Examples with Classifier com.ibm.watson.developer_cloud.natural_language_classifier.v1.model.Classifier used on opensource projects

Example 26 with Classifier

use of com.ibm.watson.developer_cloud.natural_language_classifier.v1.model.Classifier in project java-sdk by watson-developer-cloud.

the class VisualRecognitionTest method testCreateClassifier.

/**
 * Test create classifier.
 *
 * @throws IOException Signals that an I/O exception has occurred.
 * @throws InterruptedException the interrupted exception
 */
@Test
public void testCreateClassifier() throws IOException, InterruptedException {
    Classifier mockResponse = loadFixture(FIXTURE_CLASSIFIER, Classifier.class);
    server.enqueue(new MockResponse().setBody(mockResponse.toString()));
    // execute request
    File positiveImages = new File(IMAGE_FILE);
    File negativeImages = new File(IMAGE_FILE);
    String class1 = "class1";
    CreateClassifierOptions options = new CreateClassifierOptions.Builder().name(class1).addClass(class1, positiveImages).negativeExamples(negativeImages).build();
    Classifier serviceResponse = service.createClassifier(options).execute();
    // first request
    RecordedRequest request = server.takeRequest();
    String path = PATH_CLASSIFIERS + "?" + 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 27 with Classifier

use of com.ibm.watson.developer_cloud.natural_language_classifier.v1.model.Classifier in project java-sdk by watson-developer-cloud.

the class VisualRecognitionTest method testGetClassifiers.

/**
 * Test get classifiers.
 *
 * @throws InterruptedException the interrupted exception
 * @throws IOException Signals that an I/O exception has occurred.
 */
@Test
public void testGetClassifiers() throws InterruptedException, IOException {
    Classifier mockClassifier = loadFixture(FIXTURE_CLASSIFIER, Classifier.class);
    List<Classifier> classifiers = new ArrayList<Classifier>();
    classifiers.add(mockClassifier);
    classifiers.add(mockClassifier);
    classifiers.add(mockClassifier);
    JsonObject mockResponse = new JsonObject();
    mockResponse.add("classifiers", new Gson().toJsonTree(classifiers));
    server.enqueue(new MockResponse().setBody(mockResponse.toString()));
    ListClassifiersOptions options = new ListClassifiersOptions.Builder().verbose(true).build();
    List<Classifier> serviceResponse = service.listClassifiers(options).execute().getClassifiers();
    // first request
    RecordedRequest request = server.takeRequest();
    String path = PATH_CLASSIFIERS + "?" + VERSION_DATE + "=2016-05-20&verbose=true&api_key=" + API_KEY;
    assertEquals(path, request.getPath());
    assertEquals("GET", request.getMethod());
    assertEquals(serviceResponse, classifiers);
}

Example 28 with Classifier

use of com.ibm.watson.developer_cloud.natural_language_classifier.v1.model.Classifier in project java-sdk by watson-developer-cloud.

the class VisualRecognitionTest method testGetClassifier.

/**
 * Test get classifier.
 *
 * @throws InterruptedException the interrupted exception
 * @throws IOException Signals that an I/O exception has occurred.
 */
@Test
public void testGetClassifier() throws InterruptedException, IOException {
    try {
        Classifier mockResponse = loadFixture(FIXTURE_CLASSIFIER, Classifier.class);
        server.enqueue(new MockResponse().setBody(mockResponse.toString()));
        // execute request
        String class1 = "class1";
        GetClassifierOptions getOptions = new GetClassifierOptions.Builder(class1).build();
        Classifier serviceResponse = service.getClassifier(getOptions).execute();
        // first request
        RecordedRequest request = server.takeRequest();
        String path = String.format(PATH_CLASSIFIER + "?" + VERSION_DATE + "=2016-05-20&api_key=" + API_KEY, class1);
        assertEquals(path, request.getPath());
        assertEquals("GET", request.getMethod());
        assertEquals(serviceResponse, mockResponse);
    } catch (Exception e) {
        e.printStackTrace();
    }
}

Example 29 with Classifier

use of com.ibm.watson.developer_cloud.natural_language_classifier.v1.model.Classifier in project java-sdk by watson-developer-cloud.

the class VisualRecognition method createClassifier.

/**
 * Create a classifier.
 *
 * Train a new multi-faceted classifier on the uploaded image data. Create your custom classifier with positive or
 * negative examples. Include at least two sets of examples, either two positive example files or one positive and one
 * negative file. You can upload a maximum of 256 MB per call. Encode all names in UTF-8 if they contain non-ASCII
 * characters (.zip and image file names, and classifier and class names). The service assumes UTF-8 encoding if it
 * encounters non-ASCII characters.
 *
 * @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 = { "v3/classifiers" };
    RequestBuilder builder = RequestBuilder.post(RequestBuilder.constructHttpUrl(getEndPoint(), pathSegments));
    builder.query(VERSION, versionDate);
    MultipartBody.Builder multipartBuilder = new MultipartBody.Builder();
    multipartBuilder.setType(MultipartBody.FORM);
    multipartBuilder.addFormDataPart("name", createClassifierOptions.name());
    // Classes
    for (String className : createClassifierOptions.classNames()) {
        String dataName = className + "_positive_examples";
        File positiveExamples = createClassifierOptions.positiveExamplesByClassName(className);
        RequestBody body = RequestUtils.fileBody(positiveExamples, "application/octet-stream");
        multipartBuilder.addFormDataPart(dataName, positiveExamples.getName(), body);
    }
    if (createClassifierOptions.negativeExamples() != null) {
        RequestBody negativeExamplesBody = RequestUtils.inputStreamBody(createClassifierOptions.negativeExamples(), "application/octet-stream");
        multipartBuilder.addFormDataPart("negative_examples", createClassifierOptions.negativeExamplesFilename(), negativeExamplesBody);
    }
    builder.body(multipartBuilder.build());
    return createServiceCall(builder.build(), ResponseConverterUtils.getObject(Classifier.class));
}