Adds tutorials using Cloud Client

video/cloud-client/analyze.py → video/cloud-client/analyze/analyze.py

@@ -77,7 +77,7 @@ def analyze_labels(path):
     # first result is retrieved because a single video was processed
     results = operation.result().annotation_results[0]
 
-    for i, label in enumerate(results.label_annotations):
+    for label in results.label_annotations:
         print('Label description: {}'.format(label.description))
         print('Locations:')
 

video/cloud-client/labels/README.md

@@ -0,0 +1,29 @@
+# Google Cloud Video Intelligence
+
+Demonstrates label detection using the Google Cloud Video Intelligence API.
+
+## Setup
+Please follow the [Set Up Your Project](https://cloud.google.com/video-intelligence/docs/getting-started#set_up_your_project)
+steps in the Quickstart doc to create a project and enable the Google Cloud
+Video Intelligence API. Following those steps, make sure that you
+[Set Up a Service Account](https://cloud.google.com/video-intelligence/docs/common/auth#set_up_a_service_account),
+and export the following environment variable:
+
+```
+export GOOGLE_APPLICATION_CREDENTIALS=/path/to/your-project-credentials.json
+```
+
+## Run the sample
+
+Install [pip](https://pip.pypa.io/en/stable/installing) if not already installed.
+
+Install the necessary libraries using pip:
+
+```sh
+$ pip install -r requirements.txt
+```
+
+Run the sample, for example:
+```
+python labels.py gs://cloud-ml-sandbox/video/chicago.mp4
+```

video/cloud-client/labels/labels.py

@@ -0,0 +1,80 @@
+#!/usr/bin/env python
+
+# Copyright 2017 Google Inc. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""This application demonstrates how to perform basic operations with the
+Google Cloud Video Intelligence API.
+
+For more information, check out the documentation at
+https://cloud.google.com/videointelligence/docs.
+"""
+
+# [START full_tutorial]
+# [START imports]
+import argparse
+import sys
+import time
+
+from google.cloud.gapic.videointelligence.v1beta1 import enums
+from google.cloud.gapic.videointelligence.v1beta1 import (
+    video_intelligence_service_client)
+# [END imports]
+
+
+def analyze_labels(path):
+    """ Detects labels given a GCS path. """
+    # [START construct_request]
+    video_client = (video_intelligence_service_client.
+                    VideoIntelligenceServiceClient())
+    features = [enums.Feature.LABEL_DETECTION]
+    operation = video_client.annotate_video(path, features)
+    # [END construct_request]
+    print('\nProcessing video for label annotations:')
+
+    # [START check_operation]
+    while not operation.done():
+        sys.stdout.write('.')
+        sys.stdout.flush()
+        time.sleep(20)
+
+    print('\nFinished processing.')
+    # [END check_operation]
+
+    # [START parse_response]
+    results = operation.result().annotation_results[0]
+
+    for label in results.label_annotations:
+        print('Label description: {}'.format(label.description))
+        print('Locations:')
+
+        for l, location in enumerate(label.locations):
+            print('\t{}: {} to {}'.format(
+                l,
+                location.segment.start_time_offset,
+                location.segment.end_time_offset))
+    # [END parse_response]
+
+
+if __name__ == '__main__':
+    # [START running_app]
+    parser = argparse.ArgumentParser(
+        description=__doc__,
+        formatter_class=argparse.RawDescriptionHelpFormatter)
+    parser.add_argument('path', help='GCS file path for label detection.')
+    args = parser.parse_args()
+
+    analyze_labels(args.path)
+    # [END running_app]
+# [END full_tutorial]

video/cloud-client/labels/labels_test.py

@@ -0,0 +1,32 @@
+#!/usr/bin/env python
+
+# Copyright 2017 Google, Inc
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+
+import pytest
+
+import labels
+
+BUCKET = os.environ['CLOUD_STORAGE_BUCKET']
+LABELS_FILE_PATH = '/video/cat.mp4'
+
+
+@pytest.mark.slow
+def test_feline_video_labels(capsys):
+    labels.analyze_labels(
+        'gs://{}{}'.format(BUCKET, LABELS_FILE_PATH))
+    out, _ = capsys.readouterr()
+    assert 'Whiskers' in out

video/cloud-client/labels/requirements.txt

@@ -0,0 +1 @@
+https://storage.googleapis.com/videointelligence-alpha/videointelligence-python.zip

video/cloud-client/shotchange/README.md

@@ -0,0 +1,29 @@
+# Google Cloud Video Intelligence
+
+Demonstrates label detection using the Google Cloud Video Intelligence API.
+
+## Setup
+Please follow the [Set Up Your Project](https://cloud.google.com/video-intelligence/docs/getting-started#set_up_your_project)
+steps in the Quickstart doc to create a project and enable the Google Cloud
+Video Intelligence API. Following those steps, make sure that you
+[Set Up a Service Account](https://cloud.google.com/video-intelligence/docs/common/auth#set_up_a_service_account),
+and export the following environment variable:
+
+```
+export GOOGLE_APPLICATION_CREDENTIALS=/path/to/your-project-credentials.json
+```
+
+## Run the sample
+
+Install [pip](https://pip.pypa.io/en/stable/installing) if not already installed.
+
+Install the necessary libraries using pip:
+
+```sh
+$ pip install -r requirements.txt
+```
+
+Run the sample, for example:
+```
+python shotchange.py gs://cloudmleap/video/googlework.mp4
+```

video/cloud-client/shotchange/requirements.txt

@@ -0,0 +1 @@
+https://storage.googleapis.com/videointelligence-alpha/videointelligence-python.zip

video/cloud-client/shotchange/shotchange.py

@@ -0,0 +1,76 @@
+#!/usr/bin/env python
+
+# Copyright 2017 Google Inc. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""This application demonstrates how to perform basic operations with the
+Google Cloud Video Intelligence API.
+
+For more information, check out the documentation at
+https://cloud.google.com/videointelligence/docs.
+"""
+
+# [START full_tutorial]
+# [START imports]
+import argparse
+import sys
+import time
+
+from google.cloud.gapic.videointelligence.v1beta1 import enums
+from google.cloud.gapic.videointelligence.v1beta1 import (
+    video_intelligence_service_client)
+# [END imports]
+
+
+def analyze_shots(path):
+    """ Detects camera shot changes. """
+    # [START construct_request]
+    video_client = (video_intelligence_service_client.
+                    VideoIntelligenceServiceClient())
+    features = [enums.Feature.SHOT_CHANGE_DETECTION]
+    operation = video_client.annotate_video(path, features)
+    # [END construct_request]
+    print('\nProcessing video for shot change annotations:')
+
+    # [START check_operation]
+    while not operation.done():
+        sys.stdout.write('.')
+        sys.stdout.flush()
+        time.sleep(20)
+
+    print('\nFinished processing.')
+    # [END check_operation]
+
+    # [START parse_response]
+    shots = operation.result().annotation_results[0]
+
+    for note, shot in enumerate(shots.shot_annotations):
+        print('Scene {}: {} to {}'.format(
+            note,
+            shot.start_time_offset,
+            shot.end_time_offset))
+    # [END parse_response]
+
+
+if __name__ == '__main__':
+    # [START running_app]
+    parser = argparse.ArgumentParser(
+        description=__doc__,
+        formatter_class=argparse.RawDescriptionHelpFormatter)
+    parser.add_argument('path', help='GCS file path for label detection.')
+    args = parser.parse_args()
+
+    analyze_shots(args.path)
+    # [END running_app]
+# [END full_tutorial]

video/cloud-client/shotchange/shotchange_test.py

@@ -0,0 +1,32 @@
+#!/usr/bin/env python
+
+# Copyright 2017 Google, Inc
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+
+import pytest
+
+import shotchange
+
+BUCKET = os.environ['CLOUD_STORAGE_BUCKET']
+SHOTS_FILE_PATH = '/video/gbikes_dinosaur.mp4'
+
+
+@pytest.mark.slow
+def test_shots_dino(capsys):
+    shotchange.analyze_shots(
+        'gs://{}{}'.format(BUCKET, SHOTS_FILE_PATH))
+    out, _ = capsys.readouterr()
+    assert 'Scene 1:' in out