.build.json

@@ -6,7 +6,7 @@
     "output": "build.log"
   },
   "profiles": {
-    "production": ["compile", "typings", "typedoc", "lint", "changelog"],
+    "production": ["clean", "compile", "typings", "typedoc", "lint", "changelog"],
     "development": ["serve", "watch", "compile"]
   },
   "clean": {
@@ -37,13 +37,6 @@
       "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",
@@ -92,6 +85,13 @@
         "output": "dist/face-api.node-wasm.js",
         "external": ["@tensorflow"]
       },
+      { 
+        "name": "tfjs/browser/tf-version",
+        "platform": "browser",
+        "format": "esm",
+        "input": "src/tfjs/tf-version.ts",
+        "output": "dist/tfjs.version.js"
+      },
       {
         "name": "tfjs/browser/esm/nobundle",
         "platform": "browser",

.eslintrc.json

@@ -7,7 +7,7 @@
       "es2020": true
   },
   "parser": "@typescript-eslint/parser",
-  "parserOptions": { "ecmaVersion": "latest" },
+  "parserOptions": { "ecmaVersion": 2020 },
   "plugins": [
     "@typescript-eslint"
   ],
@@ -17,6 +17,7 @@
     "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"
@@ -28,8 +29,6 @@
     "@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",

.github/FUNDING.yml

@@ -1,13 +0,0 @@
-# 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']

.npmrc

@@ -2,4 +2,3 @@ force=true
 production=true
 legacy-peer-deps=true
 strict-peer-dependencies=false
-node-options='--no-deprecation'

.vscode/settings.json

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

CHANGELOG.md

@@ -1,6 +1,6 @@
 # @vladmandic/face-api  
 
-  Version: **1.7.15**  
+  Version: **1.7.1**  
   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>**  
@@ -9,75 +9,12 @@
   
 ## 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
+
+### **origin/master** 2022/05/24 mandic00@live.com
+
 
 ### **1.6.11** 2022/05/24 mandic00@live.com
 

README.md

@@ -104,10 +104,7 @@ NodeJS examples are:
 2021-03-14 08:42:09 STATE:  Main: worker exit: 1888019 0
 ```
 
-### NodeJS Notes
+Note that `@tensorflow/tfjs-node` or `@tensorflow/tfjs-node-gpu`  
-- 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>
@@ -261,7 +258,7 @@ 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-gpu
+  npm install @tensorflow/tfjs-node
   npm install @vladmandic/face-api 
 ```
 
@@ -272,24 +269,18 @@ 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 **tensorflow** binary libraries are not supported, you can use NodeJS **WASM** backend.  
+If you want to use `FaceAPI` in a NodeJS on platforms where NodeJS binary libraries are not supported, you can use JavaScript CPU 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 wasm = require('@tensorflow/tfjs-backend-wasm');
+  const faceapi = require('@vladmandic/face-api/dist/face-api.node-cpu.js');
-  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,  
@@ -317,7 +308,7 @@ faceapi.env.monkeyPatch({ Canvas, Image, ImageData })
 
 ## Weights
 
-Pretrained models and their weights are included in `./model`.
+Pretrained models and their weights are includes in `./model`.
 
 <br><hr><br>
 
@@ -449,14 +440,18 @@ Build process uses `@vladmandic/build` module that creates optimized build for e
 
 ## 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  
 
-*Why?* I needed a FaceAPI that does not cause version conflict with newer versions of TensorFlow  
+Currently using **`TensorFlow/JS` 3.17.0**  
-And since the original FaceAPI was open-source, I've released this version as well  
 
-Changes ended up being too large for a simple pull request and it ended up being a full-fledged version on its own  
+*Why?* I needed FaceAPI that does not cause version conflict with newer versions of TensorFlow  
-Plus many features were added since the original inception  
+And since original FaceAPI was open-source, I've released this version as well  
+
+Changes ended up being too large for a simple pull request  
+and it ended up being a full-fledged version on its own  
+
+Plus many features were added since 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,  
@@ -471,12 +466,11 @@ 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+ and 4.0+`  
+- Compatible with `TensorFlow/JS 2.0+ & 3.0+`  
-  Currently using **`TensorFlow/JS` 4.16**  
   Original `face-api.js` is based on `TFJS` **1.7.4**
 - Compatible with `WebGL`, `CPU` and `WASM` TFJS Browser backends  
 - Compatible with both `tfjs-node` and `tfjs-node-gpu` TFJS NodeJS backends  
-- Updated all type castings for TypeScript type checking to `TypeScript 5.3`  
+- Updated all type castings for TypeScript type checking to `TypeScript 4.6`  
 - Switched bundling from `UMD` to `ESM` + `CommonJS` with fallback to `IIFE`  
   Resulting code is optimized per-platform instead of being universal  
   Fully tree shakable when imported as an `ESM` module  
@@ -498,7 +492,7 @@ Compared to [face-api.js](https://github.com/justadudewhohacks/face-api.js) vers
 - 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
+- Created new process to generate **TypeDocs** bundle using API-Extractor
 
 <br>
 

build.js

@@ -3,44 +3,13 @@ const log = require('@vladmandic/pilogger');
 const Build = require('@vladmandic/build').Build;
 const APIExtractor = require('@microsoft/api-extractor');
 
-const regEx = [
+// eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars
-  { search: 'types="@webgpu/types/dist"', replace: 'path="../src/types/webgpu.d.ts"' },
+function copy(src, dst) {
-  { search: 'types="offscreencanvas"', replace: 'path="../src/types/offscreencanvas.d.ts"' },
+  if (!fs.existsSync(src)) return;
-];
-
-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() {
@@ -49,7 +18,7 @@ async function main() {
   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');
+  copy('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, {
@@ -64,13 +33,16 @@ async function main() {
     },
   });
   log.state('API-Extractor:', { succeeeded: extractorResult.succeeded, errors: extractorResult.errorCount, warnings: extractorResult.warningCount });
-  regExFile('types/face-api.d.ts', regEx);
+  // distribute typedefs
-  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');
+  log.state('Copy:', { input: 'types/human.d.ts' });
-  writeFile('export * from \'../types/face-api\';', 'dist/face-api.d.ts');
+  copy('types/human.d.ts', 'dist/human.esm-nobundle.d.ts');
-  writeFile('export * from \'../types/face-api\';', 'dist/face-api.node.d.ts');
+  copy('types/human.d.ts', 'dist/human.esm.d.ts');
-  writeFile('export * from \'../types/face-api\';', 'dist/face-api.node-gpu.d.ts');
+  copy('types/human.d.ts', 'dist/human.d.ts');
-  writeFile('export * from \'../types/face-api\';', 'dist/face-api.node-wasm.d.ts');
+  copy('types/human.d.ts', 'dist/human.node-gpu.d.ts');
+  copy('types/human.d.ts', 'dist/human.node.d.ts');
+  copy('types/human.d.ts', 'dist/human.node-wasm.d.ts');
+  */
   log.info('FaceAPI Build complete...');
 }
 

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; overflow-x: hidden;">
+  <body style="font-family: monospace; background: black; color: white; font-size: 16px; line-height: 22px; margin: 0;">
     <div id="log"></div>
   </body>
 </html>

demo/index.js

@@ -1,14 +1,8 @@
-/**
+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://cdn.jsdelivr.net/npm/@vladmandic/face-api/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 imgSize = 800; // maximum image size in pixels
 const minScore = 0.3; // minimum score
 const maxResults = 10; // maximum number of results to return
@@ -19,7 +13,8 @@ const str = (json) => (json ? JSON.stringify(json).replace(/{|}|"|\[|\]/g, '').r
 
 // helper function to print strings to html document as a log
 function log(...txt) {
-  console.log(...txt); // eslint-disable-line no-console
+  // eslint-disable-next-line no-console
+  console.log(...txt);
   const div = document.getElementById('log');
   if (div) div.innerHTML += `<br>${txt}`;
 }
@@ -33,9 +28,11 @@ function faces(name, title, id, data) {
   canvas.style.position = 'absolute';
   canvas.style.left = `${img.offsetLeft}px`;
   canvas.style.top = `${img.offsetTop}px`;
+  // @ts-ignore
   canvas.width = img.width;
+  // @ts-ignore
   canvas.height = img.height;
-  const ctx = canvas.getContext('2d', { willReadFrequently: true });
+  const ctx = canvas.getContext('2d');
   if (!ctx) return;
   // draw title
   ctx.font = '1rem sans-serif';
@@ -51,7 +48,6 @@ function faces(name, title, id, data) {
     ctx.beginPath();
     ctx.rect(person.detection.box.x, person.detection.box.y, person.detection.box.width, person.detection.box.height);
     ctx.stroke();
-    // draw text labels
     ctx.globalAlpha = 1;
     ctx.fillText(`${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);
@@ -71,7 +67,8 @@ function faces(name, title, id, data) {
 
 // helper function to draw processed image and its results
 function print(title, img, data) {
-  console.log('Results:', title, img, data); // eslint-disable-line no-console
+  // eslint-disable-next-line no-console
+  console.log('Results:', title, img, data);
   const el = new Image();
   el.id = Math.floor(Math.random() * 100000).toString();
   el.src = img;
@@ -94,7 +91,7 @@ async function image(url) {
       const canvas = document.createElement('canvas');
       canvas.height = img.height;
       canvas.width = img.width;
-      const ctx = canvas.getContext('2d', { willReadFrequently: true });
+      const ctx = canvas.getContext('2d');
       if (ctx) ctx.drawImage(img, 0, 0, img.width, img.height);
       // return generated canvas to be used by tfjs during detection
       resolve(canvas);
@@ -108,20 +105,19 @@ async function main() {
   // initialize tfjs
   log('FaceAPI Test');
 
-  // if you want to use wasm backend location for wasm binaries must be specified
+  const params = new URLSearchParams(location.search);
-  // await faceapi.tf?.setWasmPaths(`https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@${faceapi.tf.version_core}/dist/`);
+  if (params.has('backend')) {
-  // await faceapi.tf?.setBackend('wasm');
+    const backend = params.get('backend');
-  // log(`WASM SIMD: ${await faceapi.tf?.env().getAsync('WASM_HAS_SIMD_SUPPORT')} Threads: ${await faceapi.tf?.env().getAsync('WASM_HAS_MULTITHREAD_SUPPORT') ? 'Multi' : 'Single'}`);
+    await faceapi.tf.setWasmPaths('https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@3.17.0/dist/');
-
+    log(`Chosen backend: ${backend}`);
+    await faceapi.tf.setBackend(backend);
+  } else {
     // 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
@@ -143,9 +139,16 @@ 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);
@@ -171,6 +174,8 @@ async function main() {
       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

@@ -1,20 +1,13 @@
-/**
- * FaceAPI Demo for NodeJS
- * - Uses external library [canvas](https://www.npmjs.com/package/canvas) to decode image
- * - Loads image from provided param
- * - Outputs results to console
- */
-
-// canvas library provides full canvas (load/draw/write) functionality for nodejs
-// must be installed manually as it just a demo dependency and not actual face-api dependency
-const canvas = require('canvas'); // eslint-disable-line node/no-missing-require
 const fs = require('fs');
 const path = require('path');
 const process = require('process');
 const log = require('@vladmandic/pilogger');
+const canvas = require('canvas');
+
+// eslint-disable-next-line import/no-extraneous-dependencies, 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 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 faceapi = require('../dist/face-api.node.js'); // use this when using face-api in dev mode
 
 const modelPathRoot = '../model';
 const imgPathRoot = './demo'; // modify to include your sample images
@@ -57,9 +50,11 @@ 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: FaceAPI ${faceapi.version} TensorFlow/JS ${tf.version_core} 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);

demo/node-face-compare.js

@@ -1,35 +0,0 @@
-/**
- * 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

@@ -1,18 +1,12 @@
-/**
- * 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 image = require('@canvas/image'); // @canvas/image can decode jpeg, png, webp
 const log = require('@vladmandic/pilogger');
+
+// eslint-disable-next-line import/no-extraneous-dependencies, 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 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 faceapi = require('../dist/face-api.node.js'); // use this when using face-api in dev mode
 
 const modelPath = 'model/';
 const imageFile = 'demo/sample1.jpg';

demo/node-match.js

@@ -1,16 +1,11 @@
-/**
- * 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');
+
+// eslint-disable-next-line import/no-extraneous-dependencies, 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 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 faceapi = require('../dist/face-api.node.js'); // use this when using face-api in dev mode
 
 let optionsSSDMobileNet;
 const minConfidence = 0.1;
@@ -38,8 +33,6 @@ async function getDescriptors(imageFile) {
 }
 
 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]);
@@ -67,18 +60,14 @@ async function main() {
   await initFaceAPI();
   log.info('Input:', process.argv[2]);
   if (fs.statSync(process.argv[2]).isFile()) {
-    await registerImage(process.argv[2]); // register image
+    await registerImage(process.argv[2]);
   } 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
+    for (const f of dir) await registerImage(path.join(process.argv[2], f));
   }
-  log.info('Comparing:', process.argv[3], 'Descriptors:', labeledFaceDescriptors.length);
+  log.info('Descriptors:', labeledFaceDescriptors.length);
-  if (labeledFaceDescriptors.length > 0) {
+  const bestMatch = await findBestMatch(process.argv[3]);
-    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

@@ -1,16 +1,14 @@
-/**
+// @ts-nocheck
- * FaceAPI Demo for NodeJS
- * - Used by `node-multiprocess.js`
- */
 
 const fs = require('fs');
 const path = require('path');
 const log = require('@vladmandic/pilogger');
 
 // workers actual import tfjs and faceapi modules
+// eslint-disable-next-line import/no-extraneous-dependencies, 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 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 faceapi = require('../dist/face-api.node.js'); // use this when using face-api in dev mode
 
 // options used by faceapi
 const modelPathRoot = '../model';

demo/node-multiprocess.js

@@ -1,9 +1,3 @@
-/**
- * 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');
 const log = require('@vladmandic/pilogger'); // this is my simple logger with few extra features

demo/node-simple.js

@@ -1,13 +1,7 @@
-/**
- * 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)
+const faceapi = require('../dist/face-api.node.js'); // use this when using face-api in dev mode
 
 async function main() {
   await faceapi.nets.ssdMobilenetv1.loadFromDisk('model'); // load models from a specific patch
@@ -25,7 +19,8 @@ async function main() {
     .withFaceDescriptors()
     .withAgeAndGender();
   faceapi.tf.dispose([decodeT, expandT]); // dispose tensors to avoid memory leaks
-  console.log({ result }); // eslint-disable-line no-console
+  // eslint-disable-next-line no-console
+  console.log({ result }); // print results
 }
 
 main();

demo/node-wasm.js

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

demo/node.js

@@ -1,18 +1,12 @@
-/**
- * FaceAPI Demo for NodeJS
- * - Uses external library [node-fetch](https://www.npmjs.com/package/node-fetch) to load images via http
- * - Loads image from provided param
- * - Outputs results to console
- */
-
 const fs = require('fs');
 const process = require('process');
 const path = require('path');
 const log = require('@vladmandic/pilogger');
 
+// eslint-disable-next-line import/no-extraneous-dependencies, 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 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 faceapi = require('../dist/face-api.node.js'); // use this when using face-api in dev mode
 
 const modelPathRoot = '../model';
 const imgPathRoot = './demo'; // modify to include your sample images
@@ -93,10 +87,11 @@ 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;
-  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} Backend: ${faceapi.tf?.getBackend()}`);

demo/webcam.js

@@ -1,14 +1,8 @@
-/**
+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://cdn.jsdelivr.net/npm/@vladmandic/face-api/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 minScore = 0.2; // minimum score
 const maxResults = 5; // maximum number of results to return
 let optionsSSDMobileNet;
@@ -23,14 +17,15 @@ function str(json) {
 
 // helper function to print strings to html document as a log
 function log(...txt) {
-  console.log(...txt); // eslint-disable-line no-console
+  // eslint-disable-next-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', { willReadFrequently: true });
+  const ctx = canvas.getContext('2d');
   if (!ctx) return;
   ctx.clearRect(0, 0, canvas.width, canvas.height);
   // draw title
@@ -47,18 +42,18 @@ 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;
-    // draw text labels
+    // const expression = person.expressions.sort((a, b) => Object.values(a)[0] - Object.values(b)[0]);
     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}° pitch:${person.angle.pitch}° yaw:${person.angle.yaw}°`, person.detection.box.x, person.detection.box.y - 5);
+    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.fillStyle = 'lightblue';
     ctx.fillText(`gender: ${Math.round(100 * person.genderProbability)}% ${person.gender}`, person.detection.box.x, person.detection.box.y - 60);
     ctx.fillText(`expression: ${Math.round(100 * expression[0][1])}% ${expression[0][0]}`, person.detection.box.x, person.detection.box.y - 42);
     ctx.fillText(`age: ${Math.round(person.age)} years`, person.detection.box.x, person.detection.box.y - 24);
-    ctx.fillText(`roll:${person.angle.roll}° pitch:${person.angle.pitch}° yaw:${person.angle.yaw}°`, person.detection.box.x, person.detection.box.y - 6);
+    ctx.fillText(`roll:${person.angle.roll.toFixed(3)} pitch:${person.angle.pitch.toFixed(3)} yaw:${person.angle.yaw.toFixed(3)}`, person.detection.box.x, person.detection.box.y - 6);
     // draw face points for each face
     ctx.globalAlpha = 0.8;
     ctx.fillStyle = 'lightblue';
@@ -66,6 +61,7 @@ function drawFaces(canvas, data, fps) {
     for (let i = 0; i < person.landmarks.positions.length; i++) {
       ctx.beginPath();
       ctx.arc(person.landmarks.positions[i].x, person.landmarks.positions[i].y, pointSize, 0, 2 * Math.PI);
+      // ctx.fillText(`${i}`, person.landmarks.positions[i].x + 4, person.landmarks.positions[i].y + 4);
       ctx.fill();
     }
   }
@@ -99,6 +95,7 @@ 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) {
@@ -106,19 +103,23 @@ async function setupCamera() {
     return null;
   }
   let stream;
-  const constraints = { audio: false, video: { facingMode: 'user', resizeMode: 'crop-and-scale' } };
+  const constraints = {
+    audio: false,
+    video: { facingMode: 'user', resizeMode: 'crop-and-scale' },
+  };
   if (window.innerWidth > window.innerHeight) constraints.video.width = { ideal: window.innerWidth };
   else constraints.video.height = { ideal: window.innerHeight };
   try {
     stream = await navigator.mediaDevices.getUserMedia(constraints);
   } catch (err) {
-    if (err.name === 'PermissionDeniedError' || err.name === 'NotAllowedError') log(`Camera Error: camera permission denied: ${err.message || err}`);
+    if (err.name === 'PermissionDeniedError' || err.name === 'NotAllowedError') msg = 'camera permission denied';
-    if (err.name === 'SourceUnavailableError') log(`Camera Error: camera not available: ${err.message || err}`);
+    else if (err.name === 'SourceUnavailableError') msg = 'camera not available';
+    log(`Camera Error: ${msg}: ${err.message || err}`);
     return null;
   }
-  if (stream) {
+  // @ts-ignore
-    video.srcObject = stream;
+  if (stream) video.srcObject = stream;
-  } else {
+  else {
     log('Camera Error: stream empty');
     return null;
   }
@@ -127,23 +128,31 @@ 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}`);
+  log(`Camera active: ${track.label}`); // ${str(constraints)}
   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);
@@ -161,6 +170,7 @@ 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`);
 }
@@ -170,21 +180,19 @@ 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(`https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@${faceapi.tf.version_core}/dist/`);
+  // await faceapi.tf.setWasmPaths('../node_modules/@tensorflow/tfjs-backend-wasm/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 || '(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

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

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

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

dist/face-api.esm.d.ts

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

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

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

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

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

dist/face-api.node.d.ts

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

dist/tfjs.esm.d.ts

@@ -1,4 +1,3 @@
-/*
 import '@tensorflow/tfjs-core';
 import '@tensorflow/tfjs-core/dist/types';
 import '@tensorflow/tfjs-core/dist/register_all_gradients';
@@ -10,7 +9,6 @@ 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;
@@ -22,7 +20,7 @@ export declare const version: {
   tfjs: string;
 };
 
-export { io, browser, image } from '@tensorflow/tfjs-core';
+// 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

@@ -1,9 +0,0 @@
-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

@@ -4,4 +4,4 @@
   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};
+var e="3.19.0";var s="3.19.0";var t="3.19.0";var i="3.19.0";var n="3.19.0";var r="3.19.0";var l="3.19.0";var a="3.19.0";var G={tfjs:e,"tfjs-core":s,"tfjs-data":t,"tfjs-layers":i,"tfjs-converter":n,"tfjs-backend-cpu":r,"tfjs-backend-webgl":l,"tfjs-backend-wasm":a};export{G as version};

package.json

@@ -1,6 +1,6 @@
 {
   "name": "@vladmandic/face-api",
-  "version": "1.7.15",
+  "version": "1.7.1",
   "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",
@@ -22,8 +22,8 @@
   },
   "scripts": {
     "start": "node --no-warnings demo/node.js",
-    "build": "node build.js",
     "dev": "build --profile development",
+    "build": "node build.js",
     "lint": "eslint src/ demo/",
     "test": "node --trace-warnings test/test-node.js",
     "scan": "npx auditjs@latest ossi --dev --quiet"
@@ -41,39 +41,42 @@
     "tensorflowjs",
     "tfjs"
   ],
+  "optionalDependencies": {
+    "@canvas/image": "^1.0.1",
+    "canvas": "^2.9.3",
+    "node-fetch": "^3.2.9"
+  },
   "devDependencies": {
-    "@canvas/image": "^2.0.0",
+    "@microsoft/api-extractor": "^7.28.6",
-    "@microsoft/api-extractor": "^7.49.2",
+    "@tensorflow/tfjs": "^3.19.0",
-    "@tensorflow/tfjs": "^4.22.0",
+    "@tensorflow/tfjs-backend-cpu": "^3.19.0",
-    "@tensorflow/tfjs-backend-cpu": "^4.22.0",
+    "@tensorflow/tfjs-backend-wasm": "^3.19.0",
-    "@tensorflow/tfjs-backend-wasm": "^4.22.0",
+    "@tensorflow/tfjs-backend-webgl": "^3.19.0",
-    "@tensorflow/tfjs-backend-webgl": "^4.22.0",
+    "@tensorflow/tfjs-backend-webgpu": "0.0.1-alpha.12",
-    "@tensorflow/tfjs-backend-webgpu": "4.22.0",
+    "@tensorflow/tfjs-converter": "^3.19.0",
-    "@tensorflow/tfjs-converter": "^4.22.0",
+    "@tensorflow/tfjs-core": "^3.19.0",
-    "@tensorflow/tfjs-core": "^4.22.0",
+    "@tensorflow/tfjs-data": "^3.19.0",
-    "@tensorflow/tfjs-data": "^4.22.0",
+    "@tensorflow/tfjs-layers": "^3.19.0",
-    "@tensorflow/tfjs-layers": "^4.22.0",
+    "@tensorflow/tfjs-node": "^3.19.0",
-    "@tensorflow/tfjs-node": "^4.22.0",
+    "@tensorflow/tfjs-node-gpu": "^3.19.0",
-    "@tensorflow/tfjs-node-gpu": "^4.22.0",
+    "@types/node": "^18.6.1",
-    "@types/node": "^22.13.1",
+    "@types/offscreencanvas": "^2019.7.0",
-    "@types/offscreencanvas": "^2019.7.3",
+    "@typescript-eslint/eslint-plugin": "^5.30.7",
-    "@typescript-eslint/eslint-plugin": "^8.5.0",
+    "@typescript-eslint/parser": "^5.30.7",
-    "@typescript-eslint/parser": "^8.5.0",
+    "@vladmandic/build": "^0.7.7",
-    "@vladmandic/build": "^0.10.2",
+    "@vladmandic/pilogger": "^0.4.5",
-    "@vladmandic/pilogger": "^0.5.1",
+    "@vladmandic/tfjs": "github:vladmandic/tfjs",
-    "ajv": "^8.17.1",
+    "esbuild": "^0.14.50",
-    "esbuild": "^0.24.2",
+    "eslint": "^8.20.0",
-    "eslint": "8.57.0",
     "eslint-config-airbnb-base": "^15.0.0",
-    "eslint-plugin-import": "^2.30.0",
+    "eslint-plugin-import": "^2.26.0",
-    "eslint-plugin-json": "^4.0.1",
+    "eslint-plugin-json": "^3.1.0",
     "eslint-plugin-node": "^11.1.0",
-    "eslint-plugin-promise": "^7.1.0",
+    "eslint-plugin-promise": "^6.0.0",
-    "node-fetch": "^3.3.2",
+    "rimraf": "^3.0.2",
-    "rimraf": "^6.0.1",
     "seedrandom": "^3.0.5",
-    "tslib": "^2.8.1",
+    "tslib": "^2.4.0",
-    "typedoc": "^0.27.6",
+    "typedoc": "^0.23.9",
-    "typescript": "5.7.3"
+    "typescript": "4.7.4"
   }
 }

src/NeuralNetwork.ts

@@ -102,9 +102,8 @@ 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) => (typeof buf === 'string' ? Buffer.from(buf) : buf.buffer))));
+    const fetchWeightsFromDisk = (filePaths: string[]) => Promise.all(filePaths.map((fp) => readFile(fp).then((buf) => buf.buffer)));
-    // @ts-ignore async-vs-sync mismatch
+    const loadWeights = tf.io.weightsLoaderFactory(fetchWeightsFromDisk);
-    const loadWeights = tf['io'].weightsLoaderFactory(fetchWeightsFromDisk);
     const manifest = JSON.parse((await readFile(manifestUri)).toString());
     const weightMap = await loadWeights(manifest, modelBaseUri);
     this.loadFromWeightMap(weightMap);

src/dom/NetInput.ts

@@ -131,14 +131,14 @@ export class NetInput {
           imgTensor = padToSquare(imgTensor as tf.Tensor4D, isCenterInputs);
 
           if (imgTensor.shape[1] !== inputSize || imgTensor.shape[2] !== inputSize) {
-            imgTensor = tf['image'].resizeBilinear(imgTensor as tf.Tensor4D, [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}`);

src/dom/awaitMediaLoaded.ts

@@ -4,10 +4,7 @@ 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)) {
+    if (media instanceof env.getEnv().Canvas || isMediaLoaded(media)) resolve(null);
-      resolve(null);
-      return;
-    }
 
     function onError(e: Event) {
       if (!e.currentTarget) return;

src/dom/getContext2dOrThrow.ts

@@ -3,10 +3,21 @@ 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');
+
-  const ctx = canvas.getContext('2d', { willReadFrequently: true });
+  if (!(canvas instanceof Canvas)) {
-  if (!ctx) throw new Error('resolveContext2d - canvas 2d context is null');
+    throw new Error('resolveContext2d - expected canvas to be of instance of Canvas');
+  }
+
+  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

@@ -8,8 +8,7 @@ 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

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

src/env/createFileSystem.ts

@@ -5,7 +5,7 @@ export function createFileSystem(fs?: any): FileSystem {
   let requireFsError = '';
   if (!fs && isNodejs()) {
     try {
-      // eslint-disable-next-line global-require, @typescript-eslint/no-require-imports
+      // eslint-disable-next-line global-require
       fs = require('fs');
     } catch (err) {
       requireFsError = (err as any).toString();
@@ -13,8 +13,7 @@ export function createFileSystem(fs?: any): FileSystem {
   }
 
   const readFile = fs
-    // eslint-disable-next-line no-undef
+    ? (filePath: string) => new Promise((resolve, reject) => { fs.readFile(filePath, (err: any, 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 };
 }

src/env/createNodejsEnv.ts

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

src/env/types.ts

@@ -1,17 +1,17 @@
 export type FileSystem = {
   // eslint-disable-next-line no-unused-vars
-  readFile: (filePath: string) => Promise<string | Buffer>;
+  readFile: (filePath: string) => Promise<any>
-};
+}
 
 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

@@ -1,10 +1,12 @@
 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 * diff), 0),
+      .reduce((res, diff) => res + (diff ** 2), 0),
   );
 }

src/faceExpressionNet/FaceExpressions.ts

@@ -1,4 +1,4 @@
-export const FACE_EXPRESSION_LABELS = ['neutral', 'happy', 'sad', 'angry', 'fearful', 'disgusted', 'surprised'] as const;
+export const FACE_EXPRESSION_LABELS = ['neutral', 'happy', 'sad', 'angry', 'fearful', 'disgusted', 'surprised'];
 
 export class FaceExpressions {
   public neutral = 0;

src/factories/WithFaceLandmarks.ts

@@ -1,4 +1,3 @@
-import { Point } from '../classes';
 import { FaceDetection } from '../classes/FaceDetection';
 import { FaceLandmarks } from '../classes/FaceLandmarks';
 import { FaceLandmarks68 } from '../classes/FaceLandmarks68';
@@ -6,106 +5,72 @@ import { isWithFaceDetection, WithFaceDetection } from './WithFaceDetection';
 
 export type WithFaceLandmarks<
   TSource extends WithFaceDetection<{}>,
-  TFaceLandmarks extends FaceLandmarks = FaceLandmarks68
+  TFaceLandmarks extends FaceLandmarks = FaceLandmarks68 > = TSource & {
-> = TSource & {
+    landmarks: TFaceLandmarks,
-  landmarks: TFaceLandmarks;
+    unshiftedLandmarks: TFaceLandmarks,
-  unshiftedLandmarks: TFaceLandmarks;
+    alignedRect: FaceDetection,
-  alignedRect: FaceDetection;
+    angle: { roll: number | undefined, pitch: number | undefined, yaw: number | undefined },
-  angle: {
-    roll: number | undefined;
-    pitch: number | undefined;
-    yaw: number | undefined;
-  };
-};
-
-export function isWithFaceLandmarks(
-  obj: any,
-): obj is WithFaceLandmarks<WithFaceDetection<{}>, FaceLandmarks> {
-  return (
-    isWithFaceDetection(obj)
-    && (obj as any)['landmarks'] instanceof FaceLandmarks
-    && (obj as any)['unshiftedLandmarks'] instanceof FaceLandmarks
-    && (obj as any)['alignedRect'] instanceof FaceDetection
-  );
   }
 
-function calculateFaceAngle(mesh: FaceLandmarks) {
+export function isWithFaceLandmarks(obj: any): obj is WithFaceLandmarks<WithFaceDetection<{}>, FaceLandmarks> {
-  // Helper to convert radians to degrees
+  return isWithFaceDetection(obj)
+    // eslint-disable-next-line dot-notation
+    && obj['landmarks'] instanceof FaceLandmarks
+    // eslint-disable-next-line dot-notation
+    && obj['unshiftedLandmarks'] instanceof FaceLandmarks
+    // eslint-disable-next-line dot-notation
+    && obj['alignedRect'] instanceof FaceDetection;
+}
+
+function calculateFaceAngle(mesh) {
+  // returns the angle in the plane (in radians) between the positive x-axis and the ray from (0,0) to the point (x,y)
+  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 = (radians: number) => (radians * 180) / Math.PI;
+  const degrees = (theta) => (theta * 180) / Math.PI;
-  const calcLengthBetweenTwoPoints = (a: Point, b: Point) => Math.sqrt((a.x - b.x) ** 2 + (a.y - b.y) ** 2);
 
-  const angle = {
+  const angle = { roll: <number | undefined>undefined, pitch: <number | undefined>undefined, yaw: <number | undefined>undefined };
-    roll: <number | undefined>undefined,
-    pitch: <number | undefined>undefined,
-    yaw: <number | undefined>undefined,
-  };
 
-  const calcYaw = (leftPoint: Point, midPoint: Point, rightPoint: Point) => {
+  if (!mesh || !mesh._positions || mesh._positions.length !== 68) return angle;
-    // Calc x-distance from left side of the face ("ear") to facial midpoint ("nose")
+  const pt = mesh._positions;
-    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;
-  };
 
-  const calcRoll = (lever: Point, pivot: Point) => {
+  // values are in radians in range of -pi/2 to pi/2 which is -90 to +90 degrees
-    // When rolling, the head seems to pivot from the nose/lips/chin area.
+  // value of 0 means center
-    // 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;
-  };
 
-  const calcPitch = (leftPoint: Point, midPoint: Point, rightPoint: Point) => {
+  // roll is face lean from left to right
-    // Theory: While pitching, the nose is the most salient point --> That's what we'll use to make a trianle.
+  // comparing x,y of outside corners of leftEye and rightEye
-    // 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).
+  angle.roll = -radians(pt[36]._x, pt[36]._y, pt[45]._x, pt[45]._y);
-    // Executuin: Get the opposite & adjacent lengths of the triangle from the ear's perspective. Use it to get angle.
 
-    const base = calcLengthBetweenTwoPoints(leftPoint, rightPoint);
+  // pitch is face turn from left right
-    // adjecent is base/2 technically.
+  // comparing x distance of top of nose to left and right edge of face
-    const baseCoords = new Point((leftPoint.x + rightPoint.x) / 2, (leftPoint.y + rightPoint.y) / 2);
+  // precision is lacking since coordinates are not precise enough
-    const midToBaseLength = calcLengthBetweenTwoPoints(midPoint, baseCoords);
+  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 angleInRadians = Math.atan(midToBaseLength / base);
+
-    const angleInDegrees = Math.floor(degrees(angleInRadians));
+  // yaw is face move from up to down
-    // Account for directionality.
+  // comparing size of the box around the face with top and bottom of detected landmarks
-    // pitch forwards (_i.e. tilting your head forwards) is positive (or no sign); backward is negative.
+  // silly hack, but this gives us face compression on y-axis
-    const direction = baseCoords.y - midPoint.y < 0 ? -1 : 1;
+  // e.g., tilting head up hides the forehead that doesn't have any landmarks so ratio drops
-    const result = angleInDegrees * direction;
+  const bottom = pt.reduce((prev, cur) => (prev < cur._y ? prev : cur._y), +Infinity);
-    return result;
+  const top = pt.reduce((prev, cur) => (prev > cur._y ? prev : cur._y), -Infinity);
-  };
+  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<TSource extends WithFaceDetection<{}>, TFaceLandmarks extends FaceLandmarks = FaceLandmarks68>(
+export function extendWithFaceLandmarks<TSource extends WithFaceDetection<{}>, TFaceLandmarks extends FaceLandmarks = FaceLandmarks68 >(sourceObj: TSource, unshiftedLandmarks: TFaceLandmarks): WithFaceLandmarks<TSource, TFaceLandmarks> {
-  sourceObj: TSource,
-  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(
+  const alignedRect = new FaceDetection(sourceObj.detection.score, rect.rescale(imageDims.reverse()), imageDims);
-    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/tfjs/tf-custom.ts

@@ -0,0 +1,4 @@
+/** Creates tfjs bundle used by Human browser build target
+ * @external
+ */
+export * from '@vladmandic/tfjs';

src/tfjs/tf-node-cpu.ts

@@ -0,0 +1,4 @@
+/* eslint-disable import/no-extraneous-dependencies */
+/* eslint-disable node/no-unpublished-import */
+
+export * from '@tensorflow/tfjs';

src/tfjs/tf-node-gpu.ts

@@ -1,2 +1,4 @@
+/* eslint-disable import/no-extraneous-dependencies */
+/* eslint-disable node/no-unpublished-import */
+
 export * from '@tensorflow/tfjs-node-gpu';
-export { version } from '../../dist/tfjs.version.js';

src/tfjs/tf-node-wasm.ts

@@ -1,3 +1,5 @@
+/* eslint-disable import/no-extraneous-dependencies */
+/* eslint-disable node/no-unpublished-import */
+
 export * from '@tensorflow/tfjs';
 export * from '@tensorflow/tfjs-backend-wasm';
-export { version } from '../../dist/tfjs.version.js';

src/tfjs/tf-node.ts

@@ -1,2 +1,4 @@
+/* eslint-disable import/no-extraneous-dependencies */
+/* eslint-disable node/no-unpublished-import */
+
 export * from '@tensorflow/tfjs-node';
-export { version } from '../../dist/tfjs.version.js';

src/tfjs/tf-version.ts

@@ -1,19 +1,18 @@
 // get versions of all packages
-// import { version as tfjsVersion } from '@tensorflow/tfjs/package.json';
+import { version as tfjsVersion } from '@tensorflow/tfjs/package.json';
 import { version as tfjsCoreVersion } from '@tensorflow/tfjs-core/package.json';
-// import { version as tfjsDataVersion } from '@tensorflow/tfjs-data/package.json';
+import { version as tfjsDataVersion } from '@tensorflow/tfjs-data/package.json';
-// import { version as tfjsLayersVersion } from '@tensorflow/tfjs-layers/package.json';
+import { version as tfjsLayersVersion } from '@tensorflow/tfjs-layers/package.json';
 import { version as tfjsConverterVersion } from '@tensorflow/tfjs-converter/package.json';
 import { version as tfjsBackendCPUVersion } from '@tensorflow/tfjs-backend-cpu/package.json';
 import { version as tfjsBackendWebGLVersion } from '@tensorflow/tfjs-backend-webgl/package.json';
 import { version as tfjsBackendWASMVersion } from '@tensorflow/tfjs-backend-wasm/package.json';
 
 export const version = {
-  // tfjs: tfjsVersion,
+  tfjs: tfjsVersion,
-  tfjs: tfjsCoreVersion,
   'tfjs-core': tfjsCoreVersion,
-  // 'tfjs-data': tfjsDataVersion,
+  'tfjs-data': tfjsDataVersion,
-  // 'tfjs-layers': tfjsLayersVersion,
+  'tfjs-layers': tfjsLayersVersion,
   'tfjs-converter': tfjsConverterVersion,
   'tfjs-backend-cpu': tfjsBackendCPUVersion,
   'tfjs-backend-webgl': tfjsBackendWebGLVersion,

src/tinyYolov2/TinyYolov2Base.ts

@@ -19,7 +19,7 @@ import { extractParams } from './extractParams';
 import { extractParamsFromWeightMap } from './extractParamsFromWeightMap';
 import { leaky } from './leaky';
 import { ITinyYolov2Options, TinyYolov2Options } from './TinyYolov2Options';
-import { DefaultTinyYolov2NetParams, MobilenetParams, TinyYolov2ExtractBoxesResult, TinyYolov2NetParams } from './types';
+import { DefaultTinyYolov2NetParams, MobilenetParams, TinyYolov2NetParams } from './types';
 
 export class TinyYolov2Base extends NeuralNetwork<TinyYolov2NetParams> {
   public static DEFAULT_FILTER_SIZES = [3, 16, 32, 64, 128, 256, 512, 1024, 1024];
@@ -183,9 +183,9 @@ export class TinyYolov2Base extends NeuralNetwork<TinyYolov2NetParams> {
       return [boxes, scores, classScores];
     });
 
-    const results: TinyYolov2ExtractBoxesResult[] = [];
+    const results = [] as any;
-    const scoresData = await scoresTensor.array() as number[][][][];
+    const scoresData = await scoresTensor.array();
-    const boxesData = await boxesTensor.array() as number[][][][];
+    const boxesData = await boxesTensor.array();
     for (let row = 0; row < numCells; row++) {
       for (let col = 0; col < numCells; col++) {
         for (let anchor = 0; anchor < numBoxes; anchor++) {

src/tinyYolov2/types.ts

@@ -1,5 +1,4 @@
 import * as tf from '../../dist/tfjs.esm';
-import { BoundingBox } from '../classes';
 
 import { ConvParams } from '../common/index';
 import { SeparableConvParams } from '../common/types';
@@ -39,13 +38,3 @@ export type DefaultTinyYolov2NetParams = {
 }
 
 export type TinyYolov2NetParams = DefaultTinyYolov2NetParams | MobilenetParams
-
-export type TinyYolov2ExtractBoxesResult = {
-  box: BoundingBox;
-  score: number;
-  classScore: number;
-  label: number;
-  row: number;
-  col: number;
-  anchor: number;
-}

src/types/eslint.json

@@ -1,51 +0,0 @@
-{
-  "globals": {},
-  "env": {
-      "browser": true,
-      "commonjs": true,
-      "node": true,
-      "es2022": true
-  },
-  "parser": "@typescript-eslint/parser",
-  "parserOptions": {
-    "ecmaVersion": "latest"
-  },
-  "plugins": [
-    "@typescript-eslint"
-  ],
-  "extends": [
-    "airbnb-base",
-    "eslint:recommended",
-    "plugin:@typescript-eslint/eslint-recommended",
-    "plugin:@typescript-eslint/recommended"
-  ],
-  "rules": {
-    "max-len": [1, 1000, 3],
-    "@typescript-eslint/ban-types":"off",
-    "@typescript-eslint/no-empty-interface":"off",
-    "@typescript-eslint/no-explicit-any":"off",
-    "@typescript-eslint/no-extraneous-class":"off",
-    "@typescript-eslint/no-unnecessary-type-constraint":"off",
-    "@typescript-eslint/no-unused-vars":"off",
-    "@typescript-eslint/prefer-function-type":"off",
-    "@typescript-eslint/unified-signatures":"off",
-    "@typescript-eslint/triple-slash-reference":"off",
-    "camelcase":"off",
-    "comma-dangle":"off",
-    "import/extensions":"off",
-    "import/no-duplicates":"off",
-    "import/no-mutable-exports":"off",
-    "import/no-unresolved":"off",
-    "indent":"off",
-    "lines-between-class-members":"off",
-    "max-classes-per-file":"off",
-    "no-multiple-empty-lines":"off",
-    "no-shadow":"off",
-    "no-tabs":"off",
-    "no-underscore-dangle":"off",
-    "no-use-before-define":"off",
-    "object-curly-newline":"off",
-    "quotes":"off",
-    "semi":"off"
-  }
-}

src/types/long.d.ts

@@ -1,392 +0,0 @@
-/* eslint-disable */
-
-// Type definitions for long.js 4.0.0
-// Project: https://github.com/dcodeIO/long.js
-// Definitions by: Peter Kooijmans <https://github.com/peterkooijmans>
-// Definitions: https://github.com/DefinitelyTyped/DefinitelyTyped
-// Definitions by: Denis Cappellin <https://github.com/cappellin>
-
-export = Long;
-export as namespace Long;
-
-declare const Long: Long.LongConstructor;
-type Long = Long.Long;
-declare namespace Long {
-  interface LongConstructor {
-    /**
-     * Constructs a 64 bit two's-complement integer, given its low and high 32 bit values as signed integers. See the from* functions below for more convenient ways of constructing Longs.
-     */
-    new(low: number, high?: number, unsigned?: boolean): Long;
-    prototype: Long;
-    /**
-     * Maximum unsigned value.
-     */
-    MAX_UNSIGNED_VALUE: Long;
-
-    /**
-     * Maximum signed value.
-     */
-    MAX_VALUE: Long;
-
-    /**
-     * Minimum signed value.
-     */
-    MIN_VALUE: Long;
-
-    /**
-     * Signed negative one.
-     */
-    NEG_ONE: Long;
-
-    /**
-     * Signed one.
-     */
-    ONE: Long;
-
-    /**
-     * Unsigned one.
-     */
-    UONE: Long;
-
-    /**
-     * Unsigned zero.
-     */
-    UZERO: Long;
-
-    /**
-     * Signed zero
-     */
-    ZERO: Long;
-
-    /**
-     * Returns a Long representing the 64 bit integer that comes by concatenating the given low and high bits. Each is assumed to use 32 bits.
-     */
-    fromBits(lowBits:number, highBits:number, unsigned?:boolean): Long;
-
-    /**
-     * Returns a Long representing the given 32 bit integer value.
-     */
-    fromInt(value: number, unsigned?: boolean): Long;
-
-    /**
-     * Returns a Long representing the given value, provided that it is a finite number. Otherwise, zero is returned.
-     */
-    fromNumber(value: number, unsigned?: boolean): Long;
-
-    /**
-     * Returns a Long representation of the given string, written using the specified radix.
-     */
-    fromString(str: string, unsigned?: boolean | number, radix?: number): Long;
-
-    /**
-     * Creates a Long from its byte representation.
-     */
-    fromBytes(bytes: number[], unsigned?: boolean, le?: boolean): Long;
-
-    /**
-     * Creates a Long from its little endian byte representation.
-     */
-    fromBytesLE(bytes: number[], unsigned?: boolean): Long;
-
-    /**
-     * Creates a Long from its little endian byte representation.
-     */
-    fromBytesBE(bytes: number[], unsigned?: boolean): Long;
-
-    /**
-     * Tests if the specified object is a Long.
-     */
-    // eslint-disable-next-line @typescript-eslint/no-explicit-any
-    isLong(obj: any): obj is Long;
-
-    /**
-     * Converts the specified value to a Long.
-     */
-    fromValue(val: Long | number | string | {low: number, high: number, unsigned: boolean}): Long;
-  }
-  interface Long
-  {
-    /**
-     * The high 32 bits as a signed value.
-     */
-    high: number;
-
-    /**
-     * The low 32 bits as a signed value.
-     */
-    low: number;
-
-    /**
-     * Whether unsigned or not.
-     */
-    unsigned: boolean;
-
-    /**
-     * Returns the sum of this and the specified Long.
-     */
-    add(addend: number | Long | string): Long;
-
-    /**
-     * Returns the bitwise AND of this Long and the specified.
-     */
-    and(other: Long | number | string): Long;
-
-    /**
-     * Compares this Long's value with the specified's.
-     */
-    compare(other: Long | number | string): number;
-
-    /**
-     * Compares this Long's value with the specified's.
-     */
-    comp(other: Long | number | string): number;
-
-    /**
-     * Returns this Long divided by the specified.
-     */
-    divide(divisor: Long | number | string): Long;
-
-    /**
-     * Returns this Long divided by the specified.
-     */
-    div(divisor: Long | number | string): Long;
-
-    /**
-     * Tests if this Long's value equals the specified's.
-     */
-    equals(other: Long | number | string): boolean;
-
-    /**
-     * Tests if this Long's value equals the specified's.
-     */
-    eq(other: Long | number | string): boolean;
-
-    /**
-     * Gets the high 32 bits as a signed integer.
-     */
-    getHighBits(): number;
-
-    /**
-     * Gets the high 32 bits as an unsigned integer.
-     */
-    getHighBitsUnsigned(): number;
-
-    /**
-     * Gets the low 32 bits as a signed integer.
-     */
-    getLowBits(): number;
-
-    /**
-     * Gets the low 32 bits as an unsigned integer.
-     */
-    getLowBitsUnsigned(): number;
-
-    /**
-     * Gets the number of bits needed to represent the absolute value of this Long.
-     */
-    getNumBitsAbs(): number;
-
-    /**
-     * Tests if this Long's value is greater than the specified's.
-     */
-    greaterThan(other: Long | number | string): boolean;
-
-    /**
-     * Tests if this Long's value is greater than the specified's.
-     */
-    gt(other: Long | number | string): boolean;
-
-    /**
-     * Tests if this Long's value is greater than or equal the specified's.
-     */
-    greaterThanOrEqual(other: Long | number | string): boolean;
-
-    /**
-     * Tests if this Long's value is greater than or equal the specified's.
-     */
-    gte(other: Long | number | string): boolean;
-
-    /**
-     * Tests if this Long's value is even.
-     */
-    isEven(): boolean;
-
-    /**
-     * Tests if this Long's value is negative.
-     */
-    isNegative(): boolean;
-
-    /**
-     * Tests if this Long's value is odd.
-     */
-    isOdd(): boolean;
-
-    /**
-     * Tests if this Long's value is positive.
-     */
-    isPositive(): boolean;
-
-    /**
-     * Tests if this Long's value equals zero.
-     */
-    isZero(): boolean;
-
-    /**
-     * Tests if this Long's value is less than the specified's.
-     */
-    lessThan(other: Long | number | string): boolean;
-
-    /**
-     * Tests if this Long's value is less than the specified's.
-     */
-    lt(other: Long | number | string): boolean;
-
-    /**
-     * Tests if this Long's value is less than or equal the specified's.
-     */
-    lessThanOrEqual(other: Long | number | string): boolean;
-
-    /**
-     * Tests if this Long's value is less than or equal the specified's.
-     */
-    lte(other: Long | number | string): boolean;
-
-    /**
-     * Returns this Long modulo the specified.
-     */
-    modulo(other: Long | number | string): Long;
-
-    /**
-     * Returns this Long modulo the specified.
-     */
-    mod(other: Long | number | string): Long;
-
-    /**
-     * Returns the product of this and the specified Long.
-     */
-    multiply(multiplier: Long | number | string): Long;
-
-    /**
-     * Returns the product of this and the specified Long.
-     */
-    mul(multiplier: Long | number | string): Long;
-
-    /**
-     * Negates this Long's value.
-     */
-    negate(): Long;
-
-    /**
-     * Negates this Long's value.
-     */
-    neg(): Long;
-
-    /**
-     * Returns the bitwise NOT of this Long.
-     */
-    not(): Long;
-
-    /**
-     * Tests if this Long's value differs from the specified's.
-     */
-    notEquals(other: Long | number | string): boolean;
-
-    /**
-     * Tests if this Long's value differs from the specified's.
-     */
-    neq(other: Long | number | string): boolean;
-
-    /**
-     * Returns the bitwise OR of this Long and the specified.
-     */
-    or(other: Long | number | string): Long;
-
-    /**
-     * Returns this Long with bits shifted to the left by the given amount.
-     */
-    shiftLeft(numBits: number | Long): Long;
-
-    /**
-     * Returns this Long with bits shifted to the left by the given amount.
-     */
-    shl(numBits: number | Long): Long;
-
-    /**
-     * Returns this Long with bits arithmetically shifted to the right by the given amount.
-     */
-    shiftRight(numBits: number | Long): Long;
-
-    /**
-     * Returns this Long with bits arithmetically shifted to the right by the given amount.
-     */
-    shr(numBits: number | Long): Long;
-
-    /**
-     * Returns this Long with bits logically shifted to the right by the given amount.
-     */
-    shiftRightUnsigned(numBits: number | Long): Long;
-
-    /**
-     * Returns this Long with bits logically shifted to the right by the given amount.
-     */
-    shru(numBits: number | Long): Long;
-
-    /**
-     * Returns the difference of this and the specified Long.
-     */
-    subtract(subtrahend: number | Long | string): Long;
-
-    /**
-     * Returns the difference of this and the specified Long.
-     */
-    sub(subtrahend: number | Long |string): Long;
-
-    /**
-     * Converts the Long to a 32 bit integer, assuming it is a 32 bit integer.
-     */
-    toInt(): number;
-
-    /**
-     * Converts the Long to a the nearest floating-point representation of this value (double, 53 bit mantissa).
-     */
-    toNumber(): number;
-
-    /**
-     * Converts this Long to its byte representation.
-     */
-
-    toBytes(le?: boolean): number[];
-
-    /**
-     * Converts this Long to its little endian byte representation.
-     */
-
-    toBytesLE(): number[];
-
-    /**
-     * Converts this Long to its big endian byte representation.
-     */
-
-    toBytesBE(): number[];
-
-    /**
-     * Converts this Long to signed.
-     */
-    toSigned(): Long;
-
-    /**
-     * Converts the Long to a string written in the specified radix.
-     */
-    toString(radix?: number): string;
-
-    /**
-     * Converts this Long to unsigned.
-     */
-    toUnsigned(): Long;
-
-    /**
-     * Returns the bitwise XOR of this Long and the given one.
-     */
-    xor(other: Long | number | string): Long;
-  }
-}

src/types/offscreencanvas.d.ts

@@ -1,86 +0,0 @@
-/* eslint-disable */
-
-// explicit copy of @types/offscreencanvas to enable typedef bundling
-
-// Type definitions for non-npm package offscreencanvas-browser 2019.6
-// Project: https://html.spec.whatwg.org/multipage/canvas.html#the-offscreencanvas-interface
-// Definitions by: Klaus Reimer <https://github.com/kayahr>
-//                        Oleg Varaksin <https://github.com/ova2>
-// Definitions: https://github.com/DefinitelyTyped/DefinitelyTyped
-// TypeScript Version: 4.3
-
-// https://html.spec.whatwg.org/multipage/canvas.html#dom-canvas-transfercontroltooffscreen
-export interface HTMLCanvasElement {
-  transferControlToOffscreen(): OffscreenCanvas;
-}
-
-// https://html.spec.whatwg.org/multipage/canvas.html#offscreencanvasrenderingcontext2d
-export interface OffscreenCanvasRenderingContext2D extends CanvasState, CanvasTransform, CanvasCompositing,
-  CanvasImageSmoothing, CanvasFillStrokeStyles, CanvasShadowStyles, CanvasFilters, CanvasRect, CanvasDrawPath,
-  CanvasText, CanvasDrawImage, CanvasImageData, CanvasPathDrawingStyles, CanvasTextDrawingStyles, CanvasPath {
-  readonly canvas: OffscreenCanvas;
-}
-
-declare var OffscreenCanvasRenderingContext2D: {
-  prototype: OffscreenCanvasRenderingContext2D;
-  new(): OffscreenCanvasRenderingContext2D;
-};
-
-// https://html.spec.whatwg.org/multipage/canvas.html#the-offscreencanvas-interface
-// Possible contextId values are defined by the enum OffscreenRenderingContextId { "2d", "bitmaprenderer", "webgl", "webgl2" }
-// See also description: https://developer.mozilla.org/en-US/docs/Web/API/OffscreenCanvas/getContext
-export interface OffscreenCanvas extends EventTarget {
-  width: number;
-  height: number;
-
-  getContext(contextId: "2d", contextAttributes?: CanvasRenderingContext2DSettings): OffscreenCanvasRenderingContext2D | null;
-
-  getContext(contextId: "bitmaprenderer", contextAttributes?: WebGLContextAttributes): ImageBitmapRenderingContext | null;
-
-  getContext(contextId: "webgl", contextAttributes?: WebGLContextAttributes): WebGLRenderingContext | null;
-
-  getContext(contextId: "webgl2", contextAttributes?: WebGLContextAttributes): WebGL2RenderingContext | null;
-
-  convertToBlob(options?: { type?: string | undefined, quality?: number | undefined }): Promise<Blob>;
-
-  transferToImageBitmap(): ImageBitmap;
-}
-
-// https://html.spec.whatwg.org/multipage/canvas.html#canvasdrawimage
-export interface CanvasDrawImage {
-  drawImage(image: CanvasImageSource | OffscreenCanvas, dx: number, dy: number): void;
-
-  drawImage(image: CanvasImageSource | OffscreenCanvas, dx: number, dy: number, dw: number, dh: number): void;
-
-  drawImage(image: CanvasImageSource | OffscreenCanvas, sx: number, sy: number, sw: number, sh: number,
-            dx: number, dy: number, dw: number, dh: number): void;
-}
-
-// https://html.spec.whatwg.org/multipage/imagebitmap-and-animations.html#dom-createimagebitmap
-declare function createImageBitmap(image: ImageBitmapSource | OffscreenCanvas): Promise<ImageBitmap>;
-declare function createImageBitmap(image: ImageBitmapSource | OffscreenCanvas, sx: number, sy: number,
-                                 sw: number, sh: number): Promise<ImageBitmap>;
-
-// OffscreenCanvas should be a part of Transferable => extend all postMessage methods
-export interface Worker {
-  postMessage(message: any, transfer?: Array<Transferable | OffscreenCanvas>): void;
-}
-
-export interface ServiceWorker {
-  postMessage(message: any, transfer?: Array<Transferable | OffscreenCanvas>): void;
-}
-
-export interface MessagePort {
-  postMessage(message: any, transfer?: Array<Transferable | OffscreenCanvas>): void;
-}
-
-export interface Window {
-  postMessage(message: any, targetOrigin: string, transfer?: Array<Transferable | OffscreenCanvas>): void;
-}
-
-declare function postMessage(message: any, targetOrigin: string, transfer?: Array<Transferable | OffscreenCanvas>): void;
-
-declare var OffscreenCanvas: {
-  prototype: OffscreenCanvas;
-  new(width: number, height: number): OffscreenCanvas;
-};

src/types/tfjs.esm.d.ts

@@ -1,25 +0,0 @@
-/* eslint-disable import/no-unresolved */
-/* eslint-disable import/no-extraneous-dependencies */
-
-export * from 'types/tfjs.esm';
-
-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 * from '@tensorflow/tfjs-core';
-export * from '@tensorflow/tfjs-converter';
-export * from '@tensorflow/tfjs-data';
-export * from '@tensorflow/tfjs-layers';
-export * from '@tensorflow/tfjs-backend-cpu';
-export * from '@tensorflow/tfjs-backend-wasm';
-export * from '@tensorflow/tfjs-backend-webgl';
-export * from '@tensorflow/tfjs-backend-webgpu';
-export * from '@tensorflow/tfjs-node';
-export * from '@tensorflow/tfjs-node-gpu';

src/types/tsconfig.json

@@ -1,49 +0,0 @@
-{
-  "compilerOptions": {
-    "module": "esnext",
-    "target": "esnext",
-    "moduleResolution": "node",
-    "baseUrl": "./",
-    "lib": ["esnext", "dom"],
-    "allowJs": true,
-    "allowSyntheticDefaultImports": false,
-    "allowUnreachableCode": false,
-    "allowUnusedLabels": false,
-    "alwaysStrict": true,
-    "declaration": true,
-    "declarationMap": true,
-    "emitDecoratorMetadata": true,
-    "esModuleInterop": false,
-    "exactOptionalPropertyTypes": true,
-    "experimentalDecorators": true,
-    "forceConsistentCasingInFileNames": true,
-    "importHelpers": true,
-    "importsNotUsedAsValues": "error",
-    "isolatedModules": false,
-    "noEmitHelpers": true,
-    "noEmitOnError": false,
-    "noFallthroughCasesInSwitch": true,
-    "noImplicitAny": false,
-    "noImplicitOverride": true,
-    "noImplicitReturns": true,
-    "noImplicitThis": true,
-    "noPropertyAccessFromIndexSignature": false,
-    "noUncheckedIndexedAccess": false,
-    "noUnusedLocals": true,
-    "noUnusedParameters": true,
-    "preserveConstEnums": true,
-    "pretty": true,
-    "removeComments": false,
-    "resolveJsonModule": true,
-    "skipLibCheck": true,
-    "sourceMap": true,
-    "strictBindCallApply": true,
-    "strictFunctionTypes": true,
-    "strictNullChecks": true,
-    "strictPropertyInitialization": true,
-    "stripInternal": false,
-    "useDefineForClassFields": true,
-    "useUnknownInCatchVariables": true
-  },
-  "exclude": ["node_modules/", "dist/**/*.js"]
-}

src/xception/extractParams.ts

@@ -56,7 +56,7 @@ export function extractParams(weights: Float32Array, numMainBlocks: number): { p
     reduction_block_1: entry_flow_reduction_block_1,
   };
 
-  const middle_flow: Record<`main_block_${number}`, MainBlockParams> = {};
+  const middle_flow = {};
   range(numMainBlocks, 0, 1).forEach((idx) => {
     middle_flow[`main_block_${idx}`] = extractMainBlockParams(128, `middle_flow/main_block_${idx}`);
   });

src/xception/extractParamsFromWeightMap.ts

@@ -58,7 +58,7 @@ export function extractParamsFromWeightMap(
     reduction_block_1: entry_flow_reduction_block_1,
   };
 
-  const middle_flow: Record<`main_block_${number}`, MainBlockParams> = {};
+  const middle_flow = {};
   range(numMainBlocks, 0, 1).forEach((idx) => {
     middle_flow[`main_block_${idx}`] = extractMainBlockParams(`middle_flow/main_block_${idx}`);
   });

src/xception/types.ts

@@ -18,7 +18,7 @@ export type TinyXceptionParams = {
     reduction_block_0: ReductionBlockParams
     reduction_block_1: ReductionBlockParams
   }
-  middle_flow: Record<`main_block_${number}`, MainBlockParams>,
+  middle_flow: any,
   exit_flow: {
     reduction_block: ReductionBlockParams
     separable_conv: SeparableConvParams

test/test-node.js

@@ -1,6 +1,8 @@
 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');
+// eslint-disable-next-line import/no-extraneous-dependencies, node/no-unpublished-require
 const tf = require('@tensorflow/tfjs-node');
 const faceapi = require('../dist/face-api.node.js'); // this is equivalent to '@vladmandic/faceapi'
 

tsconfig.json

@@ -15,7 +15,7 @@
     "experimentalDecorators": true,
     "importHelpers": true,
     "noFallthroughCasesInSwitch": true,
-    "noImplicitAny": true,
+    "noImplicitAny": false,
     "noImplicitOverride": true,
     "noImplicitReturns": true,
     "noImplicitThis": true,
@@ -32,11 +32,11 @@
     "strictBindCallApply": true,
     "strictFunctionTypes": true,
     "strictNullChecks": true,
-    "strictPropertyInitialization": true
+    "strictPropertyInitialization": true,
   },
   "formatCodeOptions": { "indentSize": 2, "tabSize": 2 },
   "include": ["src"],
-  "exclude": ["node_modules/**"],
+  "exclude": ["node_modules"],
   "typedocOptions": {
     "excludePrivate": true,
     "excludeExternals": true,
@@ -48,6 +48,7 @@
     "theme": "default",
     "readme": "none",
     "out": "typedoc",
-    "logLevel": "Verbose"
+    "logLevel": "Verbose",
+    "logger": "none",
   }
 }

typedoc/assets/hierarchy.js

@@ -1 +0,0 @@
-window.hierarchyData = "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"

typedoc/assets/highlight.css

@@ -1,92 +1,22 @@
 :root {
-    --light-hl-0: #0000FF;
-    --dark-hl-0: #569CD6;
-    --light-hl-1: #000000;
-    --dark-hl-1: #D4D4D4;
-    --light-hl-2: #0070C1;
-    --dark-hl-2: #4FC1FF;
-    --light-hl-3: #795E26;
-    --dark-hl-3: #DCDCAA;
-    --light-hl-4: #098658;
-    --dark-hl-4: #B5CEA8;
-    --light-hl-5: #001080;
-    --dark-hl-5: #9CDCFE;
-    --light-hl-6: #AF00DB;
-    --dark-hl-6: #C586C0;
-    --light-hl-7: #008000;
-    --dark-hl-7: #6A9955;
-    --light-hl-8: #A31515;
-    --dark-hl-8: #CE9178;
-    --light-hl-9: #267F99;
-    --dark-hl-9: #4EC9B0;
     --light-code-background: #FFFFFF;
     --dark-code-background: #1E1E1E;
 }
 
 @media (prefers-color-scheme: light) { :root {
-    --hl-0: var(--light-hl-0);
-    --hl-1: var(--light-hl-1);
-    --hl-2: var(--light-hl-2);
-    --hl-3: var(--light-hl-3);
-    --hl-4: var(--light-hl-4);
-    --hl-5: var(--light-hl-5);
-    --hl-6: var(--light-hl-6);
-    --hl-7: var(--light-hl-7);
-    --hl-8: var(--light-hl-8);
-    --hl-9: var(--light-hl-9);
     --code-background: var(--light-code-background);
 } }
 
 @media (prefers-color-scheme: dark) { :root {
-    --hl-0: var(--dark-hl-0);
-    --hl-1: var(--dark-hl-1);
-    --hl-2: var(--dark-hl-2);
-    --hl-3: var(--dark-hl-3);
-    --hl-4: var(--dark-hl-4);
-    --hl-5: var(--dark-hl-5);
-    --hl-6: var(--dark-hl-6);
-    --hl-7: var(--dark-hl-7);
-    --hl-8: var(--dark-hl-8);
-    --hl-9: var(--dark-hl-9);
     --code-background: var(--dark-code-background);
 } }
 
 :root[data-theme='light'] {
-    --hl-0: var(--light-hl-0);
-    --hl-1: var(--light-hl-1);
-    --hl-2: var(--light-hl-2);
-    --hl-3: var(--light-hl-3);
-    --hl-4: var(--light-hl-4);
-    --hl-5: var(--light-hl-5);
-    --hl-6: var(--light-hl-6);
-    --hl-7: var(--light-hl-7);
-    --hl-8: var(--light-hl-8);
-    --hl-9: var(--light-hl-9);
     --code-background: var(--light-code-background);
 }
 
 :root[data-theme='dark'] {
-    --hl-0: var(--dark-hl-0);
-    --hl-1: var(--dark-hl-1);
-    --hl-2: var(--dark-hl-2);
-    --hl-3: var(--dark-hl-3);
-    --hl-4: var(--dark-hl-4);
-    --hl-5: var(--dark-hl-5);
-    --hl-6: var(--dark-hl-6);
-    --hl-7: var(--dark-hl-7);
-    --hl-8: var(--dark-hl-8);
-    --hl-9: var(--dark-hl-9);
     --code-background: var(--dark-code-background);
 }
 
-.hl-0 { color: var(--hl-0); }
-.hl-1 { color: var(--hl-1); }
-.hl-2 { color: var(--hl-2); }
-.hl-3 { color: var(--hl-3); }
-.hl-4 { color: var(--hl-4); }
-.hl-5 { color: var(--hl-5); }
-.hl-6 { color: var(--hl-6); }
-.hl-7 { color: var(--hl-7); }
-.hl-8 { color: var(--hl-8); }
-.hl-9 { color: var(--hl-9); }
 pre, code { background: var(--code-background); }

typedoc/assets/navigation.js

@@ -1 +0,0 @@
-window.navigationData = "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"