OPERATION_NAME/var>: the name of the operation as
returned by Video Intelligence API. The operation name has the format
projects/PROJECT_NUMBER/locations/LOCATION_ID/operations/OPERATION_ID
HTTP 方法和网址：
GET https://videointelligence.googleapis.com/v1/OPERATION_NAME
func speechTranscriptionURI(w io.Writer, file string) error {
ctx := context.Background()
client, err := video.NewClient(ctx)
if err != nil {
return err
}
defer client.Close()
op, err := client.AnnotateVideo(ctx, &videopb.AnnotateVideoRequest{
Features: []videopb.Feature{
videopb.Feature_SPEECH_TRANSCRIPTION,
},
VideoContext: &videopb.VideoContext{
SpeechTranscriptionConfig: &videopb.SpeechTranscriptionConfig{
LanguageCode: "en-US",
EnableAutomaticPunctuation: true,
},
},
InputUri: file,
})
if err != nil {
return err
}
resp, err := op.Wait(ctx)
if err != nil {
return err
}
// A single video was processed. Get the first result.
result := resp.AnnotationResults[0]
for _, transcription := range result.SpeechTranscriptions {
// The number of alternatives for each transcription is limited by
// SpeechTranscriptionConfig.MaxAlternatives.
// Each alternative is a different possible transcription
// and has its own confidence score.
for _, alternative := range transcription.GetAlternatives() {
fmt.Fprintf(w, "Alternative level information:\n")
fmt.Fprintf(w, "\tTranscript: %v\n", alternative.GetTranscript())
fmt.Fprintf(w, "\tConfidence: %v\n", alternative.GetConfidence())
fmt.Fprintf(w, "Word level information:\n")
for _, wordInfo := range alternative.GetWords() {
startTime := wordInfo.GetStartTime()
endTime := wordInfo.GetEndTime()
fmt.Fprintf(w, "\t%4.1f - %4.1f: %v (speaker %v)\n",
float64(startTime.GetSeconds())+float64(startTime.GetNanos())*1e-9, // start as seconds
float64(endTime.GetSeconds())+float64(endTime.GetNanos())*1e-9, // end as seconds
wordInfo.GetWord(),
wordInfo.GetSpeakerTag())
}
}
}
return nil
}
// Imports the Google Cloud Video Intelligence library
const videoIntelligence = require('@google-cloud/video-intelligence');
// Creates a client
const client = new videoIntelligence.VideoIntelligenceServiceClient();
/**
* TODO(developer): Uncomment the following line before running the sample.
*/
// const gcsUri = 'GCS URI of video to analyze, e.g. gs://my-bucket/my-video.mp4';
async function analyzeVideoTranscript() {
const videoContext = {
speechTranscriptionConfig: {
languageCode: 'en-US',
enableAutomaticPunctuation: true,
},
};
const request = {
inputUri: gcsUri,
features: ['SPEECH_TRANSCRIPTION'],
videoContext: videoContext,
};
const [operation] = await client.annotateVideo(request);
console.log('Waiting for operation to complete...');
const [operationResult] = await operation.promise();
// There is only one annotation_result since only
// one video is processed.
const annotationResults = operationResult.annotationResults[0];
for (const speechTranscription of annotationResults.speechTranscriptions) {
// The number of alternatives for each transcription is limited by
// SpeechTranscriptionConfig.max_alternatives.
// Each alternative is a different possible transcription
// and has its own confidence score.
for (const alternative of speechTranscription.alternatives) {
console.log('Alternative level information:');
console.log(`Transcript: ${alternative.transcript}`);
console.log(`Confidence: ${alternative.confidence}`);
console.log('Word level information:');
for (const wordInfo of alternative.words) {
const word = wordInfo.word;
const start_time =
wordInfo.startTime.seconds + wordInfo.startTime.nanos * 1e-9;
const end_time =
wordInfo.endTime.seconds + wordInfo.endTime.nanos * 1e-9;
console.log('\t' + start_time + 's - ' + end_time + 's: ' + word);
}
}
}
}
analyzeVideoTranscript();
"""Transcribe speech from a video stored on GCS."""
from google.cloud import videointelligence
video_client = videointelligence.VideoIntelligenceServiceClient()
features = [videointelligence.Feature.SPEECH_TRANSCRIPTION]
config = videointelligence.SpeechTranscriptionConfig(
language_code="en-US", enable_automatic_punctuation=True
)
video_context = videointelligence.VideoContext(speech_transcription_config=config)
operation = video_client.annotate_video(
request={
"features": features,
"input_uri": path,
"video_context": video_context,
}
)
print("\nProcessing video for speech transcription.")
result = operation.result(timeout=600)
# There is only one annotation_result since only
# one video is processed.
annotation_results = result.annotation_results[0]
for speech_transcription in annotation_results.speech_transcriptions:
# The number of alternatives for each transcription is limited by
# SpeechTranscriptionConfig.max_alternatives.
# Each alternative is a different possible transcription
# and has its own confidence score.
for alternative in speech_transcription.alternatives:
print("Alternative level information:")
print("Transcript: {}".format(alternative.transcript))
print("Confidence: {}\n".format(alternative.confidence))
print("Word level information:")
for word_info in alternative.words:
word = word_info.word
start_time = word_info.start_time
end_time = word_info.end_time
print(
"\t{}s - {}s: {}".format(
start_time.seconds + start_time.microseconds * 1e-6,
end_time.seconds + end_time.microseconds * 1e-6,
word,
)
)
