Vision support for batch processing part one. (#2967)

* Vision support for batch processing part one.

vision/google/cloud/vision/_gax.py

@@ -39,21 +39,18 @@ def annotate(self, image, features):
         :type features: list
         :param features: List of :class:`~google.cloud.vision.feature.Feature`.
 
-        :rtype: :class:`~google.cloud.vision.annotations.Annotations`
-        :returns: Instance of ``Annotations`` with results or ``None``.
+        :rtype: list
+        :returns: List of
+                  :class:`~google.cloud.vision.annotations.Annotations`.
         """
         gapic_features = [_to_gapic_feature(feature) for feature in features]
         gapic_image = _to_gapic_image(image)
         request = image_annotator_pb2.AnnotateImageRequest(
             image=gapic_image, features=gapic_features)
         requests = [request]
         annotator_client = self._annotator_client
-        images = annotator_client.batch_annotate_images(requests)
-        if len(images.responses) == 1:
-            return Annotations.from_pb(images.responses[0])
-        elif len(images.responses) > 1:
-            raise NotImplementedError(
-                'Multiple image processing is not yet supported.')
+        responses = annotator_client.batch_annotate_images(requests).responses
+        return [Annotations.from_pb(response) for response in responses]
 
 
 def _to_gapic_feature(feature):

vision/google/cloud/vision/_http.py

@@ -41,20 +41,16 @@ def annotate(self, image, features):
                          based on the number of Feature Types.
 
                          See: https://cloud.google.com/vision/docs/pricing
-        :rtype: dict
-        :returns: List of annotations.
+        :rtype: list
+        :returns: List of :class:`~googe.cloud.vision.annotations.Annotations`.
         """
         request = _make_request(image, features)
 
         data = {'requests': [request]}
         api_response = self._connection.api_request(
             method='POST', path='/images:annotate', data=data)
-        images = api_response.get('responses')
-        if len(images) == 1:
-            return Annotations.from_api_repr(images[0])
-        elif len(images) > 1:
-            raise NotImplementedError(
-                'Multiple image processing is not yet supported.')
+        responses = api_response.get('responses')
+        return [Annotations.from_api_repr(response) for response in responses]
 
 
 def _make_request(image, features):

vision/google/cloud/vision/image.py

@@ -134,7 +134,7 @@ def detect_faces(self, limit=10):
         """
         features = [Feature(FeatureTypes.FACE_DETECTION, limit)]
         annotations = self._detect_annotation(features)
-        return annotations.faces
+        return annotations[0].faces
 
     def detect_labels(self, limit=10):
         """Detect labels that describe objects in an image.
@@ -147,7 +147,7 @@ def detect_labels(self, limit=10):
         """
         features = [Feature(FeatureTypes.LABEL_DETECTION, limit)]
         annotations = self._detect_annotation(features)
-        return annotations.labels
+        return annotations[0].labels
 
     def detect_landmarks(self, limit=10):
         """Detect landmarks in an image.
@@ -161,7 +161,7 @@ def detect_landmarks(self, limit=10):
         """
         features = [Feature(FeatureTypes.LANDMARK_DETECTION, limit)]
         annotations = self._detect_annotation(features)
-        return annotations.landmarks
+        return annotations[0].landmarks
 
     def detect_logos(self, limit=10):
         """Detect logos in an image.
@@ -175,7 +175,7 @@ def detect_logos(self, limit=10):
         """
         features = [Feature(FeatureTypes.LOGO_DETECTION, limit)]
         annotations = self._detect_annotation(features)
-        return annotations.logos
+        return annotations[0].logos
 
     def detect_properties(self, limit=10):
         """Detect the color properties of an image.
@@ -189,7 +189,7 @@ def detect_properties(self, limit=10):
         """
         features = [Feature(FeatureTypes.IMAGE_PROPERTIES, limit)]
         annotations = self._detect_annotation(features)
-        return annotations.properties
+        return annotations[0].properties
 
     def detect_safe_search(self, limit=10):
         """Retreive safe search properties from an image.
@@ -203,7 +203,7 @@ def detect_safe_search(self, limit=10):
         """
         features = [Feature(FeatureTypes.SAFE_SEARCH_DETECTION, limit)]
         annotations = self._detect_annotation(features)
-        return annotations.safe_searches
+        return annotations[0].safe_searches
 
     def detect_text(self, limit=10):
         """Detect text in an image.
@@ -217,4 +217,4 @@ def detect_text(self, limit=10):
         """
         features = [Feature(FeatureTypes.TEXT_DETECTION, limit)]
         annotations = self._detect_annotation(features)
-        return annotations.texts
+        return annotations[0].texts

vision/unit_tests/_fixtures.py

@@ -1688,6 +1688,39 @@
 }
 
 
+MULTIPLE_RESPONSE = {
+    'responses': [
+        {
+            'labelAnnotations': [
+                {
+                    'mid': '/m/0k4j',
+                    'description': 'automobile',
+                    'score': 0.9776855
+                },
+                {
+                    'mid': '/m/07yv9',
+                    'description': 'vehicle',
+                    'score': 0.947987
+                },
+                {
+                    'mid': '/m/07r04',
+                    'description': 'truck',
+                    'score': 0.88429511
+                },
+            ],
+        },
+        {
+            'safeSearchAnnotation': {
+                'adult': 'VERY_UNLIKELY',
+                'spoof': 'UNLIKELY',
+                'medical': 'POSSIBLE',
+                'violence': 'VERY_UNLIKELY'
+            },
+        },
+    ],
+}
+
+
 SAFE_SEARCH_DETECTION_RESPONSE = {
     'responses': [
         {

vision/unit_tests/test__gax.py

@@ -78,11 +78,15 @@ def test_annotate_no_results(self):
         gax_api._annotator_client = mock.Mock(
             spec_set=['batch_annotate_images'], **mock_response)
         with mock.patch('google.cloud.vision._gax.Annotations'):
-            self.assertIsNone(gax_api.annotate(image, [feature]))
+            response = gax_api.annotate(image, [feature])
+        self.assertEqual(len(response), 0)
+        self.assertIsInstance(response, list)
 
         gax_api._annotator_client.batch_annotate_images.assert_called()
 
     def test_annotate_multiple_results(self):
+        from google.cloud.grpc.vision.v1 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
@@ -95,16 +99,21 @@ def test_annotate_multiple_results(self):
                         'ImageAnnotatorClient'):
             gax_api = self._make_one(client)
 
-        mock_response = {
-            'batch_annotate_images.return_value': mock.Mock(responses=[1, 2]),
-        }
+        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'], **mock_response)
-        with mock.patch('google.cloud.vision._gax.Annotations'):
-            with self.assertRaises(NotImplementedError):
-                gax_api.annotate(image, [feature])
+            spec_set=['batch_annotate_images'])
+        gax_api._annotator_client.batch_annotate_images.return_value = response
+        responses = gax_api.annotate(image, [feature])
 
+        self.assertEqual(len(responses), 2)
+        self.assertIsInstance(responses[0], Annotations)
+        self.assertIsInstance(responses[1], Annotations)
         gax_api._annotator_client.batch_annotate_images.assert_called()
 
 

vision/unit_tests/test__http.py

@@ -44,12 +44,16 @@ def test_call_annotate_with_no_results(self):
         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]))
+        response = http_api.annotate(image, [feature])
+        self.assertEqual(len(response), 0)
+        self.assertIsInstance(response, list)
 
     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)
@@ -58,9 +62,17 @@ def test_call_annotate_with_more_than_one_result(self):
 
         http_api = self._make_one(client)
         http_api._connection = mock.Mock(spec_set=['api_request'])
-        http_api._connection.api_request.return_value = {'responses': [1, 2]}
-        with self.assertRaises(NotImplementedError):
-            http_api.annotate(image, [feature])
+        http_api._connection.api_request.return_value = MULTIPLE_RESPONSE
+        responses = http_api.annotate(image, [feature])
+
+        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)
 
 
 class TestVisionRequest(unittest.TestCase):

vision/unit_tests/test_client.py

@@ -104,8 +104,10 @@ def test_face_annotation(self):
         features = [Feature(feature_type=FeatureTypes.FACE_DETECTION,
                             max_results=3)]
         image = client.image(content=IMAGE_CONTENT)
-        response = client._vision_api.annotate(image, features)
+        api_response = client._vision_api.annotate(image, features)
 
+        self.assertEqual(len(api_response), 1)
+        response = api_response[0]
         self.assertEqual(REQUEST,
                          client._connection._requested[0]['data'])
         self.assertIsInstance(response, Annotations)
@@ -166,8 +168,10 @@ def test_multiple_detection_from_content(self):
         logo_feature = Feature(FeatureTypes.LOGO_DETECTION, limit)
         features = [label_feature, logo_feature]
         image = client.image(content=IMAGE_CONTENT)
-        items = image.detect(features)
+        detected_items = image.detect(features)
 
+        self.assertEqual(len(detected_items), 1)
+        items = detected_items[0]
         self.assertEqual(len(items.logos), 2)
         self.assertEqual(len(items.labels), 3)
         first_logo = items.logos[0]