exception handling

CHANGELOG.md

@@ -1,6 +1,6 @@
 # @vladmandic/human  
 
-Version: **1.4.0**  
+Version: **1.4.1**  
 Description: **Human: AI-powered 3D Face Detection, Face Description & Recognition, Body Pose Tracking, Hand & Finger Tracking, Iris Analysis, Age & Gender & Emotion Prediction & Gesture Recognition**  
 
 Author: **Vladimir Mandic <mandic00@live.com>**  
@@ -9,8 +9,9 @@ Repository: **<git+https://github.com/vladmandic/human.git>**
 
 ## Changelog
 
-### **HEAD -> main** 2021/04/08 mandic00@live.com
+### **1.4.1** 2021/04/09 mandic00@live.com
 
+- add modelbasepath option
 
 ### **1.3.5** 2021/04/06 mandic00@live.com
 

README.md

@@ -30,9 +30,10 @@ Check out [**Live Demo**](https://vladmandic.github.io/human/demo/index.html) fo
 
 ## Demos
 
-- [**Demo Application**](https://vladmandic.github.io/human/demo/index.html)
+- [**Main Application**](https://vladmandic.github.io/human/demo/index.html)
 - [**Face Extraction, Description, Identification and Matching**](https://vladmandic.github.io/human/demo/facematch.html)
 - [**Face Extraction and 3D Rendering**](https://vladmandic.github.io/human/demo/face3d.html)
+- [**Details on Demo Applications**](https://github.com/vladmandic/human/wiki/Demos)
 
 ## Project pages
 
@@ -47,7 +48,6 @@ Check out [**Live Demo**](https://vladmandic.github.io/human/demo/index.html) fo
 ## Wiki pages
 
 - [**Home**](https://github.com/vladmandic/human/wiki)
-- [**Demos**](https://github.com/vladmandic/human/wiki/Demos)
 - [**Installation**](https://github.com/vladmandic/human/wiki/Install)
 - [**Usage & Functions**](https://github.com/vladmandic/human/wiki/Usage)
 - [**Configuration Details**](https://github.com/vladmandic/human/wiki/Configuration)
@@ -185,7 +185,7 @@ For more info, see [**Configuration Details**](https://github.com/vladmandic/hum
 
 <br><hr><br>
 
-`Human` library is written in `TypeScript` [4.3](https://www.typescriptlang.org/docs/handbook/intro.html)  
+`Human` library is written in `TypeScript` [4.2](https://www.typescriptlang.org/docs/handbook/intro.html)  
 Conforming to `JavaScript` [ECMAScript version 2020](https://www.ecma-international.org/ecma-262/11.0/index.html) standard  
 Build target is `JavaScript` **EMCAScript version 2018**  
 

demo/helpers/menu.js

@@ -1,5 +1,3 @@
-// @ts-nocheck
-
 let instance = 0;
 let CSScreated = false;
 

demo/index.js

@@ -5,6 +5,7 @@ import Menu from './helpers/menu.js';
 import GLBench from './helpers/gl-bench.js';
 
 const userConfig = { backend: 'webgl' }; // add any user configuration overrides
+let human;
 
 /*
 const userConfig = {
@@ -42,6 +43,7 @@ const ui = {
   console: true, // log messages to browser console
   maxFPSframes: 10, // keep fps history for how many frames
   modelsPreload: true, // preload human models on startup
+  modelsWarmup: true, // warmup human models on startup
   busy: false, // internal camera busy flag
   menuWidth: 0, // internal
   menuHeight: 0, // internal
@@ -89,12 +91,6 @@ function status(msg) {
   if (div) div.innerText = msg;
 }
 
-const human = new Human(userConfig);
-if (typeof tf !== 'undefined') {
-  log('TensorFlow external version:', tf.version);
-  human.tf = tf; // use externally loaded version of tfjs
-}
-
 const compare = { enabled: false, original: null };
 async function calcSimmilariry(result) {
   document.getElementById('compare-container').style.display = compare.enabled ? 'block' : 'none';
@@ -564,20 +560,57 @@ async function drawWarmup(res) {
 
 async function main() {
   log('demo starting ...');
+
+  // parse url search params
+  const params = new URLSearchParams(location.search);
+  log('url options:', params.toString());
+  if (params.has('worker')) {
+    ui.useWorker = JSON.parse(params.get('worker'));
+    log('overriding worker:', ui.useWorker);
+  }
+  if (params.has('backend')) {
+    userConfig.backend = JSON.parse(params.get('backend'));
+    log('overriding backend:', userConfig.backend);
+  }
+  if (params.has('preload')) {
+    ui.modelsPreload = JSON.parse(params.get('preload'));
+    log('overriding preload:', ui.modelsPreload);
+  }
+  if (params.has('warmup')) {
+    ui.modelsWarmup = JSON.parse(params.get('warmup'));
+    log('overriding warmup:', ui.modelsWarmup);
+  }
+
+  // create instance of human
+  human = new Human(userConfig);
+  if (typeof tf !== 'undefined') {
+    log('TensorFlow external version:', tf.version);
+    human.tf = tf; // use externally loaded version of tfjs
+  }
+
+  // setup main menu
   setupMenu();
   document.getElementById('log').innerText = `Human: version ${human.version}`;
+
+  // preload models
   if (ui.modelsPreload && !ui.useWorker) {
     status('loading');
     await human.load(userConfig); // this is not required, just pre-loads all models
     const loaded = Object.keys(human.models).filter((a) => human.models[a]);
     log('demo loaded models:', loaded);
   }
-  if (!ui.useWorker) {
+
+  // warmup models
+  if (ui.modelsWarmup && !ui.useWorker) {
     status('initializing');
     const res = await human.warmup(userConfig); // this is not required, just pre-warms all models for faster initial inference
     if (res && res.canvas && ui.drawWarmup) await drawWarmup(res);
   }
+
+  // setup camera
   await setupCamera();
+
+  // ready
   status('human: ready');
   document.getElementById('loader').style.display = 'none';
   document.getElementById('play').style.display = 'block';

server/build.js

@@ -184,8 +184,7 @@ async function compile(entryPoint, options) {
     .getPreEmitDiagnostics(program)
     .concat(emit.diagnostics);
   for (const info of diag) {
-    // @ts-ignore
+    const msg = info.messageText['messageText'] || info.messageText;
-    const msg = info.messageText.messageText || info.messageText;
     if (msg.includes('package.json')) continue;
     if (info.file) {
       const pos = info.file.getLineAndCharacterOfPosition(info.start || 0);
@@ -225,9 +224,9 @@ async function build(f, msg, dev = false) {
         // if triggered from watch mode, rebuild only browser bundle
         // if ((require.main !== module) && ((targetGroupName === 'browserNoBundle') || (targetGroupName === 'nodeGPU'))) continue;
         const meta = dev
-          // @ts-ignore
+          // @ts-ignore // eslint-typescript complains about string enums used in js code
           ? await esbuild.build({ ...config.common, ...config.debug, ...targetOptions })
-          // @ts-ignore
+          // @ts-ignore // eslint-typescript complains about string enums used in js code
           : await esbuild.build({ ...config.common, ...config.production, ...targetOptions });
         const stats = await getStats(meta);
         log.state(`Build for: ${targetGroupName} type: ${targetName}:`, stats);

server/changelog.js

@@ -21,8 +21,8 @@ Repository: **<${app.repository.url}>**
 
 async function update(f) {
   const gitLog = await git.log();
-  // @ts-ignore
+  const entries = [...gitLog.all];
-  const log = gitLog.all.sort((a, b) => (new Date(b.date).getTime() - new Date(a.date).getTime()));
+  const log = entries.sort((a, b) => (new Date(b.date).getTime() - new Date(a.date).getTime()));
 
   let previous = '';
   const headings = [];

server/serve.js

@@ -109,6 +109,7 @@ function handle(url) {
 */
 
 function handle(url) {
+  url = url.split(/[?#]/)[0];
   const result = { ok: false, stat: {}, file: '' };
   const checkFile = (f) => {
     result.file = f;

src/blazeface/facepipeline.ts

@@ -41,7 +41,6 @@ function replaceRawCoordinates(rawCoords, newCoords, prefix, keys) {
   for (let i = 0; i < coords.MESH_TO_IRIS_INDICES_MAP.length; i++) {
     const { key, indices } = coords.MESH_TO_IRIS_INDICES_MAP[i];
     const originalIndices = coords.MESH_ANNOTATIONS[`${prefix}${key}`];
-    // @ts-ignore
     if (!keys || keys.includes(key)) {
       for (let j = 0; j < indices.length; j++) {
         const index = indices[j];

src/gesture/gesture.ts

@@ -64,8 +64,7 @@ export const hand = (res) => {
   for (let i = 0; i < res.length; i++) {
     const fingers: Array<{ name: string, position: number }> = [];
     for (const [finger, pos] of Object.entries(res[i]['annotations'])) {
-      // @ts-ignore
+      if (finger !== 'palmBase' && Array.isArray(pos)) fingers.push({ name: finger.toLowerCase(), position: pos[0] }); // get tip of each finger
-      if (finger !== 'palmBase') fingers.push({ name: finger.toLowerCase(), position: pos[0] }); // get tip of each finger
     }
     if (fingers && fingers.length > 0) {
       const closest = fingers.reduce((best, a) => (best.position[2] < a.position[2] ? best : a));

src/human.ts

@@ -124,7 +124,7 @@ export class Human {
       faceres: null,
     };
     // export access to image processing
-    // @ts-ignore
+    // @ts-ignore // typescript cannot infer type
     this.image = (input: Input) => image.process(input, this.config);
     // export raw access to underlying models
     this.classes = {
@@ -214,9 +214,9 @@ export class Human {
         this.models.gender,
         this.models.emotion,
         this.models.embedding,
-        // @ts-ignore
+        // @ts-ignore // typescript cannot infer type
         this.models.handpose,
-        // @ts-ignore false warning with latest @typescript-eslint
+        // @ts-ignore // typescript cannot infer type
         this.models.posenet,
         this.models.blazepose,
         this.models.efficientpose,
@@ -422,15 +422,14 @@ export class Human {
       if (this.config.async) {
         [faceRes, bodyRes, handRes, objectRes] = await Promise.all([faceRes, bodyRes, handRes, objectRes]);
       }
-      process.tensor.dispose();
+      tf.dispose(process.tensor);
 
       if (this.config.scoped) this.tf.engine().endScope();
       this.analyze('End Scope:');
 
-      let gestureRes = [];
+      let gestureRes: any[] = [];
       if (this.config.gesture.enabled) {
         timeStamp = now();
-        // @ts-ignore
         gestureRes = [...gesture.face(faceRes), ...gesture.body(bodyRes), ...gesture.hand(handRes), ...gesture.iris(faceRes)];
         if (!this.config.async) this.perf.gesture = Math.trunc(now() - timeStamp);
         else if (this.perf.gesture) delete this.perf.gesture;
@@ -507,8 +506,8 @@ export class Human {
   #warmupNode = async () => {
     const atob = (str) => Buffer.from(str, 'base64');
     const img = this.config.warmup === 'face' ? atob(sample.face) : atob(sample.body);
-    // @ts-ignore
+    // @ts-ignore // tf.node is only defined when compiling for nodejs
-    const data = tf.node.decodeJpeg(img); // tf.node is only defined when compiling for nodejs
+    const data = tf.node?.decodeJpeg(img);
     const expanded = data.expandDims(0);
     this.tf.dispose(data);
     // log('Input:', expanded);

src/image/image.ts

@@ -1,19 +1,17 @@
-// @ts-nocheck
-
 import * as tf from '../../dist/tfjs.esm.js';
 import * as fxImage from './imagefx';
 
 const maxSize = 2048;
 // internal temp canvases
-let inCanvas = null;
+let inCanvas;
-let outCanvas = null;
+let outCanvas;
 // instance of fximage
-let fx = null;
+let fx;
 
 // process input image and return tensor
 // input can be tensor, imagedata, htmlimageelement, htmlvideoelement
 // input is resized and run through imagefx filter
-export function process(input, config): { tensor: tf.Tensor, canvas: OffscreenCanvas | HTMLCanvasElement } {
+export function process(input, config): { tensor: typeof tf.Tensor | null, canvas: OffscreenCanvas | HTMLCanvasElement } {
   let tensor;
   if (!input) throw new Error('Human: Input is missing');
   if (
@@ -32,8 +30,8 @@ export function process(input, config): { tensor: tf.Tensor, canvas: OffscreenCa
   if (input instanceof tf.Tensor) {
     tensor = tf.clone(input);
   } else {
-    const originalWidth = input.naturalWidth || input.videoWidth || input.width || (input.shape && (input.shape[1] > 0));
+    const originalWidth = input['naturalWidth'] || input['videoWidth'] || input['width'] || (input['shape'] && (input['shape'][1] > 0));
-    const originalHeight = input.naturalHeight || input.videoHeight || input.height || (input.shape && (input.shape[2] > 0));
+    const originalHeight = input['naturalHeight'] || input['videoHeight'] || input['height'] || (input['shape'] && (input['shape'][2] > 0));
     let targetWidth = originalWidth;
     let targetHeight = originalHeight;
     if (targetWidth > maxSize) {
@@ -49,19 +47,19 @@ export function process(input, config): { tensor: tf.Tensor, canvas: OffscreenCa
     if (config.filter.height > 0) targetHeight = config.filter.height;
     else if (config.filter.width > 0) targetHeight = originalHeight * (config.filter.width / originalWidth);
     if (!targetWidth || !targetHeight) throw new Error('Human: Input cannot determine dimension');
-    if (!inCanvas || (inCanvas.width !== targetWidth) || (inCanvas.height !== targetHeight)) {
+    if (!inCanvas || (inCanvas?.width !== targetWidth) || (inCanvas?.height !== targetHeight)) {
       inCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(targetWidth, targetHeight) : document.createElement('canvas');
-      if (inCanvas.width !== targetWidth) inCanvas.width = targetWidth;
+      if (inCanvas?.width !== targetWidth) inCanvas.width = targetWidth;
-      if (inCanvas.height !== targetHeight) inCanvas.height = targetHeight;
+      if (inCanvas?.height !== targetHeight) inCanvas.height = targetHeight;
     }
     const ctx = inCanvas.getContext('2d');
     if (input instanceof ImageData) ctx.putImageData(input, 0, 0);
-    else ctx.drawImage(input, 0, 0, originalWidth, originalHeight, 0, 0, inCanvas.width, inCanvas.height);
+    else ctx.drawImage(input, 0, 0, originalWidth, originalHeight, 0, 0, inCanvas?.width, inCanvas?.height);
     if (config.filter.enabled) {
-      if (!fx || !outCanvas || (inCanvas.width !== outCanvas.width) || (inCanvas.height !== outCanvas.height)) {
+      if (!fx || !outCanvas || (inCanvas.width !== outCanvas.width) || (inCanvas?.height !== outCanvas?.height)) {
-        outCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(inCanvas.width, inCanvas.height) : document.createElement('canvas');
+        outCanvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(inCanvas?.width, inCanvas?.height) : document.createElement('canvas');
-        if (outCanvas.width !== inCanvas.width) outCanvas.width = inCanvas.width;
+        if (outCanvas?.width !== inCanvas?.width) outCanvas.width = inCanvas?.width;
-        if (outCanvas.height !== inCanvas.height) outCanvas.height = inCanvas.height;
+        if (outCanvas?.height !== inCanvas?.height) outCanvas.height = inCanvas?.height;
         // log('created FX filter');
         fx = tf.ENV.flags.IS_BROWSER ? new fxImage.GLImageFilter({ canvas: outCanvas }) : null; // && (typeof document !== 'undefined')
       }

src/image/imagefx.js

@@ -17,10 +17,7 @@ function GLProgram(gl, vertexSource, fragmentSource) {
     const shader = gl.createShader(type);
     gl.shaderSource(shader, source);
     gl.compileShader(shader);
-    if (!gl.getShaderParameter(shader, gl.COMPILE_STATUS)) {
+    if (!gl.getShaderParameter(shader, gl.COMPILE_STATUS)) throw new Error('Filter: GL compile failed', gl.getShaderInfoLog(shader));
-      // @ts-ignore
-      throw new Error('Filter: GL compile failed', gl.getShaderInfoLog(shader));
-    }
     return shader;
   };
 
@@ -33,10 +30,7 @@ function GLProgram(gl, vertexSource, fragmentSource) {
   gl.attachShader(this.id, _fsh);
   gl.linkProgram(this.id);
 
-  if (!gl.getProgramParameter(this.id, gl.LINK_STATUS)) {
+  if (!gl.getProgramParameter(this.id, gl.LINK_STATUS)) throw new Error('Filter: GL link failed', gl.getProgramInfoLog(this.id));
-    // @ts-ignore
-    throw new Error('Filter: GL link failed', gl.getProgramInfoLog(this.id));
-  }
 
   gl.useProgram(this.id);
   // Collect attributes
@@ -123,7 +117,6 @@ export function GLImageFilter(params) {
   };
 
   const _getTempFramebuffer = function (index) {
-    // @ts-ignore
     _tempFramebuffers[index] = _tempFramebuffers[index] || _createFramebufferTexture(_width, _height);
     return _tempFramebuffers[index];
   };
@@ -138,7 +131,6 @@ export function GLImageFilter(params) {
       source = _sourceTexture;
     } else {
       // All following draw calls use the temp buffer last drawn to
-      // @ts-ignore
       source = _getTempFramebuffer(_currentFramebufferIndex)?.texture;
     }
     _drawCount++;
@@ -151,7 +143,6 @@ export function GLImageFilter(params) {
     } else {
       // Intermediate draw call - get a temp buffer to draw to
       _currentFramebufferIndex = (_currentFramebufferIndex + 1) % 2;
-      // @ts-ignore
       target = _getTempFramebuffer(_currentFramebufferIndex)?.fbo;
     }
     // Bind the source and target and draw the two triangles

src/nanodet/nanodet.ts

@@ -12,8 +12,9 @@ const scaleBox = 2.5; // increase box size
 export async function load(config) {
   if (!model) {
     model = await tf.loadGraphModel(join(config.modelBasePath, config.object.modelPath));
-    // @ts-ignore
+    const inputs = Object.values(model.modelSignature['inputs']);
-    model.inputSize = parseInt(Object.values(model.modelSignature['inputs'])[0].tensorShape.dim[2].size);
+    model.inputSize = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : null;
+    if (!model.inputSize) throw new Error(`Human: Cannot determine model inputSize: ${config.object.modelPath}`);
     if (!model || !model.modelUrl) log('load model failed:', config.object.modelPath);
     else if (config.debug) log('load model:', model.modelUrl);
   }

src/sysinfo.ts

@@ -4,8 +4,8 @@ export function info(): { platform: string, agent: string } {
   if (typeof navigator !== 'undefined') {
     const raw = navigator.userAgent.match(/\(([^()]+)\)/g);
     if (raw && raw[0]) {
-      // @ts-ignore
+      const platformMatch = raw[0].match(/\(([^()]+)\)/g);
-      platform = raw[0].match(/\(([^()]+)\)/g)[0].replace(/\(|\)/g, '');
+      platform = platformMatch ? platformMatch[0].replace(/\(|\)/g, '') : '';
       agent = navigator.userAgent.replace(raw[0], '');
       if (platform[1]) agent = agent.replace(raw[1], '');
       agent = agent.replace(/  /g, ' ');

src/tfjs/backend.ts

@@ -4,8 +4,8 @@ import * as tf from '../../dist/tfjs.esm.js';
 export const config = {
   name: 'humangl',
   priority: 99,
-  canvas: null,
+  canvas: <null | OffscreenCanvas | HTMLCanvasElement>null,
-  gl: null,
+  gl: <any>null,
   width: 1024,
   height: 1024,
   webGLattr: { // https://www.khronos.org/registry/webgl/specs/latest/1.0/#5.2
@@ -24,14 +24,12 @@ export function register(): void {
   if (!tf.findBackend(config.name)) {
     log('backend registration:', config.name);
     try {
-      // @ts-ignore
       config.canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(config.width, config.height) : document.createElement('canvas');
     } catch (err) {
       log('error: cannot create canvas:', err);
       return;
     }
     try {
-      // @ts-ignore
       config.gl = config.canvas.getContext('webgl2', config.webGLattr);
     } catch (err) {
       log('error: cannot get WebGL2 context:', err);
@@ -62,7 +60,6 @@ export function register(): void {
     }
     try {
       tf.ENV.set('WEBGL_VERSION', 2);
-      // @ts-ignore
       // tf.ENV.set('WEBGL_MAX_TEXTURE_SIZE', config.gl.getParameter(config.gl.MAX_TEXTURE_SIZE));
       // tf.ENV.set('WEBGL_FORCE_F16_TEXTURES', true);
       // tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);

types/image/image.d.ts

@@ -1,5 +1,5 @@
 import * as tf from '../../dist/tfjs.esm.js';
 export declare function process(input: any, config: any): {
-    tensor: tf.Tensor;
+    tensor: typeof tf.Tensor | null;
     canvas: OffscreenCanvas | HTMLCanvasElement;
 };

types/tfjs/backend.d.ts

@@ -1,8 +1,8 @@
 export declare const config: {
     name: string;
     priority: number;
-    canvas: null;
+    canvas: OffscreenCanvas | HTMLCanvasElement | null;
-    gl: null;
+    gl: any;
     width: number;
     height: number;
     webGLattr: {

wiki

@@ -1 +1 @@
-Subproject commit d09d36cf9de309728504402bf301ac3ab018de65
+Subproject commit 652dee1013ae99789199cc229d6652b3323ae7de