Java Code Examples for com.google.cloud.vision.v1.Feature.Type

The following examples show how to use com.google.cloud.vision.v1.Feature.Type. These examples are extracted from open source projects. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may check out the related API usage on the sidebar.
Example 1
Source Project: spring-cloud-gcp   Source File: CloudVisionTemplateTests.java    License: Apache License 2.0 6 votes vote down vote up
@Test
public void testAddImageContext_analyzeImage() throws IOException {
	when(this.imageAnnotatorClient.batchAnnotateImages(any(BatchAnnotateImagesRequest.class)))
			.thenReturn(DEFAULT_API_RESPONSE);

	ImageContext imageContext = Mockito.mock(ImageContext.class);

	this.cloudVisionTemplate.analyzeImage(FAKE_IMAGE, imageContext, Type.FACE_DETECTION);

	BatchAnnotateImagesRequest expectedRequest =
			BatchAnnotateImagesRequest.newBuilder()
					.addRequests(
							AnnotateImageRequest.newBuilder()
									.addFeatures(Feature.newBuilder().setType(Type.FACE_DETECTION))
									.setImageContext(imageContext)
									.setImage(Image.newBuilder().setContent(
											ByteString.readFrom(FAKE_IMAGE.getInputStream())).build()))
					.build();

	verify(this.imageAnnotatorClient, times(1)).batchAnnotateImages(expectedRequest);
}
 
Example 2
Source Project: spring-cloud-gcp   Source File: CloudVisionTemplateTests.java    License: Apache License 2.0 6 votes vote down vote up
@Test
public void testAddImageContext_extractText() throws IOException {
	when(this.imageAnnotatorClient.batchAnnotateImages(any(BatchAnnotateImagesRequest.class)))
			.thenReturn(DEFAULT_API_RESPONSE);

	ImageContext imageContext = Mockito.mock(ImageContext.class);

	this.cloudVisionTemplate.extractTextFromImage(FAKE_IMAGE, imageContext);

	BatchAnnotateImagesRequest expectedRequest =
			BatchAnnotateImagesRequest.newBuilder()
					.addRequests(
							AnnotateImageRequest.newBuilder()
									.addFeatures(Feature.newBuilder().setType(Type.TEXT_DETECTION))
									.setImageContext(imageContext)
									.setImage(Image.newBuilder().setContent(ByteString.readFrom(FAKE_IMAGE.getInputStream())).build()))
					.build();

	verify(this.imageAnnotatorClient, times(1)).batchAnnotateImages(expectedRequest);
}
 
Example 3
Source Project: spring-cloud-gcp   Source File: VisionController.java    License: Apache License 2.0 5 votes vote down vote up
/**
 * This method downloads an image from a URL and sends its contents to the Vision API for label detection.
 *
 * @param imageUrl the URL of the image
 * @param map the model map to use
 * @return a string with the list of labels and percentage of certainty
 * @throws org.springframework.cloud.gcp.vision.CloudVisionException if the Vision API call
 *    produces an error
 */
@GetMapping("/extractLabels")
public ModelAndView extractLabels(String imageUrl, ModelMap map) {
	AnnotateImageResponse response = this.cloudVisionTemplate.analyzeImage(
			this.resourceLoader.getResource(imageUrl), Type.LABEL_DETECTION);

	// This gets the annotations of the image from the response object.
	List<EntityAnnotation> annotations = response.getLabelAnnotationsList();

	map.addAttribute("annotations", annotations);
	map.addAttribute("imageUrl", imageUrl);

	return new ModelAndView("result", map);
}
 
Example 4
Source Project: spring-cloud-gcp   Source File: CloudVisionTemplate.java    License: Apache License 2.0 5 votes vote down vote up
/**
 * Extract the text out of an image and return the result as a String.
 * @param imageResource the image one wishes to analyze
 * @param imageContext the image context to customize the text extraction request
 * @return the text extracted from the image aggregated to a String
 * @throws CloudVisionException if the image could not be read or if text extraction failed
 */
public String extractTextFromImage(Resource imageResource, ImageContext imageContext) {
	AnnotateImageResponse response = analyzeImage(imageResource, imageContext, Type.TEXT_DETECTION);

	String result = response.getFullTextAnnotation().getText();
	if (result.isEmpty() && response.getError().getCode() != Code.OK.getNumber()) {
		throw new CloudVisionException(response.getError().getMessage());
	}

	return result;
}
 
Example 5
Source Project: spring-cloud-gcp   Source File: CloudVisionTemplate.java    License: Apache License 2.0 5 votes vote down vote up
/**
 * Analyze an image and extract the features of the image specified by
 * {@code featureTypes}.
 * <p>A feature describes the kind of Cloud Vision analysis one wishes to perform on an
 * image, such as text detection, image labelling, facial detection, etc. A full list of
 * feature types can be found in {@link Feature.Type}.
 * @param imageResource the image one wishes to analyze. The Cloud Vision APIs support
 *     image formats described here: https://cloud.google.com/vision/docs/supported-files
 * @param imageContext the image context used to customize the Vision API request
 * @param featureTypes the types of image analysis to perform on the image
 * @return the results of image analyses
 * @throws CloudVisionException if the image could not be read or if a malformed response
 *     is received from the Cloud Vision APIs
 */
public AnnotateImageResponse analyzeImage(
		Resource imageResource, ImageContext imageContext, Feature.Type... featureTypes) {
	ByteString imgBytes;
	try {
		imgBytes = ByteString.readFrom(imageResource.getInputStream());
	}
	catch (IOException ex) {
		throw new CloudVisionException("Failed to read image bytes from provided resource.", ex);
	}

	Image image = Image.newBuilder().setContent(imgBytes).build();

	List<Feature> featureList = Arrays.stream(featureTypes)
			.map((featureType) -> Feature.newBuilder().setType(featureType).build())
			.collect(Collectors.toList());

	BatchAnnotateImagesRequest request = BatchAnnotateImagesRequest.newBuilder()
			.addRequests(
					AnnotateImageRequest.newBuilder()
							.addAllFeatures(featureList)
							.setImageContext(imageContext)
							.setImage(image))
			.build();

	BatchAnnotateImagesResponse batchResponse = this.imageAnnotatorClient.batchAnnotateImages(request);
	List<AnnotateImageResponse> annotateImageResponses = batchResponse.getResponsesList();

	if (!annotateImageResponses.isEmpty()) {
		return annotateImageResponses.get(0);
	}
	else {
		throw new CloudVisionException(
				"Failed to receive valid response Vision APIs; empty response received.");
	}
}
 
Example 6
Source Project: spring-cloud-gcp   Source File: CloudVisionTemplateTests.java    License: Apache License 2.0 5 votes vote down vote up
@Test
public void testEmptyClientResponseError() {
	when(this.imageAnnotatorClient.batchAnnotateImages(any(BatchAnnotateImagesRequest.class)))
			.thenReturn(BatchAnnotateImagesResponse.getDefaultInstance());

	this.expectedException.expect(CloudVisionException.class);
	this.expectedException.expectMessage(
			"Failed to receive valid response Vision APIs; empty response received.");

	this.cloudVisionTemplate.analyzeImage(FAKE_IMAGE, Type.TEXT_DETECTION);
}
 
Example 7
Source Project: spring-cloud-gcp   Source File: CloudVisionTemplateTests.java    License: Apache License 2.0 5 votes vote down vote up
@Test
public void testIOError() {
	this.expectedException.expect(CloudVisionException.class);
	this.expectedException.expectMessage("Failed to read image bytes from provided resource.");

	this.cloudVisionTemplate.analyzeImage(new BadResource(), Type.LABEL_DETECTION);
}
 
Example 8
Source Project: java-docs-samples   Source File: VisionController.java    License: Apache License 2.0 5 votes vote down vote up
/**
 * This method downloads an image from a URL and sends its contents to the Vision API for label
 * detection.
 *
 * @param imageUrl the URL of the image
 * @param map the model map to use
 * @return a string with the list of labels and percentage of certainty
 */
@GetMapping("/extractLabels")
public ModelAndView extractLabels(String imageUrl, ModelMap map) {
  // [START spring_vision_image_labelling]
  AnnotateImageResponse response =
      this.cloudVisionTemplate.analyzeImage(
          this.resourceLoader.getResource(imageUrl), Type.LABEL_DETECTION);

  Map<String, Float> imageLabels =
      response
          .getLabelAnnotationsList()
          .stream()
          .collect(
              Collectors.toMap(
                  EntityAnnotation::getDescription,
                  EntityAnnotation::getScore,
                  (u, v) -> {
                    throw new IllegalStateException(String.format("Duplicate key %s", u));
                  },
                  LinkedHashMap::new));
  // [END spring_vision_image_labelling]

  map.addAttribute("annotations", imageLabels);
  map.addAttribute("imageUrl", imageUrl);

  return new ModelAndView("result", map);
}
 
Example 9
Source Project: java-docs-samples   Source File: QuickstartSample.java    License: Apache License 2.0 5 votes vote down vote up
public static void main(String... args) throws Exception {
  // Initialize client that will be used to send requests. This client only needs to be created
  // once, and can be reused for multiple requests. After completing all of your requests, call
  // the "close" method on the client to safely clean up any remaining background resources.
  try (ImageAnnotatorClient vision = ImageAnnotatorClient.create()) {

    // The path to the image file to annotate
    String fileName = "./resources/wakeupcat.jpg";

    // Reads the image file into memory
    Path path = Paths.get(fileName);
    byte[] data = Files.readAllBytes(path);
    ByteString imgBytes = ByteString.copyFrom(data);

    // Builds the image annotation request
    List<AnnotateImageRequest> requests = new ArrayList<>();
    Image img = Image.newBuilder().setContent(imgBytes).build();
    Feature feat = Feature.newBuilder().setType(Type.LABEL_DETECTION).build();
    AnnotateImageRequest request =
        AnnotateImageRequest.newBuilder().addFeatures(feat).setImage(img).build();
    requests.add(request);

    // Performs label detection on the image file
    BatchAnnotateImagesResponse response = vision.batchAnnotateImages(requests);
    List<AnnotateImageResponse> responses = response.getResponsesList();

    for (AnnotateImageResponse res : responses) {
      if (res.hasError()) {
        System.out.format("Error: %s%n", res.getError().getMessage());
        return;
      }

      for (EntityAnnotation annotation : res.getLabelAnnotationsList()) {
        annotation
            .getAllFields()
            .forEach((k, v) -> System.out.format("%s : %s%n", k, v.toString()));
      }
    }
  }
}
 
Example 10
Source Project: java-docs-samples   Source File: Detect.java    License: Apache License 2.0 5 votes vote down vote up
/**
 * Detects localized objects in the specified local image.
 *
 * @param filePath The path to the file to perform localized object detection on.
 * @throws Exception on errors while closing the client.
 * @throws IOException on Input/Output errors.
 */
public static void detectLocalizedObjects(String filePath) throws IOException {
  List<AnnotateImageRequest> requests = new ArrayList<>();

  ByteString imgBytes = ByteString.readFrom(new FileInputStream(filePath));

  Image img = Image.newBuilder().setContent(imgBytes).build();
  AnnotateImageRequest request =
      AnnotateImageRequest.newBuilder()
          .addFeatures(Feature.newBuilder().setType(Type.OBJECT_LOCALIZATION))
          .setImage(img)
          .build();
  requests.add(request);

  // Initialize client that will be used to send requests. This client only needs to be created
  // once, and can be reused for multiple requests. After completing all of your requests, call
  // the "close" method on the client to safely clean up any remaining background resources.
  try (ImageAnnotatorClient client = ImageAnnotatorClient.create()) {
    // Perform the request
    BatchAnnotateImagesResponse response = client.batchAnnotateImages(requests);
    List<AnnotateImageResponse> responses = response.getResponsesList();

    // Display the results
    for (AnnotateImageResponse res : responses) {
      for (LocalizedObjectAnnotation entity : res.getLocalizedObjectAnnotationsList()) {
        System.out.format("Object name: %s%n", entity.getName());
        System.out.format("Confidence: %s%n", entity.getScore());
        System.out.format("Normalized Vertices:%n");
        entity
            .getBoundingPoly()
            .getNormalizedVerticesList()
            .forEach(vertex -> System.out.format("- (%s, %s)%n", vertex.getX(), vertex.getY()));
      }
    }
  }
}
 
Example 11
Source Project: java-docs-samples   Source File: Detect.java    License: Apache License 2.0 5 votes vote down vote up
/**
 * Detects localized objects in a remote image on Google Cloud Storage.
 *
 * @param gcsPath The path to the remote file on Google Cloud Storage to detect localized objects
 *     on.
 * @throws Exception on errors while closing the client.
 * @throws IOException on Input/Output errors.
 */
public static void detectLocalizedObjectsGcs(String gcsPath) throws IOException {
  List<AnnotateImageRequest> requests = new ArrayList<>();

  ImageSource imgSource = ImageSource.newBuilder().setGcsImageUri(gcsPath).build();
  Image img = Image.newBuilder().setSource(imgSource).build();

  AnnotateImageRequest request =
      AnnotateImageRequest.newBuilder()
          .addFeatures(Feature.newBuilder().setType(Type.OBJECT_LOCALIZATION))
          .setImage(img)
          .build();
  requests.add(request);

  // Initialize client that will be used to send requests. This client only needs to be created
  // once, and can be reused for multiple requests. After completing all of your requests, call
  // the "close" method on the client to safely clean up any remaining background resources.
  try (ImageAnnotatorClient client = ImageAnnotatorClient.create()) {
    // Perform the request
    BatchAnnotateImagesResponse response = client.batchAnnotateImages(requests);
    List<AnnotateImageResponse> responses = response.getResponsesList();
    client.close();
    // Display the results
    for (AnnotateImageResponse res : responses) {
      for (LocalizedObjectAnnotation entity : res.getLocalizedObjectAnnotationsList()) {
        System.out.format("Object name: %s%n", entity.getName());
        System.out.format("Confidence: %s%n", entity.getScore());
        System.out.format("Normalized Vertices:%n");
        entity
            .getBoundingPoly()
            .getNormalizedVerticesList()
            .forEach(vertex -> System.out.format("- (%s, %s)%n", vertex.getX(), vertex.getY()));
      }
    }
  }
}
 
Example 12
Source Project: java-docs-samples   Source File: DetectWebEntities.java    License: Apache License 2.0 5 votes vote down vote up
public static void detectWebEntities(String filePath) throws IOException {

    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (ImageAnnotatorClient client = ImageAnnotatorClient.create()) {
      // Read in the local image
      ByteString contents = ByteString.readFrom(new FileInputStream(filePath));

      // Build the image
      Image image = Image.newBuilder().setContent(contents).build();

      // Create the request with the image and the specified feature: web detection
      AnnotateImageRequest request =
          AnnotateImageRequest.newBuilder()
              .addFeatures(Feature.newBuilder().setType(Type.WEB_DETECTION))
              .setImage(image)
              .build();

      // Perform the request
      BatchAnnotateImagesResponse response = client.batchAnnotateImages(Arrays.asList(request));

      // Display the results
      response.getResponsesList().stream()
          .forEach(
              r ->
                  r.getWebDetection().getWebEntitiesList().stream()
                      .forEach(
                          entity -> {
                            System.out.format("Description: %s%n", entity.getDescription());
                            System.out.format("Score: %f%n", entity.getScore());
                          }));
    }
  }
 
Example 13
Source Project: java-docs-samples   Source File: DetectSafeSearchGcs.java    License: Apache License 2.0 5 votes vote down vote up
public static void detectSafeSearchGcs(String gcsPath) throws IOException {
  List<AnnotateImageRequest> requests = new ArrayList<>();

  ImageSource imgSource = ImageSource.newBuilder().setGcsImageUri(gcsPath).build();
  Image img = Image.newBuilder().setSource(imgSource).build();
  Feature feat = Feature.newBuilder().setType(Type.SAFE_SEARCH_DETECTION).build();
  AnnotateImageRequest request =
      AnnotateImageRequest.newBuilder().addFeatures(feat).setImage(img).build();
  requests.add(request);

  // Initialize client that will be used to send requests. This client only needs to be created
  // once, and can be reused for multiple requests. After completing all of your requests, call
  // the "close" method on the client to safely clean up any remaining background resources.
  try (ImageAnnotatorClient client = ImageAnnotatorClient.create()) {
    BatchAnnotateImagesResponse response = client.batchAnnotateImages(requests);
    List<AnnotateImageResponse> responses = response.getResponsesList();

    for (AnnotateImageResponse res : responses) {
      if (res.hasError()) {
        System.out.format("Error: %s%n", res.getError().getMessage());
        return;
      }

      // For full list of available annotations, see http://g.co/cloud/vision/docs
      SafeSearchAnnotation annotation = res.getSafeSearchAnnotation();
      System.out.format(
          "adult: %s%nmedical: %s%nspoofed: %s%nviolence: %s%nracy: %s%n",
          annotation.getAdult(),
          annotation.getMedical(),
          annotation.getSpoof(),
          annotation.getViolence(),
          annotation.getRacy());
    }
  }
}
 
Example 14
Source Project: java-docs-samples   Source File: ImageMagick.java    License: Apache License 2.0 5 votes vote down vote up
public static void blurOffensiveImages(JsonObject data) {
  String fileName = data.get("name").getAsString();
  String bucketName = data.get("bucket").getAsString();
  BlobInfo blobInfo = BlobInfo.newBuilder(bucketName, fileName).build();
  // Construct URI to GCS bucket and file.
  String gcsPath = String.format("gs://%s/%s", bucketName, fileName);
  System.out.println(String.format("Analyzing %s", fileName));

  // Construct request.
  List<AnnotateImageRequest> requests = new ArrayList<>();
  ImageSource imgSource = ImageSource.newBuilder().setImageUri(gcsPath).build();
  Image img = Image.newBuilder().setSource(imgSource).build();
  Feature feature = Feature.newBuilder().setType(Type.SAFE_SEARCH_DETECTION).build();
  AnnotateImageRequest request =
      AnnotateImageRequest.newBuilder().addFeatures(feature).setImage(img).build();
  requests.add(request);

  // Send request to the Vision API.
  try (ImageAnnotatorClient client = ImageAnnotatorClient.create()) {
    BatchAnnotateImagesResponse response = client.batchAnnotateImages(requests);
    List<AnnotateImageResponse> responses = response.getResponsesList();
    for (AnnotateImageResponse res : responses) {
      if (res.hasError()) {
        System.out.println(String.format("Error: %s\n", res.getError().getMessage()));
        return;
      }
      // Get Safe Search Annotations
      SafeSearchAnnotation annotation = res.getSafeSearchAnnotation();
      if (annotation.getAdultValue() == 5 || annotation.getViolenceValue() == 5) {
        System.out.println(String.format("Detected %s as inappropriate.", fileName));
        blur(blobInfo);
      } else {
        System.out.println(String.format("Detected %s as OK.", fileName));
      }
    }
  } catch (Exception e) {
    System.out.println(String.format("Error with Vision API: %s", e.getMessage()));
  }
}
 
Example 15
Source Project: google-cloud-java   Source File: AnnotateImage.java    License: Apache License 2.0 5 votes vote down vote up
public static void main(String... args) throws Exception {
  // Instantiates a client
  ImageAnnotatorClient vision = ImageAnnotatorClient.create();

  // The path to the image file to annotate
  String fileName = "your/image/path.jpg"; // for example "./resources/wakeupcat.jpg";

  // Reads the image file into memory
  Path path = Paths.get(fileName);
  byte[] data = Files.readAllBytes(path);
  ByteString imgBytes = ByteString.copyFrom(data);

  // Builds the image annotation request
  List<AnnotateImageRequest> requests = new ArrayList<>();
  Image img = Image.newBuilder().setContent(imgBytes).build();
  Feature feat = Feature.newBuilder().setType(Type.LABEL_DETECTION).build();
  AnnotateImageRequest request =
      AnnotateImageRequest.newBuilder().addFeatures(feat).setImage(img).build();
  requests.add(request);

  // Performs label detection on the image file
  BatchAnnotateImagesResponse response = vision.batchAnnotateImages(requests);
  List<AnnotateImageResponse> responses = response.getResponsesList();

  for (AnnotateImageResponse res : responses) {
    if (res.hasError()) {
      System.out.printf("Error: %s\n", res.getError().getMessage());
      return;
    }

    for (EntityAnnotation annotation : res.getLabelAnnotationsList()) {
      for (Map.Entry<FieldDescriptor, Object> entry : annotation.getAllFields().entrySet()) {
        System.out.printf("%s : %s\n", entry.getKey(), entry.getValue());
      }
    }
  }
}
 
Example 16
Source Project: java-docs-samples   Source File: Detect.java    License: Apache License 2.0 4 votes vote down vote up
/**
 * Performs document text detection on a local image file.
 *
 * @param filePath The path to the local file to detect document text on.
 * @throws Exception on errors while closing the client.
 * @throws IOException on Input/Output errors.
 */
// [START vision_fulltext_detection]
public static void detectDocumentText(String filePath) throws IOException {
  List<AnnotateImageRequest> requests = new ArrayList<>();

  ByteString imgBytes = ByteString.readFrom(new FileInputStream(filePath));

  Image img = Image.newBuilder().setContent(imgBytes).build();
  Feature feat = Feature.newBuilder().setType(Type.DOCUMENT_TEXT_DETECTION).build();
  AnnotateImageRequest request =
      AnnotateImageRequest.newBuilder().addFeatures(feat).setImage(img).build();
  requests.add(request);

  // Initialize client that will be used to send requests. This client only needs to be created
  // once, and can be reused for multiple requests. After completing all of your requests, call
  // the "close" method on the client to safely clean up any remaining background resources.
  try (ImageAnnotatorClient client = ImageAnnotatorClient.create()) {
    BatchAnnotateImagesResponse response = client.batchAnnotateImages(requests);
    List<AnnotateImageResponse> responses = response.getResponsesList();
    client.close();

    for (AnnotateImageResponse res : responses) {
      if (res.hasError()) {
        System.out.format("Error: %s%n", res.getError().getMessage());
        return;
      }

      // For full list of available annotations, see http://g.co/cloud/vision/docs
      TextAnnotation annotation = res.getFullTextAnnotation();
      for (Page page : annotation.getPagesList()) {
        String pageText = "";
        for (Block block : page.getBlocksList()) {
          String blockText = "";
          for (Paragraph para : block.getParagraphsList()) {
            String paraText = "";
            for (Word word : para.getWordsList()) {
              String wordText = "";
              for (Symbol symbol : word.getSymbolsList()) {
                wordText = wordText + symbol.getText();
                System.out.format(
                    "Symbol text: %s (confidence: %f)%n",
                    symbol.getText(), symbol.getConfidence());
              }
              System.out.format(
                  "Word text: %s (confidence: %f)%n%n", wordText, word.getConfidence());
              paraText = String.format("%s %s", paraText, wordText);
            }
            // Output Example using Paragraph:
            System.out.println("%nParagraph: %n" + paraText);
            System.out.format("Paragraph Confidence: %f%n", para.getConfidence());
            blockText = blockText + paraText;
          }
          pageText = pageText + blockText;
        }
      }
      System.out.println("%nComplete annotation:");
      System.out.println(annotation.getText());
    }
  }
}
 
Example 17
Source Project: java-docs-samples   Source File: Detect.java    License: Apache License 2.0 4 votes vote down vote up
/**
 * Performs document text detection on a remote image on Google Cloud Storage.
 *
 * @param gcsPath The path to the remote file on Google Cloud Storage to detect document text on.
 * @throws Exception on errors while closing the client.
 * @throws IOException on Input/Output errors.
 */
// [START vision_fulltext_detection_gcs]
public static void detectDocumentTextGcs(String gcsPath) throws IOException {
  List<AnnotateImageRequest> requests = new ArrayList<>();

  ImageSource imgSource = ImageSource.newBuilder().setGcsImageUri(gcsPath).build();
  Image img = Image.newBuilder().setSource(imgSource).build();
  Feature feat = Feature.newBuilder().setType(Type.DOCUMENT_TEXT_DETECTION).build();
  AnnotateImageRequest request =
      AnnotateImageRequest.newBuilder().addFeatures(feat).setImage(img).build();
  requests.add(request);

  // Initialize client that will be used to send requests. This client only needs to be created
  // once, and can be reused for multiple requests. After completing all of your requests, call
  // the "close" method on the client to safely clean up any remaining background resources.
  try (ImageAnnotatorClient client = ImageAnnotatorClient.create()) {
    BatchAnnotateImagesResponse response = client.batchAnnotateImages(requests);
    List<AnnotateImageResponse> responses = response.getResponsesList();
    client.close();

    for (AnnotateImageResponse res : responses) {
      if (res.hasError()) {
        System.out.format("Error: %s%n", res.getError().getMessage());
        return;
      }
      // For full list of available annotations, see http://g.co/cloud/vision/docs
      TextAnnotation annotation = res.getFullTextAnnotation();
      for (Page page : annotation.getPagesList()) {
        String pageText = "";
        for (Block block : page.getBlocksList()) {
          String blockText = "";
          for (Paragraph para : block.getParagraphsList()) {
            String paraText = "";
            for (Word word : para.getWordsList()) {
              String wordText = "";
              for (Symbol symbol : word.getSymbolsList()) {
                wordText = wordText + symbol.getText();
                System.out.format(
                    "Symbol text: %s (confidence: %f)%n",
                    symbol.getText(), symbol.getConfidence());
              }
              System.out.format(
                  "Word text: %s (confidence: %f)%n%n", wordText, word.getConfidence());
              paraText = String.format("%s %s", paraText, wordText);
            }
            // Output Example using Paragraph:
            System.out.println("%nParagraph: %n" + paraText);
            System.out.format("Paragraph Confidence: %f%n", para.getConfidence());
            blockText = blockText + paraText;
          }
          pageText = pageText + blockText;
        }
      }
      System.out.println("%nComplete annotation:");
      System.out.println(annotation.getText());
    }
  }
}
 
Example 18
public static void detectWebEntitiesIncludeGeoResults(String filePath) throws IOException {

    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (ImageAnnotatorClient client = ImageAnnotatorClient.create()) {
      // Read in the local image
      ByteString contents = ByteString.readFrom(new FileInputStream(filePath));

      // Build the image
      Image image = Image.newBuilder().setContent(contents).build();

      // Enable `IncludeGeoResults`
      WebDetectionParams webDetectionParams =
          WebDetectionParams.newBuilder().setIncludeGeoResults(true).build();

      // Set the parameters for the image
      ImageContext imageContext =
          ImageContext.newBuilder().setWebDetectionParams(webDetectionParams).build();

      // Create the request with the image, imageContext, and the specified feature: web detection
      AnnotateImageRequest request =
          AnnotateImageRequest.newBuilder()
              .addFeatures(Feature.newBuilder().setType(Type.WEB_DETECTION))
              .setImage(image)
              .setImageContext(imageContext)
              .build();

      // Perform the request
      BatchAnnotateImagesResponse response = client.batchAnnotateImages(Arrays.asList(request));

      // Display the results
      response.getResponsesList().stream()
          .forEach(
              r ->
                  r.getWebDetection().getWebEntitiesList().stream()
                      .forEach(
                          entity -> {
                            System.out.format("Description: %s%n", entity.getDescription());
                            System.out.format("Score: %f%n", entity.getScore());
                          }));
    }
  }
 
Example 19
Source Project: java-docs-samples   Source File: ProductSearch.java    License: Apache License 2.0 4 votes vote down vote up
/**
 * Search similar products to image in local file.
 *
 * @param projectId - Id of the project.
 * @param computeRegion - Region name.
 * @param productSetId - Id of the product set.
 * @param productCategory - Category of the product.
 * @param filePath - Local file path of the image to be searched
 * @param filter - Condition to be applied on the labels. Example for filter: (color = red OR
 *     color = blue) AND style = kids It will search on all products with the following labels:
 *     color:red AND style:kids color:blue AND style:kids
 * @throws IOException - on I/O errors.
 */
public static void getSimilarProductsFile(
    String projectId,
    String computeRegion,
    String productSetId,
    String productCategory,
    String filePath,
    String filter)
    throws IOException {
  try (ImageAnnotatorClient queryImageClient = ImageAnnotatorClient.create()) {

    // Get the full path of the product set.
    String productSetPath =
        ProductSearchClient.formatProductSetName(projectId, computeRegion, productSetId);

    // Read the image as a stream of bytes.
    File imgPath = new File(filePath);
    byte[] content = Files.readAllBytes(imgPath.toPath());

    // Create annotate image request along with product search feature.
    Feature featuresElement = Feature.newBuilder().setType(Type.PRODUCT_SEARCH).build();
    // The input image can be a HTTPS link or Raw image bytes.
    // Example:
    // To use HTTP link replace with below code
    //  ImageSource source = ImageSource.newBuilder().setImageUri(imageUri).build();
    //  Image image = Image.newBuilder().setSource(source).build();
    Image image = Image.newBuilder().setContent(ByteString.copyFrom(content)).build();
    ImageContext imageContext =
        ImageContext.newBuilder()
            .setProductSearchParams(
                ProductSearchParams.newBuilder()
                    .setProductSet(productSetPath)
                    .addProductCategories(productCategory)
                    .setFilter(filter))
            .build();

    AnnotateImageRequest annotateImageRequest =
        AnnotateImageRequest.newBuilder()
            .addFeatures(featuresElement)
            .setImage(image)
            .setImageContext(imageContext)
            .build();
    List<AnnotateImageRequest> requests = Arrays.asList(annotateImageRequest);

    // Search products similar to the image.
    BatchAnnotateImagesResponse response = queryImageClient.batchAnnotateImages(requests);

    List<Result> similarProducts =
        response.getResponses(0).getProductSearchResults().getResultsList();
    System.out.println("Similar Products: ");
    for (Result product : similarProducts) {
      System.out.println(String.format("\nProduct name: %s", product.getProduct().getName()));
      System.out.println(
          String.format("Product display name: %s", product.getProduct().getDisplayName()));
      System.out.println(
          String.format("Product description: %s", product.getProduct().getDescription()));
      System.out.println(String.format("Score(Confidence): %s", product.getScore()));
      System.out.println(String.format("Image name: %s", product.getImage()));
    }
  }
}
 
Example 20
Source Project: java-docs-samples   Source File: ProductSearch.java    License: Apache License 2.0 4 votes vote down vote up
/**
 * Search similar products to image in Google Cloud Storage.
 *
 * @param projectId - Id of the project.
 * @param computeRegion - Region name.
 * @param productSetId - Id of the product set.
 * @param productCategory - Category of the product.
 * @param gcsUri - GCS file path of the image to be searched
 * @param filter - Condition to be applied on the labels. Example for filter: (color = red OR
 *     color = blue) AND style = kids It will search on all products with the following labels:
 *     color:red AND style:kids color:blue AND style:kids
 * @throws Exception - on errors.
 */
public static void getSimilarProductsGcs(
    String projectId,
    String computeRegion,
    String productSetId,
    String productCategory,
    String gcsUri,
    String filter)
    throws Exception {
  try (ImageAnnotatorClient queryImageClient = ImageAnnotatorClient.create()) {

    // Get the full path of the product set.
    String productSetPath = ProductSetName.of(projectId, computeRegion, productSetId).toString();

    // Get the image from Google Cloud Storage
    ImageSource source = ImageSource.newBuilder().setGcsImageUri(gcsUri).build();

    // Create annotate image request along with product search feature.
    Feature featuresElement = Feature.newBuilder().setType(Type.PRODUCT_SEARCH).build();
    Image image = Image.newBuilder().setSource(source).build();
    ImageContext imageContext =
        ImageContext.newBuilder()
            .setProductSearchParams(
                ProductSearchParams.newBuilder()
                    .setProductSet(productSetPath)
                    .addProductCategories(productCategory)
                    .setFilter(filter))
            .build();

    AnnotateImageRequest annotateImageRequest =
        AnnotateImageRequest.newBuilder()
            .addFeatures(featuresElement)
            .setImage(image)
            .setImageContext(imageContext)
            .build();
    List<AnnotateImageRequest> requests = Arrays.asList(annotateImageRequest);

    // Search products similar to the image.
    BatchAnnotateImagesResponse response = queryImageClient.batchAnnotateImages(requests);

    List<Result> similarProducts =
        response.getResponses(0).getProductSearchResults().getResultsList();
    System.out.println("Similar Products: ");
    for (Result product : similarProducts) {
      System.out.println(String.format("\nProduct name: %s", product.getProduct().getName()));
      System.out.println(
          String.format("Product display name: %s", product.getProduct().getDisplayName()));
      System.out.println(
          String.format("Product description: %s", product.getProduct().getDescription()));
      System.out.println(String.format("Score(Confidence): %s", product.getScore()));
      System.out.println(String.format("Image name: %s", product.getImage()));
    }
  }
}
 
Example 21
Source Project: java-docs-samples   Source File: ImageMagick.java    License: Apache License 2.0 4 votes vote down vote up
@Override
// Blurs uploaded images that are flagged as Adult or Violence.
public void accept(GcsEvent gcsEvent, Context context) {
  // Validate parameters
  if (gcsEvent.getBucket() == null || gcsEvent.getName() == null) {
    logger.severe("Error: Malformed GCS event.");
    return;
  }

  BlobInfo blobInfo = BlobInfo.newBuilder(gcsEvent.getBucket(), gcsEvent.getName()).build();

  // Construct URI to GCS bucket and file.
  String gcsPath = String.format("gs://%s/%s", gcsEvent.getBucket(), gcsEvent.getName());
  logger.info(String.format("Analyzing %s", gcsEvent.getName()));

  // Construct request.
  ImageSource imgSource = ImageSource.newBuilder().setImageUri(gcsPath).build();
  Image img = Image.newBuilder().setSource(imgSource).build();
  Feature feature = Feature.newBuilder().setType(Type.SAFE_SEARCH_DETECTION).build();
  AnnotateImageRequest request =
      AnnotateImageRequest.newBuilder().addFeatures(feature).setImage(img).build();
  List<AnnotateImageRequest> requests = List.of(request);

  // Send request to the Vision API.
  try (ImageAnnotatorClient client = ImageAnnotatorClient.create()) {
    BatchAnnotateImagesResponse response = client.batchAnnotateImages(requests);
    List<AnnotateImageResponse> responses = response.getResponsesList();
    for (AnnotateImageResponse res : responses) {
      if (res.hasError()) {
        logger.info(String.format("Error: %s", res.getError().getMessage()));
        return;
      }
      // Get Safe Search Annotations
      SafeSearchAnnotation annotation = res.getSafeSearchAnnotation();
      if (annotation.getAdultValue() == 5 || annotation.getViolenceValue() == 5) {
        logger.info(String.format("Detected %s as inappropriate.", gcsEvent.getName()));
        blur(blobInfo);
      } else {
        logger.info(String.format("Detected %s as OK.", gcsEvent.getName()));
      }
    }
  } catch (IOException e) {
    logger.log(Level.SEVERE, "Error with Vision API: " + e.getMessage(), e);
  }
}
 
Example 22
Source Project: spring-cloud-gcp   Source File: CloudVisionTemplate.java    License: Apache License 2.0 2 votes vote down vote up
/**
 * Analyze an image and extract the features of the image specified by
 * {@code featureTypes}.
 * <p>A feature describes the kind of Cloud Vision analysis one wishes to perform on an
 * image, such as text detection, image labelling, facial detection, etc. A full list of
 * feature types can be found in {@link Feature.Type}.
 * @param imageResource the image one wishes to analyze. The Cloud Vision APIs support
 *     image formats described here: https://cloud.google.com/vision/docs/supported-files
 * @param featureTypes the types of image analysis to perform on the image
 * @return the results of image analyses
 * @throws CloudVisionException if the image could not be read or if a malformed response
 *     is received from the Cloud Vision APIs
 */
public AnnotateImageResponse analyzeImage(Resource imageResource, Feature.Type... featureTypes) {
	return analyzeImage(imageResource, ImageContext.getDefaultInstance(), featureTypes);
}