update tests and demos

CHANGELOG.md

@@ -9,14 +9,16 @@ Repository: **<git+https://github.com/vladmandic/human.git>**
 
 ## Changelog
 
-### **HEAD -> main** 2021/06/01 [email protected]
+### **HEAD -> main** 2021/06/02 [email protected]
 
+- implemented drag & drop for image processing
+
+### **origin/main** 2021/06/01 [email protected]
+
+- breaking changes to results.face output properties
 - breaking changes to results.object output properties
 - breaking changes to results.hand output properties
 - breaking changes to results.body output properties
-
-### **origin/main** 2021/05/31 [email protected]
-
 - implemented human.next global interpolation method
 - finished draw buffering and smoothing and enabled by default
 - implemented service worker

README.md

@@ -30,6 +30,7 @@ Check out [**Live Demo**](https://vladmandic.github.io/human/demo/index.html) ap
 - To start video detection, simply press *Play*  
 - To process images, simply drag & drop in your Browser window  
 - Note: For optimal performance, select only models you'd like to use
+- Note: If you have modern GPU, WebGL (default) backend is preferred, otherwise select WASM backend
 
 <br>
 

demo/facematch.js

@@ -183,44 +183,36 @@ async function main() {
   // pre-load human models
   await human.load();
 
-  let res;
   let images = [];
   let dir = [];
   // load face descriptor database
   await getFaceDB();
 
   // enumerate all sample images in /assets
-  res = await fetch('/assets');
+  const res = await fetch('/samples/groups');
   dir = (res && res.ok) ? await res.json() : [];
   images = images.concat(dir.filter((img) => (img.endsWith('.jpg') && img.includes('sample'))));
-  // enumerate additional private test images in /private, not includded in git repository
-  res = await fetch('/private/me');
-  dir = (res && res.ok) ? await res.json() : [];
-  images = images.concat(dir.filter((img) => (img.endsWith('.jpg'))));
-
-  // enumerate additional error images, not includded in git repository
-  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 = [
-      'sample1.jpg',
-      'sample2.jpg',
-      'sample3.jpg',
-      'sample4.jpg',
-      'sample5.jpg',
-      'sample6.jpg',
-      'sample6.jpg',
-      'sample-me.jpg',
-      'human-sample-face.jpg',
-      'human-sample-upper.jpg',
-      'human-sample-body.jpg',
+      'groups/group1.jpg',
+      'groups/group2.jpg',
+      'groups/group3.jpg',
+      'groups/group4.jpg',
+      'groups/group5.jpg',
+      'groups/group6.jpg',
+      'groups/group7.jpg',
+      'groups/group8.jpg',
+      'groups/group9.jpg',
+      'groups/group10.jpg',
+      'groups/group11.jpg',
+      'groups/group12.jpg',
+      'groups/group13.jpg',
+      'groups/group14.jpg',
     ];
     // add prefix for gitpages
-    images = images.map((a) => `/human/assets/${a}`);
+    images = images.map((a) => `/samples/${a}`);
     log('Adding static image list:', images.length, 'images');
   }
 

samples/README.md

@@ -0,0 +1,4 @@
+# Human Library: Sample Images
+
+Sample Images used by `Human` library demos and automated tests
+Not required for normal funcioning of library

src/config.ts

@@ -244,7 +244,7 @@ const config: Config = {
       rotation: true,        // use best-guess rotated face image or just box with rotation as-is
                              // false means higher performance, but incorrect mesh mapping if face angle is above 20 degrees
                              // this parameter is not valid in nodejs
-      maxDetected: 5,        // maximum number of faces detected in the input
+      maxDetected: 15,       // maximum number of faces detected in the input
                              // should be set to the minimum number for performance
       skipFrames: 15,        // how many max frames to go without re-running the face bounding box detector
                              // only used when cacheSensitivity is not zero

src/face.ts

@@ -211,7 +211,6 @@ export const detectFace = async (parent /* instance of human */, input: Tensor):
       : 0;
 
     // combine results
-    if (faces[i].image) delete faces[i].image;
     faceRes.push({
       ...faces[i],
       id: i,
@@ -226,6 +225,8 @@ export const detectFace = async (parent /* instance of human */, input: Tensor):
     });
     // dispose original face tensor
     tf.dispose(faces[i].image);
+    // delete temp face image
+    if (faces[i].image) delete faces[i].image;
 
     parent.analyze('End Face');
   }

test/README.md

@@ -2,6 +2,8 @@
 
 ## Automatic Tests
 
+Not required for normal funcioning of library
+
 ### NodeJS using TensorFlow library
 
 - Image filters are disabled due to lack of Canvas and WeBGL access

test/test-main.js

@@ -140,22 +140,22 @@ async function test(Human, inputConfig) {
 
   log('info', 'test body variants');
   config.body = { modelPath: 'posenet.json', enabled: true };
-  await testDetect(human, 'assets/human-sample-body.jpg', 'posenet');
+  await testDetect(human, 'samples/ai-body.jpg', 'posenet');
   config.body = { modelPath: 'movenet-lightning.json', enabled: true };
-  await testDetect(human, 'assets/human-sample-body.jpg', 'movenet');
+  await testDetect(human, 'samples/ai-body.jpg', 'movenet');
 
   await testDetect(human, null, 'default');
   log('info', 'test: first instance');
-  await testDetect(human, 'assets/sample-me.jpg', 'default');
+  await testDetect(human, 'samples/ai-upper.jpg', 'default');
   log('info', 'test: second instance');
   const second = new Human(config);
-  await testDetect(second, 'assets/sample-me.jpg', 'default');
+  await testDetect(second, 'samples/ai-upper.jpg', 'default');
   log('info', 'test: concurrent');
   await Promise.all([
-    testDetect(human, 'assets/human-sample-face.jpg', 'default'),
-    testDetect(second, 'assets/human-sample-face.jpg', 'default'),
-    testDetect(human, 'assets/human-sample-body.jpg', 'default'),
-    testDetect(second, 'assets/human-sample-body.jpg', 'default'),
+    testDetect(human, 'samples/ai-face.jpg', 'default'),
+    testDetect(second, 'samples/ai-face.jpg', 'default'),
+    testDetect(human, 'samples/ai-body.jpg', 'default'),
+    testDetect(second, 'samples/ai-body.jpg', 'default'),
   ]);
   const t1 = process.hrtime.bigint();
   log('info', 'test complete:', Math.trunc(Number(t1 - t0) / 1000 / 1000), 'ms');