full rebuild

Signed-off-by: Vladimir Mandic <mandic00@live.com>

.build.json

@@ -0,0 +1,148 @@
+{
+  "log": {
+    "enabled": false,
+    "debug": false,
+    "console": true,
+    "output": "build.log"
+  },
+  "profiles": {
+    "production": ["compile", "typings", "typedoc", "lint", "changelog"],
+    "development": ["serve", "watch", "compile"]
+  },
+  "clean": {
+    "locations": ["dist/*", "typedoc/*", "types/lib/src"]
+  },
+  "lint": {
+    "locations": [ "src/" ],
+    "rules": { }
+  },
+  "changelog": {
+    "log": "CHANGELOG.md"
+  },
+  "serve": {
+    "sslKey": "cert/https.key",
+    "sslCrt": "cert/https.crt",
+    "httpPort": 8000,
+    "httpsPort": 8001,
+    "documentRoot": ".",
+    "defaultFolder": "demo",
+    "defaultFile": "index.html"
+    },
+  "build": {
+    "global": {
+      "target": "es2018",
+      "treeShaking": true,
+      "ignoreAnnotations": true,
+      "sourcemap": false,
+      "banner": { "js": "/*\n  Face-API\n  homepage: <https://github.com/vladmandic/face-api>\n  author: <https://github.com/vladmandic>'\n*/\n" }
+    },
+    "targets": [
+      { 
+        "name": "tfjs/browser/tf-version",
+        "platform": "browser",
+        "format": "esm",
+        "input": "src/tfjs/tf-version.ts",
+        "output": "dist/tfjs.version.js"
+      },
+      {
+        "name": "tfjs/node/cpu",
+        "platform": "node",
+        "format": "cjs",
+        "input": "src/tfjs/tf-node.ts",
+        "output": "dist/tfjs.esm.js",
+        "external": ["@tensorflow"]
+      },
+      {
+        "name": "faceapi/node/cpu",
+        "platform": "node",
+        "format": "cjs",
+        "input": "src/index.ts",
+        "output": "dist/face-api.node.js",
+        "external": ["@tensorflow"]
+      },
+      {
+        "name": "tfjs/node/gpu",
+        "platform": "node",
+        "format": "cjs",
+        "input": "src/tfjs/tf-node-gpu.ts",
+        "output": "dist/tfjs.esm.js",
+        "external": ["@tensorflow"]
+      },
+      {
+        "name": "faceapi/node/gpu",
+        "platform": "node",
+        "format": "cjs",
+        "input": "src/index.ts",
+        "output": "dist/face-api.node-gpu.js",
+        "external": ["@tensorflow"]
+      },
+      {
+        "name": "tfjs/node/wasm",
+        "platform": "node",
+        "format": "cjs",
+        "input": "src/tfjs/tf-node-wasm.ts",
+        "output": "dist/tfjs.esm.js",
+        "external": ["@tensorflow"]
+      },
+      {
+        "name": "faceapi/node/wasm",
+        "platform": "node",
+        "format": "cjs",
+        "input": "src/index.ts",
+        "output": "dist/face-api.node-wasm.js",
+        "external": ["@tensorflow"]
+      },
+      {
+        "name": "tfjs/browser/esm/nobundle",
+        "platform": "browser",
+        "format": "esm",
+        "input": "src/tfjs/tf-browser.ts",
+        "output": "dist/tfjs.esm.js",
+        "external": ["@tensorflow"]
+      },
+      {
+        "name": "faceapi/browser/esm/nobundle",
+        "platform": "browser",
+        "format": "esm",
+        "input": "src/index.ts",
+        "output": "dist/face-api.esm-nobundle.js",
+        "external": ["@tensorflow"]
+      },
+      {
+        "name": "tfjs/browser/esm/bundle",
+        "platform": "browser",
+        "format": "esm",
+        "input": "src/tfjs/tf-browser.ts",
+        "output": "dist/tfjs.esm.js"
+      },
+      {
+        "name": "faceapi/browser/iife/bundle",
+        "platform": "browser",
+        "format": "iife",
+        "globalName": "faceapi",
+        "minify": true,
+        "input": "src/index.ts",
+        "output": "dist/face-api.js",
+        "external": ["@tensorflow"]
+      },
+      {
+        "name": "faceapi/browser/esm/bundle",
+        "platform": "browser",
+        "format": "esm",
+        "sourcemap": true,
+        "input": "src/index.ts",
+        "output": "dist/face-api.esm.js",
+        "typings": "types/lib",
+        "typedoc": "typedoc",
+        "external": ["@tensorflow"]
+      }
+    ]
+  },
+  "watch": {
+    "enabled": true,
+    "locations": [ "src/**" ]
+  },
+  "typescript": {
+    "allowJs": false
+  }
+}

.eslintrc.json

@@ -3,50 +3,74 @@
   "env": {
       "browser": true,
       "commonjs": true,
-      "es6": true,
       "node": true,
       "es2020": true
   },
   "parser": "@typescript-eslint/parser",
-  "parserOptions": { "ecmaVersion": 2020 },
-  "plugins": ["@typescript-eslint"],
+  "parserOptions": { "ecmaVersion": "latest" },
+  "plugins": [
+    "@typescript-eslint"
+  ],
   "extends": [
     "eslint:recommended",
     "plugin:import/errors",
     "plugin:import/warnings",
-    "plugin:import/typescript",
     "plugin:node/recommended",
     "plugin:promise/recommended",
-    "plugin:json/recommended-with-comments",
+    "plugin:@typescript-eslint/eslint-recommended",
+    "plugin:@typescript-eslint/recommended",
     "airbnb-base"
   ],
   "ignorePatterns": [ "node_modules", "types" ],
-  "settings": {
-    "import/resolver": {
-      "node": {
-        "extensions": [".js", ".ts"]
-      }
-    }
-  },
   "rules": {
-    "max-len": [1, 275, 3],
+    "@typescript-eslint/no-explicit-any": "off",
+    "@typescript-eslint/ban-types": "off",
+    "@typescript-eslint/ban-ts-comment": "off",
+    "@typescript-eslint/explicit-module-boundary-types": "off",
+    "@typescript-eslint/no-var-requires": "off",
+    "@typescript-eslint/no-empty-object-type": "off",
+    "@typescript-eslint/no-require-imports": "off",
     "camelcase": "off",
     "class-methods-use-this": "off",
+    "default-param-last": "off",
+    "dot-notation": "off",
+    "func-names": "off",
+    "guard-for-in": "off",
     "import/extensions": "off",
-    "import/no-cycle": "off",
+    "import/no-extraneous-dependencies": "off",
+    "import/no-named-as-default": "off",
+    "import/no-unresolved": "off",
     "import/prefer-default-export": "off",
+    "lines-between-class-members": "off",
+    "max-len": [1, 275, 3],
+    "newline-per-chained-call": "off",
+    "no-async-promise-executor": "off",
     "no-await-in-loop": "off",
+    "no-bitwise": "off",
+    "no-case-declarations":"off",
     "no-continue": "off",
+    "no-loop-func": "off",
     "no-mixed-operators": "off",
-    "no-param-reassign": "off",
+    "no-param-reassign":"off",
     "no-plusplus": "off",
+    "no-regex-spaces": "off",
+    "no-restricted-globals": "off",
     "no-restricted-syntax": "off",
     "no-return-assign": "off",
     "no-underscore-dangle": "off",
-    "node/no-missing-import": "off",
+    "no-promise-executor-return": "off",
+    "node/no-missing-import": ["error", { "tryExtensions": [".js", ".json", ".ts"] }],
+    "node/no-unpublished-import": "off",
+    "node/no-unpublished-require": "off",
     "node/no-unsupported-features/es-syntax": "off",
+    "no-lonely-if": "off",
+    "node/shebang": "off",
+    "object-curly-newline": "off",
     "prefer-destructuring": "off",
-    "radix": "off",
-    "object-curly-newline": "off"
+    "prefer-template":"off",
+    "promise/always-return": "off",
+    "promise/catch-or-return": "off",
+    "promise/no-nesting": "off",
+    "radix": "off"
   }
 }

.github/FUNDING.yml

@@ -0,0 +1,13 @@
+# These are supported funding model platforms
+
+github: [vladmandic]
+patreon: # Replace with a single Patreon username
+open_collective: # Replace with a single Open Collective username
+ko_fi: # Replace with a single Ko-fi username
+tidelift: # Replace with a single Tidelift platform-name/package-name e.g., npm/babel
+community_bridge: # Replace with a single Community Bridge project-name e.g., cloud-foundry
+liberapay: # Replace with a single Liberapay username
+issuehunt: # Replace with a single IssueHunt username
+otechie: # Replace with a single Otechie username
+lfx_crowdfunding: # Replace with a single LFX Crowdfunding project-name e.g., cloud-foundry
+custom: # Replace with up to 4 custom sponsorship URLs e.g., ['link1', 'link2']

.github/ISSUE_TEMPLATE/ISSUE.md

@@ -1 +0,0 @@
-Please include output of `faceapi.version` object or specify details about your version and platform (OS, NodeJS version, Browser version).  

.github/ISSUE_TEMPLATE/issue.md

@@ -0,0 +1,28 @@
+---
+name: Issue
+about: Issue
+title: ''
+labels: ''
+assignees: vladmandic
+
+---
+
+**Issue Description**
+
+**Steps to Reproduce**
+
+**Expected Behavior**
+
+**Environment
+
+- Module version?
+- Built-in demo or custom code?
+- Type of module used (e.g. `js`, `esm`, `esm-nobundle`)?
+- Browser or NodeJS and version (e.g. NodeJS 14.15 or Chrome 89)?
+- OS and Hardware platform (e.g. Windows 10, Ubuntu Linux on x64, Android 10)?
+- Packager (if any) (e.g, webpack, rollup, parcel, esbuild, etc.)?
+
+**Additional**
+
+- For installation or startup issues include your `package.json`
+- For usage issues, it is recommended to post your code as [gist](https://gist.github.com/)

.github/PULL_REQUEST_TEMPLATE/pull_request_template.md

@@ -0,0 +1,3 @@
+# Pull Request Template
+
+<br>

.github/workflows/codeql-analysis.yml

@@ -0,0 +1,67 @@
+# For most projects, this workflow file will not need changing; you simply need
+# to commit it to your repository.
+#
+# You may wish to alter this file to override the set of languages analyzed,
+# or to provide custom queries or build logic.
+#
+# ******** NOTE ********
+# We have attempted to detect the languages in your repository. Please check
+# the `language` matrix defined below to confirm you have the correct set of
+# supported CodeQL languages.
+#
+name: "CodeQL"
+
+on:
+  push:
+    branches: [ master ]
+  pull_request:
+    # The branches below must be a subset of the branches above
+    branches: [ master ]
+  schedule:
+    - cron: '21 6 * * 0'
+
+jobs:
+  analyze:
+    name: Analyze
+    runs-on: ubuntu-latest
+
+    strategy:
+      fail-fast: false
+      matrix:
+        language: [ 'javascript' ]
+        # CodeQL supports [ 'cpp', 'csharp', 'go', 'java', 'javascript', 'python' ]
+        # Learn more:
+        # https://docs.github.com/en/free-pro-team@latest/github/finding-security-vulnerabilities-and-errors-in-your-code/configuring-code-scanning#changing-the-languages-that-are-analyzed
+
+    steps:
+    - name: Checkout repository
+      uses: actions/checkout@v2
+
+    # Initializes the CodeQL tools for scanning.
+    - name: Initialize CodeQL
+      uses: github/codeql-action/init@v1
+      with:
+        languages: ${{ matrix.language }}
+        # If you wish to specify custom queries, you can do so here or in a config file.
+        # By default, queries listed here will override any specified in a config file.
+        # Prefix the list here with "+" to use these queries and those in the config file.
+        # queries: ./path/to/local/query, your-org/your-repo/queries@main
+
+    # Autobuild attempts to build any compiled languages  (C/C++, C#, or Java).
+    # If this step fails, then you should remove it and run the build manually (see below)
+    - name: Autobuild
+      uses: github/codeql-action/autobuild@v1
+
+    # ℹ️ Command-line programs to run using the OS shell.
+    # 📚 https://git.io/JvXDl
+
+    # ✏️ If the Autobuild fails above, remove it and uncomment the following three lines
+    #    and modify them (or add more) to build your code if your project
+    #    uses a compiled language
+
+    #- run: |
+    #   make bootstrap
+    #   make release
+
+    - name: Perform CodeQL Analysis
+      uses: github/codeql-action/analyze@v1

.gitignore

@@ -1 +1,2 @@
 node_modules
+pnpm-lock.yaml

.hintrc

@@ -0,0 +1,13 @@
+{
+  "extends": [
+    "web-recommended"
+  ],
+  "browserslist": [
+    "last 1 versions",
+    "not ie < 20"
+  ],
+  "hints": {
+    "no-inline-styles": "off",
+    "meta-charset-utf-8": "off"
+  }
+}

.npmignore

@@ -0,0 +1,5 @@
+node_modules
+pnpm-lock.yaml
+typedoc
+test
+types/lib

.npmrc

@@ -0,0 +1,5 @@
+force=true
+production=true
+legacy-peer-deps=true
+strict-peer-dependencies=false
+node-options='--no-deprecation'

.vscode/settings.json

@@ -0,0 +1,3 @@
+{
+  "typescript.tsdk": "node_modules/typescript/lib"
+}

CHANGELOG.md

@@ -1,123 +1,317 @@
 # @vladmandic/face-api  
 
-Version: **1.0.1**  
-Description: **FaceAPI: AI-powered Face Detection, Face Embedding & Recognition Using Tensorflow/JS**  
-
-Author: **Vladimir Mandic <mandic00@live.com>**  
-License: **MIT** </LICENSE>  
-Repository: **<git+https://github.com/vladmandic/face-api.git>**  
-
+  Version: **1.7.15**  
+  Description: **FaceAPI: AI-powered Face Detection & Rotation Tracking, Face Description & Recognition, Age & Gender & Emotion Prediction for Browser and NodeJS using TensorFlow/JS**  
+  
+  Author: **Vladimir Mandic <mandic00@live.com>**  
+  License: **MIT**  
+  Repository: **<https://github.com/vladmandic/face-api>**  
+  
 ## Changelog
+  
+### **1.7.15** 2025/02/05 mandic00@live.com
+
+
+### **origin/master** 2024/09/10 mandic00@live.com
+
+
+### **1.7.14** 2024/09/10 mandic00@live.com
+
+- rebuild
+- merge pull request #188 from rebser/master
+- fixing leaking eventhandlers when using htmlcanvaselement
+- rebuild types
+- rebuild
+
+### **1.7.13** 2024/01/17 mandic00@live.com
+
+- merge pull request #186 from khwalkowicz/master
+- feat: enable noimplicitany
+
+### **release: 1.7.12** 2023/06/12 mandic00@live.com
+
+
+### **1.7.12** 2023/06/12 mandic00@live.com
+
+
+### **1.7.11** 2023/05/08 mandic00@live.com
+
+
+### **1.7.10** 2023/03/21 mandic00@live.com
+
+- change typedefs
+
+### **1.7.9** 2023/01/29 mandic00@live.com
+
+
+### **1.7.8** 2023/01/06 mandic00@live.com
+
+
+### **1.7.7** 2022/12/01 mandic00@live.com
+
+
+### **1.7.6** 2022/10/18 mandic00@live.com
+
+- fix face angles (yaw, pitch, & roll) accuracy (#130)
+
+### **1.7.5** 2022/10/09 mandic00@live.com
+
+- create funding.yml
+- add node-wasm demo
+
+### **1.7.4** 2022/09/25 mandic00@live.com
+
+- improve face compare performance
+
+### **1.7.3** 2022/08/24 mandic00@live.com
+
+- refresh release
+
+### **1.7.2** 2022/08/23 mandic00@live.com
+
+- document and remove optional dependencies
+
+### **release: 1.7.1** 2022/07/25 mandic00@live.com
+
+
+### **1.7.1** 2022/07/25 mandic00@live.com
+
+- refactor dependencies
+- full rebuild
+
+### **1.6.11** 2022/05/24 mandic00@live.com
+
+
+### **1.6.10** 2022/05/24 mandic00@live.com
+
+
+### **1.6.9** 2022/05/18 mandic00@live.com
+
+
+### **1.6.8** 2022/05/09 mandic00@live.com
+
+- exclude impossible detected face boxes
+
+### **1.6.7** 2022/04/01 mandic00@live.com
+
+- fixed typo error (#97)
+
+### **1.6.6** 2022/03/04 mandic00@live.com
+
+
+### **1.6.5** 2022/02/07 mandic00@live.com
+
+
+### **1.6.4** 2022/01/14 mandic00@live.com
+
+- add node with wasm build target
+
+### **1.6.3** 2022/01/06 mandic00@live.com
+
+
+### **1.6.2** 2022/01/01 mandic00@live.com
+
+
+### **1.6.1** 2021/12/09 mandic00@live.com
+
+- rebuild
+- release preview
+- switch to custom tfjs and new typedefs
+- rebuild
+
+### **1.5.8** 2021/11/30 mandic00@live.com
+
+
+### **1.5.7** 2021/10/28 mandic00@live.com
+
+
+### **1.5.6** 2021/10/22 mandic00@live.com
+
+
+### **release: 1.5.5** 2021/10/19 mandic00@live.com
+
+
+### **1.5.5** 2021/10/19 mandic00@live.com
+
+- allow backend change in demo via url params
+- add node-match demo
+- fix face matcher
+
+### **1.5.4** 2021/09/29 mandic00@live.com
+
+
+### **1.5.3** 2021/09/16 mandic00@live.com
+
+- simplify tfjs imports
+- reduce bundle size
+- enable webgl uniforms
+
+### **1.5.2** 2021/09/10 mandic00@live.com
+
+- redesign build platform
+
+### **1.5.1** 2021/09/08 mandic00@live.com
+
+
+### **1.4.2** 2021/08/31 mandic00@live.com
+
+
+### **release: 1.4.1** 2021/07/29 mandic00@live.com
+
+
+### **1.4.1** 2021/07/29 mandic00@live.com
+
+
+### **release: 1.3.1** 2021/06/18 mandic00@live.com
+
+
+### **1.3.1** 2021/06/08 mandic00@live.com
+
+- fix face expression detection (#56)
+- add buffertovideo
+- fix git conflicts
+- fix tsc error (#55)
+- force typescript 4.2 due to typedoc incompatibility with ts 4.3
+
+### **1.2.5** 2021/05/27 mandic00@live.com
+
+- add buffertovideo and fetchvideo (#54)
+
+### **1.2.4** 2021/05/18 mandic00@live.com
+
+
+### **1.2.3** 2021/05/04 mandic00@live.com
+
+
+### **update for tfjs 3.6.0** 2021/04/30 mandic00@live.com
+
+
+### **1.2.2** 2021/04/30 mandic00@live.com
+
+- add node-wasm demo
+- accept uri as input to demo node and node-canvas
+- major version full rebuild
+
+### **1.2.1** 2021/04/22 mandic00@live.com
+
+- add npmrc
+- add canvas/image based demo to decode webp
+
+### **1.1.12** 2021/04/13 mandic00@live.com
+
+
+### **1.1.11** 2021/04/06 mandic00@live.com
+
+- merge pull request #46 from mayankagarwals/demo_latencytest_fix
+- fixed bug which led to latency not being measured and wrong output on console for demo
+- add cdn links
+
+### **1.1.10** 2021/04/04 mandic00@live.com
+
+- added webhints
+
+### **1.1.9** 2021/04/03 mandic00@live.com
+
+- fix linting and tests
+
+### **1.1.8** 2021/04/01 mandic00@live.com
+
+
+### **1.1.7** 2021/03/31 mandic00@live.com
+
+- enable minify
+
+### **1.1.6** 2021/03/26 mandic00@live.com
+
+
+### **1.1.5** 2021/03/23 mandic00@live.com
+
+- add node-canvas demo
+- refactoring
+
+### **1.1.4** 2021/03/18 mandic00@live.com
+
+
+### **1.1.3** 2021/03/16 mandic00@live.com
+
+- fix for seedrandom
+
+### **1.1.2** 2021/03/15 mandic00@live.com
+
+- create templates
+- create codeql-analysis.yml
+
+### **1.1.1** 2021/03/14 mandic00@live.com
+
+- full rebuild
+- reformatted model manifests and weights
+- create api specs
+
+### **1.0.2** 2021/03/09 mandic00@live.com
+
+
+### **release: 1.0.1** 2021/03/09 mandic00@live.com
+
 
 ### **1.0.1** 2021/03/09 mandic00@live.com
 
 - add badges
 - optimize for npm
-
-### **0.30.6** 2021/03/08 mandic00@live.com
-
+- 0.30.6
 - added typings for face angle
 - disable landmark printing
-
-### **0.30.5** 2021/03/07 mandic00@live.com
-
+- 0.30.5
 - enabled live demo on gitpages
-
-### **0.30.4** 2021/03/07 mandic00@live.com
-
+- 0.30.4
 - added face angle calculations
 - added documentation
 - package update
-
-### **0.30.3** 2021/03/04 mandic00@live.com
-
-
-### **0.30.2** 2021/02/26 mandic00@live.com
-
-
-### **0.30.1** 2021/02/25 mandic00@live.com
-
-
-### **0.13.3** 2021/02/21 mandic00@live.com
-
+- 0.30.3
+- 0.30.2
+- 0.30.1
+- 0.13.3
 - added note-cpu target
 - merge pull request #39 from xemle/feature/node-cpu
 - add node-cpu build for non supported systems of libtensorflow
-
-### **0.13.2** 2021/02/20 mandic00@live.com
-
-
-### **0.13.1** 2021/02/20 mandic00@live.com
-
-
-### **0.12.10** 2021/02/20 mandic00@live.com
-
+- 0.13.2
+- 0.13.1
+- 0.12.10
+- exception handling
+- 0.12.9
+- exception handling
+- 0.12.8
 - exception handling
-
-### **0.12.9** 2021/02/20 mandic00@live.com
-
-
-### **0.12.8** 2021/02/20 mandic00@live.com
-
 
 ### **0.12.7** 2021/02/17 mandic00@live.com
 
 - 0.12.7
-
-### **0.12.6** 2021/02/13 mandic00@live.com
-
-
-### **0.12.5** 2021/02/12 mandic00@live.com
-
-
-### **0.12.4** 2021/02/06 mandic00@live.com
-
-
-### **0.12.3** 2021/02/06 mandic00@live.com
-
-
-### **0.12.2** 2021/02/02 mandic00@live.com
-
+- 0.12.6
+- 0.12.5
+- 0.12.4
+- 0.12.3
+- 0.12.2
 
 ### **update for tfjs 3.0.0** 2021/01/29 mandic00@live.com
 
-
-### **0.12.1** 2021/01/29 mandic00@live.com
-
+- 0.12.1
 - rebuild
-
-### **0.11.6** 2021/01/24 mandic00@live.com
-
+- 0.11.6
 - add check for null face descriptor
 - merge pull request #34 from patrickhulce/patch-1
 - fix: return empty descriptor for zero-sized faces
-
-### **0.11.5** 2021/01/22 mandic00@live.com
-
-
-### **0.11.4** 2021/01/22 mandic00@live.com
-
-
-### **0.11.3** 2021/01/20 mandic00@live.com
-
+- 0.11.5
+- 0.11.4
+- 0.11.3
 - fix typo
 - enable full minification
-
-### **0.11.2** 2021/01/12 mandic00@live.com
-
+- 0.11.2
 - full rebuild
-
-### **0.11.1** 2021/01/10 mandic00@live.com
-
+- 0.11.1
 - added live webcam demo
-
-### **0.10.2** 2021/01/03 mandic00@live.com
-
+- 0.10.2
 - ts linting
 - version bump
-
-### **0.10.1** 2020/12/23 mandic00@live.com
-
+- 0.10.1
 - full re-lint and typings generation
 - rebuild
 

CODE_OF_CONDUCT

@@ -0,0 +1,24 @@
+# Code of Conduct
+
+Use your best judgement  
+If it will possibly make others uncomfortable, do not post it
+
+- Be respectful  
+  Disagreement is not an opportunity to attack someone else's thoughts or opinions  
+  Although views may differ, remember to approach every situation with patience and care  
+- Be considerate  
+  Think about how your contribution will affect others in the community  
+- Be open minded  
+  Embrace new people and new ideas. Our community is continually evolving and we welcome positive change  
+
+Be mindful of your language  
+Any of the following behavior is unacceptable:
+
+- Offensive comments of any kind
+- Threats or intimidation
+- Sexually explicit material
+- Or any other kinds of harassment
+
+If you believe someone is violating the code of conduct, we ask that you report it
+
+Participants asked to stop any harassing behavior are expected to comply immediately  

CONTRIBUTING

@@ -0,0 +1,17 @@
+# Contributing Guidelines
+
+Pull requests from everyone are welcome
+
+Procedure for contributing:
+
+- Create a fork of the repository on github  
+  In a top right corner of a GitHub, select "Fork"
+- Clone your forked repository to your local system  
+  `git clone https://github.com/<your-username>/<your-fork>
+- Make your changes  
+- Test your changes against code guidelines  
+  `npm run lint`
+- Push changes to your fork
+- Submit a PR (pull request)
+
+Your pull request will be reviewed and pending review results, merged into main branch

LICENSE

@@ -1,6 +1,6 @@
 MIT License
 
-Copyright (c) 2018 Vincent Mühler
+Copyright (c) Vladimir Mandic
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal

README.md

@@ -1,62 +1,26 @@
-![Version](https://img.shields.io/github/package-json/v/vladmandic/face-api?style=flat-square)
-![Last Commit](https://img.shields.io/github/last-commit/vladmandic/face-api?style=flat-square)
-![License](https://img.shields.io/github/license/vladmandic/face-api?style=flat-square)
-![GitHub Status Checks](https://img.shields.io/github/checks-status/vladmandic/face-api/master?style=flat-square])
-![Vulnerabilities](https://img.shields.io/snyk/vulnerabilities/github/vladmandic/face-api?style=flat-square)
+![Git Version](https://img.shields.io/github/package-json/v/vladmandic/face-api?style=flat-square&svg=true&label=git)
+![NPM Version](https://img.shields.io/npm/v/@vladmandic/face-api.png?style=flat-square)
+![Last Commit](https://img.shields.io/github/last-commit/vladmandic/face-api?style=flat-square?svg=true)
+![License](https://img.shields.io/github/license/vladmandic/face-api?style=flat-square?svg=true)
+![GitHub Status Checks](https://img.shields.io/github/checks-status/vladmandic/face-api/master?style=flat-square?svg=true)
+![Vulnerabilities](https://img.shields.io/snyk/vulnerabilities/github/vladmandic/face-api?style=flat-square?svg=true)
 
 # FaceAPI
 
-**Face detection and recognition libary for Browser and NodeJS implemented on top of TensorFlow/JS**
+**AI-powered Face Detection & Rotation Tracking, Face Description & Recognition, Age & Gender & Emotion Prediction for Browser and NodeJS using TensorFlow/JS**
 
 <br>
 
-**Live Demo**: <https://vladmandic.github.io/face-api/example/webcam.html>
+**Live Demo**: <https://vladmandic.github.io/face-api/demo/webcam.html>
 
 <br>
 
-## Note
+## Additional Documentation
 
-This is updated **face-api.js** with latest available TensorFlow/JS as the original face-api.js is not compatible with **tfjs 2.0+**.  
+- [**Tutorial**](TUTORIAL.md)
+- [**TypeDoc API Specification**](https://vladmandic.github.io/face-api/typedoc/index.html)
 
-Forked from [face-api.js](https://github.com/justadudewhohacks/face-api.js) version **0.22.2** which was released on March 22nd, 2020  
-
-Currently based on **`TensorFlow/JS` 3.2.0**  
-
-### Why?
-
-Because I needed Face-API that does not cause version conflict with newer TFJS 2.0 that I use accross my projects  
-And since original Face-API was open-source, I've released this version as well  
-
-Unfortunately, changes ended up being too large for a simple pull request on original Face-API and it ended up being a full-fledged version on its own  
-
-### Differences
-
-- Compatible with `TensorFlow/JS 2.0+ & 3.0+`  
-- Compatible with `WebGL`, `CPU` and `WASM` TFJS Browser backends
-- Compatible with both `tfjs-node` and `tfjs-node-gpu` TFJS NodeJS backends
-- Updated all type castings for TypeScript type checking to `TypeScript 4.1`  
-- Switched bundling from `UMD` to `ESM` + `CommonJS` with fallback to `IIFE`  
-  Resulting code is optimized per-platform instead of being universal  
-  Fully tree shakable when imported as an `ESM` module  
-  Browser bundle process uses `ESBuild` instead of `Rollup`  
-- Typescript build process now targets `ES2018` and instead of dual ES5/ES6  
-  Resulting code is clean ES2018 JavaScript without polyfills  
-- Removed old tests, docs, examples  
-- Removed old package dependencies (`karma`, `jasmine`, `babel`, etc.)  
-- Updated all package dependencies  
-- Updated TensorFlow/JS dependencies since backends were removed from `@tensorflow/tfjs-core`  
-- Updated mobileNetv1 model due to `batchNorm()` dependency  
-- Added `version` class that returns JSON object with version of FaceAPI as well as linked TFJS  
-- Added test/dev built-in HTTP & HTTPS Web server
-- Removed `mtcnn` and `tinyYolov2` models as they were non-functional in latest public version of `Face-API`  
-  *If there is a demand, I can re-implement them back.*  
-- Added `face angle` calculations that returns `roll`, `yaw` and `pitch`  
-
-Which means valid models are **tinyFaceDetector** and **mobileNetv1**  
-
-<br>
-<hr>
-<br>
+<br><hr><br>
 
 ## Examples
 
@@ -64,70 +28,103 @@ Which means valid models are **tinyFaceDetector** and **mobileNetv1**
 
 ### Browser
 
-Browser example that uses static images and showcases both models as well as all of the extensions is included in `/example/index.html`  
-Example can be accessed directly using Git pages using URL: <https://vladmandic.github.io/face-api/example/index.html>  
+Browser example that uses static images and showcases both models  
+as well as all of the extensions is included in `/demo/index.html`  
+Example can be accessed directly using Git pages using URL:  
+<https://vladmandic.github.io/face-api/demo/index.html>  
 
-Browser example that uses live webcam is included in `/example/webcam.html`  
-Example can be accessed directly using Git pages using URL: <https://vladmandic.github.io/face-api/example/webcam.html>  
+Browser example that uses live webcam is included in `/demo/webcam.html`  
+Example can be accessed directly using Git pages using URL:  
+<https://vladmandic.github.io/face-api/demo/webcam.html>  
 
 
 <br>
 
+**Demo using FaceAPI to process images**  
 *Note: Photos shown below are taken by me*
 
-![screenshot](example/screenshot.png)
+![screenshot](demo/screenshot-images.png)
+
+**Demo using FaceAPI to process live webcam**  
+
+![screenshot](demo/screenshot-webcam.png)
 
 <br>
 
 ### NodeJS
 
-Two NodeJS examples are:
+NodeJS examples are:
 
-- `/example/node-singleprocess.js`: Regular usage of `FaceAPI` from `NodeJS`  
-- `/example/node-multiprocess.js`: Multiprocessing showcase that uses pool of worker processes (`node-multiprocess-worker.js`
-  Main starts fixed pool of worker processes with each worker having it's instance of `FaceAPI`  
-  Workers communicate with main when they are ready and main dispaches job to each ready worker until job queue is empty  
+- `/demo/node-simple.js`:
+  Simplest possible NodeJS demo for FaceAPI in under 30 lines of JavaScript code  
+- `/demo/node.js`:  
+  Using `TFJS` native methods to load images without external dependencies  
+- `/demo/node-canvas.js` and `/demo/node-image.js`:  
+  Using external `canvas` module to load images  
+  Which also allows for image drawing and saving inside `NodeJS` environment  
+- `/demo/node-match.js`:  
+  Simple demo that compares face similarity from a given image  
+  to a second image or list of images in a folder  
+- `/demo/node-multiprocess.js`:  
+  Multiprocessing showcase that uses pool of worker processes  
+  (`node-multiprocess-worker.js`)  
+  Main starts fixed pool of worker processes with each worker having  
+  it's instance of `FaceAPI`  
+  Workers communicate with main when they are ready and main dispaches  
+  job to each ready worker until job queue is empty  
 
 ```json
-2020-12-08 08:30:01 INFO:  @vladmandic/face-api version 0.9.1
-2020-12-08 08:30:01 INFO:  User: vlado Platform: linux Arch: x64 Node: v15.0.1
-2020-12-08 08:30:01 INFO:  FaceAPI multi-process test
-2020-12-08 08:30:01 STATE:  Main: started worker: 265238
-2020-12-08 08:30:01 STATE:  Main: started worker: 265244
-2020-12-08 08:30:02 STATE:  Worker: PID: 265238 TensorFlow/JS 2.7.0 FaceAPI 0.9.1 Backend: tensorflow
-2020-12-08 08:30:02 STATE:  Worker: PID: 265244 TensorFlow/JS 2.7.0 FaceAPI 0.9.1 Backend: tensorflow
-2020-12-08 08:30:02 STATE:  Main: dispatching to worker: 265238
-2020-12-08 08:30:02 STATE:  Main: dispatching to worker: 265244
-2020-12-08 08:30:02 DATA:  Worker received message: 265238 { image: 'example/sample (1).jpg' }
-2020-12-08 08:30:02 DATA:  Worker received message: 265244 { image: 'example/sample (2).jpg' }
-2020-12-08 08:30:04 DATA:  Main: worker finished: 265238 detected faces: 3
-2020-12-08 08:30:04 STATE:  Main: dispatching to worker: 265238
-2020-12-08 08:30:04 DATA:  Main: worker finished: 265244 detected faces: 3
-2020-12-08 08:30:04 STATE:  Main: dispatching to worker: 265244
-2020-12-08 08:30:04 DATA:  Worker received message: 265238 { image: 'example/sample (3).jpg' }
-2020-12-08 08:30:04 DATA:  Worker received message: 265244 { image: 'example/sample (4).jpg' }
-2020-12-08 08:30:06 DATA:  Main: worker finished: 265238 detected faces: 3
-2020-12-08 08:30:06 STATE:  Main: dispatching to worker: 265238
-2020-12-08 08:30:06 DATA:  Worker received message: 265238 { image: 'example/sample (5).jpg' }
-2020-12-08 08:30:06 DATA:  Main: worker finished: 265244 detected faces: 4
-2020-12-08 08:30:06 STATE:  Main: dispatching to worker: 265244
-2020-12-08 08:30:06 DATA:  Worker received message: 265244 { image: 'example/sample (6).jpg' }
-2020-12-08 08:30:07 DATA:  Main: worker finished: 265238 detected faces: 5
-2020-12-08 08:30:07 STATE:  Main: worker exit: 265238 0
-2020-12-08 08:30:08 DATA:  Main: worker finished: 265244 detected faces: 4
-2020-12-08 08:30:08 INFO:  Processed 12 images in 6826 ms
-2020-12-08 08:30:08 STATE:  Main: worker exit: 265244 0
+2021-03-14 08:42:03 INFO:  @vladmandic/face-api version 1.0.2
+2021-03-14 08:42:03 INFO:  User: vlado Platform: linux Arch: x64 Node: v15.7.0
+2021-03-14 08:42:03 INFO:  FaceAPI multi-process test
+2021-03-14 08:42:03 STATE:  Main: started worker: 1888019
+2021-03-14 08:42:03 STATE:  Main: started worker: 1888025
+2021-03-14 08:42:04 STATE:  Worker: PID: 1888025 TensorFlow/JS 3.3.0 FaceAPI 1.0.2 Backend: tensorflow
+2021-03-14 08:42:04 STATE:  Worker: PID: 1888019 TensorFlow/JS 3.3.0 FaceAPI 1.0.2 Backend: tensorflow
+2021-03-14 08:42:04 STATE:  Main: dispatching to worker: 1888019
+2021-03-14 08:42:04 STATE:  Main: dispatching to worker: 1888025
+2021-03-14 08:42:04 DATA:  Worker received message: 1888019 { image: 'demo/sample1.jpg' }
+2021-03-14 08:42:04 DATA:  Worker received message: 1888025 { image: 'demo/sample2.jpg' }
+2021-03-14 08:42:06 DATA:  Main: worker finished: 1888025 detected faces: 3
+2021-03-14 08:42:06 STATE:  Main: dispatching to worker: 1888025
+2021-03-14 08:42:06 DATA:  Worker received message: 1888025 { image: 'demo/sample3.jpg' }
+2021-03-14 08:42:06 DATA:  Main: worker finished: 1888019 detected faces: 3
+2021-03-14 08:42:06 STATE:  Main: dispatching to worker: 1888019
+2021-03-14 08:42:06 DATA:  Worker received message: 1888019 { image: 'demo/sample4.jpg' }
+2021-03-14 08:42:07 DATA:  Main: worker finished: 1888025 detected faces: 3
+2021-03-14 08:42:07 STATE:  Main: dispatching to worker: 1888025
+2021-03-14 08:42:07 DATA:  Worker received message: 1888025 { image: 'demo/sample5.jpg' }
+2021-03-14 08:42:08 DATA:  Main: worker finished: 1888019 detected faces: 4
+2021-03-14 08:42:08 STATE:  Main: dispatching to worker: 1888019
+2021-03-14 08:42:08 DATA:  Worker received message: 1888019 { image: 'demo/sample6.jpg' }
+2021-03-14 08:42:09 DATA:  Main: worker finished: 1888025 detected faces: 5
+2021-03-14 08:42:09 STATE:  Main: worker exit: 1888025 0
+2021-03-14 08:42:09 DATA:  Main: worker finished: 1888019 detected faces: 4
+2021-03-14 08:42:09 INFO:  Processed 15 images in 5944 ms
+2021-03-14 08:42:09 STATE:  Main: worker exit: 1888019 0
 ```
 
-Note that `@tensorflow/tfjs-node` or `@tensorflow/tfjs-node-gpu` must be installed before using NodeJS example
+### NodeJS Notes
+- Supported NodeJS versions are **14** up to **22**  
+  NodeJS version **23** and higher are not supported due to incompatibility with TensorFlow/JS  
+- `@tensorflow/tfjs-node` or `@tensorflow/tfjs-node-gpu`  
+  must be installed before using any **NodeJS** examples  
 
-<br>
-<hr>
-<br>
+<br><hr><br>
+
+## Quick Start
+
+Simply include latest version of `FaceAPI` directly from a CDN in your HTML:  
+(pick one, `jsdelivr` or `unpkg`)
+
+```html
+<script src="https://cdn.jsdelivr.net/npm/@vladmandic/face-api/dist/face-api.js"></script>
+<script src="https://unpkg.dev/@vladmandic/face-api/dist/face-api.js"></script>
+```
 
 ## Installation
 
-Face-API ships with several pre-build versions of the library:
+`FaceAPI` ships with several pre-build versions of the library:
 
 - `dist/face-api.js`: IIFE format for client-side Browser execution  
    *with* TFJS pre-bundled
@@ -139,8 +136,6 @@ Face-API ships with several pre-build versions of the library:
    *without* TFJS pre-bundled
 - `dist/face-api.node-gpu.js`: CommonJS format for server-side NodeJS execution  
    *without* TFJS pre-bundled and optimized for CUDA GPU acceleration
-- `dist/face-api.node-cpu.js`: CommonJS format for server-side NodeJS execution  
-   *without* TFJS pre-bundled and using JS engine for platforms where tensorflow binary library version is not available
 
 Defaults are:
 
@@ -154,29 +149,34 @@ Defaults are:
 
 Bundled `TFJS` can be used directly via export: `faceapi.tf`
 
-Reason for additional `nobundle` version is if you want to include a specific version of TFJS and not rely on  pre-packaged one  
+Reason for additional `nobundle` version is if you want to  
+include a specific version of TFJS and not rely on  pre-packaged one  
 
-`FaceAPI` is compatible with TFJS 2.0+  
+`FaceAPI` is compatible with TFJS 2.0+ and TFJS 3.0+  
 
-All versions include `sourcemap` and `asset manifest`
+All versions include `sourcemap`
 
-<br>
-<hr>
-<br>
+<br><hr><br>
 
-There are several ways to use Face-API:
+There are several ways to use FaceAPI:
 
 ### 1. IIFE script
 
 *Recommened for quick tests and backward compatibility with older Browsers that do not support ESM such as IE*
 
 This is simplest way for usage within Browser  
-Simply download `dist/face-api.js`, include it in your `HTML` file & it's ready to use
+Simply download `dist/face-api.js`, include it in your `HTML` file & it's ready to use:
 
 ```html
 <script src="dist/face-api.js"><script>
 ```
 
+Or skip the download and include it directly from a CDN:
+
+```html
+<script src="https://cdn.jsdelivr.net/npm/@vladmandic/face-api/dist/face-api.js"></script>
+```
+
 IIFE script bundles TFJS and auto-registers global namespace `faceapi` within Window object which can be accessed directly from a `<script>` tag or from your JS file.  
 
 <br>
@@ -235,7 +235,7 @@ or to use non-bundled version
 
 *Recommended for NodeJS projects*
 
-*Node: Face-API for NodeJS does not bundle TFJS due to binary dependencies that are installed during TFJS installation*
+*Node: FaceAPI for NodeJS does not bundle TFJS due to binary dependencies that are installed during TFJS installation*
 
 Install with:
 
@@ -258,10 +258,10 @@ If you want to force CommonJS module instead of relying on `recommended` field:
 ```
 
 If you want to GPU Accelerated execution in NodeJS, you must have CUDA libraries already installed and working  
-Then install appropriate version of `Face-API`:
+Then install appropriate version of `FaceAPI`:
 
 ```shell
-  npm install @tensorflow/tfjs-node
+  npm install @tensorflow/tfjs-node-gpu
   npm install @vladmandic/face-api 
 ```
 
@@ -272,21 +272,30 @@ And then use with:
   const faceapi = require('@vladmandic/face-api/dist/face-api.node-gpu.js'); // this loads face-api version with correct bindings for tfjs-node-gpu
 ```
 
-If you want to use `Face-API` in a NodeJS on platforms where NodeJS binary libraries are not supported, you can use JavaScript CPU backend.  
+If you want to use `FaceAPI` in a NodeJS on platforms where **tensorflow** binary libraries are not supported, you can use NodeJS **WASM** backend.  
 
 ```shell
   npm install @tensorflow/tfjs
+  npm install @tensorflow/tfjs-backend-wasm
   npm install @vladmandic/face-api 
 ```
 
 And then use with:
 
 ```js
-  const tf = require('@tensorflow/tfjs')
-  const faceapi = require('@vladmandic/face-api/dist/face-api.node-cpu.js');
+  const tf = require('@tensorflow/tfjs');
+  const wasm = require('@tensorflow/tfjs-backend-wasm');
+  const faceapi = require('@vladmandic/face-api/dist/face-api.node-wasm.js'); // use this when using face-api in dev mode
+  wasm.setWasmPaths('https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm/dist/');
+  await tf.setBackend('wasm');
+  await tf.ready();
+  ...
 ```
 
-If you want to use graphical functions inside NodeJS, you must provide appropriate graphical library as NodeJS does not include implementation for DOM elements such as HTMLImageElement or HTMLCanvasElement:
+If you want to use graphical functions inside NodeJS,  
+you must provide appropriate graphical library as  
+NodeJS does not include implementation for DOM elements  
+such as HTMLImageElement or HTMLCanvasElement:
 
 Install `Canvas` for NodeJS:
 
@@ -304,20 +313,18 @@ const { Canvas, Image, ImageData } = canvas
 faceapi.env.monkeyPatch({ Canvas, Image, ImageData })
 ```
 
-<br>
-<hr>
-<br>
+<br><hr><br>
 
 ## Weights
 
-Pretrained models and their weights are includes in `./model`.
+Pretrained models and their weights are included in `./model`.
 
-<br>
-<hr>
-<br>
+<br><hr><br>
 
 ## Test & Dev Web Server
 
+To install development dependencies, use `npm install --production=false`
+
 Built-in test&dev web server can be started using
 
 ```shell
@@ -326,26 +333,53 @@ npm run dev
 
 By default it starts HTTP server on port 8000 and HTTPS server on port 8001 and can be accessed as:  
 
-- <https://localhost:8001/example/index.html>
-- <https://localhost:8001/example/webcam.html>
+- <https://localhost:8001/demo/index.html>
+- <https://localhost:8001/demo/webcam.html>
 
-```json
-2021-01-10 08:39:00 INFO:  @vladmandic/face-api version 0.10.2
-2021-01-10 08:39:00 INFO:  User: vlado Platform: linux Arch: x64 Node: v15.4.0
-2021-01-10 08:39:00 INFO:  Build: file startup all target: es2018
-2021-01-10 08:39:00 STATE:  HTTP server listening: 8000
-2021-01-10 08:39:00 STATE:  HTTP2 server listening: 8001
-2021-01-10 08:39:00 STATE:  Monitoring: [ 'package.json', 'config.js', 'example', 'src', [length]: 4 ]
-2021-01-10 08:39:00 STATE:  Monitoring: [ 'package.json', 'config.js', 'example', 'src', [length]: 4 ]
-2021-01-10 08:39:01 STATE:  Build for: browserBundle type: tfjs: { modules: 1253, moduleBytes: 3997175, imports: 7, importBytes: 276, outputBytes: 1565414, outputFiles: 'dist/tfjs.esm.js' }
-2021-01-10 08:39:01 STATE:  Build for: browserBundle type: iife: { imports: 160, importBytes: 1797487, outputBytes: 1699552, outputFiles: 'dist/face-api.js' }
-2021-01-10 08:39:01 STATE:  Build for: browserBundle type: esm: { imports: 160, importBytes: 1797487, outputBytes: 1697086, outputFiles: 'dist/face-api.esm.js' }
-2021-01-10 08:39:01 INFO:  Compile: [ 'src/index.ts', [length]: 1 ]
+```js
+2022-01-14 09:56:19 INFO:  @vladmandic/face-api version 1.6.4
+2022-01-14 09:56:19 INFO:  User: vlado Platform: linux Arch: x64 Node: v17.2.0
+2022-01-14 09:56:19 INFO:  Application: { name: '@vladmandic/face-api', version: '1.6.4' }
+2022-01-14 09:56:19 INFO:  Environment: { profile: 'development', config: '.build.json', package: 'package.json', tsconfig: true, eslintrc: true, git: true }
+2022-01-14 09:56:19 INFO:  Toolchain: { build: '0.6.7', esbuild: '0.14.11', typescript: '4.5.4', typedoc: '0.22.10', eslint: '8.6.0' }
+2022-01-14 09:56:19 INFO:  Build: { profile: 'development', steps: [ 'serve', 'watch', 'compile' ] }
+2022-01-14 09:56:19 STATE: WebServer: { ssl: false, port: 8000, root: '.' }
+2022-01-14 09:56:19 STATE: WebServer: { ssl: true, port: 8001, root: '.', sslKey: 'build/cert/https.key', sslCrt: 'build/cert/https.crt' }
+2022-01-14 09:56:19 STATE: Watch: { locations: [ 'src/**', 'README.md', 'src/**', 'src/**' ] }
+2022-01-14 09:56:19 STATE: Compile: { name: 'tfjs/node/cpu', format: 'cjs', platform: 'node', input: 'src/tfjs/tf-node.ts', output: 'dist/tfjs.esm.js', files: 1, inputBytes: 143, outputBytes: 1276 }
+2022-01-14 09:56:19 STATE: Compile: { name: 'faceapi/node/cpu', format: 'cjs', platform: 'node', input: 'src/index.ts', output: 'dist/face-api.node.js', files: 162, inputBytes: 234787, outputBytes: 175203 }
+2022-01-14 09:56:19 STATE: Compile: { name: 'tfjs/node/gpu', format: 'cjs', platform: 'node', input: 'src/tfjs/tf-node-gpu.ts', output: 'dist/tfjs.esm.js', files: 1, inputBytes: 147, outputBytes: 1296 }
+2022-01-14 09:56:19 STATE: Compile: { name: 'faceapi/node/gpu', format: 'cjs', platform: 'node', input: 'src/index.ts', output: 'dist/face-api.node-gpu.js', files: 162, inputBytes: 234807, outputBytes: 175219 }
+2022-01-14 09:56:19 STATE: Compile: { name: 'tfjs/node/wasm', format: 'cjs', platform: 'node', input: 'src/tfjs/tf-node-wasm.ts', output: 'dist/tfjs.esm.js', files: 1, inputBytes: 185, outputBytes: 1367 }
+2022-01-14 09:56:19 STATE: Compile: { name: 'faceapi/node/wasm', format: 'cjs', platform: 'node', input: 'src/index.ts', output: 'dist/face-api.node-wasm.js', files: 162, inputBytes: 234878, outputBytes: 175294 }
+2022-01-14 09:56:19 STATE: Compile: { name: 'tfjs/browser/tf-version', format: 'esm', platform: 'browser', input: 'src/tfjs/tf-version.ts', output: 'dist/tfjs.version.js', files: 1, inputBytes: 1063, outputBytes: 1662 }
+2022-01-14 09:56:19 STATE: Compile: { name: 'tfjs/browser/esm/nobundle', format: 'esm', platform: 'browser', input: 'src/tfjs/tf-browser.ts', output: 'dist/tfjs.esm.js', files: 2, inputBytes: 2172, outputBytes: 811 }
+2022-01-14 09:56:19 STATE: Compile: { name: 'faceapi/browser/esm/nobundle', format: 'esm', platform: 'browser', input: 'src/index.ts', output: 'dist/face-api.esm-nobundle.js', files: 162, inputBytes: 234322, outputBytes: 169437 }
+2022-01-14 09:56:19 STATE: Compile: { name: 'tfjs/browser/esm/bundle', format: 'esm', platform: 'browser', input: 'src/tfjs/tf-browser.ts', output: 'dist/tfjs.esm.js', files: 11, inputBytes: 2172, outputBytes: 2444105 }
+2022-01-14 09:56:20 STATE: Compile: { name: 'faceapi/browser/iife/bundle', format: 'iife', platform: 'browser', input: 'src/index.ts', output: 'dist/face-api.js', files: 162, inputBytes: 2677616, outputBytes: 1252572 }
+2022-01-14 09:56:20 STATE: Compile: { name: 'faceapi/browser/esm/bundle', format: 'esm', platform: 'browser', input: 'src/index.ts', output: 'dist/face-api.esm.js', files: 162, inputBytes: 2677616, outputBytes: 2435063 }
+2022-01-14 09:56:20 INFO:  Listening...
+...
+2022-01-14 09:56:46 DATA:  HTTPS: { method: 'GET', ver: '2.0', status: 200, mime: 'text/html', size: 1047, url: '/', remote: '::1' }
+2022-01-14 09:56:46 DATA:  HTTPS: { method: 'GET', ver: '2.0', status: 200, mime: 'text/javascript', size: 6919, url: '/index.js', remote: '::1' }
+2022-01-14 09:56:46 DATA:  HTTPS: { method: 'GET', ver: '2.0', status: 200, mime: 'text/javascript', size: 2435063, url: '/dist/face-api.esm.js', remote: '::1' }
+2022-01-14 09:56:47 DATA:  HTTPS: { method: 'GET', ver: '2.0', status: 200, mime: 'application/octet-stream', size: 4125244, url: '/dist/face-api.esm.js.map', remote: '::1' }
+2022-01-14 09:56:47 DATA:  HTTPS: { method: 'GET', ver: '2.0', status: 200, mime: 'application/json', size: 3219, url: '/model/tiny_face_detector_model-weights_manifest.json', remote: '::1' }
+2022-01-14 09:56:47 DATA:  HTTPS: { method: 'GET', ver: '2.0', status: 200, mime: 'application/octet-stream', size: 193321, url: '/model/tiny_face_detector_model.bin', remote: '::1' }
+2022-01-14 09:56:47 DATA:  HTTPS: { method: 'GET', ver: '2.0', status: 200, mime: 'application/json', size: 28233, url: '/model/ssd_mobilenetv1_model-weights_manifest.json', remote: '::1' }
+2022-01-14 09:56:47 DATA:  HTTPS: { method: 'GET', ver: '2.0', status: 200, mime: 'application/octet-stream', size: 5616957, url: '/model/ssd_mobilenetv1_model.bin', remote: '::1' }
+2022-01-14 09:56:48 DATA:  HTTPS: { method: 'GET', ver: '2.0', status: 200, mime: 'application/json', size: 8392, url: '/model/age_gender_model-weights_manifest.json', remote: '::1' }
+2022-01-14 09:56:48 DATA:  HTTPS: { method: 'GET', ver: '2.0', status: 200, mime: 'application/octet-stream', size: 429708, url: '/model/age_gender_model.bin', remote: '::1' }
+2022-01-14 09:56:48 DATA:  HTTPS: { method: 'GET', ver: '2.0', status: 200, mime: 'application/json', size: 8485, url: '/model/face_landmark_68_model-weights_manifest.json', remote: '::1' }
+2022-01-14 09:56:48 DATA:  HTTPS: { method: 'GET', ver: '2.0', status: 200, mime: 'application/octet-stream', size: 356840, url: '/model/face_landmark_68_model.bin', remote: '::1' }
+2022-01-14 09:56:48 DATA:  HTTPS: { method: 'GET', ver: '2.0', status: 200, mime: 'application/json', size: 19615, url: '/model/face_recognition_model-weights_manifest.json', remote: '::1' }
+2022-01-14 09:56:48 DATA:  HTTPS: { method: 'GET', ver: '2.0', status: 200, mime: 'application/octet-stream', size: 6444032, url: '/model/face_recognition_model.bin', remote: '::1' }
+2022-01-14 09:56:48 DATA:  HTTPS: { method: 'GET', ver: '2.0', status: 200, mime: 'application/json', size: 6980, url: '/model/face_expression_model-weights_manifest.json', remote: '::1' }
+2022-01-14 09:56:48 DATA:  HTTPS: { method: 'GET', ver: '2.0', status: 200, mime: 'application/octet-stream', size: 329468, url: '/model/face_expression_model.bin', remote: '::1' }
+2022-01-14 09:56:48 DATA:  HTTPS: { method: 'GET', ver: '2.0', status: 200, mime: 'image/jpeg', size: 144516, url: '/sample1.jpg', remote: '::1' }
 ```
 
-<br>
-<hr>
-<br>
+<br><hr><br>
 
 ## Build
 
@@ -366,58 +400,120 @@ cd face-api
 Then install all dependencies and run rebuild:
 
 ```shell
-npm install
+npm install --production=false
 npm run build
 ```
 
-Build process uses script `build.js` that creates optimized build for each target:
+Build process uses `@vladmandic/build` module that creates optimized build for each target:
 
-```text
-npm run build
+```js
+> @vladmandic/face-api@1.7.1 build /home/vlado/dev/face-api
+> node build.js
 
-> @vladmandic/face-api@0.8.9 build /home/vlado/dev/face-api
-> rimraf dist/* && node ./build.js
+2022-07-25 08:21:05 INFO:  Application: { name: '@vladmandic/face-api', version: '1.7.1' }
+2022-07-25 08:21:05 INFO:  Environment: { profile: 'production', config: '.build.json', package: 'package.json', tsconfig: true, eslintrc: true, git: true }
+2022-07-25 08:21:05 INFO:  Toolchain: { build: '0.7.7', esbuild: '0.14.50', typescript: '4.7.4', typedoc: '0.23.9', eslint: '8.20.0' }
+2022-07-25 08:21:05 INFO:  Build: { profile: 'production', steps: [ 'clean', 'compile', 'typings', 'typedoc', 'lint', 'changelog' ] }
+2022-07-25 08:21:05 STATE: Clean: { locations: [ 'dist/*', 'typedoc/*', 'types/lib/src' ] }
+2022-07-25 08:21:05 STATE: Compile: { name: 'tfjs/node/cpu', format: 'cjs', platform: 'node', input: 'src/tfjs/tf-node.ts', output: 'dist/tfjs.esm.js', files: 1, inputBytes: 143, outputBytes: 614 }
+2022-07-25 08:21:05 STATE: Compile: { name: 'faceapi/node/cpu', format: 'cjs', platform: 'node', input: 'src/index.ts', output: 'dist/face-api.node.js', files: 162, inputBytes: 234137, outputBytes: 85701 }
+2022-07-25 08:21:05 STATE: Compile: { name: 'tfjs/node/gpu', format: 'cjs', platform: 'node', input: 'src/tfjs/tf-node-gpu.ts', output: 'dist/tfjs.esm.js', files: 1, inputBytes: 147, outputBytes: 618 }
+2022-07-25 08:21:05 STATE: Compile: { name: 'faceapi/node/gpu', format: 'cjs', platform: 'node', input: 'src/index.ts', output: 'dist/face-api.node-gpu.js', files: 162, inputBytes: 234141, outputBytes: 85705 }
+2022-07-25 08:21:05 STATE: Compile: { name: 'tfjs/node/wasm', format: 'cjs', platform: 'node', input: 'src/tfjs/tf-node-wasm.ts', output: 'dist/tfjs.esm.js', files: 1, inputBytes: 185, outputBytes: 670 }
+2022-07-25 08:21:05 STATE: Compile: { name: 'faceapi/node/wasm', format: 'cjs', platform: 'node', input: 'src/index.ts', output: 'dist/face-api.node-wasm.js', files: 162, inputBytes: 234193, outputBytes: 85755 }
+2022-07-25 08:21:05 STATE: Compile: { name: 'tfjs/browser/tf-version', format: 'esm', platform: 'browser', input: 'src/tfjs/tf-version.ts', output: 'dist/tfjs.version.js', files: 1, inputBytes: 1063, outputBytes: 400 }
+2022-07-25 08:21:05 STATE: Compile: { name: 'tfjs/browser/esm/nobundle', format: 'esm', platform: 'browser', input: 'src/tfjs/tf-browser.ts', output: 'dist/tfjs.esm.js', files: 2, inputBytes: 910, outputBytes: 527 }
+2022-07-25 08:21:05 STATE: Compile: { name: 'faceapi/browser/esm/nobundle', format: 'esm', platform: 'browser', input: 'src/index.ts', output: 'dist/face-api.esm-nobundle.js', files: 162, inputBytes: 234050, outputBytes: 82787 }
+2022-07-25 08:21:05 STATE: Compile: { name: 'tfjs/browser/esm/bundle', format: 'esm', platform: 'browser', input: 'src/tfjs/tf-browser.ts', output: 'dist/tfjs.esm.js', files: 11, inputBytes: 910, outputBytes: 1184871 }
+2022-07-25 08:21:05 STATE: Compile: { name: 'faceapi/browser/iife/bundle', format: 'iife', platform: 'browser', input: 'src/index.ts', output: 'dist/face-api.js', files: 162, inputBytes: 1418394, outputBytes: 1264631 }
+2022-07-25 08:21:05 STATE: Compile: { name: 'faceapi/browser/esm/bundle', format: 'esm', platform: 'browser', input: 'src/index.ts', output: 'dist/face-api.esm.js', files: 162, inputBytes: 1418394, outputBytes: 1264150 }
+2022-07-25 08:21:07 STATE: Typings: { input: 'src/index.ts', output: 'types/lib', files: 93 }
+2022-07-25 08:21:09 STATE: TypeDoc: { input: 'src/index.ts', output: 'typedoc', objects: 154, generated: true }
+2022-07-25 08:21:13 STATE: Lint: { locations: [ 'src/' ], files: 174, errors: 0, warnings: 0 }
+2022-07-25 08:21:14 STATE: ChangeLog: { repository: 'https://github.com/vladmandic/face-api', branch: 'master', output: 'CHANGELOG.md' }
+2022-07-25 08:21:14 INFO:  Done...
+2022-07-25 08:21:14 STATE: Copy: { input: 'types/lib/dist/tfjs.esm.d.ts' }
+2022-07-25 08:21:15 STATE: API-Extractor: { succeeeded: true, errors: 0, warnings: 417 }
+2022-07-25 08:21:15 INFO:  FaceAPI Build complete...
 ```
 
-```json
-2021-01-10 08:42:01 INFO:  @vladmandic/face-api version 0.10.2
-2021-01-10 08:42:01 INFO:  User: vlado Platform: linux Arch: x64 Node: v15.4.0
-2021-01-10 08:42:01 INFO:  Build: file startup all target: es2018
-2021-01-10 08:42:01 STATE:  Build for: node type: tfjs: { imports: 1, importBytes: 143, outputBytes: 1042, outputFiles: 'dist/tfjs.esm.js' }
-2021-01-10 08:42:01 STATE:  Build for: node type: node: { imports: 160, importBytes: 233115, outputBytes: 132266, outputFiles: 'dist/face-api.node.js' }
-2021-01-10 08:42:01 STATE:  Build for: nodeGPU type: tfjs: { imports: 1, importBytes: 147, outputBytes: 1046, outputFiles: 'dist/tfjs.esm.js' }
-2021-01-10 08:42:01 STATE:  Build for: nodeGPU type: node: { imports: 160, importBytes: 233119, outputBytes: 132274, outputFiles: 'dist/face-api.node-gpu.js' }
-2021-01-10 08:42:01 STATE:  Build for: browserNoBundle type: tfjs: { imports: 1, importBytes: 276, outputBytes: 244, outputFiles: 'dist/tfjs.esm.js' }
-2021-01-10 08:42:01 STATE:  Build for: browserNoBundle type: esm: { imports: 160, importBytes: 232317, outputBytes: 129069, outputFiles: 'dist/face-api.esm-nobundle.js' }
-2021-01-10 08:42:01 STATE:  Build for: browserBundle type: tfjs: { modules: 1253, moduleBytes: 3997175, imports: 7, importBytes: 276, outputBytes: 1565414, outputFiles: 'dist/tfjs.esm.js' }
-2021-01-10 08:42:02 STATE:  Build for: browserBundle type: iife: { imports: 160, importBytes: 1797487, outputBytes: 1699552, outputFiles: 'dist/face-api.js' }
-2021-01-10 08:42:02 STATE:  Build for: browserBundle type: esm: { imports: 160, importBytes: 1797487, outputBytes: 1697086, outputFiles: 'dist/face-api.esm.js' }
-2021-01-10 08:42:02 INFO:  Compile: [ 'src/index.ts', [length]: 1 ]```
-```
-
-<br>
-<hr>
-<br>
+<br><hr><br>
 
 ## Face Mesh
 
 `FaceAPI` landmark model returns 68-point face mesh as detailed in the image below:
 
-![facemesh](example/facemesh.png)
+![facemesh](demo/facemesh.png)
 
-## Documentation
+<br><hr><br>
 
-- [**Tutorial**](TUTORIAL.md)
-- [**API Documentation**](https://justadudewhohacks.github.io/face-api.js/docs/globals.html)
+## Note
+
+This is updated **face-api.js** with latest available TensorFlow/JS as the original is not compatible with **tfjs >=2.0**.  
+Forked from [face-api.js](https://github.com/justadudewhohacks/face-api.js) version **0.22.2** which was released on March 22nd, 2020  
+
+*Why?* I needed a FaceAPI that does not cause version conflict with newer versions of TensorFlow  
+And since the original FaceAPI was open-source, I've released this version as well  
+
+Changes ended up being too large for a simple pull request and it ended up being a full-fledged version on its own  
+Plus many features were added since the original inception  
+
+Although a lot of work has gone into this version of `FaceAPI` and it will continue to be maintained,  
+at this time it is completely superseded by my newer library `Human` which covers the same use cases,  
+but extends it with newer AI models, additional detection details, compatibility with latest web standard and more
+
+- [Human NPM](https://www.npmjs.com/package/@vladmandic/human)
+- [Human Git Repository](https://github.com/vladmandic/human)
+
+<br>
+
+## Differences
+
+Compared to [face-api.js](https://github.com/justadudewhohacks/face-api.js) version **0.22.2**:
+
+- Compatible with `TensorFlow/JS 2.0+, 3.0+ and 4.0+`  
+  Currently using **`TensorFlow/JS` 4.16**  
+  Original `face-api.js` is based on `TFJS` **1.7.4**  
+- Compatible with `WebGL`, `CPU` and `WASM` TFJS Browser backends  
+- Compatible with both `tfjs-node` and `tfjs-node-gpu` TFJS NodeJS backends  
+- Updated all type castings for TypeScript type checking to `TypeScript 5.3`  
+- Switched bundling from `UMD` to `ESM` + `CommonJS` with fallback to `IIFE`  
+  Resulting code is optimized per-platform instead of being universal  
+  Fully tree shakable when imported as an `ESM` module  
+  Browser bundle process uses `ESBuild` instead of `Rollup`  
+- Added separate `face-api` versions with `tfjs` pre-bundled and without `tfjs`  
+  When using `-nobundle` version, user can load any version of `tfjs` manually  
+- Typescript build process now targets `ES2018` and instead of dual `ES5`/`ES6`  
+  Resulting code is clean ES2018 JavaScript without polyfills  
+- Removed old tests, docs, examples  
+- Removed old package dependencies (`karma`, `jasmine`, `babel`, etc.)  
+- Updated all package dependencies  
+- Updated TensorFlow/JS dependencies since backends were removed from `@tensorflow/tfjs-core`  
+- Updated `mobileNetv1` model due to `batchNorm()` dependency  
+- Added `version` class that returns JSON object with version of FaceAPI as well as linked TFJS  
+- Added test/dev built-in HTTP & HTTPS Web server  
+- Removed `mtcnn` and `tinyYolov2` models as they were non-functional in latest public version of `FaceAPI`  
+  Which means valid models are **tinyFaceDetector** and **mobileNetv1**  
+  *If there is a demand, I can re-implement them back.*  
+- Added `face angle` calculations that returns `roll`, `yaw` and `pitch`  
+- Added `typdoc` automatic API specification generation during build  
+- Added `changelog` automatic generation during build  
+- New process to generate **TypeDocs** bundle using API-Extractor
+
+<br>
 
 ## Credits
 
-- Original project: [Face-API](https://github.com/justadudewhohacks/face-api.js)  
-- Original model weighs: [Face-API](https://github.com/justadudewhohacks/face-api.js-models)
+- Original project: [face-api.js](https://github.com/justadudewhohacks/face-api.js)
+- Original model weighs: [face-api.js-models](https://github.com/justadudewhohacks/face-api.js-models)
 - ML API Documentation: [Tensorflow/JS](https://js.tensorflow.org/api/latest/)
 
 <br>
 
-![Downloads](https://img.shields.io/npm/dm/@vladmandic/face-api?style=flat-square)
-![Stars](https://img.shields.io/github/stars/vladmandic/face-api?style=flat-square)
-![Code Size](https://img.shields.io/github/languages/code-size/vladmandic/face-api?style=flat-square)
+![Stars](https://img.shields.io/github/stars/vladmandic/face-api?style=flat-square?svg=true)
+![Forks](https://badgen.net/github/forks/vladmandic/face-api)
+![Code Size](https://img.shields.io/github/languages/code-size/vladmandic/face-api?style=flat-square?svg=true)
+![CDN](https://data.jsdelivr.com/v1/package/npm/@vladmandic/face-api/badge)<br>
+![Downloads](https://img.shields.io/npm/dw/@vladmandic/face-api.png?style=flat-square)
+![Downloads](https://img.shields.io/npm/dm/@vladmandic/face-api.png?style=flat-square)
+![Downloads](https://img.shields.io/npm/dy/@vladmandic/face-api.png?style=flat-square)

SECURITY.md

@@ -0,0 +1,5 @@
+# Security Policy
+
+All issues are tracked publicly on GitHub  
+
+Entire code base and indluded dependencies is automatically scanned against known security vulnerabilities  

TODO.md

@@ -0,0 +1,3 @@
+# To-do List for FaceAPI
+
+N/A

TUTORIAL.md

@@ -1,4 +1,4 @@
-# FaceAPI Usage
+# FaceAPI Tutorial
 
 ## Features
 
@@ -38,7 +38,7 @@
 
 All global neural network instances are exported via faceapi.nets:
 
-``` javascript
+```js
 console.log(faceapi.nets)
 // ageGenderNet
 // faceExpressionNet
@@ -54,7 +54,7 @@ To load a model, you have to provide the corresponding manifest.json file as wel
 
 Assuming the models reside in **public/models**:
 
-``` javascript
+```js
 await faceapi.nets.ssdMobilenetv1.loadFromUri('/models')
 // accordingly for the other models:
 // await faceapi.nets.faceLandmark68Net.loadFromUri('/models')
@@ -64,26 +64,26 @@ await faceapi.nets.ssdMobilenetv1.loadFromUri('/models')
 
 In a nodejs environment you can furthermore load the models directly from disk:
 
-``` javascript
+```js
 await faceapi.nets.ssdMobilenetv1.loadFromDisk('./models')
 ```
 
 You can also load the model from a tf.NamedTensorMap:
 
-``` javascript
+```js
 await faceapi.nets.ssdMobilenetv1.loadFromWeightMap(weightMap)
 ```
 
 Alternatively, you can also create own instances of the neural nets:
 
-``` javascript
+```js
 const net = new faceapi.SsdMobilenetv1()
 await net.loadFromUri('/models')
 ```
 
 You can also load the weights as a Float32Array (in case you want to use the uncompressed models):
 
-``` javascript
+```js
 // using fetch
 net.load(await faceapi.fetchNetWeights('/models/face_detection_model.weights'))
 
@@ -105,7 +105,7 @@ In the following **input** can be an HTML img, video or canvas element or the id
 <canvas id="myCanvas" />
 ```
 
-``` javascript
+```js
 const input = document.getElementById('myImg')
 // const input = document.getElementById('myVideo')
 // const input = document.getElementById('myCanvas')
@@ -117,19 +117,19 @@ const input = document.getElementById('myImg')
 
 Detect all faces in an image. Returns **Array<[FaceDetection](#interface-face-detection)>**:
 
-``` javascript
+```js
 const detections = await faceapi.detectAllFaces(input)
 ```
 
 Detect the face with the highest confidence score in an image. Returns **[FaceDetection](#interface-face-detection) | undefined**:
 
-``` javascript
+```js
 const detection = await faceapi.detectSingleFace(input)
 ```
 
 By default **detectAllFaces** and **detectSingleFace** utilize the SSD Mobilenet V1 Face Detector. You can specify the face detector by passing the corresponding options object:
 
-``` javascript
+```js
 const detections1 = await faceapi.detectAllFaces(input, new faceapi.SsdMobilenetv1Options())
 const detections2 = await faceapi.detectAllFaces(input, new faceapi.TinyFaceDetectorOptions())
 ```
@@ -142,19 +142,19 @@ You can tune the options of each face detector as shown [here](#getting-started-
 
 Detect all faces in an image + computes 68 Point Face Landmarks for each detected face. Returns **Array<[WithFaceLandmarks<WithFaceDetection<{}>>](#getting-started-utility-classes)>**:
 
-``` javascript
+```js
 const detectionsWithLandmarks = await faceapi.detectAllFaces(input).withFaceLandmarks()
 ```
 
 Detect the face with the highest confidence score in an image + computes 68 Point Face Landmarks for that face. Returns **[WithFaceLandmarks<WithFaceDetection<{}>>](#getting-started-utility-classes) | undefined**:
 
-``` javascript
+```js
 const detectionWithLandmarks = await faceapi.detectSingleFace(input).withFaceLandmarks()
 ```
 
 You can also specify to use the tiny model instead of the default model:
 
-``` javascript
+```js
 const useTinyModel = true
 const detectionsWithLandmarks = await faceapi.detectAllFaces(input).withFaceLandmarks(useTinyModel)
 ```
@@ -165,13 +165,13 @@ const detectionsWithLandmarks = await faceapi.detectAllFaces(input).withFaceLand
 
 Detect all faces in an image + compute 68 Point Face Landmarks for each detected face. Returns **Array<[WithFaceDescriptor<WithFaceLandmarks<WithFaceDetection<{}>>>](#getting-started-utility-classes)>**:
 
-``` javascript
+```js
 const results = await faceapi.detectAllFaces(input).withFaceLandmarks().withFaceDescriptors()
 ```
 
 Detect the face with the highest confidence score in an image + compute 68 Point Face Landmarks and face descriptor for that face. Returns **[WithFaceDescriptor<WithFaceLandmarks<WithFaceDetection<{}>>>](#getting-started-utility-classes) | undefined**:
 
-``` javascript
+```js
 const result = await faceapi.detectSingleFace(input).withFaceLandmarks().withFaceDescriptor()
 ```
 
@@ -181,13 +181,13 @@ const result = await faceapi.detectSingleFace(input).withFaceLandmarks().withFac
 
 Detect all faces in an image + recognize face expressions of each face. Returns **Array<[WithFaceExpressions<WithFaceLandmarks<WithFaceDetection<{}>>>](#getting-started-utility-classes)>**:
 
-``` javascript
+```js
 const detectionsWithExpressions = await faceapi.detectAllFaces(input).withFaceLandmarks().withFaceExpressions()
 ```
 
 Detect the face with the highest confidence score in an image + recognize the face expressions for that face. Returns **[WithFaceExpressions<WithFaceLandmarks<WithFaceDetection<{}>>>](#getting-started-utility-classes) | undefined**:
 
-``` javascript
+```js
 const detectionWithExpressions = await faceapi.detectSingleFace(input).withFaceLandmarks().withFaceExpressions()
 ```
 
@@ -195,13 +195,13 @@ const detectionWithExpressions = await faceapi.detectSingleFace(input).withFaceL
 
 Detect all faces without face alignment + recognize face expressions of each face. Returns **Array<[WithFaceExpressions<WithFaceDetection<{}>>](#getting-started-utility-classes)>**:
 
-``` javascript
+```js
 const detectionsWithExpressions = await faceapi.detectAllFaces(input).withFaceExpressions()
 ```
 
 Detect the face with the highest confidence score without face alignment + recognize the face expression for that face. Returns **[WithFaceExpressions<WithFaceDetection<{}>>](#getting-started-utility-classes) | undefined**:
 
-``` javascript
+```js
 const detectionWithExpressions = await faceapi.detectSingleFace(input).withFaceExpressions()
 ```
 
@@ -211,13 +211,13 @@ const detectionWithExpressions = await faceapi.detectSingleFace(input).withFaceE
 
 Detect all faces in an image + estimate age and recognize gender of each face. Returns **Array<[WithAge<WithGender<WithFaceLandmarks<WithFaceDetection<{}>>>>](#getting-started-utility-classes)>**:
 
-``` javascript
+```js
 const detectionsWithAgeAndGender = await faceapi.detectAllFaces(input).withFaceLandmarks().withAgeAndGender()
 ```
 
 Detect the face with the highest confidence score in an image  + estimate age and recognize gender for that face. Returns **[WithAge<WithGender<WithFaceLandmarks<WithFaceDetection<{}>>>>](#getting-started-utility-classes) | undefined**:
 
-``` javascript
+```js
 const detectionWithAgeAndGender = await faceapi.detectSingleFace(input).withFaceLandmarks().withAgeAndGender()
 ```
 
@@ -225,13 +225,13 @@ const detectionWithAgeAndGender = await faceapi.detectSingleFace(input).withFace
 
 Detect all faces without face alignment + estimate age and recognize gender of each face. Returns **Array<[WithAge<WithGender<WithFaceDetection<{}>>>](#getting-started-utility-classes)>**:
 
-``` javascript
+```js
 const detectionsWithAgeAndGender = await faceapi.detectAllFaces(input).withAgeAndGender()
 ```
 
 Detect the face with the highest confidence score without face alignment + estimate age and recognize gender for that face. Returns **[WithAge<WithGender<WithFaceDetection<{}>>>](#getting-started-utility-classes) | undefined**:
 
-``` javascript
+```js
 const detectionWithAgeAndGender = await faceapi.detectSingleFace(input).withAgeAndGender()
 ```
 
@@ -239,7 +239,7 @@ const detectionWithAgeAndGender = await faceapi.detectSingleFace(input).withAgeA
 
 **Tasks can be composed as follows:**
 
-``` javascript
+```js
 // all faces
 await faceapi.detectAllFaces(input)
 await faceapi.detectAllFaces(input).withFaceExpressions()
@@ -265,7 +265,7 @@ To perform face recognition, one can use faceapi.FaceMatcher to compare referenc
 
 First, we initialize the FaceMatcher with the reference data, for example we can simply detect faces in a **referenceImage** and match the descriptors of the detected faces to faces of subsequent images:
 
-``` javascript
+```js
 const results = await faceapi
   .detectAllFaces(referenceImage)
   .withFaceLandmarks()
@@ -282,7 +282,7 @@ const faceMatcher = new faceapi.FaceMatcher(results)
 
 Now we can recognize a persons face shown in **queryImage1**:
 
-``` javascript
+```js
 const singleResult = await faceapi
   .detectSingleFace(queryImage1)
   .withFaceLandmarks()
@@ -296,7 +296,7 @@ if (singleResult) {
 
 Or we can recognize all faces shown in **queryImage2**:
 
-``` javascript
+```js
 const results = await faceapi
   .detectAllFaces(queryImage2)
   .withFaceLandmarks()
@@ -310,7 +310,7 @@ results.forEach(fd => {
 
 You can also create labeled reference descriptors as follows:
 
-``` javascript
+```js
 const labeledDescriptors = [
   new faceapi.LabeledFaceDescriptors(
     'obama',
@@ -331,7 +331,7 @@ const faceMatcher = new faceapi.FaceMatcher(labeledDescriptors)
 
 Preparing the overlay canvas:
 
-``` javascript
+```js
 const displaySize = { width: input.width, height: input.height }
 // resize the overlay canvas to the input dimensions
 const canvas = document.getElementById('overlay')
@@ -340,7 +340,7 @@ faceapi.matchDimensions(canvas, displaySize)
 
 face-api.js predefines some highlevel drawing functions, which you can utilize:
 
-``` javascript
+```js
 /* Display detected face bounding boxes */
 const detections = await faceapi.detectAllFaces(input)
 // resize the detected boxes in case your displayed image has a different size than the original
@@ -376,7 +376,7 @@ faceapi.draw.drawFaceExpressions(canvas, resizedResults, minProbability)
 
 You can also draw boxes with custom text ([DrawBox](https://github.com/justadudewhohacks/tfjs-image-recognition-base/blob/master/src/draw/DrawBox.ts)):
 
-``` javascript
+```js
 const box = { x: 50, y: 50, width: 100, height: 100 }
 // see DrawBoxOptions below
 const drawOptions = {
@@ -389,7 +389,7 @@ drawBox.draw(document.getElementById('myCanvas'))
 
 DrawBox drawing options:
 
-``` javascript
+```js
 export interface IDrawBoxOptions {
   boxColor?: string
   lineWidth?: number
@@ -400,7 +400,7 @@ export interface IDrawBoxOptions {
 
 Finally you can draw custom text fields ([DrawTextField](https://github.com/justadudewhohacks/tfjs-image-recognition-base/blob/master/src/draw/DrawTextField.ts)):
 
-``` javascript
+```js
 const text = [
   'This is a textline!',
   'This is another textline!'
@@ -417,7 +417,7 @@ drawBox.draw(document.getElementById('myCanvas'))
 
 DrawTextField drawing options:
 
-``` javascript
+```js
 export interface IDrawTextFieldOptions {
   anchorPosition?: AnchorPosition
   backgroundColor?: string
@@ -441,7 +441,7 @@ export enum AnchorPosition {
 
 #### SsdMobilenetv1Options
 
-``` javascript
+```js
 export interface ISsdMobilenetv1Options {
   // minimum confidence threshold
   // default: 0.5
@@ -458,7 +458,7 @@ const options = new faceapi.SsdMobilenetv1Options({ minConfidence: 0.8 })
 
 #### TinyFaceDetectorOptions
 
-``` javascript
+```js
 export interface ITinyFaceDetectorOptions {
   // size at which image is processed, the smaller the faster,
   // but less precise in detecting smaller faces, must be divisible
@@ -483,7 +483,7 @@ const options = new faceapi.TinyFaceDetectorOptions({ inputSize: 320 })
 
 #### IBox
 
-``` javascript
+```js
 export interface IBox {
   x: number
   y: number
@@ -494,7 +494,7 @@ export interface IBox {
 
 #### IFaceDetection
 
-``` javascript
+```js
 export interface IFaceDetection {
   score: number
   box: Box
@@ -503,7 +503,7 @@ export interface IFaceDetection {
 
 #### IFaceLandmarks
 
-``` javascript
+```js
 export interface IFaceLandmarks {
   positions: Point[]
   shift: Point
@@ -512,7 +512,7 @@ export interface IFaceLandmarks {
 
 #### WithFaceDetection
 
-``` javascript
+```js
 export type WithFaceDetection<TSource> = TSource & {
   detection: FaceDetection
 }
@@ -520,7 +520,7 @@ export type WithFaceDetection<TSource> = TSource & {
 
 #### WithFaceLandmarks
 
-``` javascript
+```js
 export type WithFaceLandmarks<TSource> = TSource & {
   unshiftedLandmarks: FaceLandmarks
   landmarks: FaceLandmarks
@@ -533,7 +533,7 @@ export type WithFaceLandmarks<TSource> = TSource & {
 
 #### WithFaceDescriptor
 
-``` javascript
+```js
 export type WithFaceDescriptor<TSource> = TSource & {
   descriptor: Float32Array
 }
@@ -541,7 +541,7 @@ export type WithFaceDescriptor<TSource> = TSource & {
 
 #### WithFaceExpressions
 
-``` javascript
+```js
 export type WithFaceExpressions<TSource> = TSource & {
   expressions: FaceExpressions
 }
@@ -549,7 +549,7 @@ export type WithFaceExpressions<TSource> = TSource & {
 
 #### WithAge
 
-``` javascript
+```js
 export type WithAge<TSource> = TSource & {
   age: number
 }
@@ -557,7 +557,7 @@ export type WithAge<TSource> = TSource & {
 
 #### WithGender
 
-``` javascript
+```js
 export type WithGender<TSource> = TSource & {
   gender: Gender
   genderProbability: number
@@ -577,7 +577,7 @@ export enum Gender {
 
 Instead of using the high level API, you can directly use the forward methods of each neural network:
 
-``` javascript
+```js
 const detections1 = await faceapi.ssdMobilenetv1(input, options)
 const detections2 = await faceapi.tinyFaceDetector(input, options)
 const landmarks1 = await faceapi.detectFaceLandmarks(faceImage)
@@ -587,7 +587,7 @@ const descriptor = await faceapi.computeFaceDescriptor(alignedFaceImage)
 
 #### Extracting a Canvas for an Image Region
 
-``` javascript
+```js
 const regionsToExtract = [
   new faceapi.Rect(0, 0, 100, 100)
 ]
@@ -598,7 +598,7 @@ const canvases = await faceapi.extractFaces(input, regionsToExtract)
 
 #### Euclidean Distance
 
-``` javascript
+```js
 // ment to be used for computing the euclidean distance between two face descriptors
 const dist = faceapi.euclideanDistance([0, 0], [0, 10])
 console.log(dist) // 10
@@ -606,7 +606,7 @@ console.log(dist) // 10
 
 #### Retrieve the Face Landmark Points and Contours
 
-``` javascript
+```js
 const landmarkPositions = landmarks.positions
 
 // or get the positions of individual contours,
@@ -626,7 +626,7 @@ const rightEyeBrow = landmarks.getRightEyeBrow()
 <img id="myImg" src="">
 ```
 
-``` javascript
+```js
 const image = await faceapi.fetchImage('/images/example.png')
 
 console.log(image instanceof HTMLImageElement) // true
@@ -638,7 +638,7 @@ myImg.src = image.src
 
 #### Fetching JSON
 
-``` javascript
+```js
 const json = await faceapi.fetchJson('/files/example.json')
 ```
 
@@ -649,7 +649,7 @@ const json = await faceapi.fetchJson('/files/example.json')
 <input id="myFileUpload" type="file" onchange="uploadImage()" accept=".jpg, .jpeg, .png">
 ```
 
-``` javascript
+```js
 async function uploadImage() {
   const imgFile = document.getElementById('myFileUpload').files[0]
   // create an HTMLImageElement from a Blob
@@ -665,7 +665,7 @@ async function uploadImage() {
 <video id="myVideo" src="media/example.mp4" />
 ```
 
-``` javascript
+```js
 const canvas1 = faceapi.createCanvasFromMedia(document.getElementById('myImg'))
 const canvas2 = faceapi.createCanvasFromMedia(document.getElementById('myVideo'))
 ```

api-extractor.json

@@ -0,0 +1,38 @@
+{
+  "$schema": "https://developer.microsoft.com/json-schemas/api-extractor/v7/api-extractor.schema.json",
+  "mainEntryPointFilePath": "types/lib/src/index.d.ts",
+  "bundledPackages": ["@tensorflow/tfjs-core", "@tensorflow/tfjs-converter", "@types/offscreencanvas"],
+  "compiler": {
+    "skipLibCheck": false
+  },
+  "newlineKind": "lf",
+  "dtsRollup": {
+    "enabled": true,
+    "untrimmedFilePath": "types/face-api.d.ts"
+  },
+  "docModel": { "enabled": false },
+  "tsdocMetadata": {
+    "enabled": false
+  },
+  "apiReport": { "enabled": false },
+  "messages": {
+    "compilerMessageReporting": {
+      "default": {
+        "logLevel": "warning"
+      }
+    },
+    "extractorMessageReporting": {
+      "default": {
+        "logLevel": "warning"
+      },
+      "ae-missing-release-tag": {
+        "logLevel": "none"
+      }
+    },
+    "tsdocMessageReporting": {
+      "default": {
+        "logLevel": "warning"
+      }
+    }
+  }
+}

build.js

@@ -0,0 +1,77 @@
+const fs = require('fs');
+const log = require('@vladmandic/pilogger');
+const Build = require('@vladmandic/build').Build;
+const APIExtractor = require('@microsoft/api-extractor');
+
+const regEx = [
+  { search: 'types="@webgpu/types/dist"', replace: 'path="../src/types/webgpu.d.ts"' },
+  { search: 'types="offscreencanvas"', replace: 'path="../src/types/offscreencanvas.d.ts"' },
+];
+
+function copyFile(src, dst) {
+  if (!fs.existsSync(src)) {
+    log.warn('Copy:', { input: src, output: dst });
+    return;
+  }
+  log.state('Copy:', { input: src, output: dst });
+  const buffer = fs.readFileSync(src);
+  fs.writeFileSync(dst, buffer);
+}
+
+function writeFile(str, dst) {
+  log.state('Write:', { output: dst });
+  fs.writeFileSync(dst, str);
+}
+
+function regExFile(src, entries) {
+  if (!fs.existsSync(src)) {
+    log.warn('Filter:', { src });
+    return;
+  }
+  log.state('Filter:', { input: src });
+  for (const entry of entries) {
+    const buffer = fs.readFileSync(src, 'UTF-8');
+    const lines = buffer.split(/\r?\n/);
+    const out = [];
+    for (const line of lines) {
+      if (line.includes(entry.search)) out.push(line.replace(entry.search, entry.replace));
+      else out.push(line);
+    }
+    fs.writeFileSync(src, out.join('\n'));
+  }
+}
+
+const apiIgnoreList = ['ae-forgotten-export', 'ae-unresolved-link', 'tsdoc-param-tag-missing-hyphen'];
+
+async function main() {
+  // run production build
+  const build = new Build();
+  await build.run('production');
+  // patch tfjs typedefs
+  log.state('Copy:', { input: 'types/lib/dist/tfjs.esm.d.ts' });
+  copyFile('types/lib/dist/tfjs.esm.d.ts', 'dist/tfjs.esm.d.ts');
+  // run api-extractor to create typedef rollup
+  const extractorConfig = APIExtractor.ExtractorConfig.loadFileAndPrepare('api-extractor.json');
+  const extractorResult = APIExtractor.Extractor.invoke(extractorConfig, {
+    localBuild: true,
+    showVerboseMessages: false,
+    messageCallback: (msg) => {
+      msg.handled = true;
+      if (msg.logLevel === 'none' || msg.logLevel === 'verbose' || msg.logLevel === 'info') return;
+      if (msg.sourceFilePath?.includes('/node_modules/')) return;
+      if (apiIgnoreList.reduce((prev, curr) => prev || msg.messageId.includes(curr), false)) return;
+      log.data('API', { level: msg.logLevel, category: msg.category, id: msg.messageId, file: msg.sourceFilePath, line: msg.sourceFileLine, text: msg.text });
+    },
+  });
+  log.state('API-Extractor:', { succeeeded: extractorResult.succeeded, errors: extractorResult.errorCount, warnings: extractorResult.warningCount });
+  regExFile('types/face-api.d.ts', regEx);
+  writeFile('export * from \'../types/face-api\';', 'dist/face-api.esm-nobundle.d.ts');
+  writeFile('export * from \'../types/face-api\';', 'dist/face-api.esm.d.ts');
+  writeFile('export * from \'../types/face-api\';', 'dist/face-api.d.ts');
+  writeFile('export * from \'../types/face-api\';', 'dist/face-api.node.d.ts');
+  writeFile('export * from \'../types/face-api\';', 'dist/face-api.node-gpu.d.ts');
+  writeFile('export * from \'../types/face-api\';', 'dist/face-api.node-wasm.d.ts');
+  log.info('FaceAPI Build complete...');
+}
+
+main();

demo/index.html

@@ -0,0 +1,17 @@
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+    <title>FaceAPI Static Images Demo</title>
+    <meta http-equiv="content-type" content="text/html; charset=utf-8">
+    <meta name="viewport" content="width=device-width, shrink-to-fit=yes">
+    <meta name="application-name" content="FaceAPI">
+    <meta name="keywords" content="FaceAPI">
+    <meta name="description" content="FaceAPI: AI-powered Face Detection, Description & Recognition for Browser and NodeJS using Tensorflow/JS; Author: Vladimir Mandic <https://github.com/vladmandic>">
+    <meta name="msapplication-tooltip" content="FaceAPI: AI-powered Face Detection, Description & Recognition for Browser and NodeJS using Tensorflow/JS; Author: Vladimir Mandic <https://github.com/vladmandic>">
+    <link rel="shortcut icon" href="../favicon.ico" type="image/x-icon">
+    <script src="./index.js" type="module"></script>
+  </head>
+  <body style="font-family: monospace; background: black; color: white; font-size: 16px; line-height: 22px; margin: 0; overflow-x: hidden;">
+    <div id="log"></div>
+  </body>
+</html>

demo/index.js

@@ -1,27 +1,27 @@
-import * as faceapi from '../dist/face-api.esm.js';
+/**
+ * FaceAPI Demo for Browsers
+ * Loaded via `index.html`
+ */
+
+import * as faceapi from '../dist/face-api.esm.js'; // use when in dev mode
+// import * as faceapi from '@vladmandic/face-api'; // use when downloading face-api as npm
 
 // configuration options
-const modelPath = 'https://vladmandic.github.io/face-api/model/'; // path to model folder that will be loaded using http
-// const modelPath = '../model/'; // path to model folder that will be loaded using http
+const modelPath = '../model/'; // path to model folder that will be loaded using http
+// const modelPath = 'https://cdn.jsdelivr.net/npm/@vladmandic/face-api/model/'; // path to model folder that will be loaded using http
 const imgSize = 800; // maximum image size in pixels
 const minScore = 0.3; // minimum score
 const maxResults = 10; // maximum number of results to return
-const samples = ['sample (1).jpg', 'sample (2).jpg', 'sample (3).jpg', 'sample (4).jpg', 'sample (5).jpg', 'sample (6).jpg']; // sample images to be loaded using http
+const samples = ['sample1.jpg', 'sample2.jpg', 'sample3.jpg', 'sample4.jpg', 'sample5.jpg', 'sample6.jpg']; // sample images to be loaded using http
 
 // helper function to pretty-print json object to string
-function str(json) {
-  let text = '<font color="lightblue">';
-  text += json ? JSON.stringify(json).replace(/{|}|"|\[|\]/g, '').replace(/,/g, ', ') : '';
-  text += '</font>';
-  return text;
-}
+const str = (json) => (json ? JSON.stringify(json).replace(/{|}|"|\[|\]/g, '').replace(/,/g, ', ') : '');
 
 // helper function to print strings to html document as a log
 function log(...txt) {
-  // eslint-disable-next-line no-console
-  console.log(...txt);
-  // @ts-ignore
-  document.getElementById('log').innerHTML += `<br>${txt}`;
+  console.log(...txt); // eslint-disable-line no-console
+  const div = document.getElementById('log');
+  if (div) div.innerHTML += `<br>${txt}`;
 }
 
 // helper function to draw detected faces
@@ -33,11 +33,9 @@ function faces(name, title, id, data) {
   canvas.style.position = 'absolute';
   canvas.style.left = `${img.offsetLeft}px`;
   canvas.style.top = `${img.offsetTop}px`;
-  // @ts-ignore
   canvas.width = img.width;
-  // @ts-ignore
   canvas.height = img.height;
-  const ctx = canvas.getContext('2d');
+  const ctx = canvas.getContext('2d', { willReadFrequently: true });
   if (!ctx) return;
   // draw title
   ctx.font = '1rem sans-serif';
@@ -53,6 +51,7 @@ function faces(name, title, id, data) {
     ctx.beginPath();
     ctx.rect(person.detection.box.x, person.detection.box.y, person.detection.box.width, person.detection.box.height);
     ctx.stroke();
+    // draw text labels
     ctx.globalAlpha = 1;
     ctx.fillText(`${Math.round(100 * person.genderProbability)}% ${person.gender}`, person.detection.box.x, person.detection.box.y - 18);
     ctx.fillText(`${Math.round(person.age)} years`, person.detection.box.x, person.detection.box.y - 2);
@@ -72,8 +71,7 @@ function faces(name, title, id, data) {
 
 // helper function to draw processed image and its results
 function print(title, img, data) {
-  // eslint-disable-next-line no-console
-  console.log('Results:', title, img, data);
+  console.log('Results:', title, img, data); // eslint-disable-line no-console
   const el = new Image();
   el.id = Math.floor(Math.random() * 100000).toString();
   el.src = img;
@@ -96,7 +94,7 @@ async function image(url) {
       const canvas = document.createElement('canvas');
       canvas.height = img.height;
       canvas.width = img.width;
-      const ctx = canvas.getContext('2d');
+      const ctx = canvas.getContext('2d', { willReadFrequently: true });
       if (ctx) ctx.drawImage(img, 0, 0, img.width, img.height);
       // return generated canvas to be used by tfjs during detection
       resolve(canvas);
@@ -111,18 +109,23 @@ async function main() {
   log('FaceAPI Test');
 
   // if you want to use wasm backend location for wasm binaries must be specified
-  // await faceapi.tf.setWasmPaths('../node_modules/@tensorflow/tfjs-backend-wasm/dist/');
-  // await faceapi.tf.setBackend('wasm');
+  // await faceapi.tf?.setWasmPaths(`https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@${faceapi.tf.version_core}/dist/`);
+  // await faceapi.tf?.setBackend('wasm');
+  // log(`WASM SIMD: ${await faceapi.tf?.env().getAsync('WASM_HAS_SIMD_SUPPORT')} Threads: ${await faceapi.tf?.env().getAsync('WASM_HAS_MULTITHREAD_SUPPORT') ? 'Multi' : 'Single'}`);
 
   // default is webgl backend
   await faceapi.tf.setBackend('webgl');
+  await faceapi.tf.ready();
 
+  // tfjs optimizations
+  if (faceapi.tf?.env().flagRegistry.CANVAS2D_WILL_READ_FREQUENTLY) faceapi.tf.env().set('CANVAS2D_WILL_READ_FREQUENTLY', true);
+  if (faceapi.tf?.env().flagRegistry.WEBGL_EXP_CONV) faceapi.tf.env().set('WEBGL_EXP_CONV', true);
+  if (faceapi.tf?.env().flagRegistry.WEBGL_EXP_CONV) faceapi.tf.env().set('WEBGL_EXP_CONV', true);
   await faceapi.tf.enableProdMode();
-  await faceapi.tf.ENV.set('DEBUG', false);
   await faceapi.tf.ready();
 
   // check version
-  log(`Version: FaceAPI ${str(faceapi?.version.faceapi || '(not loaded)')} TensorFlow/JS ${str(faceapi?.tf?.version_core || '(not loaded)')} Backend: ${str(faceapi?.tf?.getBackend() || '(not loaded)')}`);
+  log(`Version: FaceAPI ${str(faceapi?.version || '(not loaded)')} TensorFlow/JS ${str(faceapi?.tf?.version_core || '(not loaded)')} Backend: ${str(faceapi?.tf?.getBackend() || '(not loaded)')}`);
   log(`Flags: ${JSON.stringify(faceapi?.tf?.ENV.flags || { tf: 'not loaded' })}`);
 
   // load face-api models
@@ -140,16 +143,9 @@ async function main() {
   const engine = await faceapi.tf.engine();
   log(`TF Engine State: ${str(engine.state)}`);
 
-  // const testT = faceapi.tf.tensor([0]);
-  // const testF = testT.toFloat();
-  // console.log(testT.print(), testF.print());
-  // testT.dispose();
-  // testF.dispose();
-
   // loop through all images and try to process them
   log(`Start processing: ${samples.length} images ...<br>`);
   for (const img of samples) {
-    // new line
     document.body.appendChild(document.createElement('br'));
     // load and resize image
     const canvas = await image(img);
@@ -163,7 +159,7 @@ async function main() {
         .withFaceDescriptors()
         .withAgeAndGender();
       // print results to screen
-      print('TinyFace Detector', img, dataTinyYolo);
+      print('TinyFace:', img, dataTinyYolo);
       // actual model execution
       const dataSSDMobileNet = await faceapi
         .detectAllFaces(canvas, optionsSSDMobileNet)
@@ -172,11 +168,9 @@ async function main() {
         .withFaceDescriptors()
         .withAgeAndGender();
       // print results to screen
-      print('SSD MobileNet', img, dataSSDMobileNet);
+      print('SSDMobileNet:', img, dataSSDMobileNet);
     } catch (err) {
       log(`Image: ${img} Error during processing ${str(err)}`);
-      // eslint-disable-next-line no-console
-      console.error(err);
     }
   }
 }

demo/node-canvas.js

@@ -0,0 +1,98 @@
+/**
+ * FaceAPI Demo for NodeJS
+ * - Uses external library [canvas](https://www.npmjs.com/package/canvas) to decode image
+ * - Loads image from provided param
+ * - Outputs results to console
+ */
+
+// canvas library provides full canvas (load/draw/write) functionality for nodejs
+// must be installed manually as it just a demo dependency and not actual face-api dependency
+const canvas = require('canvas'); // eslint-disable-line node/no-missing-require
+const fs = require('fs');
+const path = require('path');
+const process = require('process');
+const log = require('@vladmandic/pilogger');
+const tf = require('@tensorflow/tfjs-node'); // in nodejs environments tfjs-node is required to be loaded before face-api
+const faceapi = require('../dist/face-api.node.js'); // use this when using face-api in dev mode
+// const faceapi = require('@vladmandic/face-api'); // use this when face-api is installed as module (majority of use cases)
+
+const modelPathRoot = '../model';
+const imgPathRoot = './demo'; // modify to include your sample images
+const minConfidence = 0.15;
+const maxResults = 5;
+let optionsSSDMobileNet;
+
+async function image(input) {
+  const img = await canvas.loadImage(input);
+  const c = canvas.createCanvas(img.width, img.height);
+  const ctx = c.getContext('2d');
+  ctx.drawImage(img, 0, 0, img.width, img.height);
+  // const out = fs.createWriteStream('test.jpg');
+  // const stream = c.createJPEGStream({ quality: 0.6, progressive: true, chromaSubsampling: true });
+  // stream.pipe(out);
+  return c;
+}
+
+async function detect(tensor) {
+  const result = await faceapi
+    .detectAllFaces(tensor, optionsSSDMobileNet)
+    .withFaceLandmarks()
+    .withFaceExpressions()
+    .withFaceDescriptors()
+    .withAgeAndGender();
+  return result;
+}
+
+function print(face) {
+  const expression = Object.entries(face.expressions).reduce((acc, val) => ((val[1] > acc[1]) ? val : acc), ['', 0]);
+  const box = [face.alignedRect._box._x, face.alignedRect._box._y, face.alignedRect._box._width, face.alignedRect._box._height];
+  const gender = `Gender: ${Math.round(100 * face.genderProbability)}% ${face.gender}`;
+  log.data(`Detection confidence: ${Math.round(100 * face.detection._score)}% ${gender} Age: ${Math.round(10 * face.age) / 10} Expression: ${Math.round(100 * expression[1])}% ${expression[0]} Box: ${box.map((a) => Math.round(a))}`);
+}
+
+async function main() {
+  log.header();
+  log.info('FaceAPI single-process test');
+
+  faceapi.env.monkeyPatch({ Canvas: canvas.Canvas, Image: canvas.Image, ImageData: canvas.ImageData });
+
+  await faceapi.tf.setBackend('tensorflow');
+  await faceapi.tf.ready();
+
+  log.state(`Version: FaceAPI ${faceapi.version} TensorFlow/JS ${tf.version_core} Backend: ${faceapi.tf?.getBackend()}`);
+
+  log.info('Loading FaceAPI models');
+  const modelPath = path.join(__dirname, modelPathRoot);
+  await faceapi.nets.ssdMobilenetv1.loadFromDisk(modelPath);
+  await faceapi.nets.ageGenderNet.loadFromDisk(modelPath);
+  await faceapi.nets.faceLandmark68Net.loadFromDisk(modelPath);
+  await faceapi.nets.faceRecognitionNet.loadFromDisk(modelPath);
+  await faceapi.nets.faceExpressionNet.loadFromDisk(modelPath);
+  optionsSSDMobileNet = new faceapi.SsdMobilenetv1Options({ minConfidence, maxResults });
+
+  if (process.argv.length !== 3) {
+    const t0 = process.hrtime.bigint();
+    const dir = fs.readdirSync(imgPathRoot);
+    let numImages = 0;
+    for (const img of dir) {
+      if (!img.toLocaleLowerCase().endsWith('.jpg')) continue;
+      numImages += 1;
+      const c = await image(path.join(imgPathRoot, img));
+      const result = await detect(c);
+      log.data('Image:', img, 'Detected faces:', result.length);
+      for (const face of result) print(face);
+    }
+    const t1 = process.hrtime.bigint();
+    log.info('Processed', numImages, 'images in', Math.trunc(Number((t1 - t0).toString()) / 1000 / 1000), 'ms');
+  } else {
+    const param = process.argv[2];
+    if (fs.existsSync(param) || param.startsWith('http:') || param.startsWith('https:')) {
+      const c = await image(param);
+      const result = await detect(c);
+      log.data('Image:', param, 'Detected faces:', result.length);
+      for (const face of result) print(face);
+    }
+  }
+}
+
+main();

demo/node-face-compare.js

@@ -0,0 +1,35 @@
+/**
+ * FaceAPI demo that loads two images and finds similarity most prominant face in each image
+ */
+
+const fs = require('fs');
+const tf = require('@tensorflow/tfjs-node');
+const faceapi = require('../dist/face-api.node');
+
+let optionsSSDMobileNet;
+
+const getDescriptors = async (imageFile) => {
+  const buffer = fs.readFileSync(imageFile);
+  const tensor = tf.node.decodeImage(buffer, 3);
+  const faces = await faceapi.detectAllFaces(tensor, optionsSSDMobileNet)
+    .withFaceLandmarks()
+    .withFaceDescriptors();
+  tf.dispose(tensor);
+  return faces.map((face) => face.descriptor);
+};
+
+const main = async (file1, file2) => {
+  console.log('input images:', file1, file2); // eslint-disable-line no-console
+  await tf.ready();
+  await faceapi.nets.ssdMobilenetv1.loadFromDisk('model');
+  optionsSSDMobileNet = new faceapi.SsdMobilenetv1Options({ minConfidence: 0.5, maxResults: 1 });
+  await faceapi.nets.faceLandmark68Net.loadFromDisk('model');
+  await faceapi.nets.faceRecognitionNet.loadFromDisk('model');
+  const desc1 = await getDescriptors(file1);
+  const desc2 = await getDescriptors(file2);
+  const distance = faceapi.euclideanDistance(desc1[0], desc2[0]); // only compare first found face in each image
+  console.log('distance between most prominant detected faces:', distance); // eslint-disable-line no-console
+  console.log('similarity between most prominant detected faces:', 1 - distance); // eslint-disable-line no-console
+};
+
+main('demo/sample1.jpg', 'demo/sample2.jpg');

demo/node-image.js

@@ -0,0 +1,54 @@
+/**
+ * FaceAPI Demo for NodeJS
+ * - Uses external library [@canvas/image](https://www.npmjs.com/package/@canvas/image) to decode image
+ * - Loads image from provided param
+ * - Outputs results to console
+ */
+
+// @canvas/image can decode jpeg, png, webp
+// must be installed manually as it just a demo dependency and not actual face-api dependency
+const image = require('@canvas/image'); // eslint-disable-line node/no-missing-require
+const fs = require('fs');
+const log = require('@vladmandic/pilogger');
+const tf = require('@tensorflow/tfjs-node'); // in nodejs environments tfjs-node is required to be loaded before face-api
+const faceapi = require('../dist/face-api.node.js'); // use this when using face-api in dev mode
+// const faceapi = require('@vladmandic/face-api'); // use this when face-api is installed as module (majority of use cases)
+
+const modelPath = 'model/';
+const imageFile = 'demo/sample1.jpg';
+const ssdOptions = { minConfidence: 0.1, maxResults: 10 };
+
+async function main() {
+  log.header();
+  const buffer = fs.readFileSync(imageFile); // read image from disk
+  const canvas = await image.imageFromBuffer(buffer); // decode to canvas
+  const imageData = image.getImageData(canvas); // read decoded image data from canvas
+  log.info('image:', imageFile, canvas.width, canvas.height);
+
+  const tensor = tf.tidy(() => { // create tensor from image data
+    const data = tf.tensor(Array.from(imageData?.data || []), [canvas.height, canvas.width, 4], 'int32'); // create rgba image tensor from flat array and flip to height x width
+    const channels = tf.split(data, 4, 2); // split rgba to channels
+    const rgb = tf.stack([channels[0], channels[1], channels[2]], 2); // stack channels back to rgb
+    const reshape = tf.reshape(rgb, [1, canvas.height, canvas.width, 3]); // move extra dim from the end of tensor and use it as batch number instead
+    return reshape;
+  });
+  log.info('tensor:', tensor.shape, tensor.size);
+
+  // load models
+  await faceapi.nets.ssdMobilenetv1.loadFromDisk(modelPath);
+  await faceapi.nets.ageGenderNet.loadFromDisk(modelPath);
+  await faceapi.nets.faceLandmark68Net.loadFromDisk(modelPath);
+  await faceapi.nets.faceRecognitionNet.loadFromDisk(modelPath);
+  await faceapi.nets.faceExpressionNet.loadFromDisk(modelPath);
+
+  const optionsSSDMobileNet = new faceapi.SsdMobilenetv1Options(ssdOptions); // create options object
+  const result = await faceapi // run detection
+    .detectAllFaces(tensor, optionsSSDMobileNet)
+    .withFaceLandmarks()
+    .withFaceExpressions()
+    .withFaceDescriptors()
+    .withAgeAndGender();
+  log.data('results:', result.length);
+}
+
+main();

demo/node-match.js

@@ -0,0 +1,84 @@
+/**
+ * FaceAPI Demo for NodeJS
+ * - Analyzes face descriptors from source (image file or folder containing multiple image files)
+ * - Analyzes face descriptor from target
+ * - Finds best match
+ */
+
+const fs = require('fs');
+const path = require('path');
+const log = require('@vladmandic/pilogger');
+const tf = require('@tensorflow/tfjs-node'); // in nodejs environments tfjs-node is required to be loaded before face-api
+const faceapi = require('../dist/face-api.node.js'); // use this when using face-api in dev mode
+// const faceapi = require('@vladmandic/face-api'); // use this when face-api is installed as module (majority of use cases)
+
+let optionsSSDMobileNet;
+const minConfidence = 0.1;
+const distanceThreshold = 0.5;
+const modelPath = 'model';
+const labeledFaceDescriptors = [];
+
+async function initFaceAPI() {
+  await faceapi.nets.ssdMobilenetv1.loadFromDisk(modelPath);
+  await faceapi.nets.faceLandmark68Net.loadFromDisk(modelPath);
+  await faceapi.nets.faceExpressionNet.loadFromDisk(modelPath);
+  await faceapi.nets.faceRecognitionNet.loadFromDisk(modelPath);
+  optionsSSDMobileNet = new faceapi.SsdMobilenetv1Options({ minConfidence, maxResults: 1 });
+}
+
+async function getDescriptors(imageFile) {
+  const buffer = fs.readFileSync(imageFile);
+  const tensor = tf.node.decodeImage(buffer, 3);
+  const faces = await faceapi.detectAllFaces(tensor, optionsSSDMobileNet)
+    .withFaceLandmarks()
+    .withFaceExpressions()
+    .withFaceDescriptors();
+  tf.dispose(tensor);
+  return faces.map((face) => face.descriptor);
+}
+
+async function registerImage(inputFile) {
+  if (!inputFile.toLowerCase().endsWith('jpg') && !inputFile.toLowerCase().endsWith('png') && !inputFile.toLowerCase().endsWith('gif')) return;
+  log.data('Registered:', inputFile);
+  const descriptors = await getDescriptors(inputFile);
+  for (const descriptor of descriptors) {
+    const labeledFaceDescriptor = new faceapi.LabeledFaceDescriptors(inputFile, [descriptor]);
+    labeledFaceDescriptors.push(labeledFaceDescriptor);
+  }
+}
+
+async function findBestMatch(inputFile) {
+  const matcher = new faceapi.FaceMatcher(labeledFaceDescriptors, distanceThreshold);
+  const descriptors = await getDescriptors(inputFile);
+  const matches = [];
+  for (const descriptor of descriptors) {
+    const match = await matcher.findBestMatch(descriptor);
+    matches.push(match);
+  }
+  return matches;
+}
+
+async function main() {
+  log.header();
+  if (process.argv.length !== 4) {
+    log.error(process.argv[1], 'Expected <source image or folder> <target image>');
+    process.exit(1);
+  }
+  await initFaceAPI();
+  log.info('Input:', process.argv[2]);
+  if (fs.statSync(process.argv[2]).isFile()) {
+    await registerImage(process.argv[2]); // register image
+  } else if (fs.statSync(process.argv[2]).isDirectory()) {
+    const dir = fs.readdirSync(process.argv[2]);
+    for (const f of dir) await registerImage(path.join(process.argv[2], f)); // register all images in a folder
+  }
+  log.info('Comparing:', process.argv[3], 'Descriptors:', labeledFaceDescriptors.length);
+  if (labeledFaceDescriptors.length > 0) {
+    const bestMatch = await findBestMatch(process.argv[3]); // find best match to all registered images
+    log.data('Match:', bestMatch);
+  } else {
+    log.warn('No registered faces');
+  }
+}
+
+main();

demo/node-multiprocess-worker.js

@@ -1,18 +1,20 @@
-// @ts-nocheck
+/**
+ * FaceAPI Demo for NodeJS
+ * - Used by `node-multiprocess.js`
+ */
 
 const fs = require('fs');
 const path = require('path');
-// eslint-disable-next-line import/no-extraneous-dependencies, node/no-unpublished-require
 const log = require('@vladmandic/pilogger');
 
 // workers actual import tfjs and faceapi modules
-// eslint-disable-next-line import/no-extraneous-dependencies, node/no-unpublished-require
-const tf = require('@tensorflow/tfjs-node');
-const faceapi = require('../dist/face-api.node.js'); // this is equivalent to '@vladmandic/faceapi'
+const tf = require('@tensorflow/tfjs-node'); // in nodejs environments tfjs-node is required to be loaded before face-api
+const faceapi = require('../dist/face-api.node.js'); // use this when using face-api in dev mode
+// const faceapi = require('@vladmandic/face-api'); // use this when face-api is installed as module (majority of use cases)
 
 // options used by faceapi
 const modelPathRoot = '../model';
-const minScore = 0.1;
+const minConfidence = 0.15;
 const maxResults = 5;
 let optionsSSDMobileNet;
 
@@ -30,10 +32,10 @@ async function detect(img) {
   const tensor = await image(img);
   const result = await faceapi
     .detectAllFaces(tensor, optionsSSDMobileNet)
-    .withFaceLandmarks()
-    .withFaceExpressions()
-    .withFaceDescriptors()
-    .withAgeAndGender();
+    .withFaceLandmarks();
+    // .withFaceExpressions()
+    // .withFaceDescriptors()
+    // .withAgeAndGender();
   process.send({ image: img, detected: result }); // send results back to main
   process.send({ ready: true }); // send signal back to main that this worker is now idle and ready for next image
   tensor.dispose();
@@ -53,7 +55,7 @@ async function main() {
   await faceapi.tf.enableProdMode();
   await faceapi.tf.ENV.set('DEBUG', false);
   await faceapi.tf.ready();
-  log.state('Worker: PID:', process.pid, `TensorFlow/JS ${faceapi.tf.version_core} FaceAPI ${faceapi.version.faceapi} Backend: ${faceapi.tf.getBackend()}`);
+  log.state('Worker: PID:', process.pid, `TensorFlow/JS ${faceapi.tf.version_core} FaceAPI ${faceapi.version} Backend: ${faceapi.tf.getBackend()}`);
 
   // and load and initialize facepi models
   const modelPath = path.join(__dirname, modelPathRoot);
@@ -62,7 +64,7 @@ async function main() {
   await faceapi.nets.faceLandmark68Net.loadFromDisk(modelPath);
   await faceapi.nets.faceRecognitionNet.loadFromDisk(modelPath);
   await faceapi.nets.faceExpressionNet.loadFromDisk(modelPath);
-  optionsSSDMobileNet = new faceapi.SsdMobilenetv1Options({ minConfidence: minScore, maxResults });
+  optionsSSDMobileNet = new faceapi.SsdMobilenetv1Options({ minConfidence, maxResults });
 
   // now we're ready, so send message back to main that it knows it can use this worker
   process.send({ ready: true });

demo/node-multiprocess.js

@@ -1,24 +1,27 @@
-// @ts-nocheck
+/**
+ * FaceAPI Demo for NodeJS
+ * - Starts multiple worker processes and uses them as worker pool to process all input images
+ * - Images are enumerated in main process and sent for processing to worker processes via ipc
+ */
 
 const fs = require('fs');
 const path = require('path');
-// eslint-disable-next-line import/no-extraneous-dependencies, node/no-unpublished-require
 const log = require('@vladmandic/pilogger'); // this is my simple logger with few extra features
 const child_process = require('child_process');
-// note that main process import faceapi or tfjs at all
+// note that main process does not need to import faceapi or tfjs at all as processing is done in a worker process
 
-const imgPathRoot = './example'; // modify to include your sample images
-const numWorkers = 2; // how many workers will be started
+const imgPathRoot = './demo'; // modify to include your sample images
+const numWorkers = 4; // how many workers will be started
 const workers = []; // this holds worker processes
 const images = []; // this holds queue of enumerated images
 const t = []; // timers
-let dir;
+let numImages;
 
 // trigered by main when worker sends ready message
 // if image pool is empty, signal worker to exit otherwise dispatch image to worker and remove image from queue
 async function detect(worker) {
   if (!t[2]) t[2] = process.hrtime.bigint(); // first time do a timestamp so we can measure initial latency
-  if (images.length === dir.length) worker.send({ test: true }); // for first image in queue just measure latency
+  if (images.length === numImages) worker.send({ test: true }); // for first image in queue just measure latency
   if (images.length === 0) worker.send({ exit: true }); // nothing left in queue
   else {
     log.state('Main: dispatching to worker:', worker.pid);
@@ -33,14 +36,14 @@ function waitCompletion() {
   if (activeWorkers > 0) setImmediate(() => waitCompletion());
   else {
     t[1] = process.hrtime.bigint();
-    log.info('Processed', dir.length, 'images in', Math.trunc(parseInt(t[1] - t[0]) / 1000 / 1000), 'ms');
+    log.info('Processed:', numImages, 'images in', 'total:', Math.trunc(Number(t[1] - t[0]) / 1000000), 'ms', 'working:', Math.trunc(Number(t[1] - t[2]) / 1000000), 'ms', 'average:', Math.trunc(Number(t[1] - t[2]) / numImages / 1000000), 'ms');
   }
 }
 
 function measureLatency() {
   t[3] = process.hrtime.bigint();
-  const latencyInitialization = Math.trunc(parseInt(t[2] - t[0]) / 1000 / 1000);
-  const latencyRoundTrip = Math.trunc(parseInt(t[3] - t[2]) / 1000 / 1000);
+  const latencyInitialization = Math.trunc(Number(t[2] - t[0]) / 1000 / 1000);
+  const latencyRoundTrip = Math.trunc(Number(t[3] - t[2]) / 1000 / 1000);
   log.info('Latency: worker initializtion: ', latencyInitialization, 'message round trip:', latencyRoundTrip);
 }
 
@@ -49,16 +52,17 @@ async function main() {
   log.info('FaceAPI multi-process test');
 
   // enumerate all images into queue
-  dir = fs.readdirSync(imgPathRoot);
+  const dir = fs.readdirSync(imgPathRoot);
   for (const imgFile of dir) {
     if (imgFile.toLocaleLowerCase().endsWith('.jpg')) images.push(path.join(imgPathRoot, imgFile));
   }
+  numImages = images.length;
 
   t[0] = process.hrtime.bigint();
   // manage worker processes
   for (let i = 0; i < numWorkers; i++) {
     // create worker process
-    workers[i] = await child_process.fork('example/node-multiprocess-worker.js', ['special']);
+    workers[i] = await child_process.fork('demo/node-multiprocess-worker.js', ['special']);
     // parse message that worker process sends back to main
     // if message is ready, dispatch next image in queue
     // if message is processing result, just print how many faces were detected

demo/node-simple.js

@@ -0,0 +1,31 @@
+/**
+ * FaceAPI Demo for NodeJS
+ * - Loads image
+ * - Outputs results to console
+ */
+
+const fs = require('fs');
+
+const faceapi = require('../dist/face-api.node.js'); // use this when using face-api in dev mode
+// const faceapi = require('@vladmandic/face-api'); // use this when face-api is installed as module (majority of use cases)
+
+async function main() {
+  await faceapi.nets.ssdMobilenetv1.loadFromDisk('model'); // load models from a specific patch
+  await faceapi.nets.faceLandmark68Net.loadFromDisk('model');
+  await faceapi.nets.ageGenderNet.loadFromDisk('model');
+  await faceapi.nets.faceRecognitionNet.loadFromDisk('model');
+  await faceapi.nets.faceExpressionNet.loadFromDisk('model');
+  const options = new faceapi.SsdMobilenetv1Options({ minConfidence: 0.1, maxResults: 10 }); // set model options
+  const buffer = fs.readFileSync('demo/sample1.jpg'); // load jpg image as binary
+  const decodeT = faceapi.tf.node.decodeImage(buffer, 3); // decode binary buffer to rgb tensor
+  const expandT = faceapi.tf.expandDims(decodeT, 0); // add batch dimension to tensor
+  const result = await faceapi.detectAllFaces(expandT, options) // run detection
+    .withFaceLandmarks()
+    .withFaceExpressions()
+    .withFaceDescriptors()
+    .withAgeAndGender();
+  faceapi.tf.dispose([decodeT, expandT]); // dispose tensors to avoid memory leaks
+  console.log({ result }); // eslint-disable-line no-console
+}
+
+main();

demo/node-wasm.js

@@ -0,0 +1,53 @@
+/**
+ * FaceAPI Demo for NodeJS using WASM
+ * - Loads WASM binaries from external CDN
+ * - Loads image
+ * - Outputs results to console
+ */
+
+const fs = require('fs');
+const image = require('@canvas/image'); // eslint-disable-line node/no-missing-require
+const tf = require('@tensorflow/tfjs');
+const wasm = require('@tensorflow/tfjs-backend-wasm');
+const faceapi = require('../dist/face-api.node-wasm.js'); // use this when using face-api in dev mode
+
+async function readImage(imageFile) {
+  const buffer = fs.readFileSync(imageFile); // read image from disk
+  const canvas = await image.imageFromBuffer(buffer); // decode to canvas
+  const imageData = image.getImageData(canvas); // read decoded image data from canvas
+  const tensor = tf.tidy(() => { // create tensor from image data
+    const data = tf.tensor(Array.from(imageData?.data || []), [canvas.height, canvas.width, 4], 'int32'); // create rgba image tensor from flat array and flip to height x width
+    const channels = tf.split(data, 4, 2); // split rgba to channels
+    const rgb = tf.stack([channels[0], channels[1], channels[2]], 2); // stack channels back to rgb
+    const squeeze = tf.squeeze(rgb); // move extra dim from the end of tensor and use it as batch number instead
+    return squeeze;
+  });
+  console.log(`Image: ${imageFile} [${canvas.width} x ${canvas.height} Tensor: ${tensor.shape}, Size: ${tensor.size}`); // eslint-disable-line no-console
+  return tensor;
+}
+
+async function main() {
+  wasm.setWasmPaths('https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm/dist/', true);
+  await tf.setBackend('wasm');
+  await tf.ready();
+  console.log(`Version: FaceAPI ${faceapi.version} TensorFlow/JS ${tf.version_core} Backend: ${faceapi.tf.getBackend()}`); // eslint-disable-line no-console
+  await faceapi.nets.ssdMobilenetv1.loadFromDisk('model'); // load models from a specific patch
+  await faceapi.nets.faceLandmark68Net.loadFromDisk('model');
+  await faceapi.nets.ageGenderNet.loadFromDisk('model');
+  await faceapi.nets.faceRecognitionNet.loadFromDisk('model');
+  await faceapi.nets.faceExpressionNet.loadFromDisk('model');
+  const options = new faceapi.SsdMobilenetv1Options({ minConfidence: 0.1, maxResults: 10 }); // set model options
+  const tensor = await readImage('demo/sample1.jpg');
+  const t0 = performance.now();
+  const result = await faceapi.detectAllFaces(tensor, options) // run detection
+    .withFaceLandmarks()
+    .withFaceExpressions()
+    .withFaceDescriptors()
+    .withAgeAndGender();
+  tf.dispose(tensor); // dispose tensors to avoid memory leaks
+  const t1 = performance.now();
+  console.log('Time', t1 - t0); // eslint-disable-line no-console
+  console.log('Result', result); // eslint-disable-line no-console
+}
+
+main();

demo/node.js

@@ -0,0 +1,139 @@
+/**
+ * FaceAPI Demo for NodeJS
+ * - Uses external library [node-fetch](https://www.npmjs.com/package/node-fetch) to load images via http
+ * - Loads image from provided param
+ * - Outputs results to console
+ */
+
+const fs = require('fs');
+const process = require('process');
+const path = require('path');
+const log = require('@vladmandic/pilogger');
+
+const tf = require('@tensorflow/tfjs-node'); // in nodejs environments tfjs-node is required to be loaded before face-api
+const faceapi = require('../dist/face-api.node.js'); // use this when using face-api in dev mode
+// const faceapi = require('@vladmandic/face-api'); // use this when face-api is installed as module (majority of use cases)
+
+const modelPathRoot = '../model';
+const imgPathRoot = './demo'; // modify to include your sample images
+const minConfidence = 0.15;
+const maxResults = 5;
+let optionsSSDMobileNet;
+let fetch; // dynamically imported later
+
+async function image(input) {
+  // read input image file and create tensor to be used for processing
+  let buffer;
+  log.info('Loading image:', input);
+  if (input.startsWith('http:') || input.startsWith('https:')) {
+    const res = await fetch(input);
+    if (res && res.ok) buffer = await res.buffer();
+    else log.error('Invalid image URL:', input, res.status, res.statusText, res.headers.get('content-type'));
+  } else {
+    buffer = fs.readFileSync(input);
+  }
+
+  // decode image using tfjs-node so we don't need external depenencies
+  // can also be done using canvas.js or some other 3rd party image library
+  if (!buffer) return {};
+  const tensor = tf.tidy(() => {
+    const decode = faceapi.tf.node.decodeImage(buffer, 3);
+    let expand;
+    if (decode.shape[2] === 4) { // input is in rgba format, need to convert to rgb
+      const channels = faceapi.tf.split(decode, 4, 2); // tf.split(tensor, 4, 2); // split rgba to channels
+      const rgb = faceapi.tf.stack([channels[0], channels[1], channels[2]], 2); // stack channels back to rgb and ignore alpha
+      expand = faceapi.tf.reshape(rgb, [1, decode.shape[0], decode.shape[1], 3]); // move extra dim from the end of tensor and use it as batch number instead
+    } else {
+      expand = faceapi.tf.expandDims(decode, 0);
+    }
+    const cast = faceapi.tf.cast(expand, 'float32');
+    return cast;
+  });
+  return tensor;
+}
+
+async function detect(tensor) {
+  try {
+    const result = await faceapi
+      .detectAllFaces(tensor, optionsSSDMobileNet)
+      .withFaceLandmarks()
+      .withFaceExpressions()
+      .withFaceDescriptors()
+      .withAgeAndGender();
+    return result;
+  } catch (err) {
+    log.error('Caught error', err.message);
+    return [];
+  }
+}
+
+// eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars
+function detectPromise(tensor) {
+  return new Promise((resolve) => faceapi
+    .detectAllFaces(tensor, optionsSSDMobileNet)
+    .withFaceLandmarks()
+    .withFaceExpressions()
+    .withFaceDescriptors()
+    .withAgeAndGender()
+    .then((res) => resolve(res))
+    .catch((err) => {
+      log.error('Caught error', err.message);
+      resolve([]);
+    }));
+}
+
+function print(face) {
+  const expression = Object.entries(face.expressions).reduce((acc, val) => ((val[1] > acc[1]) ? val : acc), ['', 0]);
+  const box = [face.alignedRect._box._x, face.alignedRect._box._y, face.alignedRect._box._width, face.alignedRect._box._height];
+  const gender = `Gender: ${Math.round(100 * face.genderProbability)}% ${face.gender}`;
+  log.data(`Detection confidence: ${Math.round(100 * face.detection._score)}% ${gender} Age: ${Math.round(10 * face.age) / 10} Expression: ${Math.round(100 * expression[1])}% ${expression[0]} Box: ${box.map((a) => Math.round(a))}`);
+}
+
+async function main() {
+  log.header();
+  log.info('FaceAPI single-process test');
+
+  // eslint-disable-next-line node/no-extraneous-import
+  fetch = (await import('node-fetch')).default; // eslint-disable-line node/no-missing-import
+
+  await faceapi.tf.setBackend('tensorflow');
+  await faceapi.tf.ready();
+
+  log.state(`Version: TensorFlow/JS ${faceapi.tf?.version_core} FaceAPI ${faceapi.version} Backend: ${faceapi.tf?.getBackend()}`);
+
+  log.info('Loading FaceAPI models');
+  const modelPath = path.join(__dirname, modelPathRoot);
+  await faceapi.nets.ssdMobilenetv1.loadFromDisk(modelPath);
+  await faceapi.nets.ageGenderNet.loadFromDisk(modelPath);
+  await faceapi.nets.faceLandmark68Net.loadFromDisk(modelPath);
+  await faceapi.nets.faceRecognitionNet.loadFromDisk(modelPath);
+  await faceapi.nets.faceExpressionNet.loadFromDisk(modelPath);
+  optionsSSDMobileNet = new faceapi.SsdMobilenetv1Options({ minConfidence, maxResults });
+
+  if (process.argv.length !== 4) {
+    const t0 = process.hrtime.bigint();
+    const dir = fs.readdirSync(imgPathRoot);
+    for (const img of dir) {
+      if (!img.toLocaleLowerCase().endsWith('.jpg')) continue;
+      const tensor = await image(path.join(imgPathRoot, img));
+      const result = await detect(tensor);
+      log.data('Image:', img, 'Detected faces:', result.length);
+      for (const face of result) print(face);
+      tensor.dispose();
+    }
+    const t1 = process.hrtime.bigint();
+    log.info('Processed', dir.length, 'images in', Math.trunc(Number((t1 - t0)) / 1000 / 1000), 'ms');
+  } else {
+    const param = process.argv[2];
+    if (fs.existsSync(param) || param.startsWith('http:') || param.startsWith('https:')) {
+      const tensor = await image(param);
+      const result = await detect(tensor);
+      // const result = await detectPromise(null);
+      log.data('Image:', param, 'Detected faces:', result.length);
+      for (const face of result) print(face);
+      tensor.dispose();
+    }
+  }
+}
+
+main();

demo/webcam.html

@@ -0,0 +1,21 @@
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+    <title>FaceAPI Live WebCam Demo</title>
+    <meta http-equiv="content-type" content="text/html; charset=utf-8">
+    <meta name="viewport" content="width=device-width, shrink-to-fit=yes">
+    <meta name="application-name" content="FaceAPI">
+    <meta name="keywords" content="FaceAPI">
+    <meta name="description" content="FaceAPI: AI-powered Face Detection, Description & Recognition for Browser and NodeJS using Tensorflow/JS; Author: Vladimir Mandic <https://github.com/vladmandic>">
+    <meta name="msapplication-tooltip" content="FaceAPI: AI-powered Face Detection, Description & Recognition for Browser and NodeJS using Tensorflow/JS; Author: Vladimir Mandic <https://github.com/vladmandic>">
+    <link rel="shortcut icon" href="../favicon.ico" type="image/x-icon">
+    <script src="./webcam.js" type="module"></script>
+  </head>
+  <body style="font-family: monospace; background: black; color: white; font-size: 16px; line-height: 22px; margin: 0; overflow: hidden">
+    <video id="video" playsinline class="video"></video>
+    <canvas id="canvas" class="canvas" style="position: fixed; top: 0; left: 0; z-index: 10"></canvas>
+    <div id="log" style="overflow-y: scroll; height: 16.5rem"></div>
+  </body>
+</html>
+
+

demo/webcam.js

@@ -1,7 +1,14 @@
-import * as faceapi from '../dist/face-api.esm.js';
+/**
+ * FaceAPI Demo for Browsers
+ * Loaded via `webcam.html`
+ */
+
+import * as faceapi from '../dist/face-api.esm.js'; // use when in dev mode
+// import * as faceapi from '@vladmandic/face-api'; // use when downloading face-api as npm
 
 // configuration options
-const modelPath = 'https://vladmandic.github.io/face-api/model/'; // path to model folder that will be loaded using http
+const modelPath = '../model/'; // path to model folder that will be loaded using http
+// const modelPath = 'https://cdn.jsdelivr.net/npm/@vladmandic/face-api/model/'; // path to model folder that will be loaded using http
 const minScore = 0.2; // minimum score
 const maxResults = 5; // maximum number of results to return
 let optionsSSDMobileNet;
@@ -16,19 +23,18 @@ function str(json) {
 
 // helper function to print strings to html document as a log
 function log(...txt) {
-  // eslint-disable-next-line no-console
-  console.log(...txt);
-  // @ts-ignore
-  document.getElementById('log').innerHTML += `<br>${txt}`;
+  console.log(...txt); // eslint-disable-line no-console
+  const div = document.getElementById('log');
+  if (div) div.innerHTML += `<br>${txt}`;
 }
 
 // helper function to draw detected faces
 function drawFaces(canvas, data, fps) {
-  const ctx = canvas.getContext('2d');
+  const ctx = canvas.getContext('2d', { willReadFrequently: true });
   if (!ctx) return;
   ctx.clearRect(0, 0, canvas.width, canvas.height);
   // draw title
-  ctx.font = '1.2rem sans-serif';
+  ctx.font = 'small-caps 20px "Segoe UI"';
   ctx.fillStyle = 'white';
   ctx.fillText(`FPS: ${fps}`, 10, 25);
   for (const person of data) {
@@ -36,25 +42,30 @@ function drawFaces(canvas, data, fps) {
     ctx.lineWidth = 3;
     ctx.strokeStyle = 'deepskyblue';
     ctx.fillStyle = 'deepskyblue';
-    ctx.globalAlpha = 0.4;
+    ctx.globalAlpha = 0.6;
     ctx.beginPath();
     ctx.rect(person.detection.box.x, person.detection.box.y, person.detection.box.width, person.detection.box.height);
     ctx.stroke();
     ctx.globalAlpha = 1;
-    // const expression = person.expressions.sort((a, b) => Object.values(a)[0] - Object.values(b)[0]);
+    // draw text labels
     const expression = Object.entries(person.expressions).sort((a, b) => b[1] - a[1]);
-    ctx.fillText(`gender ${Math.round(100 * person.genderProbability)}% ${person.gender}`, person.detection.box.x, person.detection.box.y - 60);
-    ctx.fillText(`expression ${Math.round(100 * expression[0][1])}% ${expression[0][0]}`, person.detection.box.x, person.detection.box.y - 42);
-    ctx.fillText(`age ${Math.round(person.age)} years`, person.detection.box.x, person.detection.box.y - 24);
-    ctx.fillText(`roll:${person.angle.roll.toFixed(3)} pitch:${person.angle.pitch.toFixed(3)} yaw:${person.angle.yaw.toFixed(3)}`, person.detection.box.x, person.detection.box.y - 6);
-    // draw face points for each face
+    ctx.fillStyle = 'black';
+    ctx.fillText(`gender: ${Math.round(100 * person.genderProbability)}% ${person.gender}`, person.detection.box.x, person.detection.box.y - 59);
+    ctx.fillText(`expression: ${Math.round(100 * expression[0][1])}% ${expression[0][0]}`, person.detection.box.x, person.detection.box.y - 41);
+    ctx.fillText(`age: ${Math.round(person.age)} years`, person.detection.box.x, person.detection.box.y - 23);
+    ctx.fillText(`roll:${person.angle.roll}° pitch:${person.angle.pitch}° yaw:${person.angle.yaw}°`, person.detection.box.x, person.detection.box.y - 5);
+    ctx.fillStyle = 'lightblue';
+    ctx.fillText(`gender: ${Math.round(100 * person.genderProbability)}% ${person.gender}`, person.detection.box.x, person.detection.box.y - 60);
+    ctx.fillText(`expression: ${Math.round(100 * expression[0][1])}% ${expression[0][0]}`, person.detection.box.x, person.detection.box.y - 42);
+    ctx.fillText(`age: ${Math.round(person.age)} years`, person.detection.box.x, person.detection.box.y - 24);
+    ctx.fillText(`roll:${person.angle.roll}° pitch:${person.angle.pitch}° yaw:${person.angle.yaw}°`, person.detection.box.x, person.detection.box.y - 6);
+    // draw face points for each face
+    ctx.globalAlpha = 0.8;
     ctx.fillStyle = 'lightblue';
-    ctx.globalAlpha = 0.5;
     const pointSize = 2;
     for (let i = 0; i < person.landmarks.positions.length; i++) {
       ctx.beginPath();
       ctx.arc(person.landmarks.positions[i].x, person.landmarks.positions[i].y, pointSize, 0, 2 * Math.PI);
-      // ctx.fillText(`${i}`, person.landmarks.positions[i].x + 4, person.landmarks.positions[i].y + 4);
       ctx.fill();
     }
   }
@@ -88,7 +99,6 @@ async function setupCamera() {
   const canvas = document.getElementById('canvas');
   if (!video || !canvas) return null;
 
-  let msg = '';
   log('Setting up camera');
   // setup webcam. note that navigator.mediaDevices requires that page is accessed via https
   if (!navigator.mediaDevices) {
@@ -96,53 +106,44 @@ async function setupCamera() {
     return null;
   }
   let stream;
-  const constraints = {
-    audio: false,
-    video: { facingMode: 'user', resizeMode: 'crop-and-scale' },
-  };
+  const constraints = { audio: false, video: { facingMode: 'user', resizeMode: 'crop-and-scale' } };
   if (window.innerWidth > window.innerHeight) constraints.video.width = { ideal: window.innerWidth };
   else constraints.video.height = { ideal: window.innerHeight };
   try {
     stream = await navigator.mediaDevices.getUserMedia(constraints);
   } catch (err) {
-    if (err.name === 'PermissionDeniedError' || err.name === 'NotAllowedError') msg = 'camera permission denied';
-    else if (err.name === 'SourceUnavailableError') msg = 'camera not available';
-    log(`Camera Error: ${msg}: ${err.message || err}`);
+    if (err.name === 'PermissionDeniedError' || err.name === 'NotAllowedError') log(`Camera Error: camera permission denied: ${err.message || err}`);
+    if (err.name === 'SourceUnavailableError') log(`Camera Error: camera not available: ${err.message || err}`);
     return null;
   }
-  // @ts-ignore
-  if (stream) video.srcObject = stream;
-  else {
+  if (stream) {
+    video.srcObject = stream;
+  } else {
     log('Camera Error: stream empty');
     return null;
   }
   const track = stream.getVideoTracks()[0];
   const settings = track.getSettings();
-  log(`Camera active: ${track.label} ${str(constraints)}`);
+  if (settings.deviceId) delete settings.deviceId;
+  if (settings.groupId) delete settings.groupId;
+  if (settings.aspectRatio) settings.aspectRatio = Math.trunc(100 * settings.aspectRatio) / 100;
+  log(`Camera active: ${track.label}`);
   log(`Camera settings: ${str(settings)}`);
   canvas.addEventListener('click', () => {
-    // @ts-ignore
     if (video && video.readyState >= 2) {
-      // @ts-ignore
       if (video.paused) {
-        // @ts-ignore
         video.play();
         detectVideo(video, canvas);
       } else {
-        // @ts-ignore
         video.pause();
       }
     }
-    // @ts-ignore
     log(`Camera state: ${video.paused ? 'paused' : 'playing'}`);
   });
   return new Promise((resolve) => {
     video.onloadeddata = async () => {
-      // @ts-ignore
       canvas.width = video.videoWidth;
-      // @ts-ignore
       canvas.height = video.videoHeight;
-      // @ts-ignore
       video.play();
       detectVideo(video, canvas);
       resolve(true);
@@ -152,18 +153,16 @@ async function setupCamera() {
 
 async function setupFaceAPI() {
   // load face-api models
-  log('Models loading');
-  await faceapi.nets.tinyFaceDetector.load(modelPath);
+  // log('Models loading');
+  // await faceapi.nets.tinyFaceDetector.load(modelPath); // using ssdMobilenetv1
   await faceapi.nets.ssdMobilenetv1.load(modelPath);
   await faceapi.nets.ageGenderNet.load(modelPath);
   await faceapi.nets.faceLandmark68Net.load(modelPath);
   await faceapi.nets.faceRecognitionNet.load(modelPath);
   await faceapi.nets.faceExpressionNet.load(modelPath);
   optionsSSDMobileNet = new faceapi.SsdMobilenetv1Options({ minConfidence: minScore, maxResults });
-
   // check tf engine state
-  const engine = await faceapi.tf.engine();
-  log(`Models loaded: ${str(engine.state)}`);
+  log(`Models loaded: ${str(faceapi.tf.engine().state.numTensors)} tensors`);
 }
 
 async function main() {
@@ -171,19 +170,21 @@ async function main() {
   log('FaceAPI WebCam Test');
 
   // if you want to use wasm backend location for wasm binaries must be specified
-  // await faceapi.tf.setWasmPaths('../node_modules/@tensorflow/tfjs-backend-wasm/dist/');
-  // await faceapi.tf.setBackend('wasm');
+  // await faceapi.tf?.setWasmPaths(`https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@${faceapi.tf.version_core}/dist/`);
+  // await faceapi.tf?.setBackend('wasm');
+  // log(`WASM SIMD: ${await faceapi.tf?.env().getAsync('WASM_HAS_SIMD_SUPPORT')} Threads: ${await faceapi.tf?.env().getAsync('WASM_HAS_MULTITHREAD_SUPPORT') ? 'Multi' : 'Single'}`);
 
   // default is webgl backend
   await faceapi.tf.setBackend('webgl');
-
-  await faceapi.tf.enableProdMode();
-  await faceapi.tf.ENV.set('DEBUG', false);
   await faceapi.tf.ready();
 
+  // tfjs optimizations
+  if (faceapi.tf?.env().flagRegistry.CANVAS2D_WILL_READ_FREQUENTLY) faceapi.tf.env().set('CANVAS2D_WILL_READ_FREQUENTLY', true);
+  if (faceapi.tf?.env().flagRegistry.WEBGL_EXP_CONV) faceapi.tf.env().set('WEBGL_EXP_CONV', true);
+  if (faceapi.tf?.env().flagRegistry.WEBGL_EXP_CONV) faceapi.tf.env().set('WEBGL_EXP_CONV', true);
+
   // check version
-  log(`Version: FaceAPI ${str(faceapi?.version.faceapi || '(not loaded)')} TensorFlow/JS ${str(faceapi?.tf?.version_core || '(not loaded)')} Backend: ${str(faceapi?.tf?.getBackend() || '(not loaded)')}`);
-  log(`Flags: ${JSON.stringify(faceapi?.tf?.ENV.flags || { tf: 'not loaded' })}`);
+  log(`Version: FaceAPI ${str(faceapi?.version || '(not loaded)')} TensorFlow/JS ${str(faceapi.tf?.version_core || '(not loaded)')} Backend: ${str(faceapi.tf?.getBackend() || '(not loaded)')}`);
 
   await setupFaceAPI();
   await setupCamera();

dist/face-api.d.ts

@@ -0,0 +1 @@
+export * from '../types/face-api';

dist/face-api.esm-nobundle.d.ts

@@ -0,0 +1 @@
+export * from '../types/face-api';

dist/face-api.esm.d.ts

@@ -0,0 +1 @@
+export * from '../types/face-api';

dist/face-api.node-gpu.d.ts

@@ -0,0 +1 @@
+export * from '../types/face-api';

dist/face-api.node-wasm.d.ts

@@ -0,0 +1 @@
+export * from '../types/face-api';

dist/face-api.node.d.ts

@@ -0,0 +1 @@
+export * from '../types/face-api';

dist/tfjs.esm.d.ts

@@ -0,0 +1,28 @@
+/*
+import '@tensorflow/tfjs-core';
+import '@tensorflow/tfjs-core/dist/types';
+import '@tensorflow/tfjs-core/dist/register_all_gradients';
+import '@tensorflow/tfjs-core/dist/public/chained_ops/register_all_chained_ops';
+import '@tensorflow/tfjs-data';
+import '@tensorflow/tfjs-layers';
+import '@tensorflow/tfjs-converter';
+import '@tensorflow/tfjs-backend-cpu';
+import '@tensorflow/tfjs-backend-webgl';
+import '@tensorflow/tfjs-backend-wasm';
+import '@tensorflow/tfjs-backend-webgpu';
+*/
+
+export declare const version: {
+  'tfjs-core': string;
+  'tfjs-backend-cpu': string;
+  'tfjs-backend-webgl': string;
+  'tfjs-data': string;
+  'tfjs-layers': string;
+  'tfjs-converter': string;
+  tfjs: string;
+};
+
+export { io, browser, image } from '@tensorflow/tfjs-core';
+export { tensor, tidy, softmax, unstack, relu, add, conv2d, cast, zeros, concat, avgPool, stack, fill, transpose, tensor1d, tensor2d, tensor3d, tensor4d, maxPool, matMul, mul, sub, scalar } from '@tensorflow/tfjs-core';
+export { div, pad, slice, reshape, slice3d, expandDims, depthwiseConv2d, separableConv2d, sigmoid, exp, tile, batchNorm, clipByValue } from '@tensorflow/tfjs-core';
+export { ENV, Variable, Tensor, TensorLike, Rank, Tensor1D, Tensor2D, Tensor3D, Tensor4D, Tensor5D, NamedTensorMap } from '@tensorflow/tfjs-core';

dist/tfjs.version.d.ts

@@ -0,0 +1,9 @@
+export declare const version: {
+  'tfjs-core': string;
+  'tfjs-backend-cpu': string;
+  'tfjs-backend-webgl': string;
+  'tfjs-data': string;
+  'tfjs-layers': string;
+  'tfjs-converter': string;
+  tfjs: string;
+};

dist/tfjs.version.js

@@ -0,0 +1,7 @@
+/*
+  Face-API
+  homepage: <https://github.com/vladmandic/face-api>
+  author: <https://github.com/vladmandic>'
+*/
+
+var e="4.22.0";var s="4.22.0";var t="4.22.0";var n="4.22.0";var i="4.22.0";var w={tfjs:e,"tfjs-core":e,"tfjs-converter":s,"tfjs-backend-cpu":t,"tfjs-backend-webgl":n,"tfjs-backend-wasm":i};export{w as version};

example/index.html

@@ -1,13 +0,0 @@
-<!DOCTYPE html>
-<html lang="en">
-  <head>
-    <meta charset="utf-8">
-    <meta content="text/html">
-    <title>FaceAPI Static Images Demo</title>
-    <meta name="viewport" content="width=device-width, initial-scale=1.0, shrink-to-fit=yes">
-    <script src="./index.js" type="module"></script>
-  </head>
-  <body style="font-family: monospace; background: black; color: white; font-size: 16px; line-height: 22px; margin: 0;">
-    <div id="log"></div>
-  </body>
-</html>

example/node-singleprocess.js

@@ -1,84 +0,0 @@
-// @ts-nocheck
-
-const fs = require('fs');
-const process = require('process');
-const path = require('path');
-// eslint-disable-next-line import/no-extraneous-dependencies, node/no-unpublished-require
-const log = require('@vladmandic/pilogger');
-// eslint-disable-next-line import/no-extraneous-dependencies, node/no-unpublished-require
-const tf = require('@tensorflow/tfjs-node');
-const faceapi = require('../dist/face-api.node.js'); // this is equivalent to '@vladmandic/faceapi'
-
-const modelPathRoot = '../model';
-const imgPathRoot = './example'; // modify to include your sample images
-const minScore = 0.1;
-const maxResults = 5;
-let optionsSSDMobileNet;
-
-async function image(img) {
-  const buffer = fs.readFileSync(img);
-  const decoded = tf.node.decodeImage(buffer);
-  const casted = decoded.toFloat();
-  const result = casted.expandDims(0);
-  decoded.dispose();
-  casted.dispose();
-  return result;
-}
-
-async function detect(tensor) {
-  const result = await faceapi
-    .detectAllFaces(tensor, optionsSSDMobileNet)
-    .withFaceLandmarks()
-    .withFaceExpressions()
-    .withFaceDescriptors()
-    .withAgeAndGender();
-  return result;
-}
-
-async function main() {
-  log.header();
-  log.info('FaceAPI single-process test');
-
-  await faceapi.tf.setBackend('tensorflow');
-  await faceapi.tf.enableProdMode();
-  await faceapi.tf.ENV.set('DEBUG', false);
-  await faceapi.tf.ready();
-
-  log.state(`Version: TensorFlow/JS ${faceapi.tf?.version_core} FaceAPI ${faceapi.version.faceapi} Backend: ${faceapi.tf?.getBackend()}`);
-
-  log.info('Loading FaceAPI models');
-  const modelPath = path.join(__dirname, modelPathRoot);
-  await faceapi.nets.ssdMobilenetv1.loadFromDisk(modelPath);
-  await faceapi.nets.ageGenderNet.loadFromDisk(modelPath);
-  await faceapi.nets.faceLandmark68Net.loadFromDisk(modelPath);
-  await faceapi.nets.faceRecognitionNet.loadFromDisk(modelPath);
-  await faceapi.nets.faceExpressionNet.loadFromDisk(modelPath);
-  optionsSSDMobileNet = new faceapi.SsdMobilenetv1Options({ minConfidence: minScore, maxResults });
-
-  if (process.argv.length !== 3) {
-    const t0 = process.hrtime.bigint();
-    const dir = fs.readdirSync(imgPathRoot);
-    for (const img of dir) {
-      if (!img.toLocaleLowerCase().endsWith('.jpg')) continue;
-      const tensor = await image(path.join(imgPathRoot, img));
-      const result = await detect(tensor);
-      log.data('Image:', img, 'Detected faces:', result.length);
-      tensor.dispose();
-    }
-    const t1 = process.hrtime.bigint();
-    log.info('Processed', dir.length, 'images in', Math.trunc(parseInt(t1 - t0) / 1000 / 1000), 'ms');
-  } else {
-    const param = process.argv[2];
-    if (fs.existsSync(param)) {
-      const tensor = await image(param);
-      const result = await detect(tensor);
-      log.data('Image:', param, 'Detected faces:', result.length);
-      for (const i of result) {
-        log.data('Gender:', i.genderProbability, i.gender, 'Age:', i.age);
-      }
-      tensor.dispose();
-    }
-  }
-}
-
-main();

example/webcam.html

@@ -1,15 +0,0 @@
-<!DOCTYPE html>
-<html lang="en">
-  <head>
-    <meta charset="utf-8">
-    <meta content="text/html">
-    <title>FaceAPI Live WebCam Demo</title>
-    <meta name="viewport" content="width=device-width, initial-scale=1.0, shrink-to-fit=yes">
-    <script src="./webcam.js" type="module"></script>
-  </head>
-  <body style="font-family: monospace; background: black; color: white; font-size: 16px; line-height: 22px; margin: 0; overflow: hidden">
-    <video id="video" playsinline class="video"></video>
-    <canvas id="canvas" class="canvas" style="position: fixed; top: 0; left: 0; z-index: 10"></canvas>
-    <div id="log" style="overflow-y: scroll; height: 16.5rem"></div>
-  </body>
-</html>

model/face_landmark_68_tiny_model-weights_manifest.json

@@ -1 +1,39 @@
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+      ],
+      "paths":
+      [
+          "face_landmark_68_tiny_model.bin"
+      ]
+  }
+]

model/tiny_face_detector_model-weights_manifest.json

@@ -1 +1,30 @@
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+      ],
+      "paths":
+      [
+          "tiny_face_detector_model.bin"
+      ]
+  }
+]

package.json

@@ -1,65 +1,79 @@
 {
   "name": "@vladmandic/face-api",
-  "version": "1.0.1",
-  "description": "FaceAPI: AI-powered Face Detection, Face Embedding & Recognition Using Tensorflow/JS",
+  "version": "1.7.15",
+  "description": "FaceAPI: AI-powered Face Detection & Rotation Tracking, Face Description & Recognition, Age & Gender & Emotion Prediction for Browser and NodeJS using TensorFlow/JS",
   "sideEffects": false,
   "main": "dist/face-api.node.js",
   "module": "dist/face-api.esm.js",
   "browser": "dist/face-api.esm.js",
-  "types": "types/index.d.ts",
+  "types": "types/face-api.d.ts",
   "author": "Vladimir Mandic <mandic00@live.com>",
   "bugs": {
     "url": "https://github.com/vladmandic/face-api/issues"
   },
-  "homepage": "https://vladmandic.github.io/face-api/example/webcam.html",
+  "homepage": "https://vladmandic.github.io/face-api/demo/webcam.html",
   "license": "MIT",
   "engines": {
-    "node": ">=12.0.0"
+    "node": ">=14.0.0"
   },
   "repository": {
     "type": "git",
     "url": "git+https://github.com/vladmandic/face-api.git"
   },
   "scripts": {
-    "start": "node --trace-warnings example/node-singleprocess.js",
-    "dev": "npm install && node server/serve.js",
-    "build": "rimraf dist/* types/* && node server/build.js && node server/changelog.js",
-    "lint": "eslint src/**/* example/*.js server/*.js",
-    "test": "eslint src/**/* example/*.js server/*.js"
+    "start": "node --no-warnings demo/node.js",
+    "build": "node build.js",
+    "dev": "build --profile development",
+    "lint": "eslint src/ demo/",
+    "test": "node --trace-warnings test/test-node.js",
+    "scan": "npx auditjs@latest ossi --dev --quiet"
   },
   "keywords": [
-    "tensorflow",
-    "tf",
-    "tfjs",
-    "face",
     "face-api",
+    "faceapi",
     "face-detection",
     "age-gender",
     "emotion-detection",
-    "face-recognition"
+    "face-recognition",
+    "face",
+    "face-description",
+    "tensorflow",
+    "tensorflowjs",
+    "tfjs"
   ],
-  "peerDependencies": {},
   "devDependencies": {
-    "@tensorflow/tfjs": "^3.2.0",
-    "@tensorflow/tfjs-backend-wasm": "^3.2.0",
-    "@tensorflow/tfjs-node": "^3.2.0",
-    "@tensorflow/tfjs-node-gpu": "^3.2.0",
-    "@types/node": "^14.14.33",
-    "@typescript-eslint/eslint-plugin": "^4.17.0",
-    "@typescript-eslint/parser": "^4.17.0",
-    "@vladmandic/pilogger": "^0.2.14",
-    "chokidar": "^3.5.1",
-    "dayjs": "^1.10.4",
-    "esbuild": "^0.9.0",
-    "eslint": "^7.21.0",
-    "eslint-config-airbnb-base": "^14.2.1",
-    "eslint-plugin-import": "^2.22.1",
-    "eslint-plugin-json": "^2.1.2",
+    "@canvas/image": "^2.0.0",
+    "@microsoft/api-extractor": "^7.49.2",
+    "@tensorflow/tfjs": "^4.22.0",
+    "@tensorflow/tfjs-backend-cpu": "^4.22.0",
+    "@tensorflow/tfjs-backend-wasm": "^4.22.0",
+    "@tensorflow/tfjs-backend-webgl": "^4.22.0",
+    "@tensorflow/tfjs-backend-webgpu": "4.22.0",
+    "@tensorflow/tfjs-converter": "^4.22.0",
+    "@tensorflow/tfjs-core": "^4.22.0",
+    "@tensorflow/tfjs-data": "^4.22.0",
+    "@tensorflow/tfjs-layers": "^4.22.0",
+    "@tensorflow/tfjs-node": "^4.22.0",
+    "@tensorflow/tfjs-node-gpu": "^4.22.0",
+    "@types/node": "^22.13.1",
+    "@types/offscreencanvas": "^2019.7.3",
+    "@typescript-eslint/eslint-plugin": "^8.5.0",
+    "@typescript-eslint/parser": "^8.5.0",
+    "@vladmandic/build": "^0.10.2",
+    "@vladmandic/pilogger": "^0.5.1",
+    "ajv": "^8.17.1",
+    "esbuild": "^0.24.2",
+    "eslint": "8.57.0",
+    "eslint-config-airbnb-base": "^15.0.0",
+    "eslint-plugin-import": "^2.30.0",
+    "eslint-plugin-json": "^4.0.1",
     "eslint-plugin-node": "^11.1.0",
-    "eslint-plugin-promise": "^4.3.1",
-    "rimraf": "^3.0.2",
-    "simple-git": "^2.36.1",
-    "tslib": "^2.1.0",
-    "typescript": "^4.2.3"
+    "eslint-plugin-promise": "^7.1.0",
+    "node-fetch": "^3.3.2",
+    "rimraf": "^6.0.1",
+    "seedrandom": "^3.0.5",
+    "tslib": "^2.8.1",
+    "typedoc": "^0.27.6",
+    "typescript": "5.7.3"
   }
 }

server/build.js

@@ -1,236 +0,0 @@
-#!/usr/bin/env -S node --trace-warnings
-
-/* eslint-disable import/no-extraneous-dependencies */
-/* eslint-disable node/no-unpublished-require */
-/* eslint-disable node/shebang */
-
-const fs = require('fs');
-const esbuild = require('esbuild');
-const ts = require('typescript');
-const log = require('@vladmandic/pilogger');
-
-// keeps esbuild service instance cached
-let es;
-const banner = `
-  /*
-  Face-API
-  homepage: <https://github.com/vladmandic/face-api>
-  author: <https://github.com/vladmandic>'
-  */
-`;
-
-// tsc configuration
-const tsconfig = {
-  noEmitOnError: false,
-  target: ts.ScriptTarget.ES2018,
-  module: ts.ModuleKind.ES2020,
-  // outFile: "dist/face-api.d.ts",
-  outDir: 'types/',
-  declaration: true,
-  emitDeclarationOnly: true,
-  emitDecoratorMetadata: true,
-  experimentalDecorators: true,
-  skipLibCheck: true,
-  strictNullChecks: true,
-  baseUrl: './',
-  paths: {
-    tslib: ['node_modules/tslib/tslib.d.ts'],
-  },
-};
-
-// common configuration
-const common = {
-  banner,
-  minifyWhitespace: true,
-  minifyIdentifiers: true,
-  minifySyntax: true,
-  bundle: true,
-  sourcemap: true,
-  logLevel: 'error',
-  target: 'es2018',
-  // tsconfig: './tsconfig.json',
-};
-
-const targets = {
-  node: {
-    tfjs: {
-      platform: 'node',
-      format: 'cjs',
-      metafile: 'dist/tfjs.esm.json',
-      entryPoints: ['src/tfjs/tf-node.ts'],
-      outfile: 'dist/tfjs.esm.js',
-      external: ['@tensorflow'],
-    },
-    node: {
-      platform: 'node',
-      format: 'cjs',
-      metafile: 'dist/face-api.node.json',
-      entryPoints: ['src/index.ts'],
-      outfile: 'dist/face-api.node.js',
-      external: ['@tensorflow'],
-    },
-  },
-  nodeGPU: {
-    tfjs: {
-      platform: 'node',
-      format: 'cjs',
-      entryPoints: ['src/tfjs/tf-node-gpu.ts'],
-      outfile: 'dist/tfjs.esm.js',
-      metafile: 'dist/tfjs.esm.json',
-      external: ['@tensorflow'],
-    },
-    node: {
-      platform: 'node',
-      format: 'cjs',
-      entryPoints: ['src/index.ts'],
-      outfile: 'dist/face-api.node-gpu.js',
-      metafile: 'dist/face-api.node-gpu.json',
-      external: ['@tensorflow'],
-    },
-  },
-  nodeCPU: {
-    tfjs: {
-      platform: 'node',
-      format: 'cjs',
-      metafile: 'dist/tfjs.esm.json',
-      entryPoints: ['src/tfjs/tf-node-cpu.ts'],
-      outfile: 'dist/tfjs.esm.js',
-      external: ['@tensorflow'],
-    },
-    node: {
-      platform: 'node',
-      format: 'cjs',
-      metafile: 'dist/face-api.node-cpu.json',
-      entryPoints: ['src/index.ts'],
-      outfile: 'dist/face-api.node-cpu.js',
-      external: ['@tensorflow'],
-    },
-  },
-  browserNoBundle: {
-    tfjs: {
-      platform: 'browser',
-      format: 'esm',
-      entryPoints: ['src/tfjs/tf-browser.ts'],
-      outfile: 'dist/tfjs.esm.js',
-      metafile: 'dist/tfjs.esm.json',
-      external: ['fs', 'buffer', 'util', 'os', '@tensorflow'],
-    },
-    esm: {
-      platform: 'browser',
-      format: 'esm',
-      entryPoints: ['src/index.ts'],
-      outfile: 'dist/face-api.esm-nobundle.js',
-      metafile: 'dist/face-api.esm-nobundle.json',
-      external: ['fs', 'buffer', 'util', 'os', '@tensorflow', 'tfjs.esm.js'],
-    },
-  },
-  browserBundle: {
-    tfjs: {
-      platform: 'browser',
-      format: 'esm',
-      entryPoints: ['src/tfjs/tf-browser.ts'],
-      outfile: 'dist/tfjs.esm.js',
-      metafile: 'dist/tfjs.esm.json',
-      external: ['fs', 'buffer', 'util', 'os'],
-    },
-    iife: {
-      platform: 'browser',
-      format: 'iife',
-      globalName: 'faceapi',
-      entryPoints: ['src/index.ts'],
-      outfile: 'dist/face-api.js',
-      metafile: 'dist/face-api.json',
-      external: ['fs', 'buffer', 'util', 'os'],
-    },
-    esm: {
-      platform: 'browser',
-      format: 'esm',
-      entryPoints: ['src/index.ts'],
-      outfile: 'dist/face-api.esm.js',
-      metafile: 'dist/face-api.esm.json',
-      external: ['fs', 'buffer', 'util', 'os'],
-    },
-  },
-};
-
-async function getStats(metafile) {
-  const stats = {};
-  if (!fs.existsSync(metafile)) return stats;
-  const data = fs.readFileSync(metafile);
-  const json = JSON.parse(data.toString());
-  if (json && json.inputs && json.outputs) {
-    for (const [key, val] of Object.entries(json.inputs)) {
-      if (key.startsWith('node_modules')) {
-        stats.modules = (stats.modules || 0) + 1;
-        stats.moduleBytes = (stats.moduleBytes || 0) + val.bytes;
-      } else {
-        stats.imports = (stats.imports || 0) + 1;
-        stats.importBytes = (stats.importBytes || 0) + val.bytes;
-      }
-    }
-    const files = [];
-    for (const [key, val] of Object.entries(json.outputs)) {
-      if (!key.endsWith('.map')) {
-        files.push(key);
-        stats.outputBytes = (stats.outputBytes || 0) + val.bytes;
-      }
-    }
-    stats.outputFiles = files.join(', ');
-  }
-  return stats;
-}
-
-function compile(fileNames, options) {
-  log.info('Compile typings:', fileNames);
-  const program = ts.createProgram(fileNames, options);
-  const emit = program.emit();
-  const diag = ts
-    .getPreEmitDiagnostics(program)
-    .concat(emit.diagnostics);
-  for (const info of diag) {
-    // @ts-ignore
-    const msg = info.messageText.messageText || info.messageText;
-    if (msg.includes('package.json')) continue;
-    if (msg.includes('Expected 0 arguments, but got 1')) continue;
-    if (info.file) {
-      const pos = info.file.getLineAndCharacterOfPosition(info.start || 0);
-      log.error(`TSC: ${info.file.fileName} [${pos.line + 1},${pos.character + 1}]:`, msg);
-    } else {
-      log.error('TSC:', msg);
-    }
-  }
-}
-
-// rebuild on file change
-async function build(f, msg) {
-  log.info('Build: file', msg, f, 'target:', common.target);
-  if (!es) es = await esbuild.startService();
-  try {
-    // rebuild all target groups and types
-    for (const [targetGroupName, targetGroup] of Object.entries(targets)) {
-      for (const [targetName, targetOptions] of Object.entries(targetGroup)) {
-        // if triggered from watch mode, rebuild only browser bundle
-        if ((require.main !== module) && (targetGroupName !== 'browserBundle')) continue;
-        await es.build({ ...common, ...targetOptions });
-        const stats = await getStats(targetOptions.metafile);
-        log.state(`Build for: ${targetGroupName} type: ${targetName}:`, stats);
-      }
-    }
-  } catch (err) {
-    // catch errors and print where it occured
-    log.error('Build error', JSON.stringify(err.errors || err, null, 2));
-    if (require.main === module) process.exit(1);
-  }
-
-  // generate typings
-  compile(targets.browserBundle.esm.entryPoints, tsconfig);
-
-  if (require.main === module) process.exit(0);
-}
-
-if (require.main === module) {
-  log.header();
-  build('all', 'startup');
-} else {
-  exports.build = build;
-}

server/changelog.js

@@ -1,59 +0,0 @@
-const fs = require('fs');
-const path = require('path');
-const dayjs = require('dayjs');
-const simpleGit = require('simple-git/promise');
-const logger = require('@vladmandic/pilogger');
-const app = require('../package.json');
-
-const git = simpleGit();
-
-let text = `# ${app.name}  
-
-Version: **${app.version}**  
-Description: **${app.description}**  
-
-Author: **${app.author}**  
-License: **${app.license}** </LICENSE>  
-Repository: **<${app.repository.url}>**  
-
-## Changelog
-`;
-
-async function update(f) {
-  const gitLog = await git.log();
-  // @ts-ignore
-  const log = gitLog.all.sort((a, b) => (new Date(b.date).getTime() - new Date(a.date).getTime()));
-
-  let previous = '';
-  const headings = [];
-  for (const l of log) {
-    const msg = l.message.toLowerCase();
-    if ((l.refs !== '') || msg.match(/^[0-99].[0-99].[0-99]/)) {
-      const dt = dayjs(l.date).format('YYYY/MM/DD');
-      let ver = msg.match(/[0-99].[0-99].[0-99]/) ? msg : l.refs;
-      ver = ver.replace('tag: v', '').replace('tag: ', 'release: ').split(',')[0];
-      const heading = `\n### **${ver}** ${dt} ${l.author_email}\n\n`;
-      if (!headings.includes(heading) && !ver.startsWith('tag')) {
-        headings.push(heading);
-        text += heading;
-      }
-    } else if ((msg.length > 2) && !msg.startsWith('update') && (previous !== msg)) {
-      previous = msg;
-      text += `- ${msg}\n`;
-    }
-  }
-
-  const name = path.join(__dirname, f);
-  fs.writeFileSync(name, text);
-  logger.state('Change log updated:', name);
-}
-
-exports.update = update;
-
-try {
-  if (require.main === module) {
-    update('../CHANGELOG.md');
-  }
-} catch {
-  //
-}

server/https.crt

@@ -1,31 +0,0 @@
------BEGIN CERTIFICATE-----
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-87ZbN6t01+v2YyYe6Mc7p80s1R3jc8aVX8ca2KcYwsJAkg/xz0q5RJwsE1is5UY=
------END CERTIFICATE-----

server/https.key

@@ -1,52 +0,0 @@
------BEGIN PRIVATE KEY-----
-MIIJQwIBADANBgkqhkiG9w0BAQEFAASCCS0wggkpAgEAAoICAQDSC88PF8NyLkag
-K5mAZ/d739SOU16l2Cx3zE35zZQhO29+1L4L+oMksLYipo+FMgtGO+MSzFsvGgKC
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------END PRIVATE KEY-----