video: add auto-generated Logo Recognition Samples [(#2755)](GoogleCl…

…oudPlatform/python-docs-samples#2755)

* Add auto-generated Logo Recognition Samples

* Add tests

Remove boilerplate
Update copyright date
Blacken
Remove unused imports
Shorten docstrings
Remove CLI
Set defaults in function definition

* Edit test video to 3 seconds from 35

Reduce quota usage to allow for parallel tests
Retain longer version only for tests that require it

* Fix bug

Co-authored-by: Noah Negrey <[email protected]>
Co-authored-by: Leah E. Cole <[email protected]>

samples/analyze/README.rst

@@ -123,8 +123,8 @@ To run this sample:
     Google Cloud API.
 
     Usage Examples:
-        python beta_snippets.py transcription         gs://python-docs-samples-tests/video/googlework_short.mp4
-        python beta_snippets.py video-text-gcs         gs://python-docs-samples-tests/video/googlework_short.mp4
+        python beta_snippets.py transcription gs://python-docs-samples-tests/video/googlework_tiny.mp4
+        python beta_snippets.py video-text-gcs gs://python-docs-samples-tests/video/googlework_tiny.mp4
         python beta_snippets.py track-objects /resources/cat.mp4
 
     positional arguments:

samples/analyze/analyze.py

@@ -25,8 +25,8 @@
     python analyze.py explicit_content \
     gs://cloud-samples-data/video/gbikes_dinosaur.mp4
     python analyze.py text_gcs \
-    gs://cloud-samples-data/video/googlework_short.mp4
-    python analyze.py text_file resources/googlework_short.mp4
+    gs://cloud-samples-data/video/googlework_tiny.mp4
+    python analyze.py text_file resources/googlework_tiny.mp4
     python analyze.py objects_gcs gs://cloud-samples-data/video/cat.mp4
     python analyze.py objects_file resources/cat.mp4
 """

samples/analyze/analyze_test.py

@@ -18,6 +18,9 @@
 
 import analyze
 
+POSSIBLE_TEXTS = ['Google', 'SUR', 'SUR', 'ROTO', 'Vice President', '58oo9',
+                  'LONDRES', 'OMAR', 'PARIS', 'METRO', 'RUE', 'CARLO']
+
 
 @pytest.mark.slow
 def test_analyze_shots(capsys):
@@ -51,9 +54,15 @@ def test_speech_transcription(capsys):
 @pytest.mark.slow
 def test_detect_text_gcs(capsys):
     analyze.video_detect_text_gcs(
-        'gs://cloud-samples-data/video/googlework_short.mp4')
+        'gs://cloud-samples-data/video/googlework_tiny.mp4')
     out, _ = capsys.readouterr()
-    assert 'GOOGLE' in out
+
+    text_exists = False
+    out_upper = out.upper()
+    for possible_text in POSSIBLE_TEXTS:
+        if possible_text.upper() in out_upper:
+            text_exists = True
+    assert text_exists
 
 
 @pytest.mark.slow

samples/analyze/beta_snippets.py

@@ -19,10 +19,10 @@
 
 Usage Examples:
     python beta_snippets.py transcription \
-        gs://python-docs-samples-tests/video/googlework_short.mp4
+        gs://python-docs-samples-tests/video/googlework_tiny.mp4
 
     python beta_snippets.py video-text-gcs \
-        gs://python-docs-samples-tests/video/googlework_short.mp4
+        gs://python-docs-samples-tests/video/googlework_tiny.mp4
 
     python beta_snippets.py track-objects resources/cat.mp4
 

samples/analyze/beta_snippets_test.py

@@ -111,7 +111,7 @@ def test_annotation_to_storage_streaming(capsys, video_path, bucket):
 
 @pytest.mark.slow
 def test_detect_text():
-    in_file = './resources/googlework_short.mp4'
+    in_file = './resources/googlework_tiny.mp4'
     text_annotations = beta_snippets.video_detect_text(in_file)
 
     text_exists = False
@@ -124,7 +124,7 @@ def test_detect_text():
 
 @pytest.mark.slow
 def test_detect_text_gcs():
-    in_file = 'gs://python-docs-samples-tests/video/googlework_short.mp4'
+    in_file = 'gs://python-docs-samples-tests/video/googlework_tiny.mp4'
     text_annotations = beta_snippets.video_detect_text_gcs(in_file)
 
     text_exists = False

samples/analyze/video_detect_logo_beta.py

@@ -0,0 +1,107 @@
+# Copyright 2020 Google LLC
+#
+# 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
+#
+#     https://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 io
+
+# [START video_detect_logo_beta]
+
+from google.cloud import videointelligence_v1p3beta1
+from google.cloud.videointelligence_v1p3beta1 import enums
+
+
+def sample_annotate_video(local_file_path="resources/googlework_tiny.mp4"):
+    """Performs asynchronous video annotation for logo recognition on a local file."""
+
+    client = videointelligence_v1p3beta1.VideoIntelligenceServiceClient()
+
+    with io.open(local_file_path, "rb") as f:
+        input_content = f.read()
+    features_element = enums.Feature.LOGO_RECOGNITION
+    features = [features_element]
+
+    operation = client.annotate_video(input_content=input_content, features=features)
+
+    print(u"Waiting for operation to complete...")
+    response = operation.result()
+
+    # Get the first response, since we sent only one video.
+    annotation_result = response.annotation_results[0]
+    # Annotations for list of logos detected, tracked and recognized in video.
+    for logo_recognition_annotation in annotation_result.logo_recognition_annotations:
+        entity = logo_recognition_annotation.entity
+        # Opaque entity ID. Some IDs may be available in [Google Knowledge Graph
+        # Search API](https://developers.google.com/knowledge-graph/).
+        print(u"Entity Id : {}".format(entity.entity_id))
+        # Textual description, e.g. `Google`.
+        print(u"Description : {}".format(entity.description))
+        # All logo tracks where the recognized logo appears. Each track corresponds
+        # to one logo instance appearing in consecutive frames.
+        for track in logo_recognition_annotation.tracks:
+            # Video segment of a track.
+            segment = track.segment
+            segment_start_time_offset = segment.start_time_offset
+            print(
+                u"\n\tStart Time Offset : {}.{}".format(
+                    segment_start_time_offset.seconds, segment_start_time_offset.nanos
+                )
+            )
+            segment_end_time_offset = segment.end_time_offset
+            print(
+                u"\tEnd Time Offset : {}.{}".format(
+                    segment_end_time_offset.seconds, segment_end_time_offset.nanos
+                )
+            )
+            print(u"\tConfidence : {}".format(track.confidence))
+            # The object with timestamp and attributes per frame in the track.
+            for timestamped_object in track.timestamped_objects:
+                # Normalized Bounding box in a frame, where the object is located.
+                normalized_bounding_box = timestamped_object.normalized_bounding_box
+                print(u"\n\t\tLeft : {}".format(normalized_bounding_box.left))
+                print(u"\t\tTop : {}".format(normalized_bounding_box.top))
+                print(u"\t\tRight : {}".format(normalized_bounding_box.right))
+                print(u"\t\tBottom : {}".format(normalized_bounding_box.bottom))
+                # Optional. The attributes of the object in the bounding box.
+                for attribute in timestamped_object.attributes:
+                    print(u"\n\t\t\tName : {}".format(attribute.name))
+                    print(u"\t\t\tConfidence : {}".format(attribute.confidence))
+                    print(u"\t\t\tValue : {}".format(attribute.value))
+            # Optional. Attributes in the track level.
+            for track_attribute in track.attributes:
+                print(u"\n\t\tName : {}".format(track_attribute.name))
+                print(u"\t\tConfidence : {}".format(track_attribute.confidence))
+                print(u"\t\tValue : {}".format(track_attribute.value))
+        # All video segments where the recognized logo appears. There might be
+        # multiple instances of the same logo class appearing in one VideoSegment.
+        for logo_recognition_annotation_segment in logo_recognition_annotation.segments:
+            logo_recognition_annotation_segment_start_time_offset = (
+                logo_recognition_annotation_segment.start_time_offset
+            )
+            print(
+                u"\n\tStart Time Offset : {}.{}".format(
+                    logo_recognition_annotation_segment_start_time_offset.seconds,
+                    logo_recognition_annotation_segment_start_time_offset.nanos,
+                )
+            )
+            logo_recognition_annotation_segment_end_time_offset = (
+                logo_recognition_annotation_segment.end_time_offset
+            )
+            print(
+                u"\tEnd Time Offset : {}.{}".format(
+                    logo_recognition_annotation_segment_end_time_offset.seconds,
+                    logo_recognition_annotation_segment_end_time_offset.nanos,
+                )
+            )
+
+
+# [END video_detect_logo_beta]

samples/analyze/video_detect_logo_beta_test.py

@@ -0,0 +1,32 @@
+# Copyright 2020 Google
+#
+# 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 video_detect_logo_beta
+
+RESOURCES = os.path.join(os.path.dirname(__file__), "resources")
+
+
+def test_sample_annotate_video(capsys):
+    local_file_path = os.path.join(RESOURCES, "googlework_tiny.mp4")
+
+    video_detect_logo_beta.sample_annotate_video(local_file_path=local_file_path)
+
+    out, _ = capsys.readouterr()
+
+    assert "Description : Google Maps" in out
+    assert "Confidence" in out
+    assert "Start Time Offset" in out
+    assert "End Time Offset" in out

samples/analyze/video_detect_logo_gcs_beta.py

@@ -0,0 +1,104 @@
+# Copyright 2020 Google LLC
+#
+# 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
+#
+#     https://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.
+
+# [START video_detect_logo_gcs_beta]
+
+from google.cloud import videointelligence_v1p3beta1
+from google.cloud.videointelligence_v1p3beta1 import enums
+
+
+def sample_annotate_video(
+    input_uri="gs://cloud-samples-data/video/googlework_tiny.mp4",
+):
+
+    client = videointelligence_v1p3beta1.VideoIntelligenceServiceClient()
+
+    features_element = enums.Feature.LOGO_RECOGNITION
+    features = [features_element]
+
+    operation = client.annotate_video(input_uri=input_uri, features=features)
+
+    print(u"Waiting for operation to complete...")
+    response = operation.result()
+
+    # Get the first response, since we sent only one video.
+    annotation_result = response.annotation_results[0]
+    # Annotations for list of logos detected, tracked and recognized in video.
+    for logo_recognition_annotation in annotation_result.logo_recognition_annotations:
+        entity = logo_recognition_annotation.entity
+        # Opaque entity ID. Some IDs may be available in [Google Knowledge Graph
+        # Search API](https://developers.google.com/knowledge-graph/).
+        print(u"Entity Id : {}".format(entity.entity_id))
+        # Textual description, e.g. `Google`.
+        print(u"Description : {}".format(entity.description))
+        # All logo tracks where the recognized logo appears. Each track corresponds
+        # to one logo instance appearing in consecutive frames.
+        for track in logo_recognition_annotation.tracks:
+            # Video segment of a track.
+            segment = track.segment
+            segment_start_time_offset = segment.start_time_offset
+            print(
+                u"\n\tStart Time Offset : {}.{}".format(
+                    segment_start_time_offset.seconds, segment_start_time_offset.nanos
+                )
+            )
+            segment_end_time_offset = segment.end_time_offset
+            print(
+                u"\tEnd Time Offset : {}.{}".format(
+                    segment_end_time_offset.seconds, segment_end_time_offset.nanos
+                )
+            )
+            print(u"\tConfidence : {}".format(track.confidence))
+            # The object with timestamp and attributes per frame in the track.
+            for timestamped_object in track.timestamped_objects:
+                # Normalized Bounding box in a frame, where the object is located.
+                normalized_bounding_box = timestamped_object.normalized_bounding_box
+                print(u"\n\t\tLeft : {}".format(normalized_bounding_box.left))
+                print(u"\t\tTop : {}".format(normalized_bounding_box.top))
+                print(u"\t\tRight : {}".format(normalized_bounding_box.right))
+                print(u"\t\tBottom : {}".format(normalized_bounding_box.bottom))
+                # Optional. The attributes of the object in the bounding box.
+                for attribute in timestamped_object.attributes:
+                    print(u"\n\t\t\tName : {}".format(attribute.name))
+                    print(u"\t\t\tConfidence : {}".format(attribute.confidence))
+                    print(u"\t\t\tValue : {}".format(attribute.value))
+            # Optional. Attributes in the track level.
+            for track_attribute in track.attributes:
+                print(u"\n\t\tName : {}".format(track_attribute.name))
+                print(u"\t\tConfidence : {}".format(track_attribute.confidence))
+                print(u"\t\tValue : {}".format(track_attribute.value))
+        # All video segments where the recognized logo appears. There might be
+        # multiple instances of the same logo class appearing in one VideoSegment.
+        for logo_recognition_annotation_segment in logo_recognition_annotation.segments:
+            logo_recognition_annotation_segment_start_time_offset = (
+                logo_recognition_annotation_segment.start_time_offset
+            )
+            print(
+                u"\n\tStart Time Offset : {}.{}".format(
+                    logo_recognition_annotation_segment_start_time_offset.seconds,
+                    logo_recognition_annotation_segment_start_time_offset.nanos,
+                )
+            )
+            logo_recognition_annotation_segment_end_time_offset = (
+                logo_recognition_annotation_segment.end_time_offset
+            )
+            print(
+                u"\tEnd Time Offset : {}.{}".format(
+                    logo_recognition_annotation_segment_end_time_offset.seconds,
+                    logo_recognition_annotation_segment_end_time_offset.nanos,
+                )
+            )
+
+
+# [END video_detect_logo_gcs_beta]

samples/analyze/video_detect_logo_gcs_beta_test.py

@@ -0,0 +1,32 @@
+# Copyright 2020 Google
+#
+# 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 video_detect_logo_gcs_beta
+
+RESOURCES = os.path.join(os.path.dirname(__file__), "resources")
+
+
+def test_sample_annotate_video(capsys):
+    input_uri = "gs://cloud-samples-data/video/googlework_tiny.mp4"
+
+    video_detect_logo_gcs_beta.sample_annotate_video(input_uri=input_uri)
+
+    out, _ = capsys.readouterr()
+
+    assert "Description : Google Maps" in out
+    assert "Confidence" in out
+    assert "Start Time Offset" in out
+    assert "End Time Offset" in out