Perubahan shot

Analisis perubahan shot mendeteksi perubahan gambar pada video.

Kode contoh berikut menunjukkan cara menggunakan streaming Video Intelligence API untuk mengidentifikasi perubahan rekaman dalam video.

Java

Untuk mengautentikasi Video Intelligence, siapkan Kredensial Default Aplikasi. Untuk informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal.


import com.google.api.gax.rpc.BidiStream;
import com.google.cloud.videointelligence.v1p3beta1.StreamingAnnotateVideoRequest;
import com.google.cloud.videointelligence.v1p3beta1.StreamingAnnotateVideoResponse;
import com.google.cloud.videointelligence.v1p3beta1.StreamingFeature;
import com.google.cloud.videointelligence.v1p3beta1.StreamingLabelDetectionConfig;
import com.google.cloud.videointelligence.v1p3beta1.StreamingVideoAnnotationResults;
import com.google.cloud.videointelligence.v1p3beta1.StreamingVideoConfig;
import com.google.cloud.videointelligence.v1p3beta1.StreamingVideoIntelligenceServiceClient;
import com.google.cloud.videointelligence.v1p3beta1.VideoSegment;
import com.google.protobuf.ByteString;
import io.grpc.StatusRuntimeException;
import java.io.IOException;
import java.nio.file.Files;
import java.nio.file.Path;
import java.nio.file.Paths;
import java.util.Arrays;
import java.util.concurrent.TimeoutException;

class StreamingShotChangeDetection {

  // Perform streaming video detection for shot changes
  static void streamingShotChangeDetection(String filePath)
      throws IOException, TimeoutException, StatusRuntimeException {
    // String filePath = "path_to_your_video_file";

    try (StreamingVideoIntelligenceServiceClient client =
        StreamingVideoIntelligenceServiceClient.create()) {

      Path path = Paths.get(filePath);
      byte[] data = Files.readAllBytes(path);
      // Set the chunk size to 5MB (recommended less than 10MB).
      int chunkSize = 5 * 1024 * 1024;
      int numChunks = (int) Math.ceil((double) data.length / chunkSize);

      StreamingLabelDetectionConfig labelConfig =
          StreamingLabelDetectionConfig.newBuilder().setStationaryCamera(false).build();

      StreamingVideoConfig streamingVideoConfig =
          StreamingVideoConfig.newBuilder()
              .setFeature(StreamingFeature.STREAMING_SHOT_CHANGE_DETECTION)
              .setLabelDetectionConfig(labelConfig)
              .build();

      BidiStream<StreamingAnnotateVideoRequest, StreamingAnnotateVideoResponse> call =
          client.streamingAnnotateVideoCallable().call();

      // The first request must **only** contain the audio configuration:
      call.send(
          StreamingAnnotateVideoRequest.newBuilder().setVideoConfig(streamingVideoConfig).build());

      // Subsequent requests must **only** contain the audio data.
      // Send the requests in chunks
      for (int i = 0; i < numChunks; i++) {
        call.send(
            StreamingAnnotateVideoRequest.newBuilder()
                .setInputContent(
                    ByteString.copyFrom(
                        Arrays.copyOfRange(data, i * chunkSize, i * chunkSize + chunkSize)))
                .build());
      }

      // Tell the service you are done sending data
      call.closeSend();

      for (StreamingAnnotateVideoResponse response : call) {
        StreamingVideoAnnotationResults annotationResults = response.getAnnotationResults();
        if (response.hasError()) {
          System.out.println(response.getError().getMessage());
          System.out.format(
              "Error was occured with the following status: %s\n", response.getError());
        }
        for (VideoSegment segment : annotationResults.getShotAnnotationsList()) {
          double startTimeOffset =
              segment.getStartTimeOffset().getSeconds()
                  + segment.getStartTimeOffset().getNanos() / 1e9;
          double endTimeOffset =
              segment.getEndTimeOffset().getSeconds() + segment.getEndTimeOffset().getNanos() / 1e9;

          System.out.format("Shot: %fs to %fs\n", startTimeOffset, endTimeOffset);
        }
      }
    }
  }
}

Node.js

Untuk mengautentikasi Video Intelligence, siapkan Kredensial Default Aplikasi. Untuk informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal.

/**
 * TODO(developer): Uncomment these variables before running the sample.
 */
// const path = 'Local file to analyze, e.g. ./my-file.mp4';
const {StreamingVideoIntelligenceServiceClient} =
  require('@google-cloud/video-intelligence').v1p3beta1;
const fs = require('fs');

// Instantiates a client
const client = new StreamingVideoIntelligenceServiceClient();
// Streaming configuration
const configRequest = {
  videoConfig: {
    feature: 'STREAMING_SHOT_CHANGE_DETECTION',
  },
};
const readStream = fs.createReadStream(path, {
  highWaterMark: 5 * 1024 * 1024, //chunk size set to 5MB (recommended less than 10MB)
  encoding: 'base64',
});
//Load file content
const chunks = [];
readStream
  .on('data', chunk => {
    const request = {
      inputContent: chunk.toString(),
    };
    chunks.push(request);
  })
  .on('close', () => {
    // configRequest should be the first in the stream of requests
    stream.write(configRequest);
    for (let i = 0; i < chunks.length; i++) {
      stream.write(chunks[i]);
    }
    stream.end();
  });

const stream = client.streamingAnnotateVideo().on('data', response => {
  //Gets annotations for video
  const annotations = response.annotationResults;
  const shotChanges = annotations.shotAnnotations;
  console.log(JSON.stringify(shotChanges));
  if (shotChanges.length === 1) {
    console.log('The entire video is one shot.');
  }
  shotChanges.forEach(shot => {
    console.log(
      ` Shot: ${shot.startTimeOffset.seconds || 0}` +
        `.${(shot.startTimeOffset.nanos / 1e6).toFixed(0)}s to ${
          shot.endTimeOffset.seconds || 0
        }` +
        `.${(shot.endTimeOffset.nanos / 1e6).toFixed(0)}s`
    );
  });
});

Python

Untuk mengautentikasi Video Intelligence, siapkan Kredensial Default Aplikasi. Untuk informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal.

from google.cloud import videointelligence_v1p3beta1 as videointelligence

# path = 'path_to_file'

client = videointelligence.StreamingVideoIntelligenceServiceClient()

# Set streaming config.
config = videointelligence.StreamingVideoConfig(
    feature=(videointelligence.StreamingFeature.STREAMING_SHOT_CHANGE_DETECTION)
)

# config_request should be the first in the stream of requests.
config_request = videointelligence.StreamingAnnotateVideoRequest(
    video_config=config
)

# Set the chunk size to 5MB (recommended less than 10MB).
chunk_size = 5 * 1024 * 1024

# Load file content.
stream = []
with io.open(path, "rb") as video_file:
    while True:
        data = video_file.read(chunk_size)
        if not data:
            break
        stream.append(data)

def stream_generator():
    yield config_request
    for chunk in stream:
        yield videointelligence.StreamingAnnotateVideoRequest(input_content=chunk)

requests = stream_generator()

# streaming_annotate_video returns a generator.
# The default timeout is about 300 seconds.
# To process longer videos it should be set to
# larger than the length (in seconds) of the stream.
responses = client.streaming_annotate_video(requests, timeout=600)

# Each response corresponds to about 1 second of video.
for response in responses:
    # Check for errors.
    if response.error.message:
        print(response.error.message)
        break

    for annotation in response.annotation_results.shot_annotations:
        start = (
            annotation.start_time_offset.seconds
            + annotation.start_time_offset.microseconds / 1e6
        )
        end = (
            annotation.end_time_offset.seconds
            + annotation.end_time_offset.microseconds / 1e6
        )

        print("Shot: {}s to {}s".format(start, end))