Examples with VideoContext com.google.cloud.videointelligence.v1p1beta1.VideoContext used on opensource projects

Example 1 with VideoContext

use of com.google.cloud.videointelligence.v1p1beta1.VideoContext 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 VideoContext

use of com.google.cloud.videointelligence.v1p1beta1.VideoContext 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 3 with VideoContext

use of com.google.cloud.videointelligence.v1p1beta1.VideoContext in project google-cloud-java by GoogleCloudPlatform.

the class VideoIntelligenceServiceClientTest method annotateVideoTest.

@Test
@SuppressWarnings("all")
public void annotateVideoTest() throws Exception {
    AnnotateVideoResponse expectedResponse = AnnotateVideoResponse.newBuilder().build();
    Operation resultOperation = Operation.newBuilder().setName("annotateVideoTest").setDone(true).setResponse(Any.pack(expectedResponse)).build();
    mockVideoIntelligenceService.addResponse(resultOperation);
    String inputUri = "inputUri1707300727";
    List<Feature> features = new ArrayList<>();
    VideoContext videoContext = VideoContext.newBuilder().build();
    String outputUri = "outputUri-1273518802";
    String locationId = "locationId552319461";
    AnnotateVideoResponse actualResponse = client.annotateVideoAsync(inputUri, features, videoContext, outputUri, locationId).get();
    Assert.assertEquals(expectedResponse, actualResponse);
    List<GeneratedMessageV3> actualRequests = mockVideoIntelligenceService.getRequests();
    Assert.assertEquals(1, actualRequests.size());
    AnnotateVideoRequest actualRequest = (AnnotateVideoRequest) actualRequests.get(0);
    Assert.assertEquals(inputUri, actualRequest.getInputUri());
    Assert.assertEquals(features, actualRequest.getFeaturesList());
    Assert.assertEquals(videoContext, actualRequest.getVideoContext());
    Assert.assertEquals(outputUri, actualRequest.getOutputUri());
    Assert.assertEquals(locationId, actualRequest.getLocationId());
}

Example 4 with VideoContext

use of com.google.cloud.videointelligence.v1p1beta1.VideoContext 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 5 with VideoContext

use of com.google.cloud.videointelligence.v1p1beta1.VideoContext in project java-docs-samples by GoogleCloudPlatform.

the class Detect method speechTranscription.

// [END video_face_emotions]
// [START video_speech_transcription]
/**
 * Transcribe speech from a video stored on GCS.
 *
 * @param gcsUri the path to the video file to analyze.
 */
public static void speechTranscription(String gcsUri) throws Exception {
    // Instantiate a com.google.cloud.videointelligence.v1p1beta1.VideoIntelligenceServiceClient
    try (VideoIntelligenceServiceClient client = VideoIntelligenceServiceClient.create()) {
        // Set the language code
        SpeechTranscriptionConfig config = SpeechTranscriptionConfig.newBuilder().setLanguageCode("en-US").build();
        // Set the video context with the above configuration
        VideoContext context = VideoContext.newBuilder().setSpeechTranscriptionConfig(config).build();
        // Create the request
        AnnotateVideoRequest request = AnnotateVideoRequest.newBuilder().setInputUri(gcsUri).addFeatures(Feature.SPEECH_TRANSCRIPTION).setVideoContext(context).build();
        // asynchronously perform facial analysis on videos
        OperationFuture<AnnotateVideoResponse, AnnotateVideoProgress> response = client.annotateVideoAsync(request);
        System.out.println("Waiting for operation to complete...");
        // Display the results
        for (VideoAnnotationResults results : response.get(180, TimeUnit.SECONDS).getAnnotationResultsList()) {
            for (SpeechTranscription speechTranscription : results.getSpeechTranscriptionsList()) {
                try {
                    // Print the transcription
                    if (speechTranscription.getAlternativesCount() > 0) {
                        SpeechRecognitionAlternative alternative = speechTranscription.getAlternatives(0);
                        System.out.printf("Transcript: %s\n", alternative.getTranscript());
                        System.out.printf("Confidence: %.2f\n", alternative.getConfidence());
                        System.out.println("Word level information:");
                        for (WordInfo wordInfo : alternative.getWordsList()) {
                            double startTime = wordInfo.getStartTime().getSeconds() + wordInfo.getStartTime().getNanos() / 1e9;
                            double endTime = wordInfo.getEndTime().getSeconds() + wordInfo.getEndTime().getNanos() / 1e9;
                            System.out.printf("\t%4.2fs - %4.2fs: %s\n", startTime, endTime, wordInfo.getWord());
                        }
                    } else {
                        System.out.println("No transcription found");
                    }
                } catch (IndexOutOfBoundsException ioe) {
                    System.out.println("Could not retrieve frame: " + ioe.getMessage());
                }
            }
        }
    }
}