|
30 | 30 | # [START full_tutorial]
|
31 | 31 | # [START imports]
|
32 | 32 | import argparse
|
33 |
| -import sys |
34 |
| -import time |
35 | 33 |
|
36 |
| -from google.cloud import videointelligence_v1beta2 |
37 |
| -from google.cloud.videointelligence_v1beta2 import enums |
| 34 | +from google.cloud import videointelligence |
38 | 35 | # [END imports]
|
39 | 36 |
|
40 | 37 |
|
41 | 38 | def analyze_labels(path):
|
42 | 39 | """ Detects labels given a GCS path. """
|
43 | 40 | # [START construct_request]
|
44 |
| - video_client = videointelligence_v1beta2.VideoIntelligenceServiceClient() |
45 |
| - features = [enums.Feature.LABEL_DETECTION] |
46 |
| - operation = video_client.annotate_video(path, features) |
| 41 | + video_client = videointelligence.VideoIntelligenceServiceClient() |
| 42 | + features = [videointelligence.enums.Feature.LABEL_DETECTION] |
| 43 | + operation = video_client.annotate_video(path, features=features) |
47 | 44 | # [END construct_request]
|
48 | 45 | print('\nProcessing video for label annotations:')
|
49 | 46 |
|
50 | 47 | # [START check_operation]
|
51 |
| - while not operation.done(): |
52 |
| - sys.stdout.write('.') |
53 |
| - sys.stdout.flush() |
54 |
| - time.sleep(20) |
55 |
| - |
| 48 | + result = operation.result(timeout=90) |
56 | 49 | print('\nFinished processing.')
|
57 | 50 | # [END check_operation]
|
58 | 51 |
|
59 | 52 | # [START parse_response]
|
60 |
| - results = operation.result().annotation_results[0] |
61 |
| - |
62 |
| - for i, segment_label in enumerate(results.segment_label_annotations): |
| 53 | + segment_labels = result.annotation_results[0].segment_label_annotations |
| 54 | + for i, segment_label in enumerate(segment_labels): |
63 | 55 | print('Video label description: {}'.format(
|
64 | 56 | segment_label.entity.description))
|
65 | 57 | for category_entity in segment_label.category_entities:
|
|
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