Examples with TrainOptions com.ibm.watson.visual_recognition.v4.model.TrainOptions used on opensource projects

Example 1 with TrainOptions

use of com.ibm.watson.visual_recognition.v4.model.TrainOptions in project java-sdk by watson-developer-cloud.

the class VisualRecognitionIT method testTrainingOperations.

/**
 * Test training operations.
 *
 * @throws FileNotFoundException the file not found exception
 */
@Test
public void testTrainingOperations() throws FileNotFoundException {
    String testCollectionId = createTestCollection();
    // start by adding images for training
    FileWithMetadata giraffeFileZip = new FileWithMetadata.Builder().data(new File(GIRAFFE_POSITIVE_EXAMPLES_PATH)).contentType(HttpMediaType.APPLICATION_ZIP).build();
    AddImagesOptions addImagesOptions = new AddImagesOptions.Builder().addImagesFile(giraffeFileZip).collectionId(testCollectionId).build();
    ImageDetailsList imageDetailsList = service.addImages(addImagesOptions).execute().getResult();
    String imageIdForTraining = null;
    Set<String> addedImageIds = new HashSet<>();
    for (ImageDetails imageDetails : imageDetailsList.getImages()) {
        addedImageIds.add(imageDetails.getImageId());
        if (imageIdForTraining == null) {
            imageIdForTraining = imageDetails.getImageId();
        }
    }
    try {
        Long top = 64L;
        Long left = 270L;
        Long width = 755L;
        Long height = 784L;
        Location testLocation = new Location.Builder().top(top).left(left).width(width).height(height).build();
        TrainingDataObject trainingDataObject = new TrainingDataObject.Builder().object(GIRAFFE_CLASSNAME).location(testLocation).build();
        // test adding training data
        AddImageTrainingDataOptions addTrainingDataOptions = new AddImageTrainingDataOptions.Builder().collectionId(testCollectionId).addObjects(trainingDataObject).imageId(imageIdForTraining).build();
        TrainingDataObjects trainingDataObjects = service.addImageTrainingData(addTrainingDataOptions).execute().getResult();
        assertNotNull(trainingDataObjects);
        assertEquals(GIRAFFE_CLASSNAME, trainingDataObjects.getObjects().get(0).object());
        assertEquals(top, trainingDataObjects.getObjects().get(0).location().top());
        assertEquals(left, trainingDataObjects.getObjects().get(0).location().left());
        assertEquals(width, trainingDataObjects.getObjects().get(0).location().width());
        assertEquals(height, trainingDataObjects.getObjects().get(0).location().height());
        // test train
        TrainOptions trainOptions = new TrainOptions.Builder().collectionId(testCollectionId).build();
        Collection trainingCollection = service.train(trainOptions).execute().getResult();
        assertNotNull(trainingCollection);
        assertTrue(trainingCollection.getTrainingStatus().getObjects().inProgress() || trainingCollection.getTrainingStatus().getObjects().ready());
    } finally {
        // delete images we added earlier
        for (String imageId : addedImageIds) {
            DeleteImageOptions deleteImageOptions = new DeleteImageOptions.Builder().collectionId(testCollectionId).imageId(imageId).build();
            service.deleteImage(deleteImageOptions).execute();
        }
        deleteTestCollection(testCollectionId);
    }
}

Example 2 with TrainOptions

use of com.ibm.watson.visual_recognition.v4.model.TrainOptions in project java-sdk by watson-developer-cloud.

the class VisualRecognition method train.

/**
 * Train a collection.
 *
 * <p>Start training on images in a collection. The collection must have enough training data and
 * untrained data (the **training_status.objects.data_changed** is `true`). If training is in
 * progress, the request queues the next training job.
 *
 * @param trainOptions the {@link TrainOptions} containing the options for the call
 * @return a {@link ServiceCall} with a result of type {@link Collection}
 */
public ServiceCall<Collection> train(TrainOptions trainOptions) {
    com.ibm.cloud.sdk.core.util.Validator.notNull(trainOptions, "trainOptions cannot be null");
    Map<String, String> pathParamsMap = new HashMap<String, String>();
    pathParamsMap.put("collection_id", trainOptions.collectionId());
    RequestBuilder builder = RequestBuilder.post(RequestBuilder.resolveRequestUrl(getServiceUrl(), "/v4/collections/{collection_id}/train", pathParamsMap));
    Map<String, String> sdkHeaders = SdkCommon.getSdkHeaders("watson_vision_combined", "v4", "train");
    for (Entry<String, String> header : sdkHeaders.entrySet()) {
        builder.header(header.getKey(), header.getValue());
    }
    builder.header("Accept", "application/json");
    builder.query("version", String.valueOf(this.version));
    ResponseConverter<Collection> responseConverter = ResponseConverterUtils.getValue(new com.google.gson.reflect.TypeToken<Collection>() {
    }.getType());
    return createServiceCall(builder.build(), responseConverter);
}

Example 3 with TrainOptions

use of com.ibm.watson.visual_recognition.v4.model.TrainOptions in project java-sdk by watson-developer-cloud.

the class VisualRecognitionTest method testTrainWOptions.

@Test
public void testTrainWOptions() throws Throwable {
    // Schedule some responses.
    String mockResponseBody = "{\"collection_id\": \"collectionId\", \"name\": \"name\", \"description\": \"description\", \"created\": \"2019-01-01T12:00:00.000Z\", \"updated\": \"2019-01-01T12:00:00.000Z\", \"image_count\": 10, \"training_status\": {\"objects\": {\"ready\": false, \"in_progress\": true, \"data_changed\": false, \"latest_failed\": true, \"rscnn_ready\": true, \"description\": \"description\"}}}";
    String trainPath = "/v4/collections/testString/train";
    server.enqueue(new MockResponse().setHeader("Content-type", "application/json").setResponseCode(202).setBody(mockResponseBody));
    constructClientService();
    // Construct an instance of the TrainOptions model
    TrainOptions trainOptionsModel = new TrainOptions.Builder().collectionId("testString").build();
    // Invoke operation with valid options model (positive test)
    Response<Collection> response = visualRecognitionService.train(trainOptionsModel).execute();
    assertNotNull(response);
    Collection responseObj = response.getResult();
    assertNotNull(responseObj);
    // Verify the contents of the request
    RecordedRequest request = server.takeRequest();
    assertNotNull(request);
    assertEquals(request.getMethod(), "POST");
    // Check query
    Map<String, String> query = TestUtilities.parseQueryString(request);
    assertNotNull(query);
    // Get query params
    assertEquals(query.get("version"), "testString");
    // Check request path
    String parsedPath = TestUtilities.parseReqPath(request);
    assertEquals(parsedPath, trainPath);
}