### Question:
ObjectDetectionWithTensorflowSavedModel { public static DetectedObjects predict() throws IOException, ModelException, TranslateException { if (!"TensorFlow".equals(Engine.getInstance().getEngineName())) { return null; } Path imageFile = Paths.get("src/test/resources/dog_bike_car.jpg"); Image img = ImageFactory.getInstance().fromFile(imageFile); String modelUrl = "http: Criteria<Image, DetectedObjects> criteria = Criteria.builder() .optApplication(Application.CV.OBJECT_DETECTION) .setTypes(Image.class, DetectedObjects.class) .optModelUrls(modelUrl) .optModelName("ssd_mobilenet_v2_320x320_coco17_tpu-8/saved_model") .optTranslator(new MyTranslator()) .optProgress(new ProgressBar()) .build(); try (ZooModel<Image, DetectedObjects> model = ModelZoo.loadModel(criteria); Predictor<Image, DetectedObjects> predictor = model.newPredictor()) { DetectedObjects detection = predictor.predict(img); saveBoundingBoxImage(img, detection); return detection; } } private  ObjectDetectionWithTensorflowSavedModel(); static void main(String[] args); static DetectedObjects predict();  }### Answer:
@Test public void testObjectDetection() throws ModelException, TranslateException, IOException { if (Boolean.getBoolean("nightly")) { DetectedObjects result = ObjectDetectionWithTensorflowSavedModel.predict(); if (result == null) { throw new SkipException("Only works for TensorFlow engine."); } Assert.assertEquals(result.getNumberOfObjects(), 3); List<String> objects = Arrays.asList("dog", "bicycle", "car"); for (Classifications.Classification obj : result.items()) { Assert.assertTrue(objects.contains(obj.getClassName())); Assert.assertTrue(Double.compare(obj.getProbability(), 0.7) > 0); } } }