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

@@ -7,7 +7,7 @@
       "es2020": true
   },
   "parser": "@typescript-eslint/parser",
-  "parserOptions": { "ecmaVersion": 2020 },
+  "parserOptions": { "ecmaVersion": "latest" },
   "plugins": [
     "@typescript-eslint"
   ],
@@ -17,7 +17,6 @@
     "plugin:import/warnings",
     "plugin:node/recommended",
     "plugin:promise/recommended",
-    "plugin:json/recommended-with-comments",
     "plugin:@typescript-eslint/eslint-recommended",
     "plugin:@typescript-eslint/recommended",
     "airbnb-base"
@@ -29,8 +28,11 @@
     "@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",
@@ -56,6 +58,7 @@
     "no-restricted-syntax": "off",
     "no-return-assign": "off",
     "no-underscore-dangle": "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",

.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']

.gitignore

@@ -1,3 +1,2 @@
 node_modules
 pnpm-lock.yaml
-

.npmignore

@@ -2,3 +2,4 @@ node_modules
 pnpm-lock.yaml
 typedoc
 test
+types/lib

.npmrc

@@ -1 +1,5 @@
-force = true
+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

@@ -1,13 +1,163 @@
 # @vladmandic/face-api  
 
-Version: **1.4.1**  
+  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**  
+  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>**  
+  Author: **Vladimir Mandic <mandic00@live.com>**  
-License: **MIT** </LICENSE>  
+  License: **MIT**  
-Repository: **<git+https://github.com/vladmandic/face-api.git>**  
+  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
 
@@ -107,111 +257,61 @@ Repository: **<git+https://github.com/vladmandic/face-api.git>**
 
 - add badges
 - optimize for npm
-
+- 0.30.6
-### **0.30.6** 2021/03/08 mandic00@live.com
-
 - added typings for face angle
 - disable landmark printing
-
+- 0.30.5
-### **0.30.5** 2021/03/07 mandic00@live.com
-
 - enabled live demo on gitpages
-
+- 0.30.4
-### **0.30.4** 2021/03/07 mandic00@live.com
-
 - added face angle calculations
 - added documentation
 - package update
-
+- 0.30.3
-### **0.30.3** 2021/03/04 mandic00@live.com
+- 0.30.2
-
+- 0.30.1
-
+- 0.13.3
-### **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
-
 - 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
-### **0.13.2** 2021/02/20 mandic00@live.com
+- 0.13.1
-
+- 0.12.10
-
+- exception handling
-### **0.13.1** 2021/02/20 mandic00@live.com
+- 0.12.9
-
+- exception handling
-
+- 0.12.8
-### **0.12.10** 2021/02/20 mandic00@live.com
-
 - 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
-### **0.12.6** 2021/02/13 mandic00@live.com
+- 0.12.5
-
+- 0.12.4
-
+- 0.12.3
-### **0.12.5** 2021/02/12 mandic00@live.com
+- 0.12.2
-
-
-### **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
-
 
 ### **update for tfjs 3.0.0** 2021/01/29 mandic00@live.com
 
-
+- 0.12.1
-### **0.12.1** 2021/01/29 mandic00@live.com
-
 - rebuild
-
+- 0.11.6
-### **0.11.6** 2021/01/24 mandic00@live.com
-
 - 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
-### **0.11.5** 2021/01/22 mandic00@live.com
+- 0.11.4
-
+- 0.11.3
-
-### **0.11.4** 2021/01/22 mandic00@live.com
-
-
-### **0.11.3** 2021/01/20 mandic00@live.com
-
 - fix typo
 - enable full minification
-
+- 0.11.2
-### **0.11.2** 2021/01/12 mandic00@live.com
-
 - full rebuild
-
+- 0.11.1
-### **0.11.1** 2021/01/10 mandic00@live.com
-
 - added live webcam demo
-
+- 0.10.2
-### **0.10.2** 2021/01/03 mandic00@live.com
-
 - ts linting
 - version bump
-
+- 0.10.1
-### **0.10.1** 2020/12/23 mandic00@live.com
-
 - full re-lint and typings generation
 - rebuild
 

README.md

@@ -53,18 +53,18 @@ Example can be accessed directly using Git pages using URL:
 
 ### NodeJS
 
-Three NodeJS examples are:
+NodeJS examples are:
 
+- `/demo/node-simple.js`:
+  Simplest possible NodeJS demo for FaceAPI in under 30 lines of JavaScript code  
 - `/demo/node.js`:  
-  Regular usage of `FaceAPI` from `NodeJS`  
+  Using `TFJS` native methods to load images without external dependencies  
-  Using `TFJS` native methods to load images without external dependencies
+- `/demo/node-canvas.js` and `/demo/node-image.js`:  
-- `/demo/node-canvas.js`:  
-  Regular usage of `FaceAPI` from `NodeJS`  
   Using external `canvas` module to load images  
-  Which also allows for image drawing and saving inside `NodeJS` environment
+  Which also allows for image drawing and saving inside `NodeJS` environment  
-- `/demo/node-wasm.js`:
+- `/demo/node-match.js`:  
-  Same as `node-canvas`, but using `WASM` backend in `NodeJS` environment  
+  Simple demo that compares face similarity from a given image  
-  Because why not :)
+  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`)  
@@ -104,8 +104,11 @@ Three NodeJS examples are:
 2021-03-14 08:42:09 STATE:  Main: worker exit: 1888019 0
 ```
 
-Note that `@tensorflow/tfjs-node` or `@tensorflow/tfjs-node-gpu`  
+### NodeJS Notes
-must be installed before using NodeJS example
+- 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>
 
@@ -133,8 +136,6 @@ Simply include latest version of `FaceAPI` directly from a CDN in your HTML:
    *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:
 
@@ -260,7 +261,7 @@ If you want to GPU Accelerated execution in NodeJS, you must have CUDA libraries
 Then install appropriate version of `FaceAPI`:
 
 ```shell
-  npm install @tensorflow/tfjs-node
+  npm install @tensorflow/tfjs-node-gpu
   npm install @vladmandic/face-api 
 ```
 
@@ -271,18 +272,24 @@ 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 `FaceAPI` 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 tf = require('@tensorflow/tfjs');
-  const faceapi = require('@vladmandic/face-api/dist/face-api.node-cpu.js');
+  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,  
@@ -310,12 +317,14 @@ faceapi.env.monkeyPatch({ Canvas, Image, ImageData })
 
 ## Weights
 
-Pretrained models and their weights are includes in `./model`.
+Pretrained models and their weights are included in `./model`.
 
 <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
@@ -327,38 +336,47 @@ By default it starts HTTP server on port 8000 and HTTPS server on port 8001 and
 - <https://localhost:8001/demo/index.html>
 - <https://localhost:8001/demo/webcam.html>
 
-```json
+```js
-2021-07-29 09:03:02 INFO:  @vladmandic/face-api version 1.3.1
+2022-01-14 09:56:19 INFO:  @vladmandic/face-api version 1.6.4
-2021-07-29 09:03:02 INFO:  User: vlado Platform: linux Arch: x64 Node: v16.5.0
+2022-01-14 09:56:19 INFO:  User: vlado Platform: linux Arch: x64 Node: v17.2.0
-2021-07-29 09:03:02 INFO:  Build: file startup all target: es2018
+2022-01-14 09:56:19 INFO:  Application: { name: '@vladmandic/face-api', version: '1.6.4' }
-2021-07-29 09:03:02 STATE: HTTP server listening: 8000
+2022-01-14 09:56:19 INFO:  Environment: { profile: 'development', config: '.build.json', package: 'package.json', tsconfig: true, eslintrc: true, git: true }
-2021-07-29 09:03:02 STATE: HTTP2 server listening: 8001
+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' }
-2021-07-29 09:03:02 STATE: Build for: node type: tfjs: { imports: 1, importBytes: 143, outputBytes: 1327, outputFiles: 'dist/tfjs.esm.js' }
+2022-01-14 09:56:19 INFO:  Build: { profile: 'development', steps: [ 'serve', 'watch', 'compile' ] }
-2021-07-29 09:03:02 STATE: Build for: node type: node: { imports: 162, importBytes: 234303, outputBytes: 175090, outputFiles: 'dist/face-api.node.js' }
+2022-01-14 09:56:19 STATE: WebServer: { ssl: false, port: 8000, root: '.' }
-2021-07-29 09:03:02 STATE: Monitoring: [ 'package.json', 'demo', 'src', [length]: 3 ]
+2022-01-14 09:56:19 STATE: WebServer: { ssl: true, port: 8001, root: '.', sslKey: 'build/cert/https.key', sslCrt: 'build/cert/https.crt' }
-2021-07-29 09:03:02 STATE: Build for: nodeGPU type: tfjs: { imports: 1, importBytes: 147, outputBytes: 1335, outputFiles: 'dist/tfjs.esm.js' }
+2022-01-14 09:56:19 STATE: Watch: { locations: [ 'src/**', 'README.md', 'src/**', 'src/**' ] }
-2021-07-29 09:03:02 STATE: Build for: nodeGPU type: node: { imports: 162, importBytes: 234311, outputBytes: 175098, outputFiles: 'dist/face-api.node-gpu.js' }
+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 }
-2021-07-29 09:03:02 STATE: Build for: nodeCPU type: tfjs: { imports: 1, importBytes: 138, outputBytes: 1326, outputFiles: 'dist/tfjs.esm.js' }
+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 }
-2021-07-29 09:03:02 STATE: Build for: nodeCPU type: node: { imports: 162, importBytes: 234302, outputBytes: 175089, outputFiles: 'dist/face-api.node-cpu.js' }
+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 }
-2021-07-29 09:03:02 STATE: Build for: browserNoBundle type: tfjs: { imports: 1, importBytes: 276, outputBytes: 277, outputFiles: 'dist/tfjs.esm.js' }
+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 }
-2021-07-29 09:03:02 STATE: Build for: browserNoBundle type: esm: { imports: 162, importBytes: 233253, outputBytes: 168850, outputFiles: 'dist/face-api.esm-nobundle.js' }
+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 }
-2021-07-29 09:03:03 STATE: Build for: browserBundle type: tfjs: { modules: 1352, moduleBytes: 4369745, imports: 7, importBytes: 276, outputBytes: 2362345, outputFiles: 'dist/tfjs.esm.js' }
+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 }
-2021-07-29 09:03:03 STATE: Build for: browserBundle type: iife: { imports: 162, importBytes: 2595321, outputBytes: 2482864, outputFiles: 'dist/face-api.js' }
+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 }
-2021-07-29 09:03:04 STATE: Build for: browserBundle type: esm: { imports: 162, importBytes: 2595321, outputBytes: 2360761, outputFiles: 'dist/face-api.esm.js' }
+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 }
-2021-07-29 09:03:23 DATA:  GET/2.0 200 text/html; charset=utf-8 1269 /demo/webcam.html ::ffff:192.168.0.200
+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 }
-2021-07-29 09:03:23 DATA:  GET/2.0 200 text/javascript; charset=utf-8 7971 /demo/webcam.js ::ffff:192.168.0.200
+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 }
-2021-07-29 09:03:23 DATA:  GET/2.0 200 text/javascript; charset=utf-8 2360761 /dist/face-api.esm.js ::ffff:192.168.0.200
+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 }
-2021-07-29 09:03:23 DATA:  GET/2.0 200 application/json; charset=utf-8 28233 /model/ssd_mobilenetv1_model-weights_manifest.json ::ffff:192.168.0.200
+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 }
-2021-07-29 09:03:23 DATA:  GET/2.0 200 image/x-icon 5063 /favicon.ico ::ffff:192.168.0.200
+2022-01-14 09:56:20 INFO:  Listening...
-2021-07-29 09:03:23 DATA:  GET/2.0 200 application/octet-stream 5616957 /model/ssd_mobilenetv1_model.bin ::ffff:192.168.0.200
+...
-2021-07-29 09:03:24 DATA:  GET/2.0 200 application/json; charset=utf-8 8392 /model/age_gender_model-weights_manifest.json ::ffff:192.168.0.200
+2022-01-14 09:56:46 DATA:  HTTPS: { method: 'GET', ver: '2.0', status: 200, mime: 'text/html', size: 1047, url: '/', remote: '::1' }
-2021-07-29 09:03:24 DATA:  GET/2.0 200 application/octet-stream 429708 /model/age_gender_model.bin ::ffff:192.168.0.200
+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' }
-2021-07-29 09:03:24 DATA:  GET/2.0 200 application/json; charset=utf-8 8485 /model/face_landmark_68_model-weights_manifest.json ::ffff:192.168.0.200
+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' }
-2021-07-29 09:03:24 DATA:  GET/2.0 200 application/octet-stream 356840 /model/face_landmark_68_model.bin ::ffff:192.168.0.200
+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' }
-2021-07-29 09:03:24 DATA:  GET/2.0 200 application/json; charset=utf-8 19615 /model/face_recognition_model-weights_manifest.json ::ffff:192.168.0.200
+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' }
-2021-07-29 09:03:24 DATA:  GET/2.0 200 application/octet-stream 6444032 /model/face_recognition_model.bin ::ffff:192.168.0.200
+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' }
-2021-07-29 09:03:25 DATA:  GET/2.0 200 application/json; charset=utf-8 6980 /model/face_expression_model-weights_manifest.json ::ffff:192.168.0.200
+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' }
-2021-07-29 09:03:25 DATA:  GET/2.0 200 application/octet-stream 329468 /model/face_expression_model.bin ::ffff:192.168.0.200
+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>
@@ -382,38 +400,41 @@ 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
+```js
-> @vladmandic/face-api@1.0.2 build
+> @vladmandic/face-api@1.7.1 build /home/vlado/dev/face-api
-> rimraf dist/* types/* typedoc/* && node server/build.js
+> node build.js
-```
 
-```json
+2022-07-25 08:21:05 INFO:  Application: { name: '@vladmandic/face-api', version: '1.7.1' }
-2021-07-29 09:01:33 INFO:  @vladmandic/face-api version 1.3.1
+2022-07-25 08:21:05 INFO:  Environment: { profile: 'production', config: '.build.json', package: 'package.json', tsconfig: true, eslintrc: true, git: true }
-2021-07-29 09:01:33 INFO:  User: vlado Platform: linux Arch: x64 Node: v16.5.0
+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' }
-2021-07-29 09:01:33 INFO:  Toolchain: tfjs: 3.8.0 esbuild 0.12.16; typescript 4.3.5; typedoc: 0.21.4 eslint: 7.31.0
+2022-07-25 08:21:05 INFO:  Build: { profile: 'production', steps: [ 'clean', 'compile', 'typings', 'typedoc', 'lint', 'changelog' ] }
-2021-07-29 09:01:33 INFO:  Build: file startup all target: es2018
+2022-07-25 08:21:05 STATE: Clean: { locations: [ 'dist/*', 'typedoc/*', 'types/lib/src' ] }
-2021-07-29 09:01:33 STATE: Build for: node type: tfjs: { imports: 1, importBytes: 143, outputBytes: 1327, outputFiles: 'dist/tfjs.esm.js' }
+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 }
-2021-07-29 09:01:33 STATE: Build for: node type: node: { imports: 162, importBytes: 234303, outputBytes: 175090, outputFiles: 'dist/face-api.node.js' }
+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 }
-2021-07-29 09:01:33 STATE: Build for: nodeGPU type: tfjs: { imports: 1, importBytes: 147, outputBytes: 1335, outputFiles: 'dist/tfjs.esm.js' }
+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 }
-2021-07-29 09:01:33 STATE: Build for: nodeGPU type: node: { imports: 162, importBytes: 234311, outputBytes: 175098, outputFiles: 'dist/face-api.node-gpu.js' }
+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 }
-2021-07-29 09:01:33 STATE: Build for: nodeCPU type: tfjs: { imports: 1, importBytes: 138, outputBytes: 1326, outputFiles: 'dist/tfjs.esm.js' }
+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 }
-2021-07-29 09:01:33 STATE: Build for: nodeCPU type: node: { imports: 162, importBytes: 234302, outputBytes: 175089, outputFiles: 'dist/face-api.node-cpu.js' }
+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 }
-2021-07-29 09:01:33 STATE: Build for: browserNoBundle type: tfjs: { imports: 1, importBytes: 276, outputBytes: 277, outputFiles: 'dist/tfjs.esm.js' }
+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 }
-2021-07-29 09:01:33 STATE: Build for: browserNoBundle type: esm: { imports: 162, importBytes: 233253, outputBytes: 168850, outputFiles: 'dist/face-api.esm-nobundle.js' }
+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 }
-2021-07-29 09:01:33 STATE: Build for: browserBundle type: tfjs: { modules: 1352, moduleBytes: 4369745, imports: 7, importBytes: 276, outputBytes: 2362345, outputFiles: 'dist/tfjs.esm.js' }
+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 }
-2021-07-29 09:01:34 STATE: Build for: browserBundle type: iife: { imports: 162, importBytes: 2595321, outputBytes: 2482864, outputFiles: 'dist/face-api.js' }
+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 }
-2021-07-29 09:01:35 STATE: Build for: browserBundle type: esm: { imports: 162, importBytes: 2595321, outputBytes: 2360761, outputFiles: 'dist/face-api.esm.js' }
+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 }
-2021-07-29 09:01:35 INFO:  Running Linter: [ 'server/', 'demo/', 'src/', 'test/', [length]: 4 ]
+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 }
-2021-07-29 09:01:55 INFO:  Linter complete: files: 183 errors: 0 warnings: 0
+2022-07-25 08:21:07 STATE: Typings: { input: 'src/index.ts', output: 'types/lib', files: 93 }
-2021-07-29 09:01:55 INFO:  Compile typings: [ 'src/index.ts', [length]: 1 ]
+2022-07-25 08:21:09 STATE: TypeDoc: { input: 'src/index.ts', output: 'typedoc', objects: 154, generated: true }
-2021-07-29 09:01:59 INFO:  Update Change log: [ '/home/vlado/dev/face-api/CHANGELOG.md', [length]: 1 ]
+2022-07-25 08:21:13 STATE: Lint: { locations: [ 'src/' ], files: 174, errors: 0, warnings: 0 }
-2021-07-29 09:01:59 INFO:  Generate TypeDocs: [ 'src/index.ts', [length]: 1 ]
+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...
 ```
 
 <br><hr><br>
@@ -428,18 +449,14 @@ Build process uses script `build.js` that creates optimized build for each targe
 
 ## Note
 
-This is updated **face-api.js** with latest available TensorFlow/JS as the original is not compatible with **tfjs 2.0+**.  
+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  
 
-Currently based on **`TensorFlow/JS` 3.6.1**  
+*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  
 
-*Why?* I needed FaceAPI that does not cause version conflict with newer versions of TensorFlow  
+Changes ended up being too large for a simple pull request and it ended up being a full-fledged version on its own  
-And since original FaceAPI was open-source, I've released this version as well  
+Plus many features were added since the original inception  
-
-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 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,  
@@ -454,29 +471,34 @@ but extends it with newer AI models, additional detection details, compatibility
 
 Compared to [face-api.js](https://github.com/justadudewhohacks/face-api.js) version **0.22.2**:
 
-- Compatible with `TensorFlow/JS 2.0+ & 3.0+`
+- Compatible with `TensorFlow/JS 2.0+, 3.0+ and 4.0+`  
-- Compatible with `WebGL`, `CPU` and `WASM` TFJS Browser backends
+  Currently using **`TensorFlow/JS` 4.16**  
-- Compatible with both `tfjs-node` and `tfjs-node-gpu` TFJS NodeJS backends
+  Original `face-api.js` is based on `TFJS` **1.7.4**  
-- Updated all type castings for TypeScript type checking to `TypeScript 4.3`
+- Compatible with `WebGL`, `CPU` and `WASM` TFJS Browser backends  
-- Switched bundling from `UMD` to `ESM` + `CommonJS` with fallback to `IIFE`
+- Compatible with both `tfjs-node` and `tfjs-node-gpu` TFJS NodeJS backends  
-  Resulting code is optimized per-platform instead of being universal
+- Updated all type castings for TypeScript type checking to `TypeScript 5.3`  
-  Fully tree shakable when imported as an `ESM` module
+- Switched bundling from `UMD` to `ESM` + `CommonJS` with fallback to `IIFE`  
-  Browser bundle process uses `ESBuild` instead of `Rollup`
+  Resulting code is optimized per-platform instead of being universal  
-- Typescript build process now targets `ES2018` and instead of dual `ES5`/`ES6`
+  Fully tree shakable when imported as an `ESM` module  
-  Resulting code is clean ES2018 JavaScript without polyfills
+  Browser bundle process uses `ESBuild` instead of `Rollup`  
-- Removed old tests, docs, examples
+- Added separate `face-api` versions with `tfjs` pre-bundled and without `tfjs`  
-- Removed old package dependencies (`karma`, `jasmine`, `babel`, etc.)
+  When using `-nobundle` version, user can load any version of `tfjs` manually  
-- Updated all package dependencies
+- Typescript build process now targets `ES2018` and instead of dual `ES5`/`ES6`  
-- Updated TensorFlow/JS dependencies since backends were removed from `@tensorflow/tfjs-core`
+  Resulting code is clean ES2018 JavaScript without polyfills  
-- Updated `mobileNetv1` model due to `batchNorm()` dependency
+- Removed old tests, docs, examples  
-- Added `version` class that returns JSON object with version of FaceAPI as well as linked TFJS
+- Removed old package dependencies (`karma`, `jasmine`, `babel`, etc.)  
-- Added test/dev built-in HTTP & HTTPS Web server
+- Updated all package dependencies  
-- Removed `mtcnn` and `tinyYolov2` models as they were non-functional in latest public version of `FaceAPI`
+- Updated TensorFlow/JS dependencies since backends were removed from `@tensorflow/tfjs-core`  
-  Which means valid models are **tinyFaceDetector** and **mobileNetv1**
+- Updated `mobileNetv1` model due to `batchNorm()` dependency  
-  *If there is a demand, I can re-implement them back.*
+- Added `version` class that returns JSON object with version of FaceAPI as well as linked TFJS  
-- Added `face angle` calculations that returns `roll`, `yaw` and `pitch`
+- Added test/dev built-in HTTP & HTTPS Web server  
-- Added `typdoc` automatic API specification generation during build
+- Removed `mtcnn` and `tinyYolov2` models as they were non-functional in latest public version of `FaceAPI`  
-- Added `changelog` automatic generation during build
+  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>
 

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

@@ -11,7 +11,7 @@
     <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;">
+  <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

@@ -1,25 +1,25 @@
-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 = '../model/'; // path to model folder that will be loaded using http
-// const modelPath = 'https://vladmandic.github.io/face-api/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 = ['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) {
+const str = (json) => (json ? JSON.stringify(json).replace(/{|}|"|\[|\]/g, '').replace(/,/g, ', ') : '');
-  let text = '<font color="lightblue">';
-  text += json ? JSON.stringify(json).replace(/{|}|"|\[|\]/g, '').replace(/,/g, ', ') : '';
-  text += '</font>';
-  return text;
-}
 
 // helper function to print strings to html document as a log
 function log(...txt) {
-  // eslint-disable-next-line no-console
+  console.log(...txt); // eslint-disable-line no-console
-  console.log(...txt);
   const div = document.getElementById('log');
   if (div) div.innerHTML += `<br>${txt}`;
 }
@@ -33,11 +33,9 @@ function faces(name, title, id, data) {
   canvas.style.position = 'absolute';
   canvas.style.left = `${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); // eslint-disable-line no-console
-  console.log('Results:', title, img, data);
   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?.setWasmPaths(`https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@${faceapi.tf.version_core}/dist/`);
-  // await faceapi.tf.setBackend('wasm');
+  // 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

@@ -1,15 +1,20 @@
-// @ts-nocheck
+/**
+ * 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 process = require('process');
 const path = require('path');
-// eslint-disable-next-line import/no-extraneous-dependencies, node/no-unpublished-require
+const process = require('process');
 const log = require('@vladmandic/pilogger');
-// eslint-disable-next-line import/no-extraneous-dependencies, node/no-unpublished-require, no-unused-vars, @typescript-eslint/no-unused-vars
+const tf = require('@tensorflow/tfjs-node'); // in nodejs environments tfjs-node is required to be loaded before face-api
-const tf = require('@tensorflow/tfjs-node');
+const faceapi = require('../dist/face-api.node.js'); // use this when using face-api in dev mode
-// eslint-disable-next-line import/no-extraneous-dependencies, node/no-unpublished-require
+// const faceapi = require('@vladmandic/face-api'); // use this when face-api is installed as module (majority of use cases)
-const canvas = require('canvas');
-const faceapi = require('../dist/face-api.node.js'); // this is equivalent to '@vladmandic/faceapi'
 
 const modelPathRoot = '../model';
 const imgPathRoot = './demo'; // modify to include your sample images
@@ -52,11 +57,9 @@ async function main() {
   faceapi.env.monkeyPatch({ Canvas: canvas.Canvas, Image: canvas.Image, ImageData: canvas.ImageData });
 
   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.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);
@@ -80,7 +83,7 @@ async function main() {
       for (const face of result) print(face);
     }
     const t1 = process.hrtime.bigint();
-    log.info('Processed', numImages, 'images in', Math.trunc(parseInt(t1 - t0) / 1000 / 1000), 'ms');
+    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:')) {

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

@@ -1,11 +1,18 @@
+/**
+ * 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');
-// eslint-disable-next-line import/no-extraneous-dependencies, node/no-unpublished-require
-const tf = require('@tensorflow/tfjs-node');
-// eslint-disable-next-line import/no-extraneous-dependencies, node/no-unpublished-require
-const image = require('@canvas/image'); // @canvas/image can decode jpeg, png, webp
-// eslint-disable-next-line import/no-extraneous-dependencies, node/no-unpublished-require
 const log = require('@vladmandic/pilogger');
-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)
 
 const modelPath = 'model/';
 const imageFile = 'demo/sample1.jpg';
@@ -41,7 +48,7 @@ async function main() {
     .withFaceExpressions()
     .withFaceDescriptors()
     .withAgeAndGender();
-  log.data('results:', result);
+  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

@@ -1,14 +1,16 @@
-// @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'); // in nodejs environments tfjs-node is required to be loaded before face-api
-const tf = require('@tensorflow/tfjs-node');
+const faceapi = require('../dist/face-api.node.js'); // use this when using face-api in dev mode
-const faceapi = require('../dist/face-api.node.js'); // this is equivalent to '@vladmandic/faceapi'
+// 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';
@@ -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);

demo/node-multiprocess.js

@@ -1,11 +1,14 @@
-// @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 = './demo'; // modify to include your sample images
 const numWorkers = 4; // how many workers will be started
@@ -33,14 +36,14 @@ function waitCompletion() {
   if (activeWorkers > 0) setImmediate(() => waitCompletion());
   else {
     t[1] = process.hrtime.bigint();
-    log.info('Processed:', numImages, 'images in', 'total:', Math.trunc(parseInt(t[1] - t[0]) / 1000000), 'ms', 'working:', Math.trunc(parseInt(t[1] - t[2]) / 1000000), 'ms', 'average:', Math.trunc(parseInt(t[1] - t[2]) / numImages / 1000000), '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 latencyInitialization = Math.trunc(Number(t[2] - t[0]) / 1000 / 1000);
-  const latencyRoundTrip = Math.trunc(parseInt(t[3] - t[2]) / 1000 / 1000);
+  const latencyRoundTrip = Math.trunc(Number(t[3] - t[2]) / 1000 / 1000);
   log.info('Latency: worker initializtion: ', latencyInitialization, 'message round trip:', latencyRoundTrip);
 }
 

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

@@ -1,97 +1,53 @@
-// @ts-nocheck
+/**
+ * FaceAPI Demo for NodeJS using WASM
+ * - Loads WASM binaries from external CDN
+ * - Loads image
+ * - Outputs results to console
+ */
 
 const fs = require('fs');
-const process = require('process');
+const image = require('@canvas/image'); // eslint-disable-line node/no-missing-require
-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, no-unused-vars, @typescript-eslint/no-unused-vars
 const tf = require('@tensorflow/tfjs');
-// eslint-disable-next-line import/no-extraneous-dependencies, node/no-unpublished-require
+const wasm = require('@tensorflow/tfjs-backend-wasm');
-require('@tensorflow/tfjs-backend-wasm');
+const faceapi = require('../dist/face-api.node-wasm.js'); // use this when using face-api in dev mode
-// eslint-disable-next-line import/no-extraneous-dependencies, node/no-unpublished-require, no-unused-vars
-const canvas = require('canvas');
-const faceapi = require('../dist/face-api.node-cpu.js'); // this is equivalent to '@vladmandic/faceapi'
 
-const modelPathRoot = '../model';
+async function readImage(imageFile) {
-const imgPathRoot = './demo'; // modify to include your sample images
+  const buffer = fs.readFileSync(imageFile); // read image from disk
-const minConfidence = 0.15;
+  const canvas = await image.imageFromBuffer(buffer); // decode to canvas
-const maxResults = 5;
+  const imageData = image.getImageData(canvas); // read decoded image data from canvas
-let optionsSSDMobileNet;
+  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
-async function image(input) {
+    const channels = tf.split(data, 4, 2); // split rgba to channels
-  const img = await canvas.loadImage(input);
+    const rgb = tf.stack([channels[0], channels[1], channels[2]], 2); // stack channels back to rgb
-  const c = canvas.createCanvas(img.width, img.height);
+    const squeeze = tf.squeeze(rgb); // move extra dim from the end of tensor and use it as batch number instead
-  const ctx = c.getContext('2d');
+    return squeeze;
-  ctx.drawImage(img, 0, 0, img.width, img.height);
+  });
-  // const out = fs.createWriteStream('test.jpg');
+  console.log(`Image: ${imageFile} [${canvas.width} x ${canvas.height} Tensor: ${tensor.shape}, Size: ${tensor.size}`); // eslint-disable-line no-console
-  // const stream = c.createJPEGStream({ quality: 0.6, progressive: true, chromaSubsampling: true });
+  return tensor;
-  // stream.pipe(out);
-  return c;
 }
 
-async function detect(tensor) {
+async function main() {
-  const result = await faceapi
+  wasm.setWasmPaths('https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm/dist/', true);
-    .detectAllFaces(tensor, optionsSSDMobileNet)
+  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();
-  return result;
+  tf.dispose(tensor); // dispose tensors to avoid memory leaks
-}
+  const t1 = performance.now();
-
+  console.log('Time', t1 - t0); // eslint-disable-line no-console
-function print(face) {
+  console.log('Result', result); // eslint-disable-line no-console
-  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('wasm');
-  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, 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(parseInt(t1 - t0) / 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.js

@@ -1,21 +1,25 @@
-// @ts-nocheck
+/**
+ * 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');
-// 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 fetch = require('node-fetch').default;
+const tf = require('@tensorflow/tfjs-node'); // in nodejs environments tfjs-node is required to be loaded before face-api
-// eslint-disable-next-line import/no-extraneous-dependencies, node/no-unpublished-require
+const faceapi = require('../dist/face-api.node.js'); // use this when using face-api in dev mode
-const tf = require('@tensorflow/tfjs-node');
+// const faceapi = require('@vladmandic/face-api'); // use this when face-api is installed as module (majority of use cases)
-const faceapi = require('../dist/face-api.node.js'); // this is equivalent to '@vladmandic/faceapi'
 
 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
@@ -89,12 +93,13 @@ 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.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.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);
@@ -105,7 +110,7 @@ async function main() {
   await faceapi.nets.faceExpressionNet.loadFromDisk(modelPath);
   optionsSSDMobileNet = new faceapi.SsdMobilenetv1Options({ minConfidence, maxResults });
 
-  if (process.argv.length !== 3) {
+  if (process.argv.length !== 4) {
     const t0 = process.hrtime.bigint();
     const dir = fs.readdirSync(imgPathRoot);
     for (const img of dir) {
@@ -117,7 +122,7 @@ async function main() {
       tensor.dispose();
     }
     const t1 = process.hrtime.bigint();
-    log.info('Processed', dir.length, 'images in', Math.trunc(parseInt(t1 - t0) / 1000 / 1000), 'ms');
+    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:')) {

demo/webcam.js

@@ -1,8 +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 = '../model/'; // path to model folder that will be loaded using http
-// const modelPath = 'https://vladmandic.github.io/face-api/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;
@@ -17,15 +23,14 @@ 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); // eslint-disable-line no-console
-  console.log(...txt);
   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
@@ -42,18 +47,18 @@ function drawFaces(canvas, data, fps) {
     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.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.toFixed(3)} pitch:${person.angle.pitch.toFixed(3)} yaw:${person.angle.yaw.toFixed(3)}`, person.detection.box.x, person.detection.box.y - 5);
+    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.toFixed(3)} pitch:${person.angle.pitch.toFixed(3)} yaw:${person.angle.yaw.toFixed(3)}`, person.detection.box.x, person.detection.box.y - 6);
+    ctx.fillText(`roll:${person.angle.roll}° pitch:${person.angle.pitch}° yaw:${person.angle.yaw}°`, person.detection.box.x, person.detection.box.y - 6);
     // draw face points for each face
     ctx.globalAlpha = 0.8;
     ctx.fillStyle = 'lightblue';
@@ -61,7 +66,6 @@ function drawFaces(canvas, data, fps) {
     for (let i = 0; i < person.landmarks.positions.length; i++) {
       ctx.beginPath();
       ctx.arc(person.landmarks.positions[i].x, person.landmarks.positions[i].y, pointSize, 0, 2 * Math.PI);
-      // ctx.fillText(`${i}`, person.landmarks.positions[i].x + 4, person.landmarks.positions[i].y + 4);
       ctx.fill();
     }
   }
@@ -95,7 +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) {
@@ -103,23 +106,19 @@ async function setupCamera() {
     return null;
   }
   let stream;
-  const constraints = {
+  const constraints = { audio: false, video: { facingMode: 'user', resizeMode: 'crop-and-scale' } };
-    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';
+    if (err.name === 'PermissionDeniedError' || err.name === 'NotAllowedError') log(`Camera Error: camera permission denied: ${err.message || err}`);
-    else if (err.name === 'SourceUnavailableError') msg = 'camera not available';
+    if (err.name === 'SourceUnavailableError') log(`Camera Error: camera not available: ${err.message || err}`);
-    log(`Camera Error: ${msg}: ${err.message || err}`);
     return null;
   }
-  // @ts-ignore
+  if (stream) {
-  if (stream) video.srcObject = stream;
+    video.srcObject = stream;
-  else {
+  } else {
     log('Camera Error: stream empty');
     return null;
   }
@@ -128,31 +127,23 @@ async function setupCamera() {
   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}`); // ${str(constraints)}
+  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);
@@ -170,7 +161,6 @@ async function setupFaceAPI() {
   await faceapi.nets.faceRecognitionNet.load(modelPath);
   await faceapi.nets.faceExpressionNet.load(modelPath);
   optionsSSDMobileNet = new faceapi.SsdMobilenetv1Options({ minConfidence: minScore, maxResults });
-
   // check tf engine state
   log(`Models loaded: ${str(faceapi.tf.engine().state.numTensors)} tensors`);
 }
@@ -180,19 +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?.setWasmPaths(`https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@${faceapi.tf.version_core}/dist/`);
-  // await faceapi.tf.setBackend('wasm');
+  // 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(`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' })}`);
 
   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};

package.json

@@ -1,12 +1,12 @@
 {
   "name": "@vladmandic/face-api",
-  "version": "1.4.1",
+  "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"
@@ -21,10 +21,10 @@
     "url": "git+https://github.com/vladmandic/face-api.git"
   },
   "scripts": {
-    "start": "node --trace-warnings demo/node.js",
+    "start": "node --no-warnings demo/node.js",
-    "dev": "node --trace-warnings server/serve.js",
+    "build": "node build.js",
-    "build": "rimraf dist/* types/* typedoc/* && node server/build.js",
+    "dev": "build --profile development",
-    "lint": "eslint src/**/* demo/*.js server/*.js",
+    "lint": "eslint src/ demo/",
     "test": "node --trace-warnings test/test-node.js",
     "scan": "npx auditjs@latest ossi --dev --quiet"
   },
@@ -42,31 +42,38 @@
     "tfjs"
   ],
   "devDependencies": {
-    "@canvas/image": "^1.0.1",
+    "@canvas/image": "^2.0.0",
-    "@tensorflow/tfjs": "^3.8.0",
+    "@microsoft/api-extractor": "^7.49.2",
-    "@tensorflow/tfjs-backend-wasm": "^3.8.0",
+    "@tensorflow/tfjs": "^4.22.0",
-    "@tensorflow/tfjs-node": "^3.8.0",
+    "@tensorflow/tfjs-backend-cpu": "^4.22.0",
-    "@tensorflow/tfjs-node-gpu": "^3.8.0",
+    "@tensorflow/tfjs-backend-wasm": "^4.22.0",
-    "@types/node": "^16.4.6",
+    "@tensorflow/tfjs-backend-webgl": "^4.22.0",
-    "@typescript-eslint/eslint-plugin": "^4.28.5",
+    "@tensorflow/tfjs-backend-webgpu": "4.22.0",
-    "@typescript-eslint/parser": "^4.28.5",
+    "@tensorflow/tfjs-converter": "^4.22.0",
-    "@vladmandic/pilogger": "^0.2.17",
+    "@tensorflow/tfjs-core": "^4.22.0",
-    "canvas": "^2.8.0",
+    "@tensorflow/tfjs-data": "^4.22.0",
-    "chokidar": "^3.5.2",
+    "@tensorflow/tfjs-layers": "^4.22.0",
-    "dayjs": "^1.10.6",
+    "@tensorflow/tfjs-node": "^4.22.0",
-    "esbuild": "^0.12.16",
+    "@tensorflow/tfjs-node-gpu": "^4.22.0",
-    "eslint": "^7.31.0",
+    "@types/node": "^22.13.1",
-    "eslint-config-airbnb-base": "^14.2.1",
+    "@types/offscreencanvas": "^2019.7.3",
-    "eslint-plugin-import": "^2.23.4",
+    "@typescript-eslint/eslint-plugin": "^8.5.0",
-    "eslint-plugin-json": "^3.0.0",
+    "@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": "^5.1.0",
+    "eslint-plugin-promise": "^7.1.0",
-    "node-fetch": "^2.6.1",
+    "node-fetch": "^3.3.2",
-    "rimraf": "^3.0.2",
+    "rimraf": "^6.0.1",
     "seedrandom": "^3.0.5",
-    "simple-git": "^2.41.2",
+    "tslib": "^2.8.1",
-    "tslib": "^2.3.0",
+    "typedoc": "^0.27.6",
-    "typedoc": "^0.21.4",
+    "typescript": "5.7.3"
-    "typescript": "4.3.5"
   }
 }

server/build.js

@@ -1,260 +0,0 @@
-/* eslint-disable import/no-extraneous-dependencies */
-/* eslint-disable node/no-unpublished-require */
-
-const esbuild = require('esbuild');
-const ts = require('typescript');
-const log = require('@vladmandic/pilogger');
-const TypeDoc = require('typedoc');
-const { ESLint } = require('eslint');
-const tfjs = require('@tensorflow/tfjs/package.json');
-const changelog = require('./changelog');
-
-const banner = { js: `
-  /*
-  Face-API
-  homepage: <https://github.com/vladmandic/face-api>
-  author: <https://github.com/vladmandic>'
-  */
-` };
-
-let td = null;
-let eslint = null;
-
-// 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 lintLocations = ['server/', 'demo/', 'src/', 'test/'];
-
-// common configuration
-const common = {
-  banner,
-  minifyWhitespace: false,
-  minifyIdentifiers: false,
-  minifySyntax: false,
-  bundle: true,
-  sourcemap: true,
-  metafile: true,
-  logLevel: 'error',
-  target: 'es2018',
-  // tsconfig: './tsconfig.json',
-};
-
-const targets = {
-  node: {
-    tfjs: {
-      platform: 'node',
-      format: 'cjs',
-      entryPoints: ['src/tfjs/tf-node.ts'],
-      outfile: 'dist/tfjs.esm.js',
-      external: ['@tensorflow'],
-    },
-    node: {
-      platform: 'node',
-      format: 'cjs',
-      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',
-      external: ['@tensorflow'],
-    },
-    node: {
-      platform: 'node',
-      format: 'cjs',
-      entryPoints: ['src/index.ts'],
-      outfile: 'dist/face-api.node-gpu.js',
-      external: ['@tensorflow'],
-    },
-  },
-  nodeCPU: {
-    tfjs: {
-      platform: 'node',
-      format: 'cjs',
-      entryPoints: ['src/tfjs/tf-node-cpu.ts'],
-      outfile: 'dist/tfjs.esm.js',
-      external: ['@tensorflow'],
-    },
-    node: {
-      platform: 'node',
-      format: 'cjs',
-      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',
-      external: ['fs', 'buffer', 'util', 'os', '@tensorflow'],
-    },
-    esm: {
-      platform: 'browser',
-      format: 'esm',
-      entryPoints: ['src/index.ts'],
-      outfile: 'dist/face-api.esm-nobundle.js',
-      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',
-      external: ['fs', 'buffer', 'util', 'os'],
-    },
-    iife: {
-      platform: 'browser',
-      format: 'iife',
-      globalName: 'faceapi',
-      entryPoints: ['src/index.ts'],
-      outfile: 'dist/face-api.js',
-      external: ['fs', 'buffer', 'util', 'os'],
-    },
-    esm: {
-      platform: 'browser',
-      format: 'esm',
-      entryPoints: ['src/index.ts'],
-      outfile: 'dist/face-api.esm.js',
-      external: ['fs', 'buffer', 'util', 'os'],
-    },
-  },
-};
-
-async function getStats(json) {
-  const stats = {};
-  if (json && json.metafile.inputs && json.metafile.outputs) {
-    for (const [key, val] of Object.entries(json.metafile.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.metafile.outputs)) {
-      if (!key.endsWith('.map')) {
-        files.push(key);
-        stats.outputBytes = (stats.outputBytes || 0) + val.bytes;
-      }
-    }
-    stats.outputFiles = files.join(', ');
-  }
-  return stats;
-}
-
-function typings(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);
-    }
-  }
-}
-
-async function lint() {
-  log.info('Running Linter:', lintLocations);
-  if (!eslint) {
-    eslint = new ESLint();
-  }
-  const results = await eslint.lintFiles(lintLocations);
-  const errors = results.reduce((prev, curr) => prev += curr.errorCount, 0);
-  const warnings = results.reduce((prev, curr) => prev += curr.warningCount, 0);
-  log.info('Linter complete: files:', results.length, 'errors:', errors, 'warnings:', warnings);
-  if (errors > 0 || warnings > 0) {
-    const formatter = await eslint.loadFormatter('stylish');
-    const text = formatter.format(results);
-    log.warn(text);
-  }
-}
-
-async function typedoc(entryPoint) {
-  log.info('Generate TypeDocs:', entryPoint);
-  if (!td) {
-    td = new TypeDoc.Application();
-    td.options.addReader(new TypeDoc.TSConfigReader());
-    td.bootstrap({ entryPoints: entryPoint });
-  }
-  const project = td.convert();
-  const result = project ? await td.generateDocs(project, 'typedoc') : null;
-  if (result) log.warn('TypeDoc:', result);
-}
-
-// rebuild on file change
-async function build(f, msg, dev = false) {
-  log.info('Build: file', msg, f, 'target:', common.target);
-  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;
-        // @ts-ignore
-        const meta = await esbuild.build({ ...common, ...targetOptions });
-        const stats = await getStats(meta);
-        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);
-  }
-
-  if (!dev) { // only for prod builds, skipped for dev build
-    await lint(); // run linter
-    await typings(targets.browserBundle.esm.entryPoints, tsconfig); // generate typings
-    await changelog.update('../CHANGELOG.md'); // generate changelog
-    await typedoc(targets.browserBundle.esm.entryPoints); // generate typedoc
-  }
-
-  if (require.main === module) process.exit(0);
-}
-
-if (require.main === module) {
-  log.header();
-  log.info(`Toolchain: tfjs: ${tfjs.version} esbuild ${esbuild.version}; typescript ${ts.version}; typedoc: ${TypeDoc.Application.VERSION} eslint: ${ESLint.version}`);
-  build('all', 'startup');
-} else {
-  exports.build = build;
-}

server/changelog.js

@@ -1,58 +0,0 @@
-const fs = require('fs');
-const path = require('path');
-// eslint-disable-next-line node/no-unpublished-require, import/no-extraneous-dependencies
-const dayjs = require('dayjs');
-// eslint-disable-next-line node/no-unpublished-require, import/no-extraneous-dependencies
-const simpleGit = require('simple-git/promise');
-// eslint-disable-next-line node/no-unpublished-require, import/no-extraneous-dependencies
-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.info('Update Change log:', [name]);
-}
-
-if (require.main === module) {
-  update('../CHANGELOG.md');
-} else {
-  exports.update = update;
-}

server/https.crt

@@ -1,31 +0,0 @@
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server/https.key

@@ -1,52 +0,0 @@
------BEGIN PRIVATE KEY-----
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-qIRta3H9KNw2Mhpkm77TtUSV/W5aOmY=
------END PRIVATE KEY-----

server/serve.js

@@ -1,162 +0,0 @@
-/*
-  micro http2 server with file monitoring and automatic app rebuild
-  - can process concurrent http requests
-  - monitors specified filed and folders for changes
-  - triggers library and application rebuild
-  - any build errors are immediately displayed and can be corrected without need for restart
-  - passthrough data compression
-*/
-
-const fs = require('fs');
-const zlib = require('zlib');
-const http = require('http');
-const http2 = require('http2');
-const path = require('path');
-// eslint-disable-next-line node/no-unpublished-require, import/no-extraneous-dependencies
-const chokidar = require('chokidar');
-// eslint-disable-next-line node/no-unpublished-require, import/no-extraneous-dependencies
-const log = require('@vladmandic/pilogger');
-const build = require('./build.js');
-
-// app configuration
-// you can provide your server key and certificate or use provided self-signed ones
-// self-signed certificate generated using:
-// openssl req -x509 -newkey rsa:4096 -nodes -keyout https.key -out https.crt -days 365 -subj "/C=US/ST=Florida/L=Miami/O=@vladmandic"
-// client app does not work without secure server since browsers enforce https for webcam access
-const options = {
-  key: fs.readFileSync('server/https.key'),
-  cert: fs.readFileSync('server/https.crt'),
-  root: '..',
-  default: 'demo/index.html',
-  httpPort: 8000,
-  httpsPort: 8001,
-  insecureHTTPParser: false,
-  minElapsed: 2,
-  monitor: ['package.json', 'demo', 'src'],
-};
-
-// just some predefined mime types
-const mime = {
-  '.html': 'text/html; charset=utf-8',
-  '.js': 'text/javascript; charset=utf-8',
-  '.css': 'text/css; charset=utf-8',
-  '.json': 'application/json; charset=utf-8',
-  '.png': 'image/png',
-  '.jpg': 'image/jpeg',
-  '.gif': 'image/gif',
-  '.ico': 'image/x-icon',
-  '.svg': 'image/svg+xml',
-  '.wav': 'audio/wav',
-  '.mp4': 'video/mp4',
-  '.woff': 'font/woff',
-  '.woff2': 'font/woff2',
-  '.ttf': 'font/ttf',
-  '.wasm': 'application/wasm',
-};
-
-// checks for multiple events triggering within minElapsed and merge get into single event
-let last = Date.now();
-async function buildAll(evt, msg) {
-  const now = Date.now();
-  if ((now - last) > options.minElapsed) build.build(evt, msg, true);
-  else log.state('Build: merge event file', msg, evt);
-  last = now;
-}
-
-// watch filesystem for any changes and notify build when needed
-async function watch() {
-  const watcher = chokidar.watch(options.monitor, {
-    persistent: true,
-    ignorePermissionErrors: false,
-    alwaysStat: false,
-    ignoreInitial: true,
-    followSymlinks: true,
-    usePolling: false,
-    useFsEvents: false,
-    atomic: true,
-  });
-  // single event handler for file add/change/delete
-  watcher
-    .on('add', (evt) => buildAll(evt, 'add'))
-    .on('change', (evt) => buildAll(evt, 'modify'))
-    .on('unlink', (evt) => buildAll(evt, 'remove'))
-    .on('error', (err) => log.error(`Client watcher error: ${err}`))
-    .on('ready', () => log.state('Monitoring:', options.monitor));
-}
-
-// get file content for a valid url request
-function handle(url) {
-  return new Promise((resolve) => {
-    let obj = { ok: false };
-    obj.file = url;
-    if (!fs.existsSync(obj.file)) resolve(null);
-    obj.stat = fs.statSync(obj.file);
-    if (obj.stat.isFile()) obj.ok = true;
-    if (!obj.ok && obj.stat.isDirectory()) {
-      obj.file = path.join(obj.file, options.default);
-      // @ts-ignore
-      obj = handle(obj.file);
-    }
-    resolve(obj);
-  });
-}
-
-// process http requests
-async function httpRequest(req, res) {
-  handle(path.join(__dirname, options.root, decodeURI(req.url)))
-    .then((result) => {
-      // get original ip of requestor, regardless if it's behind proxy or not
-      // eslint-disable-next-line dot-notation
-      const forwarded = (req.headers['forwarded'] || '').match(/for="\[(.*)\]:/);
-      const ip = (Array.isArray(forwarded) ? forwarded[1] : null) || req.headers['x-forwarded-for'] || req.ip || req.socket.remoteAddress;
-      if (!result || !result.ok) {
-        res.writeHead(404, { 'Content-Type': 'text/html' });
-        res.end('Error 404: Not Found\n', 'utf-8');
-        log.warn(`${req.method}/${req.httpVersion}`, res.statusCode, req.url, ip);
-      } else {
-        const ext = String(path.extname(result.file)).toLowerCase();
-        const contentType = mime[ext] || 'application/octet-stream';
-        const accept = req.headers['accept-encoding'] ? req.headers['accept-encoding'].includes('br') : false; // does target accept brotli compressed data
-        res.writeHead(200, {
-          // 'Content-Length': result.stat.size, // not using as it's misleading for compressed streams
-          'Content-Language': 'en', 'Content-Type': contentType, 'Content-Encoding': accept ? 'br' : '', 'Last-Modified': result.stat.mtime, 'Cache-Control': 'no-cache', 'X-Content-Type-Options': 'nosniff',
-        });
-        const compress = zlib.createBrotliCompress({ params: { [zlib.constants.BROTLI_PARAM_QUALITY]: 5 } }); // instance of brotli compression with level 5
-        const stream = fs.createReadStream(result.file);
-        if (!accept) stream.pipe(res); // don't compress data
-        else stream.pipe(compress).pipe(res); // compress data
-
-        // alternative methods of sending data
-        /// 2. read stream and send by chunk
-        // const stream = fs.createReadStream(result.file);
-        // stream.on('data', (chunk) => res.write(chunk));
-        // stream.on('end', () => res.end());
-
-        // 3. read entire file and send it as blob
-        // const data = fs.readFileSync(result.file);
-        // res.write(data);
-        log.data(`${req.method}/${req.httpVersion}`, res.statusCode, contentType, result.stat.size, req.url, ip);
-      }
-      return null;
-    })
-    .catch((err) => log.error('handle error:', err));
-}
-
-// app main entry point
-async function main() {
-  log.header();
-  await watch();
-  if (options.httpPort && options.httpPort > 0) {
-    const server1 = http.createServer(options, httpRequest);
-    server1.on('listening', () => log.state('HTTP server listening:', options.httpPort));
-    server1.listen(options.httpPort);
-  }
-  if (options.httpsPort && options.httpsPort > 0) {
-    const server2 = http2.createSecureServer(options, httpRequest);
-    server2.on('listening', () => log.state('HTTP2 server listening:', options.httpsPort));
-    server2.listen(options.httpsPort);
-  }
-  await build.build('all', 'startup', true);
-}
-
-main();

src/NeuralNetwork.ts

@@ -10,9 +10,9 @@ export abstract class NeuralNetwork<TNetParams> {
     this._name = name;
   }
 
-  protected _params: TNetParams | undefined = undefined
+  protected _params: TNetParams | undefined = undefined;
 
-  protected _paramMappings: ParamMapping[] = []
+  protected _paramMappings: ParamMapping[] = [];
 
   public _name: any;
 
@@ -102,8 +102,9 @@ export abstract class NeuralNetwork<TNetParams> {
     }
     const { readFile } = env.getEnv();
     const { manifestUri, modelBaseUri } = getModelUris(filePath, this.getDefaultModelName());
-    const fetchWeightsFromDisk = (filePaths: string[]) => Promise.all(filePaths.map((fp) => readFile(fp).then((buf) => buf.buffer)));
+    const fetchWeightsFromDisk = (filePaths: string[]) => Promise.all(filePaths.map((fp) => readFile(fp).then((buf) => (typeof buf === 'string' ? Buffer.from(buf) : buf.buffer))));
-    const loadWeights = tf.io.weightsLoaderFactory(fetchWeightsFromDisk);
+    // @ts-ignore async-vs-sync mismatch
+    const loadWeights = tf['io'].weightsLoaderFactory(fetchWeightsFromDisk);
     const manifest = JSON.parse((await readFile(manifestUri)).toString());
     const weightMap = await loadWeights(manifest, modelBaseUri);
     this.loadFromWeightMap(weightMap);

src/Platform.ts

@@ -1,6 +1,10 @@
 export class PlatformBrowser {
   private textEncoder: TextEncoder;
 
+  constructor() {
+    this.textEncoder = new TextEncoder();
+  }
+
   fetch(path: string, init?: any): Promise<Response> {
     return fetch(path, init);
   }
@@ -13,9 +17,6 @@ export class PlatformBrowser {
     if (encoding !== 'utf-8' && encoding !== 'utf8') {
       throw new Error(`Browser's encoder only supports utf-8, but got ${encoding}`);
     }
-    if (this.textEncoder == null) {
-      this.textEncoder = new TextEncoder();
-    }
     return this.textEncoder.encode(text);
   }
 

src/ageGenderNet/AgeGenderNet.ts

@@ -1,5 +1,4 @@
-import * as tf from '../../dist/tfjs.esm';
+import * as tf from '../../dist/tfjs.esm.js';
-
 import { fullyConnectedLayer } from '../common/fullyConnectedLayer';
 import { seperateWeightMaps } from '../faceProcessor/util';
 import { TinyXception } from '../xception/TinyXception';
@@ -10,7 +9,7 @@ import { NeuralNetwork } from '../NeuralNetwork';
 import { NetInput, TNetInput, toNetInput } from '../dom/index';
 
 export class AgeGenderNet extends NeuralNetwork<NetParams> {
-  private _faceFeatureExtractor: TinyXception
+  private _faceFeatureExtractor: TinyXception;
 
   constructor(faceFeatureExtractor: TinyXception = new TinyXception(2)) {
     super('AgeGenderNet');
@@ -85,7 +84,7 @@ export class AgeGenderNet extends NeuralNetwork<NetParams> {
     return 'age_gender_model';
   }
 
-  public dispose(throwOnRedispose = true) {
+  public override dispose(throwOnRedispose = true) {
     this.faceFeatureExtractor.dispose(throwOnRedispose);
     super.dispose(throwOnRedispose);
   }

src/classes/BoundingBox.ts

@@ -7,10 +7,8 @@ export interface IBoundingBox {
   bottom: number
 }
 
-export class BoundingBox extends Box<BoundingBox> implements IBoundingBox {
+export class BoundingBox extends Box implements IBoundingBox {
   constructor(left: number, top: number, right: number, bottom: number, allowNegativeDimensions = false) {
-    super({
+    super({ left, top, right, bottom }, allowNegativeDimensions);
-      left, top, right, bottom,
-    }, allowNegativeDimensions);
   }
 }

src/classes/Box.ts

@@ -19,13 +19,13 @@ export class Box<BoxType = any> implements IBoundingBox, IRect {
     }
   }
 
-  private _x: number
+  private _x: number;
 
-  private _y: number
+  private _y: number;
 
-  private _width: number
+  private _width: number;
 
-  private _height: number
+  private _height: number;
 
   constructor(_box: IBoundingBox | IRect, allowNegativeDimensions = true) {
     const box = (_box || {}) as any;
@@ -128,9 +128,7 @@ export class Box<BoxType = any> implements IBoundingBox, IRect {
       this.width + padX,
       this.height + padY,
     ];
-    return new Box({
+    return new Box({ x, y, width, height });
-      x, y, width, height,
-    });
   }
 
   public clipAtImageBorders(imgWidth: number, imgHeight: number): Box<BoxType> {
@@ -143,9 +141,7 @@ export class Box<BoxType = any> implements IBoundingBox, IRect {
     const clippedWidth = Math.min(newWidth, imgWidth - clippedX);
     const clippedHeight = Math.min(newHeight, imgHeight - clippedY);
 
-    return (new Box({
+    return (new Box({ x: clippedX, y: clippedY, width: clippedWidth, height: clippedHeight })).floor();
-      x: clippedX, y: clippedY, width: clippedWidth, height: clippedHeight,
-    })).floor();
   }
 
   public shift(sx: number, sy: number): Box<BoxType> {
@@ -153,9 +149,7 @@ export class Box<BoxType = any> implements IBoundingBox, IRect {
     const x = this.x + sx;
     const y = this.y + sy;
 
-    return new Box({
+    return new Box({ x, y, width, height });
-      x, y, width, height,
-    });
   }
 
   public padAtBorders(imageHeight: number, imageWidth: number) {
@@ -189,9 +183,7 @@ export class Box<BoxType = any> implements IBoundingBox, IRect {
       y = 1;
     }
 
-    return {
+    return { dy, edy, dx, edx, y, ey, x, ex, w, h };
-      dy, edy, dx, edx, y, ey, x, ex, w, h,
-    };
   }
 
   public calibrate(region: Box) {

src/classes/Dimensions.ts

@@ -6,9 +6,9 @@ export interface IDimensions {
 }
 
 export class Dimensions implements IDimensions {
-  private _width: number
+  private _width: number;
 
-  private _height: number
+  private _height: number;
 
   constructor(width: number, height: number) {
     if (!isValidNumber(width) || !isValidNumber(height)) {

src/classes/FaceDetection.ts

@@ -17,7 +17,7 @@ export class FaceDetection extends ObjectDetection implements IFaceDetecion {
     super(score, score, '', relativeBox, imageDims);
   }
 
-  public forSize(width: number, height: number): FaceDetection {
+  public override forSize(width: number, height: number): FaceDetection {
     const { score, relativeBox, imageDims } = super.forSize(width, height);
     return new FaceDetection(score, relativeBox, imageDims);
   }

src/classes/FaceLandmarks.ts

@@ -18,11 +18,11 @@ export interface IFaceLandmarks {
 }
 
 export class FaceLandmarks implements IFaceLandmarks {
-  protected _shift: Point
+  protected _shift: Point;
 
-  protected _positions: Point[]
+  protected _positions: Point[];
 
-  protected _imgDims: Dimensions
+  protected _imgDims: Dimensions;
 
   constructor(
     relativeFaceLandmarkPositions: Point[],

src/classes/FaceLandmarks5.ts

@@ -3,7 +3,7 @@ import { FaceLandmarks } from './FaceLandmarks';
 import { Point } from './Point';
 
 export class FaceLandmarks5 extends FaceLandmarks {
-  protected getRefPointsForAlignment(): Point[] {
+  protected override getRefPointsForAlignment(): Point[] {
     const pts = this.positions;
     return [
       pts[0],

src/classes/FaceLandmarks68.ts

@@ -31,7 +31,7 @@ export class FaceLandmarks68 extends FaceLandmarks {
     return this.positions.slice(48, 68);
   }
 
-  protected getRefPointsForAlignment(): Point[] {
+  protected override getRefPointsForAlignment(): Point[] {
     return [
       this.getLeftEye(),
       this.getRightEye(),

src/classes/FaceMatch.ts

@@ -6,9 +6,8 @@ export interface IFaceMatch {
 }
 
 export class FaceMatch implements IFaceMatch {
-  private _label: string
+  private _label: string;
-
+  private _distance: number;
-  private _distance: number
 
   constructor(label: string, distance: number) {
     this._label = label;

src/classes/LabeledBox.ts

@@ -3,16 +3,15 @@ import { IBoundingBox } from './BoundingBox';
 import { Box } from './Box';
 import { IRect } from './Rect';
 
-export class LabeledBox extends Box<LabeledBox> {
+export class LabeledBox extends Box {
   public static assertIsValidLabeledBox(box: any, callee: string) {
     Box.assertIsValidBox(box, callee);
-
     if (!isValidNumber(box.label)) {
       throw new Error(`${callee} - expected property label (${box.label}) to be a number`);
     }
   }
 
-  private _label: number
+  private _label: number;
 
   constructor(box: IBoundingBox | IRect | any, label: number) {
     super(box);

src/classes/LabeledFaceDescriptors.ts

@@ -1,7 +1,7 @@
 export class LabeledFaceDescriptors {
-  private _label: string
+  private _label: string;
 
-  private _descriptors: Float32Array[]
+  private _descriptors: Float32Array[];
 
   constructor(label: string, descriptors: Float32Array[]) {
     if (!(typeof label === 'string')) {

src/classes/ObjectDetection.ts

@@ -3,15 +3,15 @@ import { Dimensions, IDimensions } from './Dimensions';
 import { IRect, Rect } from './Rect';
 
 export class ObjectDetection {
-  private _score: number
+  private _score: number;
 
-  private _classScore: number
+  private _classScore: number;
 
-  private _className: string
+  private _className: string;
 
-  private _box: Rect
+  private _box: Rect;
 
-  private _imageDims: Dimensions
+  private _imageDims: Dimensions;
 
   constructor(
     score: number,

src/classes/Point.ts

@@ -4,9 +4,9 @@ export interface IPoint {
 }
 
 export class Point implements IPoint {
-  private _x: number
+  private _x: number;
 
-  private _y: number
+  private _y: number;
 
   constructor(x: number, y: number) {
     this._x = x;

src/classes/PredictedBox.ts

@@ -15,9 +15,9 @@ export class PredictedBox extends LabeledBox {
     }
   }
 
-  private _score: number
+  private _score: number;
 
-  private _classScore: number
+  private _classScore: number;
 
   constructor(box: IBoundingBox | IRect | any, label: number, score: number, classScore: number) {
     super(box, label);

src/classes/Rect.ts

@@ -7,10 +7,8 @@ export interface IRect {
   height: number
 }
 
-export class Rect extends Box<Rect> implements IRect {
+export class Rect extends Box implements IRect {
   constructor(x: number, y: number, width: number, height: number, allowNegativeDimensions = false) {
-    super({
+    super({ x, y, width, height }, allowNegativeDimensions);
-      x, y, width, height,
-    }, allowNegativeDimensions);
   }
 }

src/dom/NetInput.ts

@@ -9,17 +9,17 @@ import { imageToSquare } from './imageToSquare';
 import { TResolvedNetInput } from './types';
 
 export class NetInput {
-  private _imageTensors: Array<tf.Tensor3D | tf.Tensor4D> = []
+  private _imageTensors: Array<tf.Tensor3D | tf.Tensor4D> = [];
 
-  private _canvases: HTMLCanvasElement[] = []
+  private _canvases: HTMLCanvasElement[] = [];
 
-  private _batchSize: number
+  private _batchSize: number;
 
-  private _treatAsBatchInput = false
+  private _treatAsBatchInput = false;
 
-  private _inputDimensions: number[][] = []
+  private _inputDimensions: number[][] = [];
 
-  private _inputSize: number
+  private _inputSize = 0;
 
   constructor(inputs: Array<TResolvedNetInput>, treatAsBatchInput = false) {
     if (!Array.isArray(inputs)) {
@@ -47,8 +47,9 @@ export class NetInput {
         return;
       }
 
+      // @ts-ignore
       const canvas = (input as any) instanceof env.getEnv().Canvas ? input : createCanvasFromMedia(input);
-      this._canvases[idx] = canvas;
+      this._canvases[idx] = canvas as HTMLCanvasElement;
       this._inputDimensions[idx] = [canvas.height, canvas.width, 3];
     });
   }
@@ -127,23 +128,24 @@ export class NetInput {
 
         if (input instanceof tf.Tensor) {
           let imgTensor = isTensor4D(input) ? input : tf.expandDims(input);
-          imgTensor = padToSquare(imgTensor, isCenterInputs);
+          imgTensor = padToSquare(imgTensor as tf.Tensor4D, isCenterInputs);
 
           if (imgTensor.shape[1] !== inputSize || imgTensor.shape[2] !== inputSize) {
-            imgTensor = tf.image.resizeBilinear(imgTensor, [inputSize, inputSize], false, false);
+            imgTensor = tf['image'].resizeBilinear(imgTensor as tf.Tensor4D, [inputSize, inputSize], false, false);
           }
 
           return imgTensor.as3D(inputSize, inputSize, 3);
         }
 
         if (input instanceof env.getEnv().Canvas) {
-          return tf.browser.fromPixels(imageToSquare(input, inputSize, isCenterInputs));
+          return tf['browser'].fromPixels(imageToSquare(input, inputSize, isCenterInputs));
         }
 
         throw new Error(`toBatchTensor - at batchIdx ${batchIdx}, expected input to be instanceof tf.Tensor or instanceof HTMLCanvasElement, instead have ${input}`);
       });
 
       const batchTensor = tf.stack(inputTensors.map((t) => tf.cast(t, 'float32'))).as4D(this.batchSize, inputSize, inputSize, 3);
+      // const batchTensor = tf.stack(inputTensors.map((t) => tf.cast(t, 'float32'))) as tf.Tensor4D;
 
       return batchTensor;
     });

src/dom/awaitMediaLoaded.ts

@@ -4,7 +4,10 @@ import { isMediaLoaded } from './isMediaLoaded';
 export function awaitMediaLoaded(media: HTMLImageElement | HTMLVideoElement | HTMLCanvasElement) {
   // eslint-disable-next-line consistent-return
   return new Promise((resolve, reject) => {
-    if (media instanceof env.getEnv().Canvas || isMediaLoaded(media)) return resolve(null);
+    if (media instanceof env.getEnv().Canvas || isMediaLoaded(media)) {
+      resolve(null);
+      return;
+    }
 
     function onError(e: Event) {
       if (!e.currentTarget) return;

src/dom/extractFaceTensors.ts

@@ -25,17 +25,11 @@ export async function extractFaceTensors(imageTensor: tf.Tensor3D | tf.Tensor4D,
 
   return tf.tidy(() => {
     const [imgHeight, imgWidth, numChannels] = imageTensor.shape.slice(isTensor4D(imageTensor) ? 1 : 0);
-
+    const boxes = detections.map((det) => (det instanceof FaceDetection ? det.forSize(imgWidth, imgHeight).box : det))
-    const boxes = detections
-      .map((det) => (det instanceof FaceDetection
-        ? det.forSize(imgWidth, imgHeight).box
-        : det))
       .map((box) => box.clipAtImageBorders(imgWidth, imgHeight));
-
+    const faceTensors = boxes
-    const faceTensors = boxes.map(({
+      .filter((box) => box.width > 0 && box.height > 0)
-      x, y, width, height,
+      .map(({ x, y, width, height }) => tf.slice3d(imageTensor.as3D(imgHeight, imgWidth, numChannels), [y, x, 0], [height, width, numChannels]));
-    }) => tf.slice3d(imageTensor.as3D(imgHeight, imgWidth, numChannels), [y, x, 0], [height, width, numChannels]));
-
     return faceTensors;
   });
 }

src/dom/getContext2dOrThrow.ts

@@ -3,21 +3,10 @@ import { resolveInput } from './resolveInput';
 
 export function getContext2dOrThrow(canvasArg: string | HTMLCanvasElement | CanvasRenderingContext2D): CanvasRenderingContext2D {
   const { Canvas, CanvasRenderingContext2D } = env.getEnv();
-
+  if (canvasArg instanceof CanvasRenderingContext2D) return canvasArg;
-  if (canvasArg instanceof CanvasRenderingContext2D) {
-    return canvasArg;
-  }
-
   const canvas = resolveInput(canvasArg);
-
+  if (!(canvas instanceof Canvas)) throw new Error('resolveContext2d - expected canvas to be of instance of Canvas');
-  if (!(canvas instanceof Canvas)) {
+  const ctx = canvas.getContext('2d', { willReadFrequently: true });
-    throw new Error('resolveContext2d - expected canvas to be of instance of Canvas');
+  if (!ctx) throw new Error('resolveContext2d - canvas 2d context is null');
-  }
-
-  const ctx = canvas.getContext('2d');
-  if (!ctx) {
-    throw new Error('resolveContext2d - canvas 2d context is null');
-  }
-
   return ctx;
 }

src/dom/imageTensorToCanvas.ts

@@ -11,7 +11,7 @@ export async function imageTensorToCanvas(
 
   const [height, width, numChannels] = imgTensor.shape.slice(isTensor4D(imgTensor) ? 1 : 0);
   const imgTensor3D = tf.tidy(() => imgTensor.as3D(height, width, numChannels).toInt());
-  await tf.browser.toPixels(imgTensor3D, targetCanvas);
+  await tf['browser'].toPixels(imgTensor3D, targetCanvas);
 
   imgTensor3D.dispose();
 

src/dom/loadWeightMap.ts

@@ -8,7 +8,8 @@ export async function loadWeightMap(
   defaultModelName: string,
 ): Promise<tf.NamedTensorMap> {
   const { manifestUri, modelBaseUri } = getModelUris(uri, defaultModelName);
+  // @ts-ignore
   const manifest = await fetchJson<tf.io.WeightsManifestConfig>(manifestUri);
   // if (manifest['weightsManifest']) manifest = manifest['weightsManifest'];
-  return tf.io.loadWeights(manifest, modelBaseUri);
+  return tf['io'].loadWeights(manifest, modelBaseUri);
 }

src/dom/types.ts

@@ -1,11 +1,9 @@
-import * as tf from '../../dist/tfjs.esm';
+import type { Tensor3D, Tensor4D } from '../../dist/tfjs.esm';
 
 import { NetInput } from './NetInput';
 
 export type TMediaElement = HTMLImageElement | HTMLVideoElement | HTMLCanvasElement
 
-export type TResolvedNetInput = TMediaElement | tf.Tensor3D | tf.Tensor4D
+export type TResolvedNetInput = TMediaElement | Tensor3D | Tensor4D
 
-export type TNetInputArg = string | TResolvedNetInput
+export type TNetInput = string | TResolvedNetInput | Array<string | TResolvedNetInput> | NetInput
-
-export type TNetInput = TNetInputArg | Array<TNetInputArg> | NetInput | tf.Tensor4D

src/draw/DrawBox.ts

@@ -11,13 +11,13 @@ export interface IDrawBoxOptions {
 }
 
 export class DrawBoxOptions {
-  public boxColor: string
+  public boxColor: string;
 
-  public lineWidth: number
+  public lineWidth: number;
 
-  public drawLabelOptions: DrawTextFieldOptions
+  public drawLabelOptions: DrawTextFieldOptions;
 
-  public label?: string
+  public label?: string;
 
   constructor(options: IDrawBoxOptions = {}) {
     const {
@@ -36,9 +36,9 @@ export class DrawBoxOptions {
 }
 
 export class DrawBox {
-  public box: Box
+  public box: Box;
 
-  public options: DrawBoxOptions
+  public options: DrawBoxOptions;
 
   constructor(
     box: IBoundingBox | IRect,

src/draw/DrawFaceLandmarks.ts

@@ -17,17 +17,17 @@ export interface IDrawFaceLandmarksOptions {
 }
 
 export class DrawFaceLandmarksOptions {
-  public drawLines: boolean
+  public drawLines: boolean;
 
-  public drawPoints: boolean
+  public drawPoints: boolean;
 
-  public lineWidth: number
+  public lineWidth: number;
 
-  public pointSize: number
+  public pointSize: number;
 
-  public lineColor: string
+  public lineColor: string;
 
-  public pointColor: string
+  public pointColor: string;
 
   constructor(options: IDrawFaceLandmarksOptions = {}) {
     const {
@@ -43,9 +43,9 @@ export class DrawFaceLandmarksOptions {
 }
 
 export class DrawFaceLandmarks {
-  public faceLandmarks: FaceLandmarks
+  public faceLandmarks: FaceLandmarks;
 
-  public options: DrawFaceLandmarksOptions
+  public options: DrawFaceLandmarksOptions;
 
   constructor(
     faceLandmarks: FaceLandmarks,

src/draw/DrawTextField.ts

@@ -25,17 +25,17 @@ export interface IDrawTextFieldOptions {
 }
 
 export class DrawTextFieldOptions implements IDrawTextFieldOptions {
-  public anchorPosition: AnchorPosition
+  public anchorPosition: AnchorPosition;
 
-  public backgroundColor: string
+  public backgroundColor: string;
 
-  public fontColor: string
+  public fontColor: string;
 
-  public fontSize: number
+  public fontSize: number;
 
-  public fontStyle: string
+  public fontStyle: string;
 
-  public padding: number
+  public padding: number;
 
   constructor(options: IDrawTextFieldOptions = {}) {
     const {
@@ -51,11 +51,11 @@ export class DrawTextFieldOptions implements IDrawTextFieldOptions {
 }
 
 export class DrawTextField {
-  public text: string[]
+  public text: string[];
 
-  public anchor : IPoint
+  public anchor : IPoint;
 
-  public options: DrawTextFieldOptions
+  public options: DrawTextFieldOptions;
 
   constructor(
     text: string | string[] | DrawTextField,

src/draw/drawFaceExpressions.ts

@@ -7,12 +7,7 @@ import { DrawTextField } from './DrawTextField';
 
 export type DrawFaceExpressionsInput = FaceExpressions | WithFaceExpressions<{}>
 
-export function drawFaceExpressions(
+export function drawFaceExpressions(canvasArg: string | HTMLCanvasElement, faceExpressions: DrawFaceExpressionsInput | Array<DrawFaceExpressionsInput>, minConfidence = 0.1, textFieldAnchor?: IPoint) {
-  canvasArg: string | HTMLCanvasElement,
-  faceExpressions: DrawFaceExpressionsInput | Array<DrawFaceExpressionsInput>,
-  minConfidence = 0.1,
-  textFieldAnchor?: IPoint,
-) {
   const faceExpressionsArray = Array.isArray(faceExpressions) ? faceExpressions : [faceExpressions];
 
   faceExpressionsArray.forEach((e) => {

src/env/createFileSystem.ts

@@ -1,26 +1,20 @@
 import { FileSystem } from './types';
+import { isNodejs } from './isNodejs';
 
 export function createFileSystem(fs?: any): FileSystem {
   let requireFsError = '';
-
+  if (!fs && isNodejs()) {
-  if (!fs) {
     try {
-      // eslint-disable-next-line global-require
+      // eslint-disable-next-line global-require, @typescript-eslint/no-require-imports
       fs = require('fs');
     } catch (err) {
-      requireFsError = err.toString();
+      requireFsError = (err as any).toString();
     }
   }
 
   const readFile = fs
-    ? (filePath: string) => new Promise<Buffer>((resolve, reject) => {
+    // eslint-disable-next-line no-undef
-      fs.readFile(filePath, (err: any, buffer: Buffer) => (err ? reject(err) : resolve(buffer)));
+    ? (filePath: string) => new Promise<string | Buffer>((resolve, reject) => { fs.readFile(filePath, (err: NodeJS.ErrnoException | null, buffer: string | Buffer) => (err ? reject(err) : resolve(buffer))); })
-    })
+    : () => { throw new Error(`readFile - failed to require fs in nodejs environment with error: ${requireFsError}`); };
-    : () => {
+  return { readFile };
-      throw new Error(`readFile - failed to require fs in nodejs environment with error: ${requireFsError}`);
-    };
-
-  return {
-    readFile,
-  };
 }

src/env/createNodejsEnv.ts

@@ -3,11 +3,9 @@ import { createFileSystem } from './createFileSystem';
 import { Environment } from './types';
 
 export function createNodejsEnv(): Environment {
-  // eslint-disable-next-line dot-notation
+  const Canvas: (new () => HTMLCanvasElement) = (global as any)['Canvas'] || global.HTMLCanvasElement;
-  const Canvas = global['Canvas'] || global.HTMLCanvasElement;
   const Image = global.Image || global.HTMLImageElement;
-  // eslint-disable-next-line dot-notation
+  const Video: (new () => HTMLVideoElement) = (global as any)['Video'] || global.HTMLVideoElement;
-  const Video = global['Video'] || global.HTMLVideoElement;
 
   const createCanvasElement = () => {
     if (Canvas) return new Canvas();

src/env/isNodejs.ts

@@ -1,6 +1,6 @@
 export function isNodejs(): boolean {
   return typeof global === 'object'
-    && typeof require === 'function'
+    && typeof process !== 'undefined'
-    && typeof module !== 'undefined'
+    && process.versions != null
-    && typeof process !== 'undefined' && !!process.version;
+    && process.versions.node != null;
 }

src/env/types.ts

@@ -1,17 +1,17 @@
 export type FileSystem = {
   // eslint-disable-next-line no-unused-vars
-  readFile: (filePath: string) => Promise<Buffer>
+  readFile: (filePath: string) => Promise<string | Buffer>;
-}
+};
 
 export type Environment = FileSystem & {
-  Canvas: typeof HTMLCanvasElement
+  Canvas: typeof HTMLCanvasElement;
-  CanvasRenderingContext2D: typeof CanvasRenderingContext2D
+  CanvasRenderingContext2D: typeof CanvasRenderingContext2D;
-  Image: typeof HTMLImageElement
+  Image: typeof HTMLImageElement;
-  ImageData: typeof ImageData
+  ImageData: typeof ImageData;
-  Video: typeof HTMLVideoElement
+  Video: typeof HTMLVideoElement;
-  createCanvasElement: () => HTMLCanvasElement
+  createCanvasElement: () => HTMLCanvasElement;
-  createImageElement: () => HTMLImageElement
+  createImageElement: () => HTMLImageElement;
-  createVideoElement: () => HTMLVideoElement
+  createVideoElement: () => HTMLVideoElement;
   // eslint-disable-next-line no-undef, no-unused-vars
-  fetch: (url: string, init?: RequestInit) => Promise<Response>
+  fetch: (url: string, init?: RequestInit) => Promise<Response>;
-}
+};

src/euclideanDistance.ts

@@ -1,12 +1,10 @@
 export function euclideanDistance(arr1: number[] | Float32Array, arr2: number[] | Float32Array) {
   if (arr1.length !== arr2.length) throw new Error('euclideanDistance: arr1.length !== arr2.length');
-
   const desc1 = Array.from(arr1);
   const desc2 = Array.from(arr2);
-
   return Math.sqrt(
     desc1
       .map((val, i) => val - desc2[i])
-      .reduce((res, diff) => res + (diff ** 2), 0),
+      .reduce((res, diff) => res + (diff * diff), 0),
   );
 }

src/faceExpressionNet/FaceExpressions.ts

@@ -1,19 +1,13 @@
-export const FACE_EXPRESSION_LABELS = ['neutral', 'happy', 'sad', 'angry', 'fearful', 'disgusted', 'surprised'];
+export const FACE_EXPRESSION_LABELS = ['neutral', 'happy', 'sad', 'angry', 'fearful', 'disgusted', 'surprised'] as const;
 
 export class FaceExpressions {
-  public neutral: number
+  public neutral = 0;
-
+  public happy = 0;
-  public happy: number
+  public sad = 0;
-
+  public angry = 0;
-  public sad: number
+  public fearful = 0;
-
+  public disgusted = 0;
-  public angry: number
+  public surprised = 0;
-
-  public fearful: number
-
-  public disgusted: number
-
-  public surprised: number
 
   constructor(probabilities: number[] | Float32Array) {
     if (probabilities.length !== 7) {

src/faceProcessor/FaceProcessor.ts

@@ -13,7 +13,7 @@ export abstract class FaceProcessor<
   TExtractorParams extends FaceFeatureExtractorParams | TinyFaceFeatureExtractorParams
 >
   extends NeuralNetwork<NetParams> {
-  protected _faceFeatureExtractor: IFaceFeatureExtractor<TExtractorParams>
+  protected _faceFeatureExtractor: IFaceFeatureExtractor<TExtractorParams>;
 
   constructor(_name: string, faceFeatureExtractor: IFaceFeatureExtractor<TExtractorParams>) {
     super(_name);
@@ -24,7 +24,7 @@ export abstract class FaceProcessor<
     return this._faceFeatureExtractor;
   }
 
-  protected abstract getDefaultModelName(): string
+  protected abstract override getDefaultModelName(): string
 
   protected abstract getClassifierChannelsIn(): number
 
@@ -45,7 +45,7 @@ export abstract class FaceProcessor<
     });
   }
 
-  public dispose(throwOnRedispose = true) {
+  public override dispose(throwOnRedispose = true) {
     this.faceFeatureExtractor.dispose(throwOnRedispose);
     super.dispose(throwOnRedispose);
   }

src/faceRecognitionNet/FaceRecognitionNet.ts

@@ -51,7 +51,7 @@ export class FaceRecognitionNet extends NeuralNetwork<NetParams> {
       const globalAvg = out.mean([1, 2]) as tf.Tensor2D;
       const fullyConnected = tf.matMul(globalAvg, params.fc);
 
-      return fullyConnected;
+      return fullyConnected as tf.Tensor2D;
     });
   }
 
@@ -60,6 +60,7 @@ export class FaceRecognitionNet extends NeuralNetwork<NetParams> {
   }
 
   public async computeFaceDescriptor(input: TNetInput): Promise<Float32Array|Float32Array[]> {
+    // @ts-ignore
     if (input?.shape?.some((dim) => dim <= 0)) return new Float32Array(128);
     const netInput = await toNetInput(input);
     const faceDescriptorTensors = tf.tidy(() => tf.unstack(this.forwardInput(netInput)));

src/factories/WithFaceLandmarks.ts

@@ -1,3 +1,4 @@
+import { Point } from '../classes';
 import { FaceDetection } from '../classes/FaceDetection';
 import { FaceLandmarks } from '../classes/FaceLandmarks';
 import { FaceLandmarks68 } from '../classes/FaceLandmarks68';
@@ -5,75 +6,106 @@ import { isWithFaceDetection, WithFaceDetection } from './WithFaceDetection';
 
 export type WithFaceLandmarks<
   TSource extends WithFaceDetection<{}>,
-  TFaceLandmarks extends FaceLandmarks = FaceLandmarks68 > = TSource & {
+  TFaceLandmarks extends FaceLandmarks = FaceLandmarks68
-    landmarks: TFaceLandmarks,
+> = TSource & {
-    unshiftedLandmarks: TFaceLandmarks,
+  landmarks: TFaceLandmarks;
-    alignedRect: FaceDetection,
+  unshiftedLandmarks: TFaceLandmarks;
-    angle: { roll: number | undefined, pitch: number | undefined, yaw: number | undefined },
+  alignedRect: FaceDetection;
-  }
+  angle: {
+    roll: number | undefined;
+    pitch: number | undefined;
+    yaw: number | undefined;
+  };
+};
 
-export function isWithFaceLandmarks(obj: any): obj is WithFaceLandmarks<WithFaceDetection<{}>, FaceLandmarks> {
+export function isWithFaceLandmarks(
-  return isWithFaceDetection(obj)
+  obj: any,
-    // eslint-disable-next-line dot-notation
+): obj is WithFaceLandmarks<WithFaceDetection<{}>, FaceLandmarks> {
-    && obj['landmarks'] instanceof FaceLandmarks
+  return (
-    // eslint-disable-next-line dot-notation
+    isWithFaceDetection(obj)
-    && obj['unshiftedLandmarks'] instanceof FaceLandmarks
+    && (obj as any)['landmarks'] instanceof FaceLandmarks
-    // eslint-disable-next-line dot-notation
+    && (obj as any)['unshiftedLandmarks'] instanceof FaceLandmarks
-    && obj['alignedRect'] instanceof FaceDetection;
+    && (obj as any)['alignedRect'] instanceof FaceDetection
+  );
 }
 
-function calculateFaceAngle(mesh) {
+function calculateFaceAngle(mesh: FaceLandmarks) {
-  // returns the angle in the plane (in radians) between the positive x-axis and the ray from (0,0) to the point (x,y)
+  // Helper to convert radians to degrees
-  const radians = (a1, a2, b1, b2) => (Math.atan2(b2 - a2, b1 - a1) % Math.PI);
-  // convert radians to degrees
   // eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars
-  const degrees = (theta) => (theta * 180) / Math.PI;
+  const degrees = (radians: number) => (radians * 180) / Math.PI;
+  const calcLengthBetweenTwoPoints = (a: Point, b: Point) => Math.sqrt((a.x - b.x) ** 2 + (a.y - b.y) ** 2);
 
-  const angle = { roll: <number | undefined>undefined, pitch: <number | undefined>undefined, yaw: <number | undefined>undefined };
+  const angle = {
+    roll: <number | undefined>undefined,
+    pitch: <number | undefined>undefined,
+    yaw: <number | undefined>undefined,
+  };
 
-  if (!mesh || !mesh._positions || mesh._positions.length !== 68) return angle;
+  const calcYaw = (leftPoint: Point, midPoint: Point, rightPoint: Point) => {
-  const pt = mesh._positions;
+    // Calc x-distance from left side of the face ("ear") to facial midpoint ("nose")
+    const leftToMidpoint = Math.floor(leftPoint.x - midPoint.x);
+    // Calc x-distance from facial midpoint ("nose") to the right side of the face ("ear")
+    const rightToMidpoint = Math.floor(midPoint.x - rightPoint.x);
+    // Difference in distances coincidentally approximates to angles
+    return leftToMidpoint - rightToMidpoint;
+  };
 
-  // values are in radians in range of -pi/2 to pi/2 which is -90 to +90 degrees
+  const calcRoll = (lever: Point, pivot: Point) => {
-  // value of 0 means center
+    // When rolling, the head seems to pivot from the nose/lips/chin area.
+    // So, we'll choose any two points from the facial midline, where the first point should be the pivot, and the other "lever"
+    // Plan/Execution: get the hypotenuse & opposite sides of a 90deg triangle ==> Calculate angle in radians
+    const hypotenuse = Math.hypot(pivot.x - lever.x, pivot.y - lever.y);
+    const opposite = pivot.y - lever.y;
+    const angleInRadians = Math.asin(opposite / hypotenuse);
+    const angleInDegrees = degrees(angleInRadians);
+    const normalizeAngle = Math.floor(90 - angleInDegrees);
+    // If lever more to the left of the pivot, then we're tilting left
+    // "-" is negative direction. "+", or absence of a sign is positive direction
+    const tiltDirection = pivot.x - lever.x < 0 ? -1 : 1;
+    const result = normalizeAngle * tiltDirection;
+    return result;
+  };
 
-  // roll is face lean from left to right
+  const calcPitch = (leftPoint: Point, midPoint: Point, rightPoint: Point) => {
-  // comparing x,y of outside corners of leftEye and rightEye
+    // Theory: While pitching, the nose is the most salient point --> That's what we'll use to make a trianle.
-  angle.roll = -radians(pt[36]._x, pt[36]._y, pt[45]._x, pt[45]._y);
+    // The "base" is between point that don't move when we pitch our head (i.e. an imaginary line running ear to ear through the nose).
+    // Executuin: Get the opposite & adjacent lengths of the triangle from the ear's perspective. Use it to get angle.
 
-  // pitch is face turn from left right
+    const base = calcLengthBetweenTwoPoints(leftPoint, rightPoint);
-  // comparing x distance of top of nose to left and right edge of face
+    // adjecent is base/2 technically.
-  // precision is lacking since coordinates are not precise enough
+    const baseCoords = new Point((leftPoint.x + rightPoint.x) / 2, (leftPoint.y + rightPoint.y) / 2);
-  angle.pitch = radians(0, Math.abs(pt[0]._x - pt[30]._x) / pt[30]._x, Math.PI, Math.abs(pt[16]._x - pt[30]._x) / pt[30]._x);
+    const midToBaseLength = calcLengthBetweenTwoPoints(midPoint, baseCoords);
-
+    const angleInRadians = Math.atan(midToBaseLength / base);
-  // yaw is face move from up to down
+    const angleInDegrees = Math.floor(degrees(angleInRadians));
-  // comparing size of the box around the face with top and bottom of detected landmarks
+    // Account for directionality.
-  // silly hack, but this gives us face compression on y-axis
+    // pitch forwards (_i.e. tilting your head forwards) is positive (or no sign); backward is negative.
-  // e.g., tilting head up hides the forehead that doesn't have any landmarks so ratio drops
+    const direction = baseCoords.y - midPoint.y < 0 ? -1 : 1;
-  const bottom = pt.reduce((prev, cur) => (prev < cur._y ? prev : cur._y), +Infinity);
+    const result = angleInDegrees * direction;
-  const top = pt.reduce((prev, cur) => (prev > cur._y ? prev : cur._y), -Infinity);
+    return result;
-  angle.yaw = Math.PI * (mesh._imgDims._height / (top - bottom) / 1.40 - 1);
+  };
 
+  if (!mesh || !mesh.positions || mesh.positions.length !== 68) return angle;
+  const pt = mesh.positions;
+  angle.roll = calcRoll(pt[27], pt[66]);
+  angle.pitch = calcPitch(pt[14], pt[30], pt[2]);
+  angle.yaw = calcYaw(pt[14], pt[33], pt[2]);
   return angle;
 }
 
-export function extendWithFaceLandmarks<
+export function extendWithFaceLandmarks<TSource extends WithFaceDetection<{}>, TFaceLandmarks extends FaceLandmarks = FaceLandmarks68>(
-  TSource extends WithFaceDetection<{}>,
+  sourceObj: TSource,
-  TFaceLandmarks extends FaceLandmarks = FaceLandmarks68 >(sourceObj: TSource, unshiftedLandmarks: TFaceLandmarks): WithFaceLandmarks<TSource, TFaceLandmarks> {
+  unshiftedLandmarks: TFaceLandmarks,
+): WithFaceLandmarks<TSource, TFaceLandmarks> {
   const { box: shift } = sourceObj.detection;
   const landmarks = unshiftedLandmarks.shiftBy<TFaceLandmarks>(shift.x, shift.y);
-
   const rect = landmarks.align();
   const { imageDims } = sourceObj.detection;
-  const alignedRect = new FaceDetection(sourceObj.detection.score, rect.rescale(imageDims.reverse()), imageDims);
+  const alignedRect = new FaceDetection(
+    sourceObj.detection.score,
+    rect.rescale(imageDims.reverse()),
+    imageDims,
+  );
   const angle = calculateFaceAngle(unshiftedLandmarks);
-
+  const extension = { landmarks, unshiftedLandmarks, alignedRect, angle };
-  const extension = {
-    landmarks,
-    unshiftedLandmarks,
-    alignedRect,
-    angle,
-  };
-
   return { ...sourceObj, ...extension };
 }

src/globalApi/ComputeFaceDescriptorsTasks.ts

@@ -21,7 +21,7 @@ export class ComputeFaceDescriptorsTaskBase<TReturn, TParentReturn> extends Comp
 }
 
 export class ComputeAllFaceDescriptorsTask<TSource extends WithFaceLandmarks<WithFaceDetection<{}>>> extends ComputeFaceDescriptorsTaskBase<WithFaceDescriptor<TSource>[], TSource[]> {
-  public async run(): Promise<WithFaceDescriptor<TSource>[]> {
+  public override async run(): Promise<WithFaceDescriptor<TSource>[]> {
     const parentResults = await this.parentTask;
     const descriptors = await extractAllFacesAndComputeResults<TSource, Float32Array[]>(
       parentResults,
@@ -43,20 +43,17 @@ export class ComputeAllFaceDescriptorsTask<TSource extends WithFaceLandmarks<Wit
 }
 
 export class ComputeSingleFaceDescriptorTask<TSource extends WithFaceLandmarks<WithFaceDetection<{}>>> extends ComputeFaceDescriptorsTaskBase<WithFaceDescriptor<TSource> | undefined, TSource | undefined> {
-  public async run(): Promise<WithFaceDescriptor<TSource> | undefined> {
+  public override async run(): Promise<WithFaceDescriptor<TSource> | undefined> {
     const parentResult = await this.parentTask;
-    if (!parentResult) {
+    if (!parentResult) return undefined;
-      return undefined;
-    }
     const descriptor = await extractSingleFaceAndComputeResult<TSource, Float32Array>(
       parentResult,
       this.input,
       (face) => nets.faceRecognitionNet.computeFaceDescriptor(face) as Promise<Float32Array>,
       null,
-      // eslint-disable-next-line no-shadow
+      // eslint-disable-next-line no-shadow, @typescript-eslint/no-shadow
       (parentResult) => parentResult.landmarks.align(null, { useDlibAlignment: true }),
     );
-
     return extendWithFaceDescriptor(parentResult, descriptor);
   }
 

src/globalApi/DetectFaceLandmarksTasks.ts

@@ -33,17 +33,18 @@ export class DetectFaceLandmarksTaskBase<TReturn, TParentReturn> extends Composa
 }
 
 export class DetectAllFaceLandmarksTask<TSource extends WithFaceDetection<{}>> extends DetectFaceLandmarksTaskBase<WithFaceLandmarks<TSource>[], TSource[]> {
-  public async run(): Promise<WithFaceLandmarks<TSource>[]> {
+  public override async run(): Promise<WithFaceLandmarks<TSource>[]> {
     const parentResults = await this.parentTask;
     const detections = parentResults.map((res) => res.detection);
     const faces: Array<HTMLCanvasElement | tf.Tensor3D> = this.input instanceof tf.Tensor
       ? await extractFaceTensors(this.input, detections)
       : await extractFaces(this.input, detections);
-    const faceLandmarksByFace = await Promise.all(
+    const faceLandmarksByFace = await Promise.all(faces.map((face) => this.landmarkNet.detectLandmarks(face))) as FaceLandmarks68[];
-      faces.map((face) => this.landmarkNet.detectLandmarks(face)),
-    ) as FaceLandmarks68[];
     faces.forEach((f) => f instanceof tf.Tensor && f.dispose());
-    return parentResults.map((parentResult, i) => extendWithFaceLandmarks<TSource>(parentResult, faceLandmarksByFace[i]));
+    const result = parentResults
+      .filter((_parentResult, i) => faceLandmarksByFace[i])
+      .map((parentResult, i) => extendWithFaceLandmarks<TSource>(parentResult, faceLandmarksByFace[i]));
+    return result;
   }
 
   withFaceExpressions() {
@@ -60,7 +61,7 @@ export class DetectAllFaceLandmarksTask<TSource extends WithFaceDetection<{}>> e
 }
 
 export class DetectSingleFaceLandmarksTask<TSource extends WithFaceDetection<{}>> extends DetectFaceLandmarksTaskBase<WithFaceLandmarks<TSource> | undefined, TSource | undefined> {
-  public async run(): Promise<WithFaceLandmarks<TSource> | undefined> {
+  public override async run(): Promise<WithFaceLandmarks<TSource> | undefined> {
     const parentResult = await this.parentTask;
     if (!parentResult) {
       return undefined;

src/globalApi/DetectFacesTasks.ts

@@ -20,7 +20,7 @@ export class DetectFacesTaskBase<TReturn> extends ComposableTask<TReturn> {
 }
 
 export class DetectAllFacesTask extends DetectFacesTaskBase<FaceDetection[]> {
-  public async run(): Promise<FaceDetection[]> {
+  public override async run(): Promise<FaceDetection[]> {
     const { input, options } = this;
     let result;
     if (options instanceof TinyFaceDetectorOptions) result = nets.tinyFaceDetector.locateFaces(input, options);
@@ -62,7 +62,7 @@ export class DetectAllFacesTask extends DetectFacesTaskBase<FaceDetection[]> {
 }
 
 export class DetectSingleFaceTask extends DetectFacesTaskBase<FaceDetection | undefined> {
-  public async run(): Promise<FaceDetection | undefined> {
+  public override async run(): Promise<FaceDetection | undefined> {
     const faceDetections = await new DetectAllFacesTask(this.input, this.options);
     let faceDetectionWithHighestScore = faceDetections[0];
     faceDetections.forEach((faceDetection) => {

src/globalApi/FaceMatcher.ts

@@ -4,38 +4,19 @@ import { euclideanDistance } from '../euclideanDistance';
 import { WithFaceDescriptor } from '../factories/index';
 
 export class FaceMatcher {
-  private _labeledDescriptors: LabeledFaceDescriptors[]
+  private _labeledDescriptors: LabeledFaceDescriptors[];
+  private _distanceThreshold: number;
 
-  private _distanceThreshold: number
+  constructor(inputs: LabeledFaceDescriptors | WithFaceDescriptor<any> | Float32Array | Array<LabeledFaceDescriptors | WithFaceDescriptor<any> | Float32Array>, distanceThreshold = 0.6) {
-
-  constructor(
-    inputs: LabeledFaceDescriptors | WithFaceDescriptor<any> | Float32Array | Array<LabeledFaceDescriptors | WithFaceDescriptor<any> | Float32Array>,
-    distanceThreshold = 0.6,
-  ) {
     this._distanceThreshold = distanceThreshold;
-
     const inputArray = Array.isArray(inputs) ? inputs : [inputs];
-
+    if (!inputArray.length) throw new Error('FaceRecognizer.constructor - expected atleast one input');
-    if (!inputArray.length) {
-      throw new Error('FaceRecognizer.constructor - expected atleast one input');
-    }
-
     let count = 1;
     const createUniqueLabel = () => `person ${count++}`;
-
     this._labeledDescriptors = inputArray.map((desc) => {
-      if (desc instanceof LabeledFaceDescriptors) {
+      if (desc instanceof LabeledFaceDescriptors) return desc;
-        return desc;
+      if (desc instanceof Float32Array) return new LabeledFaceDescriptors(createUniqueLabel(), [desc]);
-      }
+      if (desc.descriptor && desc.descriptor instanceof Float32Array) return new LabeledFaceDescriptors(createUniqueLabel(), [desc.descriptor]);
-
-      if (desc instanceof Float32Array) {
-        return new LabeledFaceDescriptors(createUniqueLabel(), [desc]);
-      }
-
-      if (desc.descriptor && desc.descriptor instanceof Float32Array) {
-        return new LabeledFaceDescriptors(createUniqueLabel(), [desc.descriptor]);
-      }
-
       throw new Error('FaceRecognizer.constructor - expected inputs to be of type LabeledFaceDescriptors | WithFaceDescriptor<any> | Float32Array | Array<LabeledFaceDescriptors | WithFaceDescriptor<any> | Float32Array>');
     });
   }
@@ -47,36 +28,29 @@ export class FaceMatcher {
   public computeMeanDistance(queryDescriptor: Float32Array, descriptors: Float32Array[]): number {
     return descriptors
       .map((d) => euclideanDistance(d, queryDescriptor))
-      .reduce((d1, d2) => d1 + d2, 0)
+      .reduce((d1, d2) => d1 + d2, 0) / (descriptors.length || 1);
-        / (descriptors.length || 1);
   }
 
   public matchDescriptor(queryDescriptor: Float32Array): FaceMatch {
     return this.labeledDescriptors
-      .map(({ descriptors, label }) => new FaceMatch(
+      .map(({ descriptors, label }) => new FaceMatch(label, this.computeMeanDistance(queryDescriptor, descriptors)))
-        label,
-        this.computeMeanDistance(queryDescriptor, descriptors),
-      ))
       .reduce((best, curr) => (best.distance < curr.distance ? best : curr));
   }
 
   public findBestMatch(queryDescriptor: Float32Array): FaceMatch {
     const bestMatch = this.matchDescriptor(queryDescriptor);
-    return bestMatch.distance < this.distanceThreshold
+    return (bestMatch.distance < this._distanceThreshold) ? bestMatch : new FaceMatch('unknown', bestMatch.distance);
-      ? bestMatch
-      : new FaceMatch('unknown', bestMatch.distance);
   }
 
   public toJSON(): any {
     return {
-      distanceThreshold: this.distanceThreshold,
+      distanceThreshold: this._distanceThreshold,
-      labeledDescriptors: this.labeledDescriptors.map((ld) => ld.toJSON()),
+      labeledDescriptors: this._labeledDescriptors.map((ld) => ld.toJSON()),
     };
   }
 
   public static fromJSON(json: any): FaceMatcher {
-    const labeledDescriptors = json.labeledDescriptors
+    const labeledDescriptors = json.labeledDescriptors.map((ld: any) => LabeledFaceDescriptors.fromJSON(ld));
-      .map((ld: any) => LabeledFaceDescriptors.fromJSON(ld));
     return new FaceMatcher(labeledDescriptors, json.distanceThreshold);
   }
 }

src/globalApi/PredictAgeAndGenderTask.ts

@@ -27,7 +27,7 @@ export class PredictAgeAndGenderTaskBase<TReturn, TParentReturn> extends Composa
 }
 
 export class PredictAllAgeAndGenderTask<TSource extends WithFaceDetection<{}>> extends PredictAgeAndGenderTaskBase<WithAge<WithGender<TSource>>[], TSource[]> {
-  public async run(): Promise<WithAge<WithGender<TSource>>[]> {
+  public override async run(): Promise<WithAge<WithGender<TSource>>[]> {
     const parentResults = await this.parentTask;
     const ageAndGenderByFace = await extractAllFacesAndComputeResults<TSource, AgeAndGenderPrediction[]>(
       parentResults,
@@ -47,7 +47,7 @@ export class PredictAllAgeAndGenderTask<TSource extends WithFaceDetection<{}>> e
 }
 
 export class PredictSingleAgeAndGenderTask<TSource extends WithFaceDetection<{}>> extends PredictAgeAndGenderTaskBase<WithAge<WithGender<TSource>> | undefined, TSource | undefined> {
-  public async run(): Promise<WithAge<WithGender<TSource>> | undefined> {
+  public override async run(): Promise<WithAge<WithGender<TSource>> | undefined> {
     const parentResult = await this.parentTask;
     if (!parentResult) return undefined;
     const { age, gender, genderProbability } = await extractSingleFaceAndComputeResult<TSource, AgeAndGenderPrediction>(
@@ -65,7 +65,7 @@ export class PredictSingleAgeAndGenderTask<TSource extends WithFaceDetection<{}>
 }
 
 export class PredictAllAgeAndGenderWithFaceAlignmentTask<TSource extends WithFaceLandmarks<WithFaceDetection<{}>>> extends PredictAllAgeAndGenderTask<TSource> {
-  withFaceExpressions() {
+  override withFaceExpressions() {
     return new PredictAllFaceExpressionsWithFaceAlignmentTask(this, this.input);
   }
 
@@ -75,7 +75,7 @@ export class PredictAllAgeAndGenderWithFaceAlignmentTask<TSource extends WithFac
 }
 
 export class PredictSingleAgeAndGenderWithFaceAlignmentTask<TSource extends WithFaceLandmarks<WithFaceDetection<{}>>> extends PredictSingleAgeAndGenderTask<TSource> {
-  withFaceExpressions() {
+  override withFaceExpressions() {
     return new PredictSingleFaceExpressionsWithFaceAlignmentTask(this, this.input);
   }
 

src/globalApi/PredictFaceExpressionsTask.ts

@@ -26,7 +26,7 @@ export class PredictFaceExpressionsTaskBase<TReturn, TParentReturn> extends Comp
 }
 
 export class PredictAllFaceExpressionsTask<TSource extends WithFaceDetection<{}>> extends PredictFaceExpressionsTaskBase<WithFaceExpressions<TSource>[], TSource[]> {
-  public async run(): Promise<WithFaceExpressions<TSource>[]> {
+  public override async run(): Promise<WithFaceExpressions<TSource>[]> {
     const parentResults = await this.parentTask;
 
     const faceExpressionsByFace = await extractAllFacesAndComputeResults<TSource, FaceExpressions[]>(
@@ -49,7 +49,7 @@ export class PredictAllFaceExpressionsTask<TSource extends WithFaceDetection<{}>
 }
 
 export class PredictSingleFaceExpressionsTask<TSource extends WithFaceDetection<{}>> extends PredictFaceExpressionsTaskBase<WithFaceExpressions<TSource> | undefined, TSource | undefined> {
-  public async run(): Promise<WithFaceExpressions<TSource> | undefined> {
+  public override async run(): Promise<WithFaceExpressions<TSource> | undefined> {
     const parentResult = await this.parentTask;
     if (!parentResult) {
       return undefined;
@@ -71,7 +71,7 @@ export class PredictSingleFaceExpressionsTask<TSource extends WithFaceDetection<
 }
 
 export class PredictAllFaceExpressionsWithFaceAlignmentTask<TSource extends WithFaceLandmarks<WithFaceDetection<{}>>> extends PredictAllFaceExpressionsTask<TSource> {
-  withAgeAndGender() {
+  override withAgeAndGender() {
     return new PredictAllAgeAndGenderWithFaceAlignmentTask(this, this.input);
   }
 
@@ -81,7 +81,7 @@ export class PredictAllFaceExpressionsWithFaceAlignmentTask<TSource extends With
 }
 
 export class PredictSingleFaceExpressionsWithFaceAlignmentTask<TSource extends WithFaceLandmarks<WithFaceDetection<{}>>> extends PredictSingleFaceExpressionsTask<TSource> {
-  withAgeAndGender() {
+  override withAgeAndGender() {
     return new PredictSingleAgeAndGenderWithFaceAlignmentTask(this, this.input);
   }
 

src/index.ts

@@ -22,6 +22,7 @@ export * from './euclideanDistance';
 export * from './NeuralNetwork';
 export * from './resizeResults';
 
-const node = (typeof process !== 'undefined');
+export const version = pkg.version as string;
-const browser = (typeof navigator !== 'undefined') && (typeof navigator.userAgent !== 'undefined');
+
-export const version = { faceapi: pkg.version as string, node, browser };
+// set webgl defaults
+// if (browser) tf.ENV.set('WEBGL_USE_SHAPES_UNIFORMS', true);

src/ops/padToSquare.ts

@@ -8,40 +8,24 @@ import * as tf from '../../dist/tfjs.esm';
  * both sides of the minor dimension oof the image.
  * @returns The padded tensor with width === height.
  */
-export function padToSquare(
+export function padToSquare(imgTensor: tf.Tensor4D, isCenterImage = false): tf.Tensor4D {
-  imgTensor: tf.Tensor4D,
-  isCenterImage = false,
-): tf.Tensor4D {
   return tf.tidy(() => {
     const [height, width] = imgTensor.shape.slice(1);
-    if (height === width) {
+    if (height === width) return imgTensor;
-      return imgTensor;
-    }
-
     const dimDiff = Math.abs(height - width);
     const paddingAmount = Math.round(dimDiff * (isCenterImage ? 0.5 : 1));
     const paddingAxis = height > width ? 2 : 1;
-
     const createPaddingTensor = (paddingAmountLocal: number): tf.Tensor => {
       const paddingTensorShape = imgTensor.shape.slice();
       paddingTensorShape[paddingAxis] = paddingAmountLocal;
       return tf.fill(paddingTensorShape, 0, 'float32');
     };
-
     const paddingTensorAppend = createPaddingTensor(paddingAmount);
     const remainingPaddingAmount = dimDiff - (paddingTensorAppend.shape[paddingAxis] as number);
-
+    const paddingTensorPrepend = isCenterImage && remainingPaddingAmount ? createPaddingTensor(remainingPaddingAmount) : null;
-    const paddingTensorPrepend = isCenterImage && remainingPaddingAmount
+    const tensorsToStack = [paddingTensorPrepend, imgTensor, paddingTensorAppend]
-      ? createPaddingTensor(remainingPaddingAmount)
-      : null;
-
-    const tensorsToStack = [
-      paddingTensorPrepend,
-      imgTensor,
-      paddingTensorAppend,
-    ]
       .filter((t) => !!t)
-      .map((t: tf.Tensor) => tf.cast(t, 'float32')) as tf.Tensor4D[];
+      .map((t) => tf.cast(t as tf.Tensor4D, 'float32')) as tf.Tensor4D[];
     return tf.concat(tensorsToStack, paddingAxis);
   });
 }

src/ssdMobilenetv1/SsdMobilenetv1Options.ts

@@ -4,11 +4,11 @@ export interface ISsdMobilenetv1Options {
 }
 
 export class SsdMobilenetv1Options {
-  protected _name = 'SsdMobilenetv1Options'
+  protected _name = 'SsdMobilenetv1Options';
 
-  private _minConfidence: number
+  private _minConfidence: number;
 
-  private _maxResults: number
+  private _maxResults: number;
 
   constructor({ minConfidence, maxResults }: ISsdMobilenetv1Options = {}) {
     this._minConfidence = minConfidence || 0.5;

src/tfjs/tf-browser.ts

@@ -1,7 +1,15 @@
-/* eslint-disable import/no-extraneous-dependencies */
+/**
-/* eslint-disable node/no-unpublished-import */
+ * Creates tfjs bundle used by Human browser build target
-
+ * @external
-// wrapper to load tfjs in a single place so version can be changed quickly
+ */
 
+// export all from build bundle
 export * from '@tensorflow/tfjs/dist/index.js';
-export * from '@tensorflow/tfjs-backend-wasm';
+export * from '@tensorflow/tfjs-backend-webgl/dist/index.js';
+export * from '@tensorflow/tfjs-backend-wasm/dist/index.js';
+
+// add webgpu to bundle, experimental
+// export * from '@tensorflow/tfjs-backend-webgpu/dist/index.js';
+
+// export versions, overrides version object from @tensorflow/tfjs
+export { version } from '../../dist/tfjs.version.js';