input type validation

CHANGELOG.md

@@ -9,6 +9,10 @@ Repository: **<git+https://github.com/vladmandic/human.git>**
 
 ## Changelog
 
+### **HEAD -> main** 2021/04/02 mandic00@live.com
+
+- normalize all scores
+
 ### **1.3.1** 2021/03/30 mandic00@live.com
 
 - added face3d demo

demo/face3d.html

@@ -28,6 +28,7 @@
     <div id="media">
       <canvas id="canvas" class="canvas"></canvas>
       <video id="video" playsinline class="video"></video>
+      <div id="log"></div>
     </div>
   </body>
 </html>

demo/face3d.js

@@ -134,6 +134,19 @@ async function setupCamera() {
   const stream = await navigator.mediaDevices.getUserMedia(constraints);
   if (stream) video.srcObject = stream;
   else return null;
+  // get information data
+  const track = stream.getVideoTracks()[0];
+  const settings = track.getSettings();
+  // log('camera constraints:', constraints, 'window:', { width: window.innerWidth, height: window.innerHeight }, 'settings:', settings, 'track:', track);
+  const engineData = human.tf.engine();
+  const gpuData = (engineData.backendInstance && engineData.backendInstance.numBytesInGPU > 0) ? `gpu: ${(engineData.backendInstance.numBytesInGPU ? engineData.backendInstance.numBytesInGPU : 0).toLocaleString()} bytes` : '';
+  const cameraData = { name: track.label?.toLowerCase(), width: settings.width, height: settings.height, facing: settings.facingMode === 'user' ? 'front' : 'back' };
+  const memoryData = `system: ${engineData.state.numBytes.toLocaleString()} bytes ${gpuData} | tensors: ${engineData.state.numTensors.toLocaleString()}`;
+  document.getElementById('log').innerHTML = `
+  video: ${cameraData.name} | facing: ${cameraData.facing} | screen: ${window.innerWidth} x ${window.innerHeight} camera: ${cameraData.width} x ${cameraData.height}<br>
+  backend: ${human.tf.getBackend()} | ${memoryData}<br>
+  `;
+  // return when camera is ready
   return new Promise((resolve) => {
     video.onloadeddata = async () => {
       video.width = video.videoWidth;
@@ -147,6 +160,7 @@ async function setupCamera() {
 }
 
 async function main() {
+  await human.load();
   const video = await setupCamera();
   if (video) {
     const videoTexture = new VideoTexture(video); // now load textures from video

demo/facematch.js

@@ -43,7 +43,8 @@ function log(...msg) {
 async function getFaceDB() {
   // download db with known faces
   try {
-    const res = await fetch('/demo/facematch-faces.json');
+    let res = await fetch('/demo/facematch-faces.json');
+    if (!res || !res.ok) res = await fetch('/human/demo/facematch-faces.json');
     db = (res && res.ok) ? await res.json() : [];
     for (const rec of db) {
       rec.embedding = rec.embedding.map((a) => parseFloat(a.toFixed(4)));
@@ -171,7 +172,9 @@ async function main() {
   let res;
   let images = [];
   let dir = [];
+  // load face descriptor database
   await getFaceDB();
+
   // enumerate all sample images in /assets
   res = await fetch('/assets');
   dir = (res && res.ok) ? await res.json() : [];
@@ -185,24 +188,25 @@ async function main() {
   res = await fetch('/private/err');
   dir = (res && res.ok) ? await res.json() : [];
   images = images.concat(dir.filter((img) => (img.endsWith('.jpg'))));
-
   log('Enumerated:', images.length, 'images');
 
   // could not dynamically enumerate images so using static list
   if (images.length === 0) {
     images = [
-      '/human/assets/sample1.jpg',
+      'sample1.jpg',
-      '/human/assets/sample2.jpg',
+      'sample2.jpg',
-      '/human/assets/sample3.jpg',
+      'sample3.jpg',
-      '/human/assets/sample4.jpg',
+      'sample4.jpg',
-      '/human/assets/sample5.jpg',
+      'sample5.jpg',
-      '/human/assets/sample6.jpg',
+      'sample6.jpg',
-      '/human/assets/sample6.jpg',
+      'sample6.jpg',
-      '/human/assets/sample-me.jpg',
+      'sample-me.jpg',
-      '/human/assets/human-sample-face.jpg',
+      'human-sample-face.jpg',
-      '/human/assets/human-sample-upper.jpg',
+      'human-sample-upper.jpg',
-      '/human/assets/human-sample-body.jpg',
+      'human-sample-body.jpg',
     ];
+    // add prefix for gitpages
+    images = images.map((a) => `/human/assets/${a}`);
     log('Adding static image list:', images.length, 'images');
   }
 

src/human.ts

@@ -28,7 +28,7 @@ export type Tensor = typeof tf.Tensor;
 export type { Config } from './config';
 export type { Result } from './result';
 /** Defines all possible input types for **Human** detection */
-export type Input = Tensor | ImageData | ImageBitmap | HTMLVideoElement | HTMLCanvasElement | OffscreenCanvas;
+export type Input = Tensor | ImageData | ImageBitmap | HTMLImageElement | HTMLVideoElement | HTMLCanvasElement | OffscreenCanvas;
 /** Error message */
 export type Error = { error: string };
 /** Instance of TensorFlow/JS */

src/image/image.ts

@@ -16,7 +16,16 @@ let fx = null;
 export function process(input, config): { tensor: tf.Tensor, canvas: OffscreenCanvas | HTMLCanvasElement } {
   let tensor;
   if (!input) throw new Error('Human: Input is missing');
-  if (!(input instanceof tf.Tensor) && !(input instanceof ImageData) && !(input instanceof ImageBitmap) && !(input instanceof HTMLVideoElement) && !(input instanceof HTMLCanvasElement) && !(input instanceof OffscreenCanvas)) {
+  if (
+    !(input instanceof tf.Tensor)
+    && !(input instanceof Image)
+    && !(input instanceof ImageData)
+    && !(input instanceof ImageBitmap)
+    && !(input instanceof HTMLImageElement)
+    && !(input instanceof HTMLVideoElement)
+    && !(input instanceof HTMLCanvasElement)
+    && !(input instanceof OffscreenCanvas)
+  ) {
     throw new Error('Human: Input type is not recognized');
   }
   if (input instanceof tf.Tensor) {

types/human.d.ts

@@ -16,7 +16,7 @@ export declare type Tensor = typeof tf.Tensor;
 export type { Config } from './config';
 export type { Result } from './result';
 /** Defines all possible input types for **Human** detection */
-export declare type Input = Tensor | ImageData | ImageBitmap | HTMLVideoElement | HTMLCanvasElement | OffscreenCanvas;
+export declare type Input = Tensor | ImageData | ImageBitmap | HTMLImageElement | HTMLVideoElement | HTMLCanvasElement | OffscreenCanvas;
 /** Error message */
 export declare type Error = {
     error: string;