changed build for optimized node & browser

demo/browser.js

@@ -282,7 +282,7 @@ function runHumanDetect(input, canvas, timestamp) {
     else log(`camera not ready: track state: ${input.srcObject?.getVideoTracks()[0].readyState} stream state: ${input.readyState}`);
     clearTimeout(ui.drawThread);
     ui.drawThread = null;
-    log('frame statistics: drawn:', ui.framesDraw, 'detected:', ui.framesDetect);
+    log('frame statistics: process:', ui.framesDetect, 'refresh:', ui.framesDraw);
     return;
   }
   status('');

demo/node.js

@@ -1,29 +1,12 @@
-const tf = require('@tensorflow/tfjs-node');
+const log = require('@vladmandic/pilogger');
 const fs = require('fs');
 const process = require('process');
-const console = require('console');
-const Human = require('..').default; // this resolves to project root which is '@vladmandic/human'
+// for Node, `tfjs-node` or `tfjs-node-gpu` should be loaded before using Human
+const tf = require('@tensorflow/tfjs-node'); // or const tf = require('@tensorflow/tfjs-node-gpu');
+// load specific version of Human library that matches TensorFlow mode
+const Human = require('../dist/human.node.js').default; // or const Human = require('../dist/human.node-gpu.js').default;
 
-const logger = new console.Console({
-  stdout: process.stdout,
-  stderr: process.stderr,
-  ignoreErrors: true,
-  groupIndentation: 2,
-  inspectOptions: {
-    showHidden: true,
-    depth: 5,
-    colors: true,
-    showProxy: true,
-    maxArrayLength: 1024,
-    maxStringLength: 10240,
-    breakLength: 200,
-    compact: 64,
-    sorted: false,
-    getters: true,
-  },
-});
-
-const config = {
+const myConfig = {
   backend: 'tensorflow',
   console: true,
   videoOptimized: false,
@@ -31,9 +14,9 @@ const config = {
     detector: { modelPath: 'file://models/blazeface-back.json' },
     mesh: { modelPath: 'file://models/facemesh.json' },
     iris: { modelPath: 'file://models/iris.json' },
-    age: { modelPath: 'file://models/ssrnet-age-imdb.json' },
-    gender: { modelPath: 'file://models/ssrnet-gender-imdb.json' },
-    emotion: { modelPath: 'file://models/emotion.json' },
+    age: { modelPath: 'file://models/age-ssrnet-imdb.json' },
+    gender: { modelPath: 'file://models/gender-ssrnet-imdb.json' },
+    emotion: { modelPath: 'file://models/emotion-large.json' },
   },
   body: { modelPath: 'file://models/posenet.json' },
   hand: {
@@ -42,30 +25,37 @@ const config = {
   },
 };
 
-async function detect(input, output) {
-  await tf.setBackend('tensorflow');
+async function detect(input) {
+  // wait until tf is ready
   await tf.ready();
-  logger.info('TFJS Flags:', tf.env().features);
-  logger.log('Loading:', input);
+  // create instance of human
+  const human = new Human(myConfig);
+  // pre-load models
+  await human.load();
+  // read input image file and create tensor to be used for processing
   const buffer = fs.readFileSync(input);
-  const decoded = tf.node.decodeImage(buffer);
+  const decoded = human.tf.node.decodeImage(buffer);
   const casted = decoded.toFloat();
   const image = casted.expandDims(0);
   decoded.dispose();
   casted.dispose();
-  logger.log('Processing:', image.shape);
-  const human = new Human();
-  const result = await human.detect(image, config);
+  // image shape contains image dimensions and depth
+  log.state('Processing:', image.shape);
+  // must disable face model when runing in tfjs-node as it's missing required ops
+  // see <https://github.com/tensorflow/tfjs/issues/4066>
+  myConfig.face.enabled = false;
+  // run actual detection
+  const result = await human.detect(image, myConfig);
+  // dispose image tensor as we no longer need it
   image.dispose();
-  logger.log(result);
-  // Draw detected data and save processed image
-  logger.log('TODO Saving:', output);
+  // print data to console
+  log.data(result);
 }
 
 async function main() {
-  if (process.argv.length !== 4) logger.error('Parameters: <input image> <output image>');
-  else if (!fs.existsSync(process.argv[2])) logger.error(`File not found: ${process.argv[2]}`);
-  else detect(process.argv[2], process.argv[3]);
+  if (process.argv.length !== 3) log.error('Parameters: <input image>');
+  else if (!fs.existsSync(process.argv[2])) log.error(`File not found: ${process.argv[2]}`);
+  else detect(process.argv[2]);
 }
 
 main();

package.json

@@ -31,6 +31,7 @@
     "@tensorflow/tfjs-data": "^2.7.0",
     "@tensorflow/tfjs-layers": "^2.7.0",
     "@tensorflow/tfjs-node": "^2.7.0",
+    "@tensorflow/tfjs-node-gpu": "^2.7.0",
     "@vladmandic/pilogger": "^0.2.7",
     "chokidar": "^3.4.3",
     "dayjs": "^1.9.6",
@@ -49,7 +50,7 @@
     "start": "node --trace-warnings --unhandled-rejections=strict --trace-uncaught --no-deprecation src/node.js",
     "lint": "eslint src/*.js demo/*.js",
     "dev": "npm install && node server/dev.js",
-    "build": "npm install && npm run lint && rimraf dist/* && node server/build.js && node server/changelog.js",
+    "build": "npm install && rimraf dist/* && node server/build.js && node server/changelog.js",
     "update": "npm update --depth 20 --force && npm dedupe && npm prune && npm audit"
   },
   "keywords": [

src/human.js

@@ -117,9 +117,11 @@ class Human {
 
     if (this.firstRun) {
       this.log(`version: ${this.version} TensorFlow/JS version: ${tf.version_core}`);
-      this.checkBackend(true);
-      this.log('configuration:', this.config);
-      this.log('flags:', tf.ENV.flags);
+      await this.checkBackend(true);
+      if (tf.ENV.flags.IS_BROWSER) {
+        this.log('configuration:', this.config);
+        this.log('tf flags:', tf.ENV.flags);
+      }
       this.firstRun = false;
     }
     if (this.config.async) {
@@ -155,8 +157,8 @@ class Human {
 
   // check if backend needs initialization if it changed
   async checkBackend(force) {
-    const timeStamp = now();
     if (this.config.backend && (this.config.backend !== '') && force || (tf.getBackend() !== this.config.backend)) {
+      const timeStamp = now();
       this.state = 'backend';
       /* force backend reload
       if (this.config.backend in tf.engine().registry) {
@@ -189,11 +191,12 @@ class Human {
         }
         tf.ENV.set('WEBGL_FORCE_F16_TEXTURES', true);
         tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', true);
+        const gl = await tf.backend().getGPGPUContext().gl;
+        this.log(`gl version:${gl.getParameter(gl.VERSION)} renderer:${gl.getParameter(gl.RENDERER)}`);
       }
       await tf.ready();
+      this.perf.backend = Math.trunc(now() - timeStamp);
     }
-    const current = Math.trunc(now() - timeStamp);
-    if (current > (this.perf.backend || 0)) this.perf.backend = current;
   }
 
   async detectFace(input) {
@@ -418,6 +421,7 @@ class Human {
 
   async warmup(userConfig, sample) {
     if (!sample) sample = new ImageData(255, 255);
+    // const sample = tf.zeros([1, 255, 255, 3]);
     const warmup = await this.detect(sample, userConfig);
     this.log('warmed up');
     return warmup;

src/tfjs/tf-node-gpu.js

@@ -0,0 +1 @@
+export * from '@tensorflow/tfjs-node-gpu';

src/tfjs/tf-node.js

@@ -0,0 +1 @@
+export * from '@tensorflow/tfjs-node';

wiki

@@ -1 +1 @@
-Subproject commit 0815d53e582c26b6297e1a5ac42f23b9057f56fa
+Subproject commit 8b7ff45ead1ade2f530a45f06702c9fa65c8dc35