Examples with FaceDetectionAnnotation com.google.cloud.videointelligence.v1.FaceDetectionAnnotation used on opensource projects

Example 1 with FaceDetectionAnnotation

use of com.google.cloud.videointelligence.v1.FaceDetectionAnnotation in project java-docs-samples by GoogleCloudPlatform.

the class Detect method analyzeFacesBoundingBoxes.

// [START video_face_bounding_boxes]
/**
 * Detects faces' bounding boxes on the video at the provided Cloud Storage path.
 *
 * @param gcsUri the path to the video file to analyze.
 */
public static void analyzeFacesBoundingBoxes(String gcsUri) throws Exception {
    // Instantiate a com.google.cloud.videointelligence.v1p1beta1.VideoIntelligenceServiceClient
    try (VideoIntelligenceServiceClient client = VideoIntelligenceServiceClient.create()) {
        // Set the configuration to include bounding boxes
        FaceConfig config = FaceConfig.newBuilder().setIncludeBoundingBoxes(true).build();
        // Set the video context with the above configuration
        VideoContext context = VideoContext.newBuilder().setFaceDetectionConfig(config).build();
        // Create the request
        AnnotateVideoRequest request = AnnotateVideoRequest.newBuilder().setInputUri(gcsUri).addFeatures(Feature.FACE_DETECTION).setVideoContext(context).build();
        // asynchronously perform facial analysis on videos
        OperationFuture<AnnotateVideoResponse, AnnotateVideoProgress> response = client.annotateVideoAsync(request);
        System.out.println("Waiting for operation to complete...");
        boolean faceFound = false;
        // Display the results
        for (VideoAnnotationResults results : response.get(900, TimeUnit.SECONDS).getAnnotationResultsList()) {
            int faceCount = 0;
            // Display the results for each face
            for (FaceDetectionAnnotation faceAnnotation : results.getFaceDetectionAnnotationsList()) {
                faceFound = true;
                System.out.println("\nFace: " + ++faceCount);
                // Each FaceDetectionAnnotation has only one segment.
                for (FaceSegment segment : faceAnnotation.getSegmentsList()) {
                    double startTime = segment.getSegment().getStartTimeOffset().getSeconds() + segment.getSegment().getStartTimeOffset().getNanos() / 1e9;
                    double endTime = segment.getSegment().getEndTimeOffset().getSeconds() + segment.getSegment().getEndTimeOffset().getNanos() / 1e9;
                    System.out.printf("Segment location: %.3fs to %.3f\n", startTime, endTime);
                }
                // There are typically many frames for each face,
                try {
                    // Here we process only the first frame.
                    if (faceAnnotation.getFramesCount() > 0) {
                        // get the first frame
                        FaceDetectionFrame frame = faceAnnotation.getFrames(0);
                        double timeOffset = frame.getTimeOffset().getSeconds() + frame.getTimeOffset().getNanos() / 1e9;
                        System.out.printf("First frame time offset: %.3fs\n", timeOffset);
                        // print info on the first normalized bounding box
                        NormalizedBoundingBox box = frame.getAttributes(0).getNormalizedBoundingBox();
                        System.out.printf("\tLeft: %.3f\n", box.getLeft());
                        System.out.printf("\tTop: %.3f\n", box.getTop());
                        System.out.printf("\tBottom: %.3f\n", box.getBottom());
                        System.out.printf("\tRight: %.3f\n", box.getRight());
                    } else {
                        System.out.println("No frames found in annotation");
                    }
                } catch (IndexOutOfBoundsException ioe) {
                    System.out.println("Could not retrieve frame: " + ioe.getMessage());
                }
            }
        }
        if (!faceFound) {
            System.out.println("No faces detected in " + gcsUri);
        }
    }
}

Example 2 with FaceDetectionAnnotation

use of com.google.cloud.videointelligence.v1.FaceDetectionAnnotation in project java-docs-samples by GoogleCloudPlatform.

the class Detect method analyzeFaceEmotions.

// [END video_face_bounding_boxes]
// [START video_face_emotions]
/**
 * Analyze faces' emotions over frames on the video at the provided Cloud Storage path.
 *
 * @param gcsUri the path to the video file to analyze.
 */
public static void analyzeFaceEmotions(String gcsUri) throws Exception {
    // Instantiate a com.google.cloud.videointelligence.v1p1beta1.VideoIntelligenceServiceClient
    try (VideoIntelligenceServiceClient client = VideoIntelligenceServiceClient.create()) {
        // Set the configuration to include bounding boxes
        FaceConfig config = FaceConfig.newBuilder().setIncludeEmotions(true).build();
        // Set the video context with the above configuration
        VideoContext context = VideoContext.newBuilder().setFaceDetectionConfig(config).build();
        // Create the request
        AnnotateVideoRequest request = AnnotateVideoRequest.newBuilder().setInputUri(gcsUri).addFeatures(Feature.FACE_DETECTION).setVideoContext(context).build();
        // asynchronously perform facial analysis on videos
        OperationFuture<AnnotateVideoResponse, AnnotateVideoProgress> response = client.annotateVideoAsync(request);
        System.out.println("Waiting for operation to complete...");
        boolean faceFound = false;
        // Display the results
        for (VideoAnnotationResults results : response.get(600, TimeUnit.SECONDS).getAnnotationResultsList()) {
            int faceCount = 0;
            // Display the results for each face
            for (FaceDetectionAnnotation faceAnnotation : results.getFaceDetectionAnnotationsList()) {
                faceFound = true;
                System.out.println("\nFace: " + ++faceCount);
                // Each FaceDetectionAnnotation has only one segment.
                for (FaceSegment segment : faceAnnotation.getSegmentsList()) {
                    double startTime = segment.getSegment().getStartTimeOffset().getSeconds() + segment.getSegment().getStartTimeOffset().getNanos() / 1e9;
                    double endTime = segment.getSegment().getEndTimeOffset().getSeconds() + segment.getSegment().getEndTimeOffset().getNanos() / 1e9;
                    System.out.printf("Segment location: %.3fs to %.3f\n", startTime, endTime);
                }
                try {
                    // Print each frame's highest emotion
                    for (FaceDetectionFrame frame : faceAnnotation.getFramesList()) {
                        double timeOffset = frame.getTimeOffset().getSeconds() + frame.getTimeOffset().getNanos() / 1e9;
                        float highestScore = 0.0f;
                        String emotion = "";
                        // Get the highest scoring emotion for the current frame
                        for (EmotionAttribute emotionAttribute : frame.getAttributes(0).getEmotionsList()) {
                            if (emotionAttribute.getScore() > highestScore) {
                                highestScore = emotionAttribute.getScore();
                                emotion = emotionAttribute.getEmotion().name();
                            }
                        }
                        System.out.printf("\t%4.2fs: %14s %4.3f\n", timeOffset, emotion, highestScore);
                    }
                } catch (IndexOutOfBoundsException ioe) {
                    System.out.println("Could not retrieve frame: " + ioe.getMessage());
                }
            }
        }
        if (!faceFound) {
            System.out.println("No faces detected in " + gcsUri);
        }
    }
}

Example 3 with FaceDetectionAnnotation

use of com.google.cloud.videointelligence.v1.FaceDetectionAnnotation in project java-video-intelligence by googleapis.

the class DetectFaces method detectFaces.

// Detects faces in a video stored in a local file using the Cloud Video Intelligence API.
public static void detectFaces(String localFilePath) throws Exception {
    try (VideoIntelligenceServiceClient videoIntelligenceServiceClient = VideoIntelligenceServiceClient.create()) {
        // Reads a local video file and converts it to base64.
        Path path = Paths.get(localFilePath);
        byte[] data = Files.readAllBytes(path);
        ByteString inputContent = ByteString.copyFrom(data);
        FaceDetectionConfig faceDetectionConfig = FaceDetectionConfig.newBuilder().setIncludeBoundingBoxes(true).setIncludeAttributes(true).build();
        VideoContext videoContext = VideoContext.newBuilder().setFaceDetectionConfig(faceDetectionConfig).build();
        AnnotateVideoRequest request = AnnotateVideoRequest.newBuilder().setInputContent(inputContent).addFeatures(Feature.FACE_DETECTION).setVideoContext(videoContext).build();
        // Detects faces in a video
        OperationFuture<AnnotateVideoResponse, AnnotateVideoProgress> future = videoIntelligenceServiceClient.annotateVideoAsync(request);
        System.out.println("Waiting for operation to complete...");
        AnnotateVideoResponse response = future.get();
        // Gets annotations for video
        VideoAnnotationResults annotationResult = response.getAnnotationResultsList().get(0);
        // Annotations for list of faces detected, tracked and recognized in video.
        for (FaceDetectionAnnotation faceDetectionAnnotation : annotationResult.getFaceDetectionAnnotationsList()) {
            System.out.print("Face detected:\n");
            for (Track track : faceDetectionAnnotation.getTracksList()) {
                VideoSegment segment = track.getSegment();
                System.out.printf("\tStart: %d.%.0fs\n", segment.getStartTimeOffset().getSeconds(), segment.getStartTimeOffset().getNanos() / 1e6);
                System.out.printf("\tEnd: %d.%.0fs\n", segment.getEndTimeOffset().getSeconds(), segment.getEndTimeOffset().getNanos() / 1e6);
                // Each segment includes timestamped objects that
                // include characteristics of the face detected.
                TimestampedObject firstTimestampedObject = track.getTimestampedObjects(0);
                for (DetectedAttribute attribute : firstTimestampedObject.getAttributesList()) {
                    // Attributes include glasses, headwear, smiling, direction of gaze
                    System.out.printf("\tAttribute %s: %s %s\n", attribute.getName(), attribute.getValue(), attribute.getConfidence());
                }
            }
        }
    }
}

Example 4 with FaceDetectionAnnotation

use of com.google.cloud.videointelligence.v1.FaceDetectionAnnotation in project java-video-intelligence by googleapis.

the class DetectFacesGcs method detectFacesGcs.

// Detects faces in a video stored in Google Cloud Storage using the Cloud Video Intelligence API.
public static void detectFacesGcs(String gcsUri) throws Exception {
    try (VideoIntelligenceServiceClient videoIntelligenceServiceClient = VideoIntelligenceServiceClient.create()) {
        FaceDetectionConfig faceDetectionConfig = FaceDetectionConfig.newBuilder().setIncludeBoundingBoxes(true).setIncludeAttributes(true).build();
        VideoContext videoContext = VideoContext.newBuilder().setFaceDetectionConfig(faceDetectionConfig).build();
        AnnotateVideoRequest request = AnnotateVideoRequest.newBuilder().setInputUri(gcsUri).addFeatures(Feature.FACE_DETECTION).setVideoContext(videoContext).build();
        // Detects faces in a video
        OperationFuture<AnnotateVideoResponse, AnnotateVideoProgress> future = videoIntelligenceServiceClient.annotateVideoAsync(request);
        System.out.println("Waiting for operation to complete...");
        AnnotateVideoResponse response = future.get();
        // Gets annotations for video
        VideoAnnotationResults annotationResult = response.getAnnotationResultsList().get(0);
        // Annotations for list of people detected, tracked and recognized in video.
        for (FaceDetectionAnnotation faceDetectionAnnotation : annotationResult.getFaceDetectionAnnotationsList()) {
            System.out.print("Face detected:\n");
            for (Track track : faceDetectionAnnotation.getTracksList()) {
                VideoSegment segment = track.getSegment();
                System.out.printf("\tStart: %d.%.0fs\n", segment.getStartTimeOffset().getSeconds(), segment.getStartTimeOffset().getNanos() / 1e6);
                System.out.printf("\tEnd: %d.%.0fs\n", segment.getEndTimeOffset().getSeconds(), segment.getEndTimeOffset().getNanos() / 1e6);
                // Each segment includes timestamped objects that
                // include characteristics of the face detected.
                TimestampedObject firstTimestampedObject = track.getTimestampedObjects(0);
                for (DetectedAttribute attribute : firstTimestampedObject.getAttributesList()) {
                    // Attributes include glasses, headwear, smiling, direction of gaze
                    System.out.printf("\tAttribute %s: %s %s\n", attribute.getName(), attribute.getValue(), attribute.getConfidence());
                }
            }
        }
    }
}