffer = fs.readFileSync(imageFile);
-  const decoded = tf.node.decodeImage(buffer);
-  const casted = decoded.toFloat();
-  const image = casted.expandDims(0);
-  decoded.dispose();
-  casted.dispose();
-  logger.log('Processing:', image.shape);
-  const human = new Human.Human();
-  const result = await human.detect(image, config);
-  image.dispose();
-```
-
-<hr>
-
-## Configuration 
-
-Detailed configuration options are explained below, but they are best seen in the menus present in the `demo` application:  
-
-![Menus](assets/screenshot-menu.png)  
-
-Below is output of `human.defaults` object  
-Any property can be overriden by passing user object during `human.detect()`  
-Note that user object and default configuration are merged using deep-merge, so you do not need to redefine entire configuration  
-
-All configuration details can be changed in real-time!  
-
-
-```js
-config = {
-  backend: 'webgl',          // select tfjs backend to use
-  console: true,             // enable debugging output to console
-  async: true,               // execute enabled models in parallel
-                             // this disables per-model performance data but slightly increases performance
-                             // cannot be used if profiling is enabled
-  profile: false,            // enable tfjs profiling
-                             // this has significant performance impact, only enable for debugging purposes
-                             // currently only implemented for age,gender,emotion models
-  deallocate: false,         // aggresively deallocate gpu memory after each usage
-                             // only valid for webgl backend and only during first call, cannot be changed unless library is reloaded
-                             // this has significant performance impact, only enable on low-memory devices
-  scoped: false,             // enable scoped runs
-                             // some models *may* have memory leaks, this wrapps everything in a local scope at a cost of performance
-                             // typically not needed
-  videoOptimized: true,      // perform additional optimizations when input is video, must be disabled for images
-  filter: {                  // note: image filters are only available in Browser environments and not in NodeJS as they require WebGL for processing
-    enabled: true,           // enable image pre-processing filters
-    return: true,            // return processed canvas imagedata in result
-    width: 0,                // resize input width
-    height: 0,               // resize input height
-                             // usefull on low-performance devices to reduce the size of processed input
-                             // if both width and height are set to 0, there is no resizing
-                             // if just one is set, second one is scaled automatically
-                             // if both are set, values are used as-is
-    brightness: 0,           // range: -1 (darken) to 1 (lighten)
-    contrast: 0,             // range: -1 (reduce contrast) to 1 (increase contrast)
-    sharpness: 0,            // range: 0 (no sharpening) to 1 (maximum sharpening)
-    blur: 0,                 // range: 0 (no blur) to N (blur radius in pixels)
-    saturation: 0,           // range: -1 (reduce saturation) to 1 (increase saturation)
-    hue: 0,                  // range: 0 (no change) to 360 (hue rotation in degrees)
-    negative: false,         // image negative
-    sepia: false,            // image sepia colors
-    vintage: false,          // image vintage colors
-    kodachrome: false,       // image kodachrome colors
-    technicolor: false,      // image technicolor colors
-    polaroid: false,         // image polaroid camera effect
-    pixelate: 0,             // range: 0 (no pixelate) to N (number of pixels to pixelate)
-  },
-  face: {
-    enabled: true,           // controls if specified modul is enabled
-                             // face.enabled is required for all face models: detector, mesh, iris, age, gender, emotion
-                             // note: module is not loaded until it is required
-    detector: {
-      modelPath: '../models/blazeface/back/model.json', // can be 'front' or 'back'.
-                                                        // 'front' is optimized for large faces such as front-facing camera and 'back' is optimized for distanct faces.
-      inputSize: 256,        // fixed value: 128 for front and 256 for 'back'
-      maxFaces: 10,          // maximum number of faces detected in the input, should be set to the minimum number for performance
-      skipFrames: 10,        // how many frames to go without re-running the face bounding box detector
-                             // only used for video inputs, ignored for static inputs
-                             // if model is running st 25 FPS, we can re-use existing bounding box for updated face mesh analysis
-                             // as the face probably hasn't moved much in short time (10 * 1/25 = 0.25 sec)
-      minConfidence: 0.5,    // threshold for discarding a prediction
-      iouThreshold: 0.3,     // threshold for deciding whether boxes overlap too much in non-maximum suppression
-      scoreThreshold: 0.7,   // threshold for deciding when to remove boxes based on score in non-maximum suppression
-    },
-    mesh: {
-      enabled: true,
-      modelPath: '../models/facemesh/model.json',
-      inputSize: 192,        // fixed value
-    },
-    iris: {
-      enabled: true,
-      modelPath: '../models/iris/model.json',
-      enlargeFactor: 2.3,    // empiric tuning
-      inputSize: 64,         // fixed value
-    },
-    age: {
-      enabled: true,
-      modelPath: '../models/ssrnet-age/imdb/model.json', // can be 'imdb' or 'wiki'
-                                                         // which determines training set for model
-      inputSize: 64,         // fixed value
-      skipFrames: 10,        // how many frames to go without re-running the detector, only used for video inputs
-    },
-    gender: {
-      enabled: true,
-      minConfidence: 0.8,    // threshold for discarding a prediction
-      modelPath: '../models/ssrnet-gender/imdb/model.json',
-    },
-    emotion: {
-      enabled: true,
-      inputSize: 64,         // fixed value
-      minConfidence: 0.5,    // threshold for discarding a prediction
-      skipFrames: 10,        // how many frames to go without re-running the detector, only used for video inputs
-      modelPath: '../models/emotion/model.json',
-    },
-  },
-  body: {
-    enabled: true,
-    modelPath: '../models/posenet/model.json',
-    inputResolution: 257,    // fixed value
-    outputStride: 16,        // fixed value
-    maxDetections: 10,       // maximum number of people detected in the input, should be set to the minimum number for performance
-    scoreThreshold: 0.7,     // threshold for deciding when to remove boxes based on score in non-maximum suppression
-    nmsRadius: 20,           // radius for deciding points are too close in non-maximum suppression
-  },
-  hand: {
-    enabled: true,
-    inputSize: 256,          // fixed value
-    skipFrames: 10,          // how many frames to go without re-running the hand bounding box detector
-                             // only used for video inputs
-                             // if model is running st 25 FPS, we can re-use existing bounding box for updated hand skeleton analysis
-                             // as the hand probably hasn't moved much in short time (10 * 1/25 = 0.25 sec)
-    minConfidence: 0.5,      // threshold for discarding a prediction
-    iouThreshold: 0.3,       // threshold for deciding whether boxes overlap too much in non-maximum suppression
-    scoreThreshold: 0.7,     // threshold for deciding when to remove boxes based on score in non-maximum suppression
-    enlargeFactor: 1.65,     // empiric tuning as skeleton prediction prefers hand box with some whitespace
-    maxHands: 10,            // maximum number of hands detected in the input, should be set to the minimum number for performance
-    detector: {
-      modelPath: '../models/handdetect/model.json',
-    },
-    skeleton: {
-      modelPath: '../models/handskeleton/model.json',
-    },
-  },
-  gesture: {
-    enabled: true,           // enable simple gesture recognition
-                             // takes processed data and based on geometry detects simple gestures
-                             // easily expandable via code, see `src/gesture.js`
-  },
-};
-```
-
-Any user configuration and default configuration are merged using deep-merge, so you do not need to redefine entire configuration  
-Configurtion object is large, but typically you only need to modify few values:  
-
-- `enabled`: Choose which models to use
-- `modelPath`: Update as needed to reflect your application's relative path
-
-for example,
-
-```js
-const myConfig = {
-  backend: 'wasm',
-  filter: { enabled: false },
-}
-const result = await human.detect(image, myConfig)
-```
-
-<hr>
-
-## Outputs
-
-Result of `humand.detect()` is a single object that includes data for all enabled modules and all detected objects:
-
-```js
-result = {
-  version:         // <string> version string of the human library
-  face:            // <array of detected objects>
-  [
-    {
-      confidence,  // <number>
-      box,         // <array [x, y, width, height]>
-      mesh,        // <array of 3D points [x, y, z]> 468 base points & 10 iris points
-      annotations, // <list of object { landmark: array of points }> 32 base annotated landmarks & 2 iris annotations
-      iris,        // <number> relative distance of iris to camera, multiple by focal lenght to get actual distance
-      age,         // <number> estimated age
-      gender,      // <string> 'male', 'female'
-    }
-  ],
-  body:            // <array of detected objects>
-  [
-    {
-      score,       // <number>,
-      keypoints,   // <array of 2D landmarks [ score, landmark, position [x, y] ]> 17 annotated landmarks
-    }
-  ],
-  hand:            // <array of detected objects>
-  [
-    {
-      confidence,  // <number>,
-      box,         // <array [x, y, width, height]>,
-      landmarks,   // <array of 3D points [x, y,z]> 21 points
-      annotations, // <array of 3D landmarks [ landmark: <array of points> ]> 5 annotated landmakrs
-    }
-  ],
-  emotion:         // <array of emotions>
-  [
-    {
-      score,       // <number> probabily of emotion
-      emotion,     // <string> 'angry', 'discust', 'fear', 'happy', 'sad', 'surpise', 'neutral'
-    }
-  ],
-  gesture:         // object containing parsed gestures
-  {
-    face,          // <array of string>
-    body,          // <array of string>
-    hand,          // <array of string>
-  }
-  performance = {  // performance data of last execution for each module measuredin miliseconds
-                   // note that per-model performance data is not available in async execution mode
-    backend,       // time to initialize tf backend, keeps longest value measured
-    load,          // time to load models, keeps longest value measured
-    image,         // time for image processing
-    gesture,       // gesture analysis time
-    body,          // model time
-    hand,          // model time
-    face,          // model time
-    agegender,     // model time
-    emotion,       // model time
-    total,         // end to end time
-  }
-}
-```
-
-<hr>
-
-## Profile
-
-If `config.profile` is enabled, call to `human.profile()` will return detailed profiling data from the last detect invokation.
-
-example:
-```js
-  result = {
-    {age: {…}, gender: {…}, emotion: {…}}
-      age:
-        timeKernelOps: 53.78892800000002
-        newBytes: 4
-        newTensors: 1
-        numKernelOps: 341
-        peakBytes: 46033948
-        largestKernelOps: Array(5)
-          0: {name: "Reshape", bytesAdded: 107648, totalBytesSnapshot: 46033948, tensorsAdded: 1, totalTensorsSnapshot: 1149, …}
-          1: {name: "Reshape", bytesAdded: 0, totalBytesSnapshot: 45818652, tensorsAdded: 1, totalTensorsSnapshot: 1147, …}
-          2: {name: "Reshape", bytesAdded: 0, totalBytesSnapshot: 45633996, tensorsAdded: 1, totalTensorsSnapshot: 1148, …}
-          3: {name: "Reshape", bytesAdded: 0, totalBytesSnapshot: 45389376, tensorsAdded: 1, totalTensorsSnapshot: 1154, …}
-          4: {name: "Reshape", bytesAdded: 53824, totalBytesSnapshot: 45381776, tensorsAdded: 1, totalTensorsSnapshot: 1155, …}
-        slowestKernelOps: Array(5)
-          0: {name: "_FusedMatMul", bytesAdded: 12, totalBytesSnapshot: 44802280, tensorsAdded: 1, totalTensorsSnapshot: 1156, …}
-          1: {name: "_FusedMatMul", bytesAdded: 4, totalBytesSnapshot: 44727564, tensorsAdded: 1, totalTensorsSnapshot: 1152, …}
-          2: {name: "_FusedMatMul", bytesAdded: 12, totalBytesSnapshot: 44789100, tensorsAdded: 1, totalTensorsSnapshot: 1157, …}
-          3: {name: "Add", bytesAdded: 4, totalBytesSnapshot: 44788748, tensorsAdded: 1, totalTensorsSnapshot: 1158, …}
-          4: {name: "Add", bytesAdded: 4, totalBytesSnapshot: 44788748, tensorsAdded: 1, totalTensorsSnapshot: 1158, …}
-  }
-```
-
-## Build
-
-If you want to modify the library and perform a full rebuild:  
-
-*clone repository, install dependencies, check for errors and run full rebuild from which creates bundles from `/src` into `/dist`:*
-
-```shell
-git clone https://github.com/vladmandic/human
-cd human
-npm install # installs all project dependencies
-npm run lint
-npm run build
-```
-
-This will rebuild library itself (all variations) as well as demo  
-
-Project is written in pure `JavaScript` [ECMAScript version 2020](https://www.ecma-international.org/ecma-262/11.0/index.html)  
-Build target is `JavaScript` **EMCAScript version 2018**  
-
-Only project depdendency is [@tensorflow/tfjs](https://github.com/tensorflow/tfjs)
-Development dependencies are [eslint](https://github.com/eslint) used for code linting and [esbuild](https://github.com/evanw/esbuild) used for IIFE and ESM script bundling  
-
-<hr>
-
-## Performance
-
-Performance will vary depending on your hardware, but also on number of resolution of input video/image, enabled modules as well as their parameters  
-
-For example, it can perform multiple face detections at 60+ FPS, but drops to ~15 FPS on a medium complex images if all modules are enabled  
-
-### Performance per module on a **notebook** with nVidia GTX1050 GPU on a FullHD input:
-
-- Enabled all: 15 FPS
-- Image filters: 80 FPS (standalone)
-- Gesture: 80 FPS (standalone)
-- Face Detect: 80 FPS (standalone)
-- Face Geometry: 30 FPS (includes face detect)
-- Face Iris: 30 FPS (includes face detect and face geometry)
-- Age: 60 FPS (includes face detect)
-- Gender: 60 FPS (includes face detect)
-- Emotion: 60 FPS (includes face detect)
-- Hand: 40 FPS (standalone)
-- Body: 50 FPS (standalone)
-
-### Performance per module on a **smartphone** with Snapdragon 855 on a FullHD input:
-
-- Enabled all: 5 FPS
-- Image filters: 30 FPS (standalone)
-- Gesture: 30 FPS (standalone)
-- Face Detect: 20 FPS (standalone)
-- Face Geometry: 10 FPS (includes face detect)
-- Face Iris: 5 FPS (includes face detect and face geometry)
-- Age: 20 FPS (includes face detect)
-- Gender: 20 FPS (includes face detect)
-- Emotion: 20 FPS (includes face detect)
-- Hand: 40 FPS (standalone)
-- Body: 10 FPS (standalone)
-
-For performance details, see output of `result.performance` object during after running inference  
-
-<hr>
-
-## Credits
-
-- Face Detection: [**MediaPipe BlazeFace**](https://drive.google.com/file/d/1f39lSzU5Oq-j_OXgS67KfN5wNsoeAZ4V/view)
-- Facial Spacial Geometry: [**MediaPipe FaceMesh**](https://drive.google.com/file/d/1VFC_wIpw4O7xBOiTgUldl79d9LA-LsnA/view)
-- Eye Iris Details: [**MediaPipe Iris**](https://drive.google.com/file/d/1bsWbokp9AklH2ANjCfmjqEzzxO1CNbMu/view)
-- Hand Detection & Skeleton: [**MediaPipe HandPose**](https://drive.google.com/file/d/1sv4sSb9BSNVZhLzxXJ0jBv9DqD-4jnAz/view)
-- Body Pose Detection: [**PoseNet**](https://medium.com/tensorflow/real-time-human-pose-estimation-in-the-browser-with-tensorflow-js-7dd0bc881cd5)
-- Age & Gender Prediction: [**SSR-Net**](https://github.com/shamangary/SSR-Net)
-- Emotion Prediction: [**Oarriaga**](https://github.com/oarriaga/face_classification)
-- Image Filters: [**WebGLImageFilter**](https://github.com/phoboslab/WebGLImageFilter)
-
-<hr>
diff --git a/changelog.js b/changelog.js
index e017a85a..34cc8fff 100644
--- a/changelog.js
+++ b/changelog.js
@@ -45,5 +45,5 @@ async function update(f) {
 exports.update = update;
 
 if (!module.parent) {
-  update('CHANGELOG.md');
+  update('wiki/Change-Log.md');
 }
diff --git a/package.json b/package.json
index a431595e..cd3d573a 100644
--- a/package.json
+++ b/package.json
@@ -41,6 +41,7 @@
   "scripts": {
     "start": "node --trace-warnings --unhandled-rejections=strict --trace-uncaught --no-deprecation src/node.js",
     "lint": "eslint src/*.js demo/*.js",
+    "wiki": "cd wiki; git add *; git commit -a -m 'update'; git push; cd ..",
     "dev": "npm install && node --trace-warnings --unhandled-rejections=strict --trace-uncaught --no-deprecation dev-server.js",
     "build-iife": "esbuild --bundle --minify --platform=browser --sourcemap --target=es2018 --format=iife --external:fs --global-name=Human --metafile=dist/human.json --outfile=dist/human.js src/human.js",
     "build-esm-bundle": "esbuild --bundle --minify --platform=browser --sourcemap --target=es2018 --format=esm --external:fs --metafile=dist/human.esm.json --outfile=dist/human.esm.js src/human.js",
diff --git a/wiki b/wiki
new file mode 160000
index 00000000..343eedc6
--- /dev/null
+++ b/wiki
@@ -0,0 +1 @@
+Subproject commit 343eedc6b4c9fd13bde6f92c746fb1a46b25849e