Examples with Feature de.micromata.opengis.kml.v_2_2_0.Feature used on opensource projects

Example 6 with Feature

use of de.micromata.opengis.kml.v_2_2_0.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());
            }
        }
    }
}

Example 7 with Feature

use of de.micromata.opengis.kml.v_2_2_0.Feature in project java-docs-samples by GoogleCloudPlatform.

the class Detect method detectDocumentTextGcs.

// [END vision_detect_document]
// [START vision_detect_document_uri]
/**
 * 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.
 * @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 detectDocumentTextGcs(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.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 8 with Feature

use of de.micromata.opengis.kml.v_2_2_0.Feature in project java-docs-samples by GoogleCloudPlatform.

the class Detect method detectFaces.

/**
 * Detects faces in the specified local image.
 *
 * @param filePath The path to the file 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 detectFaces(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.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());
            }
        }
    }
}

Example 9 with Feature

use of de.micromata.opengis.kml.v_2_2_0.Feature in project java-docs-samples by GoogleCloudPlatform.

the class Detect method detectWebDetections.

// [END vision_detect_safe_search_uri]
// [START vision_detect_web]
/**
 * Finds references to the specified image on the web.
 *
 * @param filePath The path to the local file used for web annotation detection.
 * @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 detectWebDetections(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.WEB_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;
            }
            // Search the web for usages of the image. You could use these signals later
            // for user input moderation or linking external references.
            // For a full list of available annotations, see http://g.co/cloud/vision/docs
            WebDetection annotation = res.getWebDetection();
            out.println("Entity:Id:Score");
            out.println("===============");
            for (WebEntity entity : annotation.getWebEntitiesList()) {
                out.println(entity.getDescription() + " : " + entity.getEntityId() + " : " + entity.getScore());
            }
            for (WebLabel label : annotation.getBestGuessLabelsList()) {
                out.format("\nBest guess label: %s", label.getLabel());
            }
            out.println("\nPages with matching images: Score\n==");
            for (WebPage page : annotation.getPagesWithMatchingImagesList()) {
                out.println(page.getUrl() + " : " + page.getScore());
            }
            out.println("\nPages with partially matching images: Score\n==");
            for (WebImage image : annotation.getPartialMatchingImagesList()) {
                out.println(image.getUrl() + " : " + image.getScore());
            }
            out.println("\nPages with fully matching images: Score\n==");
            for (WebImage image : annotation.getFullMatchingImagesList()) {
                out.println(image.getUrl() + " : " + image.getScore());
            }
            out.println("\nPages with visually similar images: Score\n==");
            for (WebImage image : annotation.getVisuallySimilarImagesList()) {
                out.println(image.getUrl() + " : " + image.getScore());
            }
        }
    }
}

Example 10 with Feature

use of de.micromata.opengis.kml.v_2_2_0.Feature in project java-docs-samples by GoogleCloudPlatform.

the class Detect method detectLabels.

/**
 * Detects labels in the specified local image.
 *
 * @param filePath The path to the file to perform label detection on.
 * @param out A {@link PrintStream} to write detected labels to.
 * @throws Exception on errors while closing the client.
 * @throws IOException on Input/Output errors.
 */
public static void detectLabels(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.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()));
            }
        }
    }
}