Examples with Classifier com.ibm.watson.developer_cloud.visual_recognition.v3.model.Classifier used on opensource projects

Example 6 with Classifier

use of com.ibm.watson.developer_cloud.visual_recognition.v3.model.Classifier in project java-sdk by watson-developer-cloud.

the class VisualRecognitionIT method testCreateClassifierAndClassifyImage.

/**
 * Test create a classifier.
 *
 * @throws FileNotFoundException the file not found exception
 * @throws InterruptedException the interrupted exception
 */
@Ignore
@Test
public void testCreateClassifierAndClassifyImage() throws FileNotFoundException, InterruptedException {
    String classifierName = "integration-test-java-sdk";
    String carClassifier = "car";
    String baseballClassifier = "baseball";
    File carImages = new File("src/test/resources/visual_recognition/car_positive.zip");
    File baseballImages = new File("src/test/resources/visual_recognition/baseball_positive.zip");
    File negativeImages = new File("src/test/resources/visual_recognition/negative.zip");
    File imageToClassify = new File("src/test/resources/visual_recognition/car.png");
    CreateClassifierOptions.Builder builder = new CreateClassifierOptions.Builder().name(classifierName);
    builder.addClass(carClassifier, carImages);
    builder.addClass(baseballClassifier, baseballImages);
    builder.negativeExamples(negativeImages);
    Classifier newClassifier = service.createClassifier(builder.build()).execute();
    try {
        assertEquals(classifierName, newClassifier.getName());
        boolean ready = false;
        for (int x = 0; (x < 20) && !ready; x++) {
            Thread.sleep(2000);
            GetClassifierOptions getOptions = new GetClassifierOptions.Builder(newClassifier.getClassifierId()).build();
            newClassifier = service.getClassifier(getOptions).execute();
            ready = newClassifier.getStatus().equals(Status.READY);
        }
        assertEquals(Status.READY, newClassifier.getStatus());
        ClassifyOptions options = new ClassifyOptions.Builder().imagesFile(imageToClassify).build();
        ClassifiedImages classification = service.classify(options).execute();
        assertNotNull(classification);
    } finally {
        DeleteClassifierOptions deleteOptions = new DeleteClassifierOptions.Builder(newClassifier.getClassifierId()).build();
        service.deleteClassifier(deleteOptions).execute();
    }
}

Example 7 with Classifier

use of com.ibm.watson.developer_cloud.visual_recognition.v3.model.Classifier in project java-sdk by watson-developer-cloud.

the class VisualRecognitionTest method testUpdateClassifier.

/**
 * Test update classifier.
 *
 * @throws IOException Signals that an I/O exception has occurred.
 * @throws InterruptedException the interrupted exception
 */
@Test
public void testUpdateClassifier() throws IOException, InterruptedException {
    Classifier mockResponse = loadFixture(FIXTURE_CLASSIFIER, Classifier.class);
    server.enqueue(new MockResponse().setBody(mockResponse.toString()));
    // execute request
    File images = new File(IMAGE_FILE);
    String class1 = "class1";
    String classifierId = "foo123";
    UpdateClassifierOptions options = new UpdateClassifierOptions.Builder(classifierId).addClass(class1, images).build();
    Classifier serviceResponse = service.updateClassifier(options).execute();
    // first request
    String path = String.format(PATH_CLASSIFIER, classifierId);
    RecordedRequest request = server.takeRequest();
    path += "?" + VERSION_DATE + "=2016-05-20&api_key=" + API_KEY;
    assertEquals(path, request.getPath());
    assertEquals("POST", request.getMethod());
    String body = request.getBody().readUtf8();
    String contentDisposition = "Content-Disposition: form-data; name=\"class1_positive_examples\"; filename=\"test.zip\"";
    assertTrue(body.contains(contentDisposition));
    assertTrue(!body.contains("Content-Disposition: form-data; name=\"name\""));
    assertEquals(serviceResponse, mockResponse);
}

Example 8 with Classifier

use of com.ibm.watson.developer_cloud.visual_recognition.v3.model.Classifier in project java-sdk by watson-developer-cloud.

the class NaturalLanguageClassifier method getClassifier.

/**
 * Get information about a classifier.
 *
 * Returns status and other information about a classifier.
 *
 * @param getClassifierOptions the {@link GetClassifierOptions} containing the options for the call
 * @return a {@link ServiceCall} with a response type of {@link Classifier}
 */
public ServiceCall<Classifier> getClassifier(GetClassifierOptions getClassifierOptions) {
    Validator.notNull(getClassifierOptions, "getClassifierOptions cannot be null");
    String[] pathSegments = { "v1/classifiers" };
    String[] pathParameters = { getClassifierOptions.classifierId() };
    RequestBuilder builder = RequestBuilder.get(RequestBuilder.constructHttpUrl(getEndPoint(), pathSegments, pathParameters));
    return createServiceCall(builder.build(), ResponseConverterUtils.getObject(Classifier.class));
}

Example 9 with Classifier

use of com.ibm.watson.developer_cloud.visual_recognition.v3.model.Classifier in project java-sdk by watson-developer-cloud.

the class NaturalLanguageClassifier method createClassifier.

/**
 * Create classifier.
 *
 * Sends data to create and train a classifier and returns information about the new classifier.
 *
 * @param createClassifierOptions the {@link CreateClassifierOptions} containing the options for the call
 * @return a {@link ServiceCall} with a response type of {@link Classifier}
 */
public ServiceCall<Classifier> createClassifier(CreateClassifierOptions createClassifierOptions) {
    Validator.notNull(createClassifierOptions, "createClassifierOptions cannot be null");
    String[] pathSegments = { "v1/classifiers" };
    RequestBuilder builder = RequestBuilder.post(RequestBuilder.constructHttpUrl(getEndPoint(), pathSegments));
    MultipartBody.Builder multipartBuilder = new MultipartBody.Builder();
    multipartBuilder.setType(MultipartBody.FORM);
    RequestBody trainingMetadataBody = RequestUtils.inputStreamBody(createClassifierOptions.metadata(), "application/json");
    multipartBuilder.addFormDataPart("training_metadata", createClassifierOptions.metadataFilename(), trainingMetadataBody);
    RequestBody trainingDataBody = RequestUtils.inputStreamBody(createClassifierOptions.trainingData(), "text/csv");
    multipartBuilder.addFormDataPart("training_data", createClassifierOptions.trainingDataFilename(), trainingDataBody);
    builder.body(multipartBuilder.build());
    return createServiceCall(builder.build(), ResponseConverterUtils.getObject(Classifier.class));
}

Example 10 with Classifier

use of com.ibm.watson.developer_cloud.visual_recognition.v3.model.Classifier in project java-sdk by watson-developer-cloud.

the class VisualRecognitionExample method main.

public static void main(String[] args) {
    VisualRecognition service = new VisualRecognition("2016-05-20");
    service.setApiKey("<api-key>");
    System.out.println("Classify an image");
    ClassifyOptions options = new ClassifyOptions.Builder().imagesFile(new File("src/test/resources/visual_recognition/car.png")).imagesFilename("car.png").build();
    ClassifiedImages result = service.classify(options).execute();
    System.out.println(result);
    System.out.println("Create a classifier with positive and negative images");
    CreateClassifierOptions createOptions = new CreateClassifierOptions.Builder().name("foo").addClass("car", new File("src/test/resources/visual_recognition/car_positive.zip")).addClass("baseball", new File("src/test/resources/visual_recognition/baseball_positive.zip")).negativeExamples(new File("src/test/resources/visual_recognition/negative.zip")).build();
    Classifier foo = service.createClassifier(createOptions).execute();
    System.out.println(foo);
    System.out.println("Classify using the 'Car' classifier");
    options = new ClassifyOptions.Builder().imagesFile(new File("src/test/resources/visual_recognition/car.png")).imagesFilename("car.png").addClassifierId(foo.getClassifierId()).build();
    result = service.classify(options).execute();
    System.out.println(result);
    System.out.println("Update a classifier with more positive images");
    UpdateClassifierOptions updateOptions = new UpdateClassifierOptions.Builder().classifierId(foo.getClassifierId()).addClass("car", new File("src/test/resources/visual_recognition/car_positive.zip")).build();
    Classifier updatedFoo = service.updateClassifier(updateOptions).execute();
    System.out.println(updatedFoo);
}