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

Example 1 with UpdateClassifierOptions

use of com.ibm.watson.visual_recognition.v3.model.UpdateClassifierOptions 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 2 with UpdateClassifierOptions

use of com.ibm.watson.visual_recognition.v3.model.UpdateClassifierOptions 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);
}

Example 3 with UpdateClassifierOptions

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

the class VisualRecognition method updateClassifier.

/**
 * Update a classifier.
 *
 * <p>Update a custom classifier by adding new positive or negative classes or by adding new
 * images to existing classes. You must supply at least one set of positive or negative examples.
 * For details, see [Updating custom
 * classifiers](https://cloud.ibm.com/docs/visual-recognition?topic=visual-recognition-customizing#updating-custom-classifiers).
 *
 * <p>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.
 *
 * <p>**Tips about retraining:**
 *
 * <p>- You can't update the classifier if the **X-Watson-Learning-Opt-Out** header parameter was
 * set to `true` when the classifier was created. Training images are not stored in that case.
 * Instead, create another classifier. For more information, see [Data
 * collection](#data-collection).
 *
 * <p>- Don't make retraining calls on a classifier until the status is ready. When you submit
 * retraining requests in parallel, the last request overwrites the previous requests. The
 * `retrained` property shows the last time the classifier retraining finished.
 *
 * @param updateClassifierOptions the {@link UpdateClassifierOptions} containing the options for
 *     the call
 * @return a {@link ServiceCall} with a result of type {@link Classifier}
 */
public ServiceCall<Classifier> updateClassifier(UpdateClassifierOptions updateClassifierOptions) {
    com.ibm.cloud.sdk.core.util.Validator.notNull(updateClassifierOptions, "updateClassifierOptions cannot be null");
    com.ibm.cloud.sdk.core.util.Validator.isTrue((updateClassifierOptions.positiveExamples() != null) || (updateClassifierOptions.negativeExamples() != null), "At least one of positiveExamples or negativeExamples must be supplied.");
    Map<String, String> pathParamsMap = new HashMap<String, String>();
    pathParamsMap.put("classifier_id", updateClassifierOptions.classifierId());
    RequestBuilder builder = RequestBuilder.post(RequestBuilder.resolveRequestUrl(getServiceUrl(), "/v3/classifiers/{classifier_id}", pathParamsMap));
    Map<String, String> sdkHeaders = SdkCommon.getSdkHeaders("watson_vision_combined", "v3", "updateClassifier");
    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));
    MultipartBody.Builder multipartBuilder = new MultipartBody.Builder();
    multipartBuilder.setType(MultipartBody.FORM);
    if (updateClassifierOptions.positiveExamples() != null) {
        for (Map.Entry<String, InputStream> entry : updateClassifierOptions.positiveExamples().entrySet()) {
            String partName = String.format("%s_positive_examples", entry.getKey());
            okhttp3.RequestBody part = RequestUtils.inputStreamBody(entry.getValue(), "application/octet-stream");
            multipartBuilder.addFormDataPart(partName, entry.getKey(), part);
        }
    }
    if (updateClassifierOptions.negativeExamples() != null) {
        okhttp3.RequestBody negativeExamplesBody = RequestUtils.inputStreamBody(updateClassifierOptions.negativeExamples(), "application/octet-stream");
        multipartBuilder.addFormDataPart("negative_examples", updateClassifierOptions.negativeExamplesFilename(), negativeExamplesBody);
    }
    builder.body(multipartBuilder.build());
    ResponseConverter<Classifier> responseConverter = ResponseConverterUtils.getValue(new com.google.gson.reflect.TypeToken<Classifier>() {
    }.getType());
    return createServiceCall(builder.build(), responseConverter);
}

Example 4 with UpdateClassifierOptions

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

the class VisualRecognitionTest method testUpdateClassifierWOptions.

@Test
public void testUpdateClassifierWOptions() throws Throwable {
    // Schedule some responses.
    String mockResponseBody = "{\"classifier_id\": \"classifierId\", \"name\": \"name\", \"owner\": \"owner\", \"status\": \"ready\", \"core_ml_enabled\": false, \"explanation\": \"explanation\", \"created\": \"2019-01-01T12:00:00.000Z\", \"classes\": [{\"class\": \"xClass\"}], \"retrained\": \"2019-01-01T12:00:00.000Z\", \"updated\": \"2019-01-01T12:00:00.000Z\"}";
    String updateClassifierPath = "/v3/classifiers/testString";
    server.enqueue(new MockResponse().setHeader("Content-type", "application/json").setResponseCode(200).setBody(mockResponseBody));
    constructClientService();
    // Construct an instance of the UpdateClassifierOptions model
    UpdateClassifierOptions updateClassifierOptionsModel = new UpdateClassifierOptions.Builder().classifierId("testString").positiveExamples(mockStreamMap).negativeExamples(TestUtilities.createMockStream("This is a mock file.")).negativeExamplesFilename("testString").build();
    // Invoke operation with valid options model (positive test)
    Response<Classifier> response = visualRecognitionService.updateClassifier(updateClassifierOptionsModel).execute();
    assertNotNull(response);
    Classifier 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, updateClassifierPath);
}