GoogleCloudPlatform
diff --git a/‎videointelligence/samples/labels/README.rst
Lines changed: 135 additions & 0 deletions b/‎videointelligence/samples/labels/README.rst
Lines changed: 135 additions & 0 deletions
diff --git a/‎videointelligence/samples/labels/README.rst.in
Lines changed: 22 additions & 0 deletions b/‎videointelligence/samples/labels/README.rst.in
Lines changed: 22 additions & 0 deletions
diff --git a/‎videointelligence/samples/labels/labels.py
Lines changed: 84 additions & 0 deletions b/‎videointelligence/samples/labels/labels.py
Lines changed: 84 additions & 0 deletions
diff --git a/‎videointelligence/samples/labels/labels_test.py
Lines changed: 26 additions & 0 deletions b/‎videointelligence/samples/labels/labels_test.py
Lines changed: 26 additions & 0 deletions
@@ -0,0 +1,135 @@
+
+.. This file is automatically generated. Do not edit this file directly.
+
+Google Cloud Video Intelligence API Python Samples
+===============================================================================
+
+.. image:: https://gstatic.com/cloudssh/images/open-btn.png
+   :target: https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/GoogleCloudPlatform/python-docs-samples&page=editor&open_in_editor=video/cloud-client/labels/README.rst
+
+
+This directory contains samples for Google Cloud Video Intelligence API. `Google Cloud Video Intelligence API`_ allows developers to easily integrate feature detection in video.
+
+
+
+
+.. _Google Cloud Video Intelligence API: https://cloud.google.com/video-intelligence/docs
+
+
+Setup
+-------------------------------------------------------------------------------
+
+
+
+Authentication
+++++++++++++++
+
+This sample requires you to have authentication setup. Refer to the
+`Authentication Getting Started Guide`_ for instructions on setting up
+credentials for applications.
+
+.. _Authentication Getting Started Guide:
+    https://cloud.google.com/docs/authentication/getting-started
+
+
+
+
+Install Dependencies
+++++++++++++++++++++
+
+#. Clone python-docs-samples and change directory to the sample directory you want to use.
+
+    .. code-block:: bash
+
+        $ git clone https://github.com/GoogleCloudPlatform/python-docs-samples.git
+
+#. Install `pip`_ and `virtualenv`_ if you do not already have them. You may want to refer to the `Python Development Environment Setup Guide`_ for Google Cloud Platform for instructions.
+
+   .. _Python Development Environment Setup Guide:
+       https://cloud.google.com/python/setup
+
+#. Create a virtualenv. Samples are compatible with Python 3.6+.
+
+    .. code-block:: bash
+
+        $ virtualenv env
+        $ source env/bin/activate
+
+#. Install the dependencies needed to run the samples.
+
+    .. code-block:: bash
+
+        $ pip install -r requirements.txt
+
+.. _pip: https://pip.pypa.io/
+.. _virtualenv: https://virtualenv.pypa.io/
+
+
+
+
+
+
+Samples
+-------------------------------------------------------------------------------
+
+
+labels
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+
+.. image:: https://gstatic.com/cloudssh/images/open-btn.png
+   :target: https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/GoogleCloudPlatform/python-docs-samples&page=editor&open_in_editor=video/cloud-client/labels/labels.py,video/cloud-client/labels/README.rst
+
+
+
+
+To run this sample:
+
+.. code-block:: bash
+
+    $ python labels.py
+
+
+    usage: labels.py [-h] path
+
+    This application demonstrates how to detect labels from a video
+    based on the image content with the Google Cloud Video Intelligence
+    API.
+
+    For more information, check out the documentation at
+    https://cloud.google.com/videointelligence/docs.
+
+    Usage Example:
+
+        python labels.py gs://cloud-ml-sandbox/video/chicago.mp4
+
+    positional arguments:
+      path        GCS file path for label detection.
+
+    optional arguments:
+      -h, --help  show this help message and exit
+
+
+
+
+
+
+
+
+
+The client library
+-------------------------------------------------------------------------------
+
+This sample uses the `Google Cloud Client Library for Python`_.
+You can read the documentation for more details on API usage and use GitHub
+to `browse the source`_ and  `report issues`_.
+
+.. _Google Cloud Client Library for Python:
+    https://googlecloudplatform.github.io/google-cloud-python/
+.. _browse the source:
+    https://github.com/GoogleCloudPlatform/google-cloud-python
+.. _report issues:
+    https://github.com/GoogleCloudPlatform/google-cloud-python/issues
+
+
+
+.. _Google Cloud SDK: https://cloud.google.com/sdk/
@@ -0,0 +1,22 @@
+# This file is used to generate README.rst
+
+product:
+  name: Google Cloud Video Intelligence API
+  short_name: Cloud Video Intelligence API
+  url: https://cloud.google.com/video-intelligence/docs
+  description: >
+    `Google Cloud Video Intelligence API`_ allows developers to easily
+    integrate feature detection in video.
+
+setup:
+- auth
+- install_deps
+
+samples:
+- name: labels
+  file: labels.py
+  show_help: True
+
+cloud_client_library: true
+
+folder: video/cloud-client/labels
@@ -0,0 +1,84 @@
+#!/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 detect labels from a video
+based on the image content with the Google Cloud Video Intelligence
+API.
+
+For more information, check out the documentation at
+https://cloud.google.com/videointelligence/docs.
+
+Usage Example:
+
+    python labels.py gs://cloud-ml-sandbox/video/chicago.mp4
+
+"""
+
+# [START video_label_tutorial]
+# [START video_label_tutorial_imports]
+import argparse
+
+from google.cloud import videointelligence
+# [END video_label_tutorial_imports]
+
+
+def analyze_labels(path):
+    """ Detects labels given a GCS path. """
+    # [START video_label_tutorial_construct_request]
+    video_client = videointelligence.VideoIntelligenceServiceClient()
+    features = [videointelligence.enums.Feature.LABEL_DETECTION]
+    operation = video_client.annotate_video(input_uri=path, features=features)
+    # [END video_label_tutorial_construct_request]
+    print('\nProcessing video for label annotations:')
+
+    # [START video_label_tutorial_check_operation]
+    result = operation.result(timeout=90)
+    print('\nFinished processing.')
+    # [END video_label_tutorial_check_operation]
+
+    # [START video_label_tutorial_parse_response]
+    segment_labels = result.annotation_results[0].segment_label_annotations
+    for i, segment_label in enumerate(segment_labels):
+        print('Video label description: {}'.format(
+            segment_label.entity.description))
+        for category_entity in segment_label.category_entities:
+            print('\tLabel category description: {}'.format(
+                category_entity.description))
+
+        for i, segment in enumerate(segment_label.segments):
+            start_time = (segment.segment.start_time_offset.seconds +
+                          segment.segment.start_time_offset.nanos / 1e9)
+            end_time = (segment.segment.end_time_offset.seconds +
+                        segment.segment.end_time_offset.nanos / 1e9)
+            positions = '{}s to {}s'.format(start_time, end_time)
+            confidence = segment.confidence
+            print('\tSegment {}: {}'.format(i, positions))
+            print('\tConfidence: {}'.format(confidence))
+        print('\n')
+    # [END video_label_tutorial_parse_response]
+
+
+if __name__ == '__main__':
+    # [START video_label_tutorial_run_application]
+    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 video_label_tutorial_run_application]
+# [END video_label_tutorial]
@@ -0,0 +1,26 @@
+#!/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 pytest
+
+import labels
+
+
+@pytest.mark.slow
+def test_feline_video_labels(capsys):
+    labels.analyze_labels('gs://cloud-samples-data/video/cat.mp4')
+    out, _ = capsys.readouterr()
+    assert 'Video label description: cat' in out