Add tests to imageclassifier

fix video issue in imageclassifier

Author: cvalenzuela

src/ImageClassifier/index.js

@@ -46,9 +46,11 @@ class ImageClassifier {
     await this.ready;
     await tf.nextFrame();
 
-    // Classify the image using the selected model
-    this.addedListener = true;
-    await new Promise(resolve => this.video.addEventListener('onloadstart', resolve));
+    if (this.video) {
+      this.addedListener = true;
+      await new Promise(resolve => this.video.addEventListener('onloadstart', resolve));
+    }
+
     return this.model.classify(imgToPredict, numberOfClasses);
   }
 

src/ImageClassifier/index_test.js

@@ -1,45 +1,39 @@
 /* eslint new-cap: 0 */
 
-// const { ImageClassifier } = ml5;
-
-// const DEFAULTS = {
-//   learningRate: 0.0001,
-//   hiddenUnits: 100,
-//   epochs: 20,
-//   numClasses: 2,
-//   batchSize: 0.4,
-// };
-
-describe('underlying Mobilenet', () => {
-  // This is the core issue: Mobilenet itself cannot be initialized
-  // in the karma / webpack / etc environment
-  // it('Can initialize mobilenet', async () => {
-  //   await mobilenet.load();
-  // });
-});
+const { tf, imageClassifier } = ml5;
+
+const DEFAULTS = {
+  learningRate: 0.0001,
+  hiddenUnits: 100,
+  epochs: 20,
+  numClasses: 2,
+  batchSize: 0.4,
+  topk: 3,
+  alpha: 1,
+  version: 1,
+};
 
 describe('Create an image classifier', () => {
-  // let classifier;
-
-
-  // beforeEach(async () => {
-  //   jasmine.DEFAULT_TIMEOUT_INTERVAL = 10000;
-  //   classifier = await imageClassifier('MobileNet', undefined, {});
-  // });
-
-  // it('Should create a classifier with all the defaults', async () => {
-  //   expect(classifier.version).toBe(MOBILENET_DEFAULTS.version);
-  //   expect(classifier.alpha).toBe(MOBILENET_DEFAULTS.alpha);
-  //   expect(classifier.topk).toBe(MOBILENET_DEFAULTS.topk);
-  //   expect(classifier.ready).toBeTruthy();
-  // });
-
-  // it('Should classify an image', async () => {
-  //   const img = new Image();
-  //   img.crossOrigin = '';
-  //   img.src = 'https://ml5js.org/docs/assets/img/bird.jpg';
-  //   await new Promise((resolve) => { img.onload = resolve; });
-  //   const results = await classifier.predict(img);
-  //   expect(results[0].className).toBe('robin, American robin, Turdus migratorius');
-  // });
+  let classifier;
+
+  beforeEach(async () => {
+    jasmine.DEFAULT_TIMEOUT_INTERVAL = 10000;
+    classifier = await imageClassifier('MobileNet', undefined, {});
+  });
+
+  it('Should create a classifier with all the defaults', async () => {
+    expect(classifier.version).toBe(DEFAULTS.version);
+    expect(classifier.alpha).toBe(DEFAULTS.alpha);
+    expect(classifier.topk).toBe(DEFAULTS.topk);
+    expect(classifier.ready).toBeTruthy();
+  });
+
+  it('Should classify an robin, American robin, Turdus migratorius', async () => {
+    const img = new Image();
+    img.crossOrigin = '';
+    img.src = 'https://ml5js.org/docs/assets/img/bird.jpg';
+    await new Promise((resolve) => { img.onload = resolve; });
+    classifier.predict(img)
+      .then(results => expect(results[0].className).toBe('robin, American robin, Turdus migratorius'));
+  });
 });

src/Word2vec/index_test.js

@@ -1,5 +1,5 @@
 /* eslint no-loop-func: 0 */
-const { tf, word2vec } = ml5;
+const { word2vec } = ml5;
 
 const URL = 'https://raw.githubusercontent.com/ml5js/ml5-data-and-training/master/models/wordvecs/common-english/wordvecs1000.json';