use of com.google.cloud.videointelligence.v1p2beta1.NormalizedVertex in project java-video-intelligence by googleapis.
the class TextDetection method detectText.
// [START video_detect_text_beta]
/**
* Detect text in a video.
*
* @param filePath the path to the video file to analyze.
*/
public static VideoAnnotationResults detectText(String filePath) throws IOException, StatusRuntimeException, TimeoutException, ExecutionException, InterruptedException {
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.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;
}
}
use of com.google.cloud.videointelligence.v1p2beta1.NormalizedVertex in project java-video-intelligence by googleapis.
the class TextDetection method detectTextGcs.
// [END video_detect_text]
// [START video_detect_text_gcs]
/**
* 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(300, 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;
}
}
use of com.google.cloud.videointelligence.v1p2beta1.NormalizedVertex in project java-video-intelligence by googleapis.
the class TextDetection method detectText.
// [START video_detect_text]
/**
* Detect text in a video.
*
* @param filePath the path to the video file to analyze.
*/
public static VideoAnnotationResults detectText(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.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(300, 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;
}
}
use of com.google.cloud.videointelligence.v1p2beta1.NormalizedVertex in project java-automl by googleapis.
the class VisionObjectDetectionPredict method predict.
static void predict(String projectId, String modelId, String filePath) throws IOException {
// the "close" method on the client to safely clean up any remaining background resources.
try (PredictionServiceClient client = PredictionServiceClient.create()) {
// Get the full path of the model.
ModelName name = ModelName.of(projectId, "us-central1", modelId);
ByteString content = ByteString.copyFrom(Files.readAllBytes(Paths.get(filePath)));
Image image = Image.newBuilder().setImageBytes(content).build();
ExamplePayload payload = ExamplePayload.newBuilder().setImage(image).build();
PredictRequest predictRequest = PredictRequest.newBuilder().setName(name.toString()).setPayload(payload).putParams("score_threshold", // [0.0-1.0] Only produce results higher than this value
"0.5").build();
PredictResponse response = client.predict(predictRequest);
for (AnnotationPayload annotationPayload : response.getPayloadList()) {
System.out.format("Predicted class name: %s\n", annotationPayload.getDisplayName());
System.out.format("Predicted class score: %.2f\n", annotationPayload.getImageObjectDetection().getScore());
BoundingPoly boundingPoly = annotationPayload.getImageObjectDetection().getBoundingBox();
System.out.println("Normalized Vertices:");
for (NormalizedVertex vertex : boundingPoly.getNormalizedVerticesList()) {
System.out.format("\tX: %.2f, Y: %.2f\n", vertex.getX(), vertex.getY());
}
}
}
}
use of com.google.cloud.videointelligence.v1p2beta1.NormalizedVertex in project java-video-intelligence by googleapis.
the class TextDetection method detectTextGcs.
// [END video_detect_text]
// [START video_detect_text_gcs]
/**
* 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(300, 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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