use of com.google.cloud.videointelligence.v1p2beta1.VideoSegment in project java-video-intelligence by googleapis.
the class TrackObjects method trackObjects.
// [START video_object_tracking]
/**
* Track objects in a video.
*
* @param filePath the path to the video file to analyze.
*/
public static VideoAnnotationResults trackObjects(String filePath) throws Exception {
try (VideoIntelligenceServiceClient client = VideoIntelligenceServiceClient.create()) {
// Read file
Path path = Paths.get(filePath);
byte[] data = Files.readAllBytes(path);
// Create the request
AnnotateVideoRequest request = AnnotateVideoRequest.newBuilder().setInputContent(ByteString.copyFrom(data)).addFeatures(Feature.OBJECT_TRACKING).setLocationId("us-east1").build();
// asynchronously perform object tracking on videos
OperationFuture<AnnotateVideoResponse, AnnotateVideoProgress> future = client.annotateVideoAsync(request);
System.out.println("Waiting for operation to complete...");
// The first result is retrieved because a single video was processed.
AnnotateVideoResponse response = future.get(450, TimeUnit.SECONDS);
VideoAnnotationResults results = response.getAnnotationResults(0);
// Get only the first annotation for demo purposes.
ObjectTrackingAnnotation annotation = results.getObjectAnnotations(0);
System.out.println("Confidence: " + annotation.getConfidence());
if (annotation.hasEntity()) {
Entity entity = annotation.getEntity();
System.out.println("Entity description: " + entity.getDescription());
System.out.println("Entity id:: " + entity.getEntityId());
}
if (annotation.hasSegment()) {
VideoSegment videoSegment = annotation.getSegment();
Duration startTimeOffset = videoSegment.getStartTimeOffset();
Duration endTimeOffset = videoSegment.getEndTimeOffset();
// Display the segment time in seconds, 1e9 converts nanos to seconds
System.out.println(String.format("Segment: %.2fs to %.2fs", startTimeOffset.getSeconds() + startTimeOffset.getNanos() / 1e9, endTimeOffset.getSeconds() + endTimeOffset.getNanos() / 1e9));
}
// Here we print only the bounding box of the first frame in this segment.
ObjectTrackingFrame frame = annotation.getFrames(0);
// Display the offset time in seconds, 1e9 converts nanos to seconds
Duration timeOffset = frame.getTimeOffset();
System.out.println(String.format("Time offset of the first frame: %.2fs", timeOffset.getSeconds() + timeOffset.getNanos() / 1e9));
// Display the bounding box of the detected object
NormalizedBoundingBox normalizedBoundingBox = frame.getNormalizedBoundingBox();
System.out.println("Bounding box position:");
System.out.println("\tleft: " + normalizedBoundingBox.getLeft());
System.out.println("\ttop: " + normalizedBoundingBox.getTop());
System.out.println("\tright: " + normalizedBoundingBox.getRight());
System.out.println("\tbottom: " + normalizedBoundingBox.getBottom());
return results;
}
}
use of com.google.cloud.videointelligence.v1p2beta1.VideoSegment in project java-video-intelligence by googleapis.
the class Detect method analyzeShots.
/**
* Performs shot analysis on the video at the provided Cloud Storage path.
*
* @param gcsUri the path to the video file to analyze.
*/
public static void analyzeShots(String gcsUri) throws Exception {
// Instantiate a com.google.cloud.videointelligence.v1.VideoIntelligenceServiceClient
try (VideoIntelligenceServiceClient client = VideoIntelligenceServiceClient.create()) {
// Provide path to file hosted on GCS as "gs://bucket-name/..."
AnnotateVideoRequest request = AnnotateVideoRequest.newBuilder().setInputUri(gcsUri).addFeatures(Feature.SHOT_CHANGE_DETECTION).build();
// Create an operation that will contain the response when the operation completes.
OperationFuture<AnnotateVideoResponse, AnnotateVideoProgress> response = client.annotateVideoAsync(request);
System.out.println("Waiting for operation to complete...");
// Print detected shot changes and their location ranges in the analyzed video.
for (VideoAnnotationResults result : response.get().getAnnotationResultsList()) {
if (result.getShotAnnotationsCount() > 0) {
System.out.println("Shots: ");
for (VideoSegment segment : result.getShotAnnotationsList()) {
double startTime = segment.getStartTimeOffset().getSeconds() + segment.getStartTimeOffset().getNanos() / 1e9;
double endTime = segment.getEndTimeOffset().getSeconds() + segment.getEndTimeOffset().getNanos() / 1e9;
System.out.printf("Location: %.3f:%.3f\n", startTime, endTime);
}
} else {
System.out.println("No shot changes detected in " + gcsUri);
}
}
}
// [END video_analyze_shots]
}
use of com.google.cloud.videointelligence.v1p2beta1.VideoSegment 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());
}
}
}
}
}
use of com.google.cloud.videointelligence.v1p2beta1.VideoSegment 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());
}
}
}
}
}
use of com.google.cloud.videointelligence.v1p2beta1.VideoSegment in project java-video-intelligence by googleapis.
the class TextDetection method detectTextGcs.
// [END video_detect_text_beta]
// [START video_detect_text_gcs_beta]
/**
* Detect Text in a video.
*
* @param gcsUri the path to the video file to analyze.
*/
public static VideoAnnotationResults detectTextGcs(String gcsUri) throws Exception {
try (VideoIntelligenceServiceClient client = VideoIntelligenceServiceClient.create()) {
// Create the request
AnnotateVideoRequest request = AnnotateVideoRequest.newBuilder().setInputUri(gcsUri).addFeatures(Feature.TEXT_DETECTION).build();
// asynchronously perform object tracking on videos
OperationFuture<AnnotateVideoResponse, AnnotateVideoProgress> future = client.annotateVideoAsync(request);
System.out.println("Waiting for operation to complete...");
// The first result is retrieved because a single video was processed.
AnnotateVideoResponse response = future.get(600, TimeUnit.SECONDS);
VideoAnnotationResults results = response.getAnnotationResults(0);
// Get only the first annotation for demo purposes.
TextAnnotation annotation = results.getTextAnnotations(0);
System.out.println("Text: " + annotation.getText());
// Get the first text segment.
TextSegment textSegment = annotation.getSegments(0);
System.out.println("Confidence: " + textSegment.getConfidence());
// For the text segment display it's time offset
VideoSegment videoSegment = textSegment.getSegment();
Duration startTimeOffset = videoSegment.getStartTimeOffset();
Duration endTimeOffset = videoSegment.getEndTimeOffset();
// Display the offset times in seconds, 1e9 is part of the formula to convert nanos to seconds
System.out.println(String.format("Start time: %.2f", startTimeOffset.getSeconds() + startTimeOffset.getNanos() / 1e9));
System.out.println(String.format("End time: %.2f", endTimeOffset.getSeconds() + endTimeOffset.getNanos() / 1e9));
// Show the first result for the first frame in the segment.
TextFrame textFrame = textSegment.getFrames(0);
Duration timeOffset = textFrame.getTimeOffset();
System.out.println(String.format("Time offset for the first frame: %.2f", timeOffset.getSeconds() + timeOffset.getNanos() / 1e9));
// Display the rotated bounding box for where the text is on the frame.
System.out.println("Rotated Bounding Box Vertices:");
List<NormalizedVertex> vertices = textFrame.getRotatedBoundingBox().getVerticesList();
for (NormalizedVertex normalizedVertex : vertices) {
System.out.println(String.format("\tVertex.x: %.2f, Vertex.y: %.2f", normalizedVertex.getX(), normalizedVertex.getY()));
}
return results;
}
}
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