def get_image_labels_from_url(image_url, limit=DEFAULT_LIMIT):
"""
:param image_url: str URL
:param limit: int Max number of results to return
:return: list of `google.cloud.vision.entity.EntityAnnotation` instances
"""
image = Image(get_vision_client(), source_uri=image_url)
return image.detect_labels(limit=limit)
def get_image_labels_from_bytes(image_bytes, limit=DEFAULT_LIMIT):
"""
:param image_bytes: str image bytes
:param limit: int Max number of results to return
:return: list of `google.cloud.vision.entity.EntityAnnotation` instances
"""
image = Image(get_vision_client(), content=image_bytes)
return image.detect_labels(limit=limit)
def test_annotate_no_results(self):
from google.cloud.vision.feature import Feature
from google.cloud.vision.feature import FeatureTypes
from google.cloud.vision.image import Image
client = mock.Mock(spec_set=['_credentials'])
feature = Feature(FeatureTypes.LABEL_DETECTION, 5)
image_content = b'abc 1 2 3'
image = Image(client, content=image_content)
with mock.patch('google.cloud.vision._gax.image_annotator_client.'
'ImageAnnotatorClient'):
gax_api = self._make_one(client)
mock_response = {
'batch_annotate_images.return_value': mock.Mock(responses=[]),
}
gax_api._annotator_client = mock.Mock(
spec_set=['batch_annotate_images'], **mock_response)
with mock.patch('google.cloud.vision._gax.Annotations'):
images = ((image, [feature]), )
response = gax_api.annotate(images)
self.assertEqual(len(response), 0)
self.assertIsInstance(response, list)
gax_api._annotator_client.batch_annotate_images.assert_called()
def test_call_annotate_with_more_than_one_result(self):
from google.cloud.vision.feature import Feature
from google.cloud.vision.feature import FeatureTypes
from google.cloud.vision.image import Image
from google.cloud.vision.likelihood import Likelihood
from unit_tests._fixtures import MULTIPLE_RESPONSE
client = mock.Mock(spec_set=['_connection'])
feature = Feature(FeatureTypes.LABEL_DETECTION, 5)
image_content = b'abc 1 2 3'
image = Image(client, content=image_content)
http_api = self._make_one(client)
http_api._connection = mock.Mock(spec_set=['api_request'])
http_api._connection.api_request.return_value = MULTIPLE_RESPONSE
images = ((image, [feature]), )
responses = http_api.annotate(images)
self.assertEqual(len(responses), 2)
image_one = responses[0]
image_two = responses[1]
self.assertEqual(len(image_one.labels), 3)
self.assertIsInstance(image_one.safe_searches, tuple)
self.assertEqual(image_two.safe_searches.adult,
Likelihood.VERY_UNLIKELY)
self.assertEqual(len(image_two.labels), 0)
def annotate(self, image, features):
"""Annotate an image to discover it's attributes.
:type image: str
:param image: A string which can be a URL, a Google Cloud Storage path,
or a byte stream of the image.
:type features: list of :class:`google.cloud.vision.feature.Feature`
:param features: The type of detection that the Vision API should
use to determine image attributes. Pricing is
based on the number of Feature Types.
See: https://cloud.google.com/vision/docs/pricing
:rtype: dict
:returns: List of annotations.
"""
img = Image(image, self)
request = VisionRequest(img, features)
data = {'requests': [request.as_dict()]}
response = self.connection.api_request(method='POST',
path='/images:annotate',
data=data)
return response['responses'][0]
def test_call_vision_request_with_list_bad_features(self):
from google.cloud.vision.image import Image
client = object()
image = Image(client, content=IMAGE_CONTENT)
with self.assertRaises(TypeError):
self._call_fut(image, ['nonsensefeature'])
def test_annotation(self):
from google.cloud.vision.feature import Feature
from google.cloud.vision.feature import FeatureTypes
from google.cloud.vision.image import Image
client = mock.Mock(spec_set=['_credentials'])
feature = Feature(FeatureTypes.LABEL_DETECTION, 5)
image_content = b'abc 1 2 3'
image = Image(client, content=image_content)
with mock.patch('google.cloud.vision._gax.image_annotator_client.'
'ImageAnnotatorClient'):
gax_api = self._make_one(client)
mock_response = {
'batch_annotate_images.return_value':
mock.Mock(responses=['mock response data']),
}
gax_api._annotator_client = mock.Mock(
spec_set=['batch_annotate_images'], **mock_response)
with mock.patch('google.cloud.vision._gax.Annotations') as mock_anno:
images = ((image, [feature]), )
gax_api.annotate(images)
mock_anno.from_pb.assert_called_with('mock response data')
gax_api._annotator_client.batch_annotate_images.assert_called()
def test_annotate_multiple_results(self):
from google.cloud.vision_v1.proto import image_annotator_pb2
from google.cloud.vision.annotations import Annotations
from google.cloud.vision.feature import Feature
from google.cloud.vision.feature import FeatureTypes
from google.cloud.vision.image import Image
client = mock.Mock(spec_set=['_credentials'])
feature = Feature(FeatureTypes.LABEL_DETECTION, 5)
image_content = b'abc 1 2 3'
image = Image(client, content=image_content)
with mock.patch('google.cloud.vision._gax.image_annotator_client.'
'ImageAnnotatorClient'):
gax_api = self._make_one(client)
responses = [
image_annotator_pb2.AnnotateImageResponse(),
image_annotator_pb2.AnnotateImageResponse(),
]
response = image_annotator_pb2.BatchAnnotateImagesResponse(
responses=responses)
gax_api._annotator_client = mock.Mock(
spec_set=['batch_annotate_images'])
gax_api._annotator_client.batch_annotate_images.return_value = response
images = ((image, [feature]), )
responses = gax_api.annotate(images)
self.assertEqual(len(responses), 2)
self.assertIsInstance(responses[0], Annotations)
self.assertIsInstance(responses[1], Annotations)
gax_api._annotator_client.batch_annotate_images.assert_called()
def test__to_gapic_invalid_image_uri(self):
from google.cloud.vision.image import Image
image_uri = 'ftp://1234/34.jpg'
client = object()
image = Image(client, source_uri=image_uri)
with self.assertRaises(ValueError):
self._call_fut(image)
def test__to_gapic_image_uri(self):
from google.cloud.vision.image import Image
from google.cloud.vision_v1.proto import image_annotator_pb2
image_uri = 'http://1234/34.jpg'
client = object()
image = Image(client, source_uri=image_uri)
image_pb = self._call_fut(image)
self.assertIsInstance(image_pb, image_annotator_pb2.Image)
self.assertEqual(image_pb.source.image_uri, image_uri)
def test__to_gapic_image_content(self):
from google.cloud.vision.image import Image
from google.cloud.vision_v1.proto import image_annotator_pb2
image_content = b'abc 1 2 3'
client = object()
image = Image(client, content=image_content)
image_pb = self._call_fut(image)
self.assertIsInstance(image_pb, image_annotator_pb2.Image)
self.assertEqual(image_pb.content, image_content)
def test__to_gapic_image_content(self):
import base64
from google.cloud.vision.image import Image
from google.cloud.grpc.vision.v1 import image_annotator_pb2
image_content = b'abc 1 2 3'
b64_content = base64.b64encode(image_content)
client = object()
image = Image(client, content=image_content)
image_pb = self._call_fut(image)
self.assertIsInstance(image_pb, image_annotator_pb2.Image)
self.assertEqual(image_pb.content, b64_content)
def image(self, content=None, source_uri=None):
"""Get instance of Image using current client.
:type content: bytes
:param content: Byte stream of an image.
:type source_uri: str
:param source_uri: Google Cloud Storage URI of image.
:rtype: :class:`~google.cloud.vision.image.Image`
:returns: Image instance with the current client attached.
"""
return Image(client=self, content=content, source_uri=source_uri)
def test_call_annotate_with_no_results(self):
from google.cloud.vision.feature import Feature
from google.cloud.vision.feature import FeatureTypes
from google.cloud.vision.image import Image
client = mock.Mock(spec_set=['_connection'])
feature = Feature(FeatureTypes.LABEL_DETECTION, 5)
image_content = b'abc 1 2 3'
image = Image(client, content=image_content)
http_api = self._make_one(client)
http_api._connection = mock.Mock(spec_set=['api_request'])
http_api._connection.api_request.return_value = {'responses': []}
self.assertIsNone(http_api.annotate(image, [feature]))
def test_call_vision_request(self):
from google.cloud.vision.feature import Feature
from google.cloud.vision.feature import FeatureTypes
from google.cloud.vision.image import Image
client = object()
image = Image(client, content=IMAGE_CONTENT)
feature = Feature(feature_type=FeatureTypes.FACE_DETECTION,
max_results=3)
request = self._call_fut(image, feature)
self.assertEqual(request['image'].get('content'), B64_IMAGE_CONTENT)
features = request['features']
self.assertEqual(len(features), 1)
feature = features[0]
self.assertEqual(feature['type'], FeatureTypes.FACE_DETECTION)
self.assertEqual(feature['maxResults'], 3)
def test_ctor(self):
from google.cloud.vision.feature import Feature
from google.cloud.vision.feature import FeatureTypes
from google.cloud.vision.image import Image
client = mock.Mock(spec=[])
image = Image(client, source_uri='gs://images/imageone.jpg')
face_feature = Feature(FeatureTypes.FACE_DETECTION, 5)
logo_feature = Feature(FeatureTypes.LOGO_DETECTION, 3)
batch = self._make_one(client)
batch.add_image(image, [logo_feature, face_feature])
self.assertEqual(len(batch.images), 1)
self.assertEqual(len(batch.images[0]), 2)
self.assertIsInstance(batch.images[0][0], Image)
self.assertEqual(len(batch.images[0][1]), 2)
self.assertIsInstance(batch.images[0][1][0], Feature)
self.assertIsInstance(batch.images[0][1][1], Feature)
def test_annotate_multiple_results(self):
from google.cloud.vision.feature import Feature
from google.cloud.vision.feature import FeatureTypes
from google.cloud.vision.image import Image
client = mock.Mock(spec_set=[])
feature = Feature(FeatureTypes.LABEL_DETECTION, 5)
image_content = b'abc 1 2 3'
image = Image(client, content=image_content)
with mock.patch('google.cloud.vision._gax.image_annotator_client.'
'ImageAnnotatorClient'):
gax_api = self._make_one(client)
mock_response = {
'batch_annotate_images.return_value': mock.Mock(responses=[1, 2]),
}
gax_api._annotator_client = mock.Mock(
spec_set=['batch_annotate_images'], **mock_response)
with mock.patch('google.cloud.vision._gax.Annotations'):
with self.assertRaises(NotImplementedError):
gax_api.annotate(image, [feature])
gax_api._annotator_client.batch_annotate_images.assert_called()
features.append(
Feature(feature_type=FeatureTypes.SAFE_SEARCH_DETECTION,
max_results=limit))
features.append(
Feature(feature_type=FeatureTypes.LOGO_DETECTION,
max_results=limit))
features.append(
Feature(feature_type=FeatureTypes.DOCUMENT_TEXT_DETECTION,
max_results=limit))
imagebatch = images[start:start + imagesperbatch]
for image in imagebatch:
path = image[1]
if path is None:
continue
if 'http' in path or path.startswith('gs:'):
image = Image(source_uri=path, client=client)
vision_client.add_image(image=image, features=features)
else:
with io.open(path, 'rb') as image_file:
content = image_file.read()
image = Image(content=content, client=client)
vision_client.add_image(image=image, features=features)
count = 0
results = vision_client.detect()
for image in imagebatch:
if image[1] is None:
imgfeats[image[0]] = None
continue
# print 'Extracting for',count+1
