Examples with Feature com.google.cloud.vision.v1.Feature used on opensource projects

Example 1 with Feature

use of com.google.cloud.vision.v1.Feature in project google-cloud-java by GoogleCloudPlatform.

the class VideoIntelligenceServiceClientTest method annotateVideoExceptionTest.

@Test
@SuppressWarnings("all")
public void annotateVideoExceptionTest() throws Exception {
    StatusRuntimeException exception = new StatusRuntimeException(Status.INVALID_ARGUMENT);
    mockVideoIntelligenceService.addException(exception);
    try {
        String inputUri = "inputUri1707300727";
        List<Feature> features = new ArrayList<>();
        VideoContext videoContext = VideoContext.newBuilder().build();
        String outputUri = "outputUri-1273518802";
        String locationId = "locationId552319461";
        client.annotateVideoAsync(inputUri, features, videoContext, outputUri, locationId).get();
        Assert.fail("No exception raised");
    } catch (ExecutionException e) {
        Assert.assertEquals(ApiException.class, e.getCause().getClass());
        ApiException apiException = (ApiException) e.getCause();
        Assert.assertEquals(Status.INVALID_ARGUMENT.getCode(), apiException.getStatusCode());
    }
}

Example 2 with Feature

use of com.google.cloud.vision.v1.Feature in project spring-cloud-gcp by spring-cloud.

the class VisionController method uploadImage.

/**
 * 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
 * @return a string with the list of labels and percentage of certainty
 * @throws Exception if the Vision API call produces an error
 */
@GetMapping("/vision")
public String uploadImage(String imageUrl) throws Exception {
    // Copies the content of the image to memory.
    byte[] imageBytes = StreamUtils.copyToByteArray(this.resourceLoader.getResource(imageUrl).getInputStream());
    BatchAnnotateImagesResponse responses;
    Image image = Image.newBuilder().setContent(ByteString.copyFrom(imageBytes)).build();
    // Sets the type of request to label detection, to detect broad sets of categories in an image.
    Feature feature = Feature.newBuilder().setType(Feature.Type.LABEL_DETECTION).build();
    AnnotateImageRequest request = AnnotateImageRequest.newBuilder().setImage(image).addFeatures(feature).build();
    responses = this.imageAnnotatorClient.batchAnnotateImages(Collections.singletonList(request));
    StringBuilder responseBuilder = new StringBuilder("<table border=\"1\">");
    responseBuilder.append("<tr><th>description</th><th>score</th></tr>");
    // We're only expecting one response.
    if (responses.getResponsesCount() == 1) {
        AnnotateImageResponse response = responses.getResponses(0);
        if (response.hasError()) {
            throw new Exception(response.getError().getMessage());
        }
        for (EntityAnnotation annotation : response.getLabelAnnotationsList()) {
            responseBuilder.append("<tr><td>").append(annotation.getDescription()).append("</td><td>").append(annotation.getScore()).append("</td></tr>");
        }
    }
    responseBuilder.append("</table>");
    responseBuilder.append("<p><img src='" + imageUrl + "'/></p>");
    return responseBuilder.toString();
}

Example 3 with Feature

use of com.google.cloud.vision.v1.Feature in project java-docs-samples by GoogleCloudPlatform.

the class Detect method detectDocumentText.

// [START vision_detect_document]
/**
 * Performs document text detection on a local image file.
 *
 * @param filePath The path to the local file to detect document text on.
 * @param out A {@link PrintStream} to write the results to.
 * @throws Exception on errors while closing the client.
 * @throws IOException on Input/Output errors.
 */
public static void detectDocumentText(String filePath, PrintStream out) throws Exception, 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);
    try (ImageAnnotatorClient client = ImageAnnotatorClient.create()) {
        BatchAnnotateImagesResponse response = client.batchAnnotateImages(requests);
        List<AnnotateImageResponse> responses = response.getResponsesList();
        client.close();
        for (AnnotateImageResponse res : responses) {
            if (res.hasError()) {
                out.printf("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();
                                out.format("Symbol text: %s (confidence: %f)\n", symbol.getText(), symbol.getConfidence());
                            }
                            out.format("Word text: %s (confidence: %f)\n\n", wordText, word.getConfidence());
                            paraText = String.format("%s %s", paraText, wordText);
                        }
                        // Output Example using Paragraph:
                        out.println("\nParagraph: \n" + paraText);
                        out.format("Paragraph Confidence: %f\n", para.getConfidence());
                        blockText = blockText + paraText;
                    }
                    pageText = pageText + blockText;
                }
            }
            out.println("\nComplete annotation:");
            out.println(annotation.getText());
        }
    }
}

Example 4 with Feature

use of com.google.cloud.vision.v1.Feature in project java-docs-samples by GoogleCloudPlatform.

the class Detect method detectLabelsGcs.

/**
 * Detects labels in the specified remote image on Google Cloud Storage.
 *
 * @param gcsPath The path to the remote file on Google Cloud Storage to perform label detection
 *                on.
 * @param out A {@link PrintStream} to write detected features to.
 * @throws Exception on errors while closing the client.
 * @throws IOException on Input/Output errors.
 */
public static void detectLabelsGcs(String gcsPath, PrintStream out) throws Exception, 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.LABEL_DETECTION).build();
    AnnotateImageRequest request = AnnotateImageRequest.newBuilder().addFeatures(feat).setImage(img).build();
    requests.add(request);
    try (ImageAnnotatorClient client = ImageAnnotatorClient.create()) {
        BatchAnnotateImagesResponse response = client.batchAnnotateImages(requests);
        List<AnnotateImageResponse> responses = response.getResponsesList();
        for (AnnotateImageResponse res : responses) {
            if (res.hasError()) {
                out.printf("Error: %s\n", res.getError().getMessage());
                return;
            }
            // For full list of available annotations, see http://g.co/cloud/vision/docs
            for (EntityAnnotation annotation : res.getLabelAnnotationsList()) {
                annotation.getAllFields().forEach((k, v) -> out.printf("%s : %s\n", k, v.toString()));
            }
        }
    }
}

Example 5 with Feature

use of com.google.cloud.vision.v1.Feature in project java-docs-samples by GoogleCloudPlatform.

the class Detect method detectFacesGcs.

/**
 * Detects faces in the specified remote image on Google Cloud Storage.
 *
 * @param gcsPath The path to the remote file on Google Cloud Storage to perform face detection
 *                on.
 * @param out A {@link PrintStream} to write detected features to.
 * @throws Exception on errors while closing the client.
 * @throws IOException on Input/Output errors.
 */
public static void detectFacesGcs(String gcsPath, PrintStream out) throws Exception, 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.FACE_DETECTION).build();
    AnnotateImageRequest request = AnnotateImageRequest.newBuilder().addFeatures(feat).setImage(img).build();
    requests.add(request);
    try (ImageAnnotatorClient client = ImageAnnotatorClient.create()) {
        BatchAnnotateImagesResponse response = client.batchAnnotateImages(requests);
        List<AnnotateImageResponse> responses = response.getResponsesList();
        for (AnnotateImageResponse res : responses) {
            if (res.hasError()) {
                out.printf("Error: %s\n", res.getError().getMessage());
                return;
            }
            // For full list of available annotations, see http://g.co/cloud/vision/docs
            for (FaceAnnotation annotation : res.getFaceAnnotationsList()) {
                out.printf("anger: %s\njoy: %s\nsurprise: %s\nposition: %s", annotation.getAngerLikelihood(), annotation.getJoyLikelihood(), annotation.getSurpriseLikelihood(), annotation.getBoundingPoly());
            }
        }
    }
}