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Commit 188114d

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eapl-gemugamieapl-gemugami
authored
chore(video): delete samples in beta_snippets.py (GoogleCloudPlatform#13193)
* chore(video): skip tests without required permissions - Find details in b/330632499 * chore(video): delete sample 'video_detect_text_beta' * chore(video): delete sample 'video_detect_text_gcs_beta' * chore(video): delete sample 'video_speech_transcription_gcs_beta'
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‎videointelligence/samples/analyze/beta_snippets.py

Copy file name to clipboardExpand all lines: videointelligence/samples/analyze/beta_snippets.py
+1-191Lines changed: 1 addition & 191 deletions
Original file line numberDiff line numberDiff line change
@@ -18,12 +18,6 @@
1818
Google Cloud API.
1919
2020
Usage Examples:
21-
python beta_snippets.py transcription \
22-
gs://python-docs-samples-tests/video/googlework_tiny.mp4
23-
24-
python beta_snippets.py video-text-gcs \
25-
gs://python-docs-samples-tests/video/googlework_tiny.mp4
26-
2721
python beta_snippets.py streaming-labels resources/cat.mp4
2822
2923
python beta_snippets.py streaming-shot-change resources/cat.mp4
@@ -49,169 +43,6 @@
4943
import io
5044

5145

52-
def speech_transcription(input_uri, timeout=180):
53-
# [START video_speech_transcription_gcs_beta]
54-
"""Transcribe speech from a video stored on GCS."""
55-
from google.cloud import videointelligence_v1p1beta1 as videointelligence
56-
57-
video_client = videointelligence.VideoIntelligenceServiceClient()
58-
59-
features = [videointelligence.Feature.SPEECH_TRANSCRIPTION]
60-
61-
config = videointelligence.SpeechTranscriptionConfig(
62-
language_code="en-US", enable_automatic_punctuation=True
63-
)
64-
video_context = videointelligence.VideoContext(speech_transcription_config=config)
65-
66-
operation = video_client.annotate_video(
67-
request={
68-
"features": features,
69-
"input_uri": input_uri,
70-
"video_context": video_context,
71-
}
72-
)
73-
74-
print("\nProcessing video for speech transcription.")
75-
76-
result = operation.result(timeout)
77-
78-
# There is only one annotation_result since only
79-
# one video is processed.
80-
annotation_results = result.annotation_results[0]
81-
for speech_transcription in annotation_results.speech_transcriptions:
82-
# The number of alternatives for each transcription is limited by
83-
# SpeechTranscriptionConfig.max_alternatives.
84-
# Each alternative is a different possible transcription
85-
# and has its own confidence score.
86-
for alternative in speech_transcription.alternatives:
87-
print("Alternative level information:")
88-
89-
print("Transcript: {}".format(alternative.transcript))
90-
print("Confidence: {}\n".format(alternative.confidence))
91-
92-
print("Word level information:")
93-
for word_info in alternative.words:
94-
word = word_info.word
95-
start_time = word_info.start_time
96-
end_time = word_info.end_time
97-
print(
98-
"\t{}s - {}s: {}".format(
99-
start_time.seconds + start_time.microseconds * 1e-6,
100-
end_time.seconds + end_time.microseconds * 1e-6,
101-
word,
102-
)
103-
)
104-
# [END video_speech_transcription_gcs_beta]
105-
106-
107-
def video_detect_text_gcs(input_uri):
108-
# [START video_detect_text_gcs_beta]
109-
"""Detect text in a video stored on GCS."""
110-
from google.cloud import videointelligence_v1p2beta1 as videointelligence
111-
112-
video_client = videointelligence.VideoIntelligenceServiceClient()
113-
features = [videointelligence.Feature.TEXT_DETECTION]
114-
115-
operation = video_client.annotate_video(
116-
request={"features": features, "input_uri": input_uri}
117-
)
118-
119-
print("\nProcessing video for text detection.")
120-
result = operation.result(timeout=300)
121-
122-
# The first result is retrieved because a single video was processed.
123-
annotation_result = result.annotation_results[0]
124-
125-
# Get only the first result
126-
text_annotation = annotation_result.text_annotations[0]
127-
print("\nText: {}".format(text_annotation.text))
128-
129-
# Get the first text segment
130-
text_segment = text_annotation.segments[0]
131-
start_time = text_segment.segment.start_time_offset
132-
end_time = text_segment.segment.end_time_offset
133-
print(
134-
"start_time: {}, end_time: {}".format(
135-
start_time.seconds + start_time.microseconds * 1e-6,
136-
end_time.seconds + end_time.microseconds * 1e-6,
137-
)
138-
)
139-
140-
print("Confidence: {}".format(text_segment.confidence))
141-
142-
# Show the result for the first frame in this segment.
143-
frame = text_segment.frames[0]
144-
time_offset = frame.time_offset
145-
print(
146-
"Time offset for the first frame: {}".format(
147-
time_offset.seconds + time_offset.microseconds * 1e-6
148-
)
149-
)
150-
print("Rotated Bounding Box Vertices:")
151-
for vertex in frame.rotated_bounding_box.vertices:
152-
print("\tVertex.x: {}, Vertex.y: {}".format(vertex.x, vertex.y))
153-
# [END video_detect_text_gcs_beta]
154-
return annotation_result.text_annotations
155-
156-
157-
def video_detect_text(path):
158-
# [START video_detect_text_beta]
159-
"""Detect text in a local video."""
160-
from google.cloud import videointelligence_v1p2beta1 as videointelligence
161-
162-
video_client = videointelligence.VideoIntelligenceServiceClient()
163-
features = [videointelligence.Feature.TEXT_DETECTION]
164-
video_context = videointelligence.VideoContext()
165-
166-
with io.open(path, "rb") as file:
167-
input_content = file.read()
168-
169-
operation = video_client.annotate_video(
170-
request={
171-
"features": features,
172-
"input_content": input_content,
173-
"video_context": video_context,
174-
}
175-
)
176-
177-
print("\nProcessing video for text detection.")
178-
result = operation.result(timeout=300)
179-
180-
# The first result is retrieved because a single video was processed.
181-
annotation_result = result.annotation_results[0]
182-
183-
# Get only the first result
184-
text_annotation = annotation_result.text_annotations[0]
185-
print("\nText: {}".format(text_annotation.text))
186-
187-
# Get the first text segment
188-
text_segment = text_annotation.segments[0]
189-
start_time = text_segment.segment.start_time_offset
190-
end_time = text_segment.segment.end_time_offset
191-
print(
192-
"start_time: {}, end_time: {}".format(
193-
start_time.seconds + start_time.microseconds * 1e-6,
194-
end_time.seconds + end_time.microseconds * 1e-6,
195-
)
196-
)
197-
198-
print("Confidence: {}".format(text_segment.confidence))
199-
200-
# Show the result for the first frame in this segment.
201-
frame = text_segment.frames[0]
202-
time_offset = frame.time_offset
203-
print(
204-
"Time offset for the first frame: {}".format(
205-
time_offset.seconds + time_offset.microseconds * 1e-6
206-
)
207-
)
208-
print("Rotated Bounding Box Vertices:")
209-
for vertex in frame.rotated_bounding_box.vertices:
210-
print("\tVertex.x: {}, Vertex.y: {}".format(vertex.x, vertex.y))
211-
# [END video_detect_text_beta]
212-
return annotation_result.text_annotations
213-
214-
21546
def detect_labels_streaming(path):
21647
# [START video_streaming_label_detection_beta]
21748
from google.cloud import videointelligence_v1p3beta1 as videointelligence
@@ -826,21 +657,6 @@ def stream_generator():
826657
)
827658
subparsers = parser.add_subparsers(dest="command")
828659

829-
speech_transcription_parser = subparsers.add_parser(
830-
"transcription", help=speech_transcription.__doc__
831-
)
832-
speech_transcription_parser.add_argument("gcs_uri")
833-
834-
video_text_gcs_parser = subparsers.add_parser(
835-
"video-text-gcs", help=video_detect_text_gcs.__doc__
836-
)
837-
video_text_gcs_parser.add_argument("gcs_uri")
838-
839-
video_text_parser = subparsers.add_parser(
840-
"video-text", help=video_detect_text.__doc__
841-
)
842-
video_text_parser.add_argument("path")
843-
844660
video_streaming_labels_parser = subparsers.add_parser(
845661
"streaming-labels", help=detect_labels_streaming.__doc__
846662
)
@@ -892,13 +708,7 @@ def stream_generator():
892708

893709
args = parser.parse_args()
894710

895-
if args.command == "transcription":
896-
speech_transcription(args.gcs_uri)
897-
elif args.command == "video-text-gcs":
898-
video_detect_text_gcs(args.gcs_uri)
899-
elif args.command == "video-text":
900-
video_detect_text(args.path)
901-
elif args.command == "streaming-labels":
711+
if args.command == "streaming-labels":
902712
detect_labels_streaming(args.path)
903713
elif args.command == "streaming-shot-change":
904714
detect_shot_change_streaming(args.path)

‎videointelligence/samples/analyze/beta_snippets_test.py

Copy file name to clipboardExpand all lines: videointelligence/samples/analyze/beta_snippets_test.py
+8-26Lines changed: 8 additions & 26 deletions
Original file line numberDiff line numberDiff line change
@@ -69,14 +69,7 @@ def delete_bucket():
6969
delete_bucket()
7070

7171

72-
def test_speech_transcription(capsys):
73-
beta_snippets.speech_transcription(
74-
"gs://python-docs-samples-tests/video/googlework_short.mp4", timeout=240
75-
)
76-
out, _ = capsys.readouterr()
77-
assert "cultural" in out
78-
79-
72+
@pytest.mark.skip(reason="b/330632499")
8073
@pytest.mark.flaky(max_runs=3, min_passes=1)
8174
def test_detect_labels_streaming(capsys, video_path):
8275
beta_snippets.detect_labels_streaming(video_path)
@@ -85,13 +78,15 @@ def test_detect_labels_streaming(capsys, video_path):
8578
assert "cat" in out
8679

8780

81+
@pytest.mark.skip(reason="b/330632499")
8882
def test_detect_shot_change_streaming(capsys, video_path):
8983
beta_snippets.detect_shot_change_streaming(video_path)
9084

9185
out, _ = capsys.readouterr()
9286
assert "Shot" in out
9387

9488

89+
@pytest.mark.skip(reason="b/330632499")
9590
# Flaky ServiceUnavailable
9691
@pytest.mark.flaky(max_runs=3, min_passes=1)
9792
def test_track_objects_streaming(capsys, video_path):
@@ -101,6 +96,7 @@ def test_track_objects_streaming(capsys, video_path):
10196
assert "cat" in out
10297

10398

99+
@pytest.mark.skip(reason="b/330632499")
104100
@pytest.mark.flaky(max_runs=3, min_passes=1)
105101
def test_detect_explicit_content_streaming(capsys, video_path):
106102
beta_snippets.detect_explicit_content_streaming(video_path)
@@ -109,6 +105,7 @@ def test_detect_explicit_content_streaming(capsys, video_path):
109105
assert "Time" in out
110106

111107

108+
@pytest.mark.skip(reason="b/330632499")
112109
@pytest.mark.flaky(max_runs=3, min_passes=1)
113110
def test_annotation_to_storage_streaming(capsys, video_path, bucket):
114111
output_uri = "gs://{}".format(bucket.name)
@@ -118,24 +115,7 @@ def test_annotation_to_storage_streaming(capsys, video_path, bucket):
118115
assert "Storage" in out
119116

120117

121-
# Flaky timeout
122-
@pytest.mark.flaky(max_runs=3, min_passes=1)
123-
def test_detect_text(capsys):
124-
in_file = "./resources/googlework_tiny.mp4"
125-
beta_snippets.video_detect_text(in_file)
126-
out, _ = capsys.readouterr()
127-
assert "Text" in out
128-
129-
130-
# Flaky timeout
131-
@pytest.mark.flaky(max_runs=3, min_passes=1)
132-
def test_detect_text_gcs(capsys):
133-
in_file = "gs://python-docs-samples-tests/video/googlework_tiny.mp4"
134-
beta_snippets.video_detect_text_gcs(in_file)
135-
out, _ = capsys.readouterr()
136-
assert "Text" in out
137-
138-
118+
@pytest.mark.skip(reason="b/330632499")
139119
# Flaky Gateway
140120
@pytest.mark.flaky(max_runs=3, min_passes=1)
141121
def test_streaming_automl_classification(capsys, video_path):
@@ -146,6 +126,7 @@ def test_streaming_automl_classification(capsys, video_path):
146126
assert "brush_hair" in out
147127

148128

129+
@pytest.mark.skip(reason="b/330632499")
149130
# Flaky Gateway
150131
@pytest.mark.flaky(max_runs=3, min_passes=1)
151132
def test_streaming_automl_object_tracking(capsys, video_path):
@@ -156,6 +137,7 @@ def test_streaming_automl_object_tracking(capsys, video_path):
156137
assert "Track Id" in out
157138

158139

140+
@pytest.mark.skip(reason="b/330632499")
159141
# Flaky Gateway
160142
@pytest.mark.flaky(max_runs=3, min_passes=1)
161143
def test_streaming_automl_action_recognition(capsys, video_path):

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