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Commit 29b0060

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gguussJon Wayne Parrott
gguuss
authored and
Jon Wayne Parrott
committed
Adds tutorials using Cloud Client (GoogleCloudPlatform#930)
* Adds tutorials. * Removes unused enumerate
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‎video/cloud-client/README.md renamed to ‎video/cloud-client/analyze/README.md

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‎video/cloud-client/analyze.py renamed to ‎video/cloud-client/analyze/analyze.py

Copy file name to clipboardExpand all lines: video/cloud-client/analyze/analyze.py
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@@ -77,7 +77,7 @@ def analyze_labels(path):
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# first result is retrieved because a single video was processed
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results = operation.result().annotation_results[0]
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for i, label in enumerate(results.label_annotations):
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for label in results.label_annotations:
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print('Label description: {}'.format(label.description))
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print('Locations:')
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‎video/cloud-client/analyze_test.py renamed to ‎video/cloud-client/analyze/analyze_test.py

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‎video/cloud-client/requirements.txt renamed to ‎video/cloud-client/analyze/requirements.txt

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‎video/cloud-client/labels/README.md

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# Google Cloud Video Intelligence
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Demonstrates label detection using the Google Cloud Video Intelligence API.
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## Setup
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Please follow the [Set Up Your Project](https://cloud.google.com/video-intelligence/docs/getting-started#set_up_your_project)
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steps in the Quickstart doc to create a project and enable the Google Cloud
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Video Intelligence API. Following those steps, make sure that you
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[Set Up a Service Account](https://cloud.google.com/video-intelligence/docs/common/auth#set_up_a_service_account),
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and export the following environment variable:
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```
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export GOOGLE_APPLICATION_CREDENTIALS=/path/to/your-project-credentials.json
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```
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## Run the sample
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Install [pip](https://pip.pypa.io/en/stable/installing) if not already installed.
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Install the necessary libraries using pip:
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```sh
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$ pip install -r requirements.txt
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```
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Run the sample, for example:
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```
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python labels.py gs://cloud-ml-sandbox/video/chicago.mp4
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```

‎video/cloud-client/labels/labels.py

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#!/usr/bin/env python
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# Copyright 2017 Google Inc. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""This application demonstrates how to perform basic operations with the
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Google Cloud Video Intelligence API.
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For more information, check out the documentation at
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https://cloud.google.com/videointelligence/docs.
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"""
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# [START full_tutorial]
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# [START imports]
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import argparse
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import sys
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import time
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from google.cloud.gapic.videointelligence.v1beta1 import enums
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from google.cloud.gapic.videointelligence.v1beta1 import (
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video_intelligence_service_client)
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# [END imports]
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def analyze_labels(path):
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""" Detects labels given a GCS path. """
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# [START construct_request]
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video_client = (video_intelligence_service_client.
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VideoIntelligenceServiceClient())
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features = [enums.Feature.LABEL_DETECTION]
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operation = video_client.annotate_video(path, features)
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# [END construct_request]
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print('\nProcessing video for label annotations:')
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# [START check_operation]
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while not operation.done():
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sys.stdout.write('.')
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sys.stdout.flush()
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time.sleep(20)
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print('\nFinished processing.')
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# [END check_operation]
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# [START parse_response]
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results = operation.result().annotation_results[0]
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for label in results.label_annotations:
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print('Label description: {}'.format(label.description))
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print('Locations:')
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for l, location in enumerate(label.locations):
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print('\t{}: {} to {}'.format(
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l,
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location.segment.start_time_offset,
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location.segment.end_time_offset))
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# [END parse_response]
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if __name__ == '__main__':
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# [START running_app]
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parser = argparse.ArgumentParser(
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description=__doc__,
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formatter_class=argparse.RawDescriptionHelpFormatter)
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parser.add_argument('path', help='GCS file path for label detection.')
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args = parser.parse_args()
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analyze_labels(args.path)
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# [END running_app]
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# [END full_tutorial]

‎video/cloud-client/labels/labels_test.py

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#!/usr/bin/env python
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# Copyright 2017 Google, Inc
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import os
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import pytest
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import labels
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BUCKET = os.environ['CLOUD_STORAGE_BUCKET']
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LABELS_FILE_PATH = '/video/cat.mp4'
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@pytest.mark.slow
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def test_feline_video_labels(capsys):
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labels.analyze_labels(
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'gs://{}{}'.format(BUCKET, LABELS_FILE_PATH))
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out, _ = capsys.readouterr()
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assert 'Whiskers' in out

‎video/cloud-client/labels/requirements.txt

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https://storage.googleapis.com/videointelligence-alpha/videointelligence-python.zip

‎video/cloud-client/shotchange/README.md

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# Google Cloud Video Intelligence
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Demonstrates label detection using the Google Cloud Video Intelligence API.
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5+
## Setup
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Please follow the [Set Up Your Project](https://cloud.google.com/video-intelligence/docs/getting-started#set_up_your_project)
7+
steps in the Quickstart doc to create a project and enable the Google Cloud
8+
Video Intelligence API. Following those steps, make sure that you
9+
[Set Up a Service Account](https://cloud.google.com/video-intelligence/docs/common/auth#set_up_a_service_account),
10+
and export the following environment variable:
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```
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export GOOGLE_APPLICATION_CREDENTIALS=/path/to/your-project-credentials.json
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```
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## Run the sample
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Install [pip](https://pip.pypa.io/en/stable/installing) if not already installed.
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Install the necessary libraries using pip:
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```sh
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$ pip install -r requirements.txt
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```
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Run the sample, for example:
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```
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python shotchange.py gs://cloudmleap/video/googlework.mp4
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```

‎video/cloud-client/shotchange/requirements.txt

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https://storage.googleapis.com/videointelligence-alpha/videointelligence-python.zip

‎video/cloud-client/shotchange/shotchange.py

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#!/usr/bin/env python
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# Copyright 2017 Google Inc. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""This application demonstrates how to perform basic operations with the
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Google Cloud Video Intelligence API.
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For more information, check out the documentation at
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https://cloud.google.com/videointelligence/docs.
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"""
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# [START full_tutorial]
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# [START imports]
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import argparse
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import sys
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import time
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from google.cloud.gapic.videointelligence.v1beta1 import enums
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from google.cloud.gapic.videointelligence.v1beta1 import (
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video_intelligence_service_client)
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# [END imports]
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def analyze_shots(path):
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""" Detects camera shot changes. """
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# [START construct_request]
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video_client = (video_intelligence_service_client.
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VideoIntelligenceServiceClient())
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features = [enums.Feature.SHOT_CHANGE_DETECTION]
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operation = video_client.annotate_video(path, features)
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# [END construct_request]
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print('\nProcessing video for shot change annotations:')
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# [START check_operation]
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while not operation.done():
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sys.stdout.write('.')
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sys.stdout.flush()
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time.sleep(20)
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print('\nFinished processing.')
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# [END check_operation]
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# [START parse_response]
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shots = operation.result().annotation_results[0]
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for note, shot in enumerate(shots.shot_annotations):
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print('Scene {}: {} to {}'.format(
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note,
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shot.start_time_offset,
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shot.end_time_offset))
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# [END parse_response]
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if __name__ == '__main__':
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# [START running_app]
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parser = argparse.ArgumentParser(
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description=__doc__,
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formatter_class=argparse.RawDescriptionHelpFormatter)
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parser.add_argument('path', help='GCS file path for label detection.')
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args = parser.parse_args()
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analyze_shots(args.path)
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# [END running_app]
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# [END full_tutorial]

‎video/cloud-client/shotchange/shotchange_test.py

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#!/usr/bin/env python
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# Copyright 2017 Google, Inc
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
12+
# distributed under the License is distributed on an "AS IS" BASIS,
13+
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import os
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import pytest
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import shotchange
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BUCKET = os.environ['CLOUD_STORAGE_BUCKET']
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SHOTS_FILE_PATH = '/video/gbikes_dinosaur.mp4'
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@pytest.mark.slow
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def test_shots_dino(capsys):
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shotchange.analyze_shots(
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'gs://{}{}'.format(BUCKET, SHOTS_FILE_PATH))
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out, _ = capsys.readouterr()
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assert 'Scene 1:' in out

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