L'analyse des thèmes identifie les objets, les lieux, les activités, les espèces animales, les produits, etc.
Utiliser le modèle standard
Le code suivant montre comment annoter une vidéo à l'aide de la détection de thèmes en streaming de l'API Video Intelligence.
Java
Pour vous authentifier auprès de Video Intelligence, configurez les Identifiants par défaut de l'application. Pour en savoir plus, consultez Configurer l'authentification pour un environnement de développement local.
import com.google.api.gax.rpc.BidiStream;
import com.google.cloud.videointelligence.v1p3beta1.LabelAnnotation;
import com.google.cloud.videointelligence.v1p3beta1.LabelFrame;
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.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 StreamingLabelDetection {
// Perform streaming video label detection
static void streamingLabelDetection(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_LABEL_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();
for (LabelAnnotation annotation : annotationResults.getLabelAnnotationsList()) {
String entity = annotation.getEntity().getDescription();
// There is only one frame per annotation
LabelFrame labelFrame = annotation.getFrames(0);
double offset =
labelFrame.getTimeOffset().getSeconds() + labelFrame.getTimeOffset().getNanos() / 1e9;
float confidence = labelFrame.getConfidence();
System.out.format("%fs: %s (%f)\n", offset, entity, confidence);
}
}
}
}
}
Node.js
Pour vous authentifier auprès de Video Intelligence, configurez les Identifiants par défaut de l'application. Pour en savoir plus, consultez Configurer l'authentification pour un environnement de développement local.
/**
* 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_LABEL_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 labels = annotations.labelAnnotations;
labels.forEach(label => {
console.log(
`Label ${label.entity.description} occurs at: ${
label.frames[0].timeOffset.seconds || 0
}` + `.${(label.frames[0].timeOffset.nanos / 1e6).toFixed(0)}s`
);
console.log(` Confidence: ${label.frames[0].confidence}`);
});
});
Python
Pour vous authentifier auprès de Video Intelligence, configurez les Identifiants par défaut de l'application. Pour en savoir plus, consultez Configurer l'authentification pour un environnement de développement local.
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_LABEL_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
label_annotations = response.annotation_results.label_annotations
# label_annotations could be empty
if not label_annotations:
continue
for annotation in label_annotations:
# Each annotation has one frame, which has a timeoffset.
frame = annotation.frames[0]
time_offset = (
frame.time_offset.seconds + frame.time_offset.microseconds / 1e6
)
description = annotation.entity.description
confidence = annotation.frames[0].confidence
# description is in Unicode
print(
"{}s: {} (confidence: {})".format(time_offset, description, confidence)
)