added custom webgl backend

config.js

@@ -3,7 +3,7 @@
 
 export default {
   backend: 'webgl',          // select tfjs backend to use
-  wasmPath: '../assets/',      // path for wasm binaries
+  wasmPath: '../assets/',    // path for wasm binaries
                              // only used for backend: wasm
   async: true,               // execute enabled models in parallel
                              // this disables per-model performance data but
@@ -26,7 +26,7 @@ export default {
                              // must be disabled for images
                              // basically this skips object box boundary detection for every n frames
                              // while maintaining in-box detection since objects cannot move that fast
-  warmup: 'full',            // what to use for human.warmup(), can be 'none', 'face', 'full'
+  warmup: 'face',            // what to use for human.warmup(), can be 'none', 'face', 'full'
                              // warmup pre-initializes all models for faster inference but can take
                              // significant time on startup
   filter: {

demo/browser.js

@@ -4,13 +4,6 @@ import Menu from './menu.js';
 import GLBench from './gl-bench.js';
 
 const userConfig = {}; // add any user configuration overrides
-/*
-const userConfig = {
-  async: false,
-  face: { enabled: false },
-  body: { enabled: false },
-};
-*/
 
 const human = new Human(userConfig);
 
@@ -441,7 +434,7 @@ function setupMenu() {
   menu.image.addBool('polaroid', human.config.filter, 'polaroid');
 
   menu.process = new Menu(document.body, '', { top: `${document.getElementById('menubar').offsetHeight}px`, left: x[2] });
-  menu.process.addList('backend', ['cpu', 'webgl', 'wasm'], human.config.backend, (val) => human.config.backend = val);
+  menu.process.addList('backend', ['cpu', 'webgl', 'wasm', 'humangl'], human.config.backend, (val) => human.config.backend = val);
   menu.process.addBool('async operations', human.config, 'async', (val) => human.config.async = val);
   menu.process.addBool('enable profiler', human.config, 'profile', (val) => human.config.profile = val);
   menu.process.addBool('memory shield', human.config, 'deallocate', (val) => human.config.deallocate = val);

src/human.js

@@ -1,5 +1,6 @@
 import { log } from './log.js';
 import * as tf from '../dist/tfjs.esm.js';
+import * as backend from './tfjs/backend.js';
 import * as facemesh from './face/facemesh.js';
 import * as age from './age/age.js';
 import * as gender from './gender/gender.js';
@@ -176,6 +177,11 @@ class Human {
         if (!simd) log('warning: wasm simd support is not enabled');
       }
 
+      if (this.config.backend === 'humangl') {
+        log('registering humangl backend');
+        backend.register();
+      }
+
       await tf.setBackend(this.config.backend);
       tf.enableProdMode();
       /* debug mode is really too mcuh

src/tfjs/backend.js

@@ -0,0 +1,38 @@
+import * as tf from '../../dist/tfjs.esm.js';
+
+export const config = {
+  name: 'humangl',
+  priority: 99,
+  canvas: null,
+  width: 1024,
+  height: 1024,
+  webGLattr: { // https://www.khronos.org/registry/webgl/specs/latest/1.0/#5.2
+    alpha: false,
+    antialias: false,
+    premultipliedAlpha: false,
+    preserveDrawingBuffer: false,
+    depth: false,
+    stencil: false,
+    failIfMajorPerformanceCaveat: false,
+    desynchronized: true,
+  },
+};
+
+export function register() {
+  if (!tf.findBackend(config.name)) {
+    config.canvas = (typeof OffscreenCanvas !== 'undefined') ? new OffscreenCanvas(config.width, config.height) : document.createElement('canvas');
+    const gl = config.canvas.getContext('webgl2', config.webGLattr);
+    tf.setWebGLContext(2, gl);
+    const ctx = new tf.GPGPUContext(gl);
+    tf.registerBackend(config.name, () => new tf.MathBackendWebGL(ctx), config.priority);
+    const kernels = tf.getKernelsForBackend('webgl');
+    kernels.forEach((kernelConfig) => {
+      const newKernelConfig = { ...kernelConfig, backendName: config.name };
+      tf.registerKernel(newKernelConfig);
+    });
+    tf.ENV.set('WEBGL_VERSION', 2);
+    tf.ENV.set('WEBGL_MAX_TEXTURE_SIZE', gl.getParameter(gl.MAX_TEXTURE_SIZE));
+    tf.ENV.set('WEBGL_FORCE_F16_TEXTURES', true);
+    tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);
+  }
+}

src/tfjs/tf-browser.js

@@ -3,13 +3,12 @@
 // simplified
 // { modules: 1061, moduleBytes: 3772720, outputBytes: 1531035 }
 
-export * from '@tensorflow/tfjs/dist/index.js';
+// export * from '@tensorflow/tfjs/dist/index.js';
-export * from '@tensorflow/tfjs-backend-wasm';
+// export * from '@tensorflow/tfjs-backend-wasm';
 
 // modular
 // { modules: 1064, moduleBytes: 3793219, outputBytes: 1535600 }
 
-/*
 // get versions of all packages.
 import { version as tfjs } from '@tensorflow/tfjs/package.json';
 import { version as versionCore } from '@tensorflow/tfjs-core/package.json';
@@ -41,4 +40,3 @@ export const version = {
   'tfjs-backend-webgl': version_webgl,
   'tfjs-backend-wasm': version_wasm,
 };
-*/