prevent validation failed on some model combinations

CHANGELOG.md

@@ -9,11 +9,19 @@
   
 ## Changelog
   
+### **HEAD -> main** 2021/09/17 mandic00@live.com
+
+
+### **2.2.2** 2021/09/17 mandic00@live.com
+
+- experimental webgl status monitoring
+
+### **release: 2.2.1** 2021/09/16 mandic00@live.com
+
+
 ### **2.2.1** 2021/09/16 mandic00@live.com
 
-
-### **origin/main** 2021/09/16 mandic00@live.com
-
+- add vr model demo
 - all tests passing
 - redefine draw helpers interface
 - add simple webcam and webrtc demo

demo/index.js

@@ -34,7 +34,6 @@ let userConfig = {
   warmup: 'none',
   backend: 'humangl',
   debug: true,
-  filter: { enabled: false },
   /*
   wasmPath: 'https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@3.9.0/dist/',
   async: false,
@@ -106,6 +105,7 @@ const ui = {
   lastFrame: 0, // time of last frame processing
   viewportSet: false, // internal, has custom viewport been set
   background: null, // holds instance of segmentation background image
+  exceptionHandler: true, // should capture all unhandled exceptions
 
   // webrtc
   useWebRTC: false, // use webrtc as camera source instead of local webcam
@@ -920,16 +920,18 @@ async function pwaRegister() {
 }
 
 async function main() {
-  window.addEventListener('unhandledrejection', (evt) => {
-    if (ui.detectThread) cancelAnimationFrame(ui.detectThread);
-    if (ui.drawThread) cancelAnimationFrame(ui.drawThread);
-    const msg = evt.reason.message || evt.reason || evt;
-    // eslint-disable-next-line no-console
-    console.error(msg);
-    document.getElementById('log').innerHTML = msg;
-    status(`exception: ${msg}`);
-    evt.preventDefault();
-  });
+  if (ui.exceptionHandler) {
+    window.addEventListener('unhandledrejection', (evt) => {
+      if (ui.detectThread) cancelAnimationFrame(ui.detectThread);
+      if (ui.drawThread) cancelAnimationFrame(ui.drawThread);
+      const msg = evt.reason.message || evt.reason || evt;
+      // eslint-disable-next-line no-console
+      console.error(msg);
+      document.getElementById('log').innerHTML = msg;
+      status(`exception: ${msg}`);
+      evt.preventDefault();
+    });
+  }
 
   log('demo starting ...');
 
@@ -985,7 +987,8 @@ async function main() {
   // create instance of human
   human = new Human(userConfig);
   log('human version:', human.version);
-  userConfig = { ...human.config, ...userConfig };
+  // we've merged human defaults with user config and now lets store it back so it can be accessed by methods such as menu
+  userConfig = human.config;
   if (typeof tf !== 'undefined') {
     // eslint-disable-next-line no-undef
     log('TensorFlow external version:', tf.version);

package.json

@@ -66,7 +66,7 @@
     "@tensorflow/tfjs-layers": "^3.9.0",
     "@tensorflow/tfjs-node": "^3.9.0",
     "@tensorflow/tfjs-node-gpu": "^3.9.0",
-    "@types/node": "^16.9.1",
+    "@types/node": "^16.9.2",
     "@typescript-eslint/eslint-plugin": "^4.31.1",
     "@typescript-eslint/parser": "^4.31.1",
     "@vladmandic/build": "^0.4.1",

src/models.ts

@@ -90,8 +90,13 @@ export async function validate(instance) {
   for (const defined of Object.keys(instance.models)) {
     if (instance.models[defined]) { // check if model is loaded
       let models: GraphModel[] = [];
-      if (Array.isArray(instance.models[defined])) models = instance.models[defined].map((model) => ((model && model.executor) ? model : model.model));
-      else models = [instance.models[defined]];
+      if (Array.isArray(instance.models[defined])) {
+        models = instance.models[defined]
+          .filter((model) => (model !== null))
+          .map((model) => ((model && model.executor) ? model : model.model));
+      } else {
+        models = [instance.models[defined]];
+      }
       for (const model of models) {
         if (!model) {
           if (instance.config.debug) log('model marked as loaded but not defined:', defined);

src/warmup.ts

@@ -52,7 +52,7 @@ async function warmupCanvas(instance) {
         resolve({});
       } else {
         const ctx = canvas.getContext('2d');
-        ctx.drawImage(img, 0, 0);
+        if (ctx) ctx.drawImage(img, 0, 0);
         // const data = ctx?.getImageData(0, 0, canvas.height, canvas.width);
         const tensor = await instance.image(canvas);
         const res = await instance.detect(tensor.tensor, instance.config);