def streaming_annotate(stream_file):
"""Annotate a local video file through streaming API."""
client = videointelligence.StreamingVideoIntelligenceServiceClient()
# Set the chunk size to 5MB (recommended less than 10MB).
chunk_size = 5 * 1024 * 1024
# Open file.
with open(stream_file) as video_file:
requests = (
types.StreamingAnnotateVideoRequest(input_content=chunk)
for chunk in stream(video_file, chunk_size))
# Set streaming config.
config = types.StreamingVideoConfig(
feature=enums.StreamingFeature.STREAMING_EXPLICIT_CONTENT_DETECTION)
config_request = types.StreamingAnnotateVideoRequest(video_config=config)
# streaming_annotate_video returns a generator.
# timeout argument specifies the maximum allowable time duration between
# the time that the last packet is sent to Google video intelligence API
# and the time that an annotation result is returned from the API.
# timeout argument is represented in number of seconds.
responses = client.streaming_annotate_video(
config_request, requests, timeout=10800)
print('\nReading response.')
# Retrieve results from the response generator.
for response in responses:
for frame in response.annotation_results.explicit_annotation.frames:
likelihood = enums.Likelihood(frame.pornography_likelihood)
frame_time = frame.time_offset.seconds + frame.time_offset.nanos / 1e9
print('Time: {}s'.format(frame_time))
print('\tpornography: {}'.format(likelihood.name))
def analyze_explicit_content(path):
# [START video_analyze_explicit_content]
""" Detects explicit content from the GCS path to a video. """
video_client = videointelligence.VideoIntelligenceServiceClient()
features = [videointelligence.enums.Feature.EXPLICIT_CONTENT_DETECTION]
operation = video_client.annotate_video(path, features=features)
print('\nProcessing video for explicit content annotations:')
result = operation.result(timeout=90)
print('\nFinished processing.')
# first result is retrieved because a single video was processed
for frame in result.annotation_results[0].explicit_annotation.frames:
likelihood = enums.Likelihood(frame.pornography_likelihood)
frame_time = frame.time_offset.seconds + frame.time_offset.nanos / 1e9
print('Time: {}s'.format(frame_time))
print('\tpornography: {}'.format(likelihood.name))
