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Move vision api labelling sample. #365

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3 changes: 3 additions & 0 deletions vision/api/label/README.md
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Python label detection [Vision API](https://cloud.google.com/vision/) example.
See the [tutorial](https://cloud.google.com/vision/docs/label-tutorial).

77 changes: 77 additions & 0 deletions vision/api/label/label.py
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#!/usr/bin/env python
# Copyright 2015 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 script uses the Vision API's label detection capabilities to find a label
based on an image's content.
To run the example, install the necessary libraries by running:
pip install -r requirements.txt
Run the script on an image to get a label, E.g.:
./label.py <path-to-image>
"""

# [START import_libraries]
import argparse
import base64

from googleapiclient import discovery
from oauth2client.client import GoogleCredentials

# The url template to retrieve the discovery document for trusted testers.
DISCOVERY_URL = 'https://{api}.googleapis.com/$discovery/rest?version={apiVersion}' # noqa
# [END import_libraries]


def main(photo_file):
"""Run a label request on a single image"""

# [START authenticate]
credentials = GoogleCredentials.get_application_default()
service = discovery.build('vision', 'v1', credentials=credentials,
discoveryServiceUrl=DISCOVERY_URL)
# [END authenticate]

# [START construct_request]
with open(photo_file, 'rb') as image:
image_content = base64.b64encode(image.read())
service_request = service.images().annotate(body={
'requests': [{
'image': {
'content': image_content.decode('UTF-8')
},
'features': [{
'type': 'LABEL_DETECTION',
'maxResults': 1
}]
}]
})
# [END construct_request]
# [START parse_response]
response = service_request.execute()
label = response['responses'][0]['labelAnnotations'][0]['description']
print('Found label: %s for %s' % (label, photo_file))
# [END parse_response]

# [START run_application]
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('image_file', help='The image you\'d like to label.')
args = parser.parse_args()
main(args.image_file)
# [END run_application]
25 changes: 25 additions & 0 deletions vision/api/label/label_test.py
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# Copyright 2016, 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 re

from label import main


def test_main(resource, capsys):
in_file = resource('cat.jpg')
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great pic!


main(in_file)

stdout, _ = capsys.readouterr()
assert re.match(r'Found label:.*cat', stdout)
1 change: 1 addition & 0 deletions vision/api/label/requirements.txt
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google-api-python-client==1.5.1
Binary file added vision/api/label/resources/cat.jpg
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