From 1b81609b0d669cf2bf415d515d0948a43eb2cac0 Mon Sep 17 00:00:00 2001
From: Yu-Han Liu <yuhanliu@google.com>
Date: Wed, 23 Aug 2017 21:07:06 -0700
Subject: [PATCH 01/16] update analyze_safe_search

---
 video/cloud-client/analyze/analyze.py | 32 ++++++++++++---------------
 1 file changed, 14 insertions(+), 18 deletions(-)

diff --git a/video/cloud-client/analyze/analyze.py b/video/cloud-client/analyze/analyze.py
index c85f9d78a280..1de4669daa0a 100644
--- a/video/cloud-client/analyze/analyze.py
+++ b/video/cloud-client/analyze/analyze.py
@@ -33,18 +33,17 @@
 import sys
 import time
 
-from google.cloud.gapic.videointelligence.v1beta1 import enums
-from google.cloud.gapic.videointelligence.v1beta1 import (
-    video_intelligence_service_client)
-
+from google.cloud import videointelligence_v1beta2
+from google.cloud.videointelligence_v1beta2 import enums
+from google.cloud.videointelligence_v1beta2 import types
 
 def analyze_safe_search(path):
-    """ Detects safe search features the GCS path to a video. """
-    video_client = (video_intelligence_service_client.
-                    VideoIntelligenceServiceClient())
-    features = [enums.Feature.SAFE_SEARCH_DETECTION]
+    """ Detects explicit content from the GCS path to a video. """
+    video_client = videointelligence_v1beta2.VideoIntelligenceServiceClient()
+    features = [enums.Feature.EXPLICIT_CONTENT_DETECTION]
+
     operation = video_client.annotate_video(path, features)
-    print('\nProcessing video for safe search annotations:')
+    print('\nProcessing video for explicit content annotations:')
 
     while not operation.done():
         sys.stdout.write('.')
@@ -54,19 +53,16 @@ def analyze_safe_search(path):
     print('\nFinished processing.')
 
     # first result is retrieved because a single video was processed
-    safe_annotations = (operation.result().annotation_results[0].
-                        safe_search_annotations)
+    explicit_annotation = (operation.result().annotation_results[0].
+                        explicit_annotation)
 
     likely_string = ("Unknown", "Very unlikely", "Unlikely", "Possible",
                      "Likely", "Very likely")
 
-    for note in safe_annotations:
-        print('Time: {}s'.format(note.time_offset / 1000000.0))
-        print('\tadult: {}'.format(likely_string[note.adult]))
-        print('\tspoof: {}'.format(likely_string[note.spoof]))
-        print('\tmedical: {}'.format(likely_string[note.medical]))
-        print('\tracy: {}'.format(likely_string[note.racy]))
-        print('\tviolent: {}\n'.format(likely_string[note.violent]))
+    for frame in explicit_annotation.frames:
+        frame_time = frame.time_offset.seconds + frame.time_offset.nanos / 1e9
+        print('Time: {}s'.format(frame_time))
+        print('\tadult: {}'.format(likely_string[frame.pornography_likelihood]))
 
 
 def analyze_faces(path):

From 23ce5088d2f5f246941bf1916514a04844aefc4a Mon Sep 17 00:00:00 2001
From: Yu-Han Liu <yuhanliu@google.com>
Date: Wed, 23 Aug 2017 21:18:28 -0700
Subject: [PATCH 02/16] update analyze_shots

---
 video/cloud-client/analyze/analyze.py | 14 ++++++--------
 1 file changed, 6 insertions(+), 8 deletions(-)

diff --git a/video/cloud-client/analyze/analyze.py b/video/cloud-client/analyze/analyze.py
index 1de4669daa0a..03ef867d8afa 100644
--- a/video/cloud-client/analyze/analyze.py
+++ b/video/cloud-client/analyze/analyze.py
@@ -175,8 +175,7 @@ def analyze_labels_file(path):
 
 def analyze_shots(path):
     """ Detects camera shot changes. """
-    video_client = (video_intelligence_service_client.
-                    VideoIntelligenceServiceClient())
+    video_client = videointelligence_v1beta2.VideoIntelligenceServiceClient()
     features = [enums.Feature.SHOT_CHANGE_DETECTION]
     operation = video_client.annotate_video(path, features)
     print('\nProcessing video for shot change annotations:')
@@ -189,13 +188,12 @@ def analyze_shots(path):
     print('\nFinished processing.')
 
     # first result is retrieved because a single video was processed
-    shots = operation.result().annotation_results[0]
+    shots = operation.result().annotation_results[0].shot_annotations
 
-    for note, shot in enumerate(shots.shot_annotations):
-        print('\tScene {}: {} to {}'.format(
-            note,
-            shot.start_time_offset / 1000000.0,
-            shot.end_time_offset / 1000000.0))
+    for i, shot in enumerate(shots):
+        start_time = shot.start_time_offset.seconds + shot.end_time_offset.nanos / 1e9
+        end_time = shot.end_time_offset.seconds + shot.end_time_offset.nanos / 1e9
+        print('\tScene {}: {} to {}'.format(i, start_time, end_time))
 
 
 if __name__ == '__main__':

From 4295e5e0e3f882d2172f8687b7c4ed17a48af92d Mon Sep 17 00:00:00 2001
From: Yu-Han Liu <yuhanliu@google.com>
Date: Fri, 25 Aug 2017 11:34:12 -0700
Subject: [PATCH 03/16] update explicit_content_detection and test

---
 video/cloud-client/analyze/analyze.py      | 16 ++++++++--------
 video/cloud-client/analyze/analyze_test.py | 10 +++++-----
 2 files changed, 13 insertions(+), 13 deletions(-)

diff --git a/video/cloud-client/analyze/analyze.py b/video/cloud-client/analyze/analyze.py
index 03ef867d8afa..417a14ea5b9c 100644
--- a/video/cloud-client/analyze/analyze.py
+++ b/video/cloud-client/analyze/analyze.py
@@ -23,7 +23,7 @@
     python analyze.py labels gs://cloud-ml-sandbox/video/chicago.mp4
     python analyze.py labels_file resources/cat.mp4
     python analyze.py shots gs://demomaker/gbikes_dinosaur.mp4
-    python analyze.py safe_search gs://demomaker/gbikes_dinosaur.mp4
+    python analyze.py explicit_content gs://demomaker/gbikes_dinosaur.mp4
 
 """
 
@@ -37,7 +37,7 @@
 from google.cloud.videointelligence_v1beta2 import enums
 from google.cloud.videointelligence_v1beta2 import types
 
-def analyze_safe_search(path):
+def analyze_explicit_content(path):
     """ Detects explicit content from the GCS path to a video. """
     video_client = videointelligence_v1beta2.VideoIntelligenceServiceClient()
     features = [enums.Feature.EXPLICIT_CONTENT_DETECTION]
@@ -62,7 +62,7 @@ def analyze_safe_search(path):
     for frame in explicit_annotation.frames:
         frame_time = frame.time_offset.seconds + frame.time_offset.nanos / 1e9
         print('Time: {}s'.format(frame_time))
-        print('\tadult: {}'.format(likely_string[frame.pornography_likelihood]))
+        print('\tpornography: {}'.format(likely_string[frame.pornography_likelihood]))
 
 
 def analyze_faces(path):
@@ -210,9 +210,9 @@ def analyze_shots(path):
     analyze_labels_file_parser = subparsers.add_parser(
         'labels_file', help=analyze_labels_file.__doc__)
     analyze_labels_file_parser.add_argument('path')
-    analyze_safe_search_parser = subparsers.add_parser(
-        'safe_search', help=analyze_safe_search.__doc__)
-    analyze_safe_search_parser.add_argument('path')
+    analyze_explicit_content_parser = subparsers.add_parser(
+        'explicit_content', help=analyze_explicit_content.__doc__)
+    analyze_explicit_content_parser.add_argument('path')
     analyze_shots_parser = subparsers.add_parser(
         'shots', help=analyze_shots.__doc__)
     analyze_shots_parser.add_argument('path')
@@ -227,5 +227,5 @@ def analyze_shots(path):
         analyze_labels_file(args.path)
     if args.command == 'shots':
         analyze_shots(args.path)
-    if args.command == 'safe_search':
-        analyze_safe_search(args.path)
+    if args.command == 'explicit_content':
+        analyze_explicit_content(args.path)
diff --git a/video/cloud-client/analyze/analyze_test.py b/video/cloud-client/analyze/analyze_test.py
index 2aac755f0735..138f0e4d2baa 100644
--- a/video/cloud-client/analyze/analyze_test.py
+++ b/video/cloud-client/analyze/analyze_test.py
@@ -24,7 +24,7 @@
 BUCKET = os.environ['CLOUD_STORAGE_BUCKET']
 LABELS_FILE_PATH = '/video/cat.mp4'
 FACES_FILE_PATH = '/video/googlework.mp4'
-SAFE_SEARCH_FILE_PATH = '/video/cat.mp4'
+EXPLiCIT_CONTENT_FILE_PATH = '/video/cat.mp4'
 SHOTS_FILE_PATH = '/video/gbikes_dinosaur.mp4'
 
 
@@ -53,8 +53,8 @@ def test_dino_video_labels(capsys):
 
 
 @pytest.mark.slow
-def test_cat_safe_search(capsys):
-    analyze.analyze_safe_search(
-        'gs://{}{}'.format(BUCKET, SAFE_SEARCH_FILE_PATH))
+def test_cat_explicit_content(capsys):
+    analyze.analyze_explicit_content(
+        'gs://{}{}'.format(BUCKET, EXPLiCIT_CONTENT_FILE_PATH))
     out, _ = capsys.readouterr()
-    assert 'medical' in out
+    assert 'pornography' in out

From 5ff54fa51a8c1b8b2e8538ef39b03c621fc77940 Mon Sep 17 00:00:00 2001
From: Yu-Han Liu <yuhanliu@google.com>
Date: Mon, 28 Aug 2017 10:12:01 -0700
Subject: [PATCH 04/16] update fece detection

---
 video/cloud-client/analyze/analyze.py | 50 +++++++++++++++++----------
 1 file changed, 32 insertions(+), 18 deletions(-)

diff --git a/video/cloud-client/analyze/analyze.py b/video/cloud-client/analyze/analyze.py
index 417a14ea5b9c..53ebec5b321a 100644
--- a/video/cloud-client/analyze/analyze.py
+++ b/video/cloud-client/analyze/analyze.py
@@ -67,10 +67,13 @@ def analyze_explicit_content(path):
 
 def analyze_faces(path):
     """ Detects faces given a GCS path. """
-    video_client = (video_intelligence_service_client.
-                    VideoIntelligenceServiceClient())
+    video_client = videointelligence_v1beta2.VideoIntelligenceServiceClient()
     features = [enums.Feature.FACE_DETECTION]
-    operation = video_client.annotate_video(path, features)
+
+    config = types.FaceDetectionConfig(include_bounding_boxes=True)
+    context = types.VideoContext(face_detection_config=config)
+
+    operation = video_client.annotate_video(path, features, video_context=context)
     print('\nProcessing video for face annotations:')
 
     while not operation.done():
@@ -85,27 +88,39 @@ def analyze_faces(path):
                         face_annotations)
 
     for face_id, face in enumerate(face_annotations):
+        print('Face {}'.format(face_id))
         print('Thumbnail size: {}'.format(len(face.thumbnail)))
 
         for segment_id, segment in enumerate(face.segments):
-            positions = 'Entire video'
-            if (segment.start_time_offset != -1 or
-                    segment.end_time_offset != -1):
-                positions = '{}s to {}s'.format(
-                    segment.start_time_offset / 1000000.0,
-                    segment.end_time_offset / 1000000.0)
-
-            print('\tTrack {}: {}'.format(segment_id, positions))
-
+            start_time = segment.segment.start_time_offset.seconds + segment.segment.end_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)
+            print('\tSegment {}: {}'.format(segment_id, positions))
+
+        # There are typically many frames for each face,
+        # here we print information on only the first frame.
+        frame = face.frames[0]
+        time_offset = frame.time_offset.seconds + frame.time_offset.nanos / 1e9
+        box = frame.normalized_bounding_boxes[0]
+        print('First frame time offset: {}s'.format(time_offset))
+        print('First frame normalized bounding box:')
+        print('\tleft: {}'.format(box.left))
+        print('\ttop: {}'.format(box.top))
+        print('\tright: {}'.format(box.right))
+        print('\tbottom: {}'.format(box.bottom))
         print('\n')
 
 
 def analyze_labels(path):
     """ Detects labels given a GCS path. """
-    video_client = (video_intelligence_service_client.
-                    VideoIntelligenceServiceClient())
+    video_client = videointelligence_v1beta2.VideoIntelligenceServiceClient()
     features = [enums.Feature.LABEL_DETECTION]
-    operation = video_client.annotate_video(path, features)
+
+    config = types.LabelDetectionConfig(
+        label_detection_mode=enums.LabelDetectionMode.FRAME_MODE)
+    context = types.VideoContext(label_detection_config=config)
+
+    operation = video_client.annotate_video(path, features, video_context=context)
     print('\nProcessing video for label annotations:')
 
     while not operation.done():
@@ -136,8 +151,7 @@ def analyze_labels(path):
 
 def analyze_labels_file(path):
     """ Detects labels given a file path. """
-    video_client = (video_intelligence_service_client.
-                    VideoIntelligenceServiceClient())
+    video_client = videointelligence_v1beta2.VideoIntelligenceServiceClient()
     features = [enums.Feature.LABEL_DETECTION]
 
     with io.open(path, "rb") as movie:
@@ -193,7 +207,7 @@ def analyze_shots(path):
     for i, shot in enumerate(shots):
         start_time = shot.start_time_offset.seconds + shot.end_time_offset.nanos / 1e9
         end_time = shot.end_time_offset.seconds + shot.end_time_offset.nanos / 1e9
-        print('\tScene {}: {} to {}'.format(i, start_time, end_time))
+        print('\tShot {}: {} to {}'.format(i, start_time, end_time))
 
 
 if __name__ == '__main__':

From 4ed1aceb4846c8fa8c9123233e6d67867aa60598 Mon Sep 17 00:00:00 2001
From: Yu-Han Liu <yuhanliu@google.com>
Date: Mon, 28 Aug 2017 10:57:00 -0700
Subject: [PATCH 05/16] update label detection (path)

---
 video/cloud-client/analyze/analyze.py | 50 ++++++++++++++++++++-------
 1 file changed, 38 insertions(+), 12 deletions(-)

diff --git a/video/cloud-client/analyze/analyze.py b/video/cloud-client/analyze/analyze.py
index 53ebec5b321a..cac7b686cf33 100644
--- a/video/cloud-client/analyze/analyze.py
+++ b/video/cloud-client/analyze/analyze.py
@@ -117,7 +117,7 @@ def analyze_labels(path):
     features = [enums.Feature.LABEL_DETECTION]
 
     config = types.LabelDetectionConfig(
-        label_detection_mode=enums.LabelDetectionMode.FRAME_MODE)
+        label_detection_mode=enums.LabelDetectionMode.SHOT_AND_FRAME_MODE)
     context = types.VideoContext(label_detection_config=config)
 
     operation = video_client.annotate_video(path, features, video_context=context)
@@ -133,19 +133,45 @@ def analyze_labels(path):
     # first result is retrieved because a single video was processed
     results = operation.result().annotation_results[0]
 
-    for i, label in enumerate(results.label_annotations):
-        print('Label description: {}'.format(label.description))
-        print('Locations:')
+    for i, segment_label in enumerate(results.segment_label_annotations):
+        print('Segment label description: {}'.format(segment_label.entity.description))
+        for category_entity in segment_label.category_entities:
+            print('\tLabel category description: {}'.format(category_entity.description))
 
-        for l, location in enumerate(label.locations):
-            positions = 'Entire video'
-            if (location.segment.start_time_offset != -1 or
-                    location.segment.end_time_offset != -1):
-                positions = '{}s to {}s'.format(
-                    location.segment.start_time_offset / 1000000.0,
-                    location.segment.end_time_offset / 1000000.0)
-            print('\t{}: {}'.format(l, positions))
+        for segment in segment_label.segments:
+            start_time = segment.segment.start_time_offset.seconds + segment.segment.end_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(positions))
+            print('\tConfidence: {}'.format(confidence))
+        print('\n')
+
+    for i, shot_label in enumerate(results.shot_label_annotations):
+        print('Shot label description: {}'.format(shot_label.entity.description))
+        for category_entity in shot_label.category_entities:
+            print('\tLabel category description: {}'.format(category_entity.description))
 
+        for shot in shot_label.segments:
+            start_time = shot.segment.start_time_offset.seconds + shot.segment.end_time_offset.nanos / 1e9
+            end_time = shot.segment.end_time_offset.seconds + shot.segment.end_time_offset.nanos / 1e9
+            positions = '{}s to {}s'.format(start_time, end_time)
+            confidence = shot.confidence
+            print('\tSegment: {}'.format(positions))
+            print('\tConfidence: {}'.format(confidence))
+        print('\n')
+
+    for i, frame_label in enumerate(results.frame_label_annotations):
+        print('Frame label description: {}'.format(frame_label.entity.description))
+        for category_entity in frame_label.category_entities:
+            print('\tLabel category description: {}'.format(category_entity.description))
+
+        # Each frame_label_annotation has many frames,
+        # here we print information only about the first frame.
+        frame = frame_label.frames[0]
+        time_offset = frame.time_offset.seconds + frame.time_offset.nanos / 1e9
+        print('\tFirst frame time offset: {}s'.format(time_offset))
+        print('\tFirst frame confidence: {}'.format(frame.confidence))
         print('\n')
 
 

From a1d680e907140e36f7dbd1f0b5c30b27d629d6da Mon Sep 17 00:00:00 2001
From: Yu-Han Liu <yuhanliu@google.com>
Date: Mon, 28 Aug 2017 13:26:54 -0700
Subject: [PATCH 06/16] update label detection (file)

---
 video/cloud-client/analyze/analyze.py      | 64 ++++++++++++++++------
 video/cloud-client/analyze/analyze_test.py | 12 ++--
 2 files changed, 54 insertions(+), 22 deletions(-)

diff --git a/video/cloud-client/analyze/analyze.py b/video/cloud-client/analyze/analyze.py
index cac7b686cf33..aff1dd366b18 100644
--- a/video/cloud-client/analyze/analyze.py
+++ b/video/cloud-client/analyze/analyze.py
@@ -133,34 +133,37 @@ def analyze_labels(path):
     # first result is retrieved because a single video was processed
     results = operation.result().annotation_results[0]
 
+    # Process video/segment level label annotations
     for i, segment_label in enumerate(results.segment_label_annotations):
-        print('Segment label description: {}'.format(segment_label.entity.description))
+        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 segment in segment_label.segments:
+        for i, segment in enumerate(segment_label.segments):
             start_time = segment.segment.start_time_offset.seconds + segment.segment.end_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(positions))
+            print('\tSegment {}: {}'.format(i, positions))
             print('\tConfidence: {}'.format(confidence))
         print('\n')
 
+    # Process shot level label annotations
     for i, shot_label in enumerate(results.shot_label_annotations):
         print('Shot label description: {}'.format(shot_label.entity.description))
         for category_entity in shot_label.category_entities:
             print('\tLabel category description: {}'.format(category_entity.description))
 
-        for shot in shot_label.segments:
+        for i, shot in enumerate(shot_label.segments):
             start_time = shot.segment.start_time_offset.seconds + shot.segment.end_time_offset.nanos / 1e9
             end_time = shot.segment.end_time_offset.seconds + shot.segment.end_time_offset.nanos / 1e9
             positions = '{}s to {}s'.format(start_time, end_time)
             confidence = shot.confidence
-            print('\tSegment: {}'.format(positions))
+            print('\tSegment {}: {}'.format(i, positions))
             print('\tConfidence: {}'.format(confidence))
         print('\n')
 
+    # Process frame level label annotations
     for i, frame_label in enumerate(results.frame_label_annotations):
         print('Frame label description: {}'.format(frame_label.entity.description))
         for category_entity in frame_label.category_entities:
@@ -197,19 +200,48 @@ def analyze_labels_file(path):
     # first result is retrieved because a single video was processed
     results = operation.result().annotation_results[0]
 
-    for i, label in enumerate(results.label_annotations):
-        print('Label description: {}'.format(label.description))
-        print('Locations:')
+    # Process video/segment level label annotations
+    for i, segment_label in enumerate(results.segment_label_annotations):
+        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.end_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')
+
+    # Process shot level label annotations
+    for i, shot_label in enumerate(results.shot_label_annotations):
+        print('Shot label description: {}'.format(shot_label.entity.description))
+        for category_entity in shot_label.category_entities:
+            print('\tLabel category description: {}'.format(category_entity.description))
+
+        for i, shot in enumerate(shot_label.segments):
+            start_time = shot.segment.start_time_offset.seconds + shot.segment.end_time_offset.nanos / 1e9
+            end_time = shot.segment.end_time_offset.seconds + shot.segment.end_time_offset.nanos / 1e9
+            positions = '{}s to {}s'.format(start_time, end_time)
+            confidence = shot.confidence
+            print('\tSegment {}: {}'.format(i, positions))
+            print('\tConfidence: {}'.format(confidence))
+        print('\n')
 
-        for l, location in enumerate(label.locations):
-            positions = 'Entire video'
-            if (location.segment.start_time_offset != -1 or
-                    location.segment.end_time_offset != -1):
-                positions = '{} to {}'.format(
-                    location.segment.start_time_offset / 1000000.0,
-                    location.segment.end_time_offset / 1000000.0)
-            print('\t{}: {}'.format(l, positions))
+    # Process frame level label annotations
+    for i, frame_label in enumerate(results.frame_label_annotations):
+        print('Frame label description: {}'.format(frame_label.entity.description))
+        for category_entity in frame_label.category_entities:
+            print('\tLabel category description: {}'.format(category_entity.description))
 
+        # Each frame_label_annotation has many frames,
+        # here we print information only about the first frame.
+        frame = frame_label.frames[0]
+        time_offset = frame.time_offset.seconds + frame.time_offset.nanos / 1e9
+        print('\tFirst frame time offset: {}s'.format(time_offset))
+        print('\tFirst frame confidence: {}'.format(frame.confidence))
         print('\n')
 
 
diff --git a/video/cloud-client/analyze/analyze_test.py b/video/cloud-client/analyze/analyze_test.py
index 138f0e4d2baa..bc9750c40a30 100644
--- a/video/cloud-client/analyze/analyze_test.py
+++ b/video/cloud-client/analyze/analyze_test.py
@@ -29,15 +29,15 @@
 
 
 @pytest.mark.slow
-def test_cat_video_shots(capsys):
+def test_analyze_shots(capsys):
     analyze.analyze_shots(
         'gs://{}{}'.format(BUCKET, SHOTS_FILE_PATH))
     out, _ = capsys.readouterr()
-    assert 'Scene 1:' in out
+    assert 'Shot 1:' in out
 
 
 @pytest.mark.slow
-def test_work_video_faces(capsys):
+def test_analyze_faces(capsys):
     analyze.analyze_faces(
         'gs://{}{}'.format(BUCKET, FACES_FILE_PATH))
     out, _ = capsys.readouterr()
@@ -45,15 +45,15 @@ def test_work_video_faces(capsys):
 
 
 @pytest.mark.slow
-def test_dino_video_labels(capsys):
+def test_analyze_labels(capsys):
     analyze.analyze_labels(
         'gs://{}{}'.format(BUCKET, LABELS_FILE_PATH))
     out, _ = capsys.readouterr()
-    assert 'Whiskers' in out
+    assert 'label description: cat' in out
 
 
 @pytest.mark.slow
-def test_cat_explicit_content(capsys):
+def test_analyze_explicit_content(capsys):
     analyze.analyze_explicit_content(
         'gs://{}{}'.format(BUCKET, EXPLiCIT_CONTENT_FILE_PATH))
     out, _ = capsys.readouterr()

From 82c75367e4d79e301bbe7bdc6305f7c83710d670 Mon Sep 17 00:00:00 2001
From: Yu-Han Liu <yuhanliu@google.com>
Date: Mon, 28 Aug 2017 13:39:03 -0700
Subject: [PATCH 07/16] flake

---
 video/cloud-client/analyze/analyze.py      | 90 ++++++++++++++--------
 video/cloud-client/analyze/analyze_test.py |  4 +-
 2 files changed, 61 insertions(+), 33 deletions(-)

diff --git a/video/cloud-client/analyze/analyze.py b/video/cloud-client/analyze/analyze.py
index aff1dd366b18..c5f1bab560cb 100644
--- a/video/cloud-client/analyze/analyze.py
+++ b/video/cloud-client/analyze/analyze.py
@@ -37,6 +37,7 @@
 from google.cloud.videointelligence_v1beta2 import enums
 from google.cloud.videointelligence_v1beta2 import types
 
+
 def analyze_explicit_content(path):
     """ Detects explicit content from the GCS path to a video. """
     video_client = videointelligence_v1beta2.VideoIntelligenceServiceClient()
@@ -54,7 +55,7 @@ def analyze_explicit_content(path):
 
     # first result is retrieved because a single video was processed
     explicit_annotation = (operation.result().annotation_results[0].
-                        explicit_annotation)
+                           explicit_annotation)
 
     likely_string = ("Unknown", "Very unlikely", "Unlikely", "Possible",
                      "Likely", "Very likely")
@@ -62,7 +63,8 @@ def analyze_explicit_content(path):
     for frame in explicit_annotation.frames:
         frame_time = frame.time_offset.seconds + frame.time_offset.nanos / 1e9
         print('Time: {}s'.format(frame_time))
-        print('\tpornography: {}'.format(likely_string[frame.pornography_likelihood]))
+        print('\tpornography: {}'.format(
+            likely_string[frame.pornography_likelihood]))
 
 
 def analyze_faces(path):
@@ -73,7 +75,8 @@ def analyze_faces(path):
     config = types.FaceDetectionConfig(include_bounding_boxes=True)
     context = types.VideoContext(face_detection_config=config)
 
-    operation = video_client.annotate_video(path, features, video_context=context)
+    operation = video_client.annotate_video(
+        path, features, video_context=context)
     print('\nProcessing video for face annotations:')
 
     while not operation.done():
@@ -92,15 +95,18 @@ def analyze_faces(path):
         print('Thumbnail size: {}'.format(len(face.thumbnail)))
 
         for segment_id, segment in enumerate(face.segments):
-            start_time = segment.segment.start_time_offset.seconds + segment.segment.end_time_offset.nanos / 1e9
-            end_time = segment.segment.end_time_offset.seconds + segment.segment.end_time_offset.nanos / 1e9
+            start_time = (segment.segment.start_time_offset.seconds +
+                          segment.segment.end_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)
             print('\tSegment {}: {}'.format(segment_id, positions))
 
         # There are typically many frames for each face,
         # here we print information on only the first frame.
         frame = face.frames[0]
-        time_offset = frame.time_offset.seconds + frame.time_offset.nanos / 1e9
+        time_offset = (frame.time_offset.seconds +
+                       frame.time_offset.nanos / 1e9)
         box = frame.normalized_bounding_boxes[0]
         print('First frame time offset: {}s'.format(time_offset))
         print('First frame normalized bounding box:')
@@ -120,7 +126,8 @@ def analyze_labels(path):
         label_detection_mode=enums.LabelDetectionMode.SHOT_AND_FRAME_MODE)
     context = types.VideoContext(label_detection_config=config)
 
-    operation = video_client.annotate_video(path, features, video_context=context)
+    operation = video_client.annotate_video(
+        path, features, video_context=context)
     print('\nProcessing video for label annotations:')
 
     while not operation.done():
@@ -135,13 +142,17 @@ def analyze_labels(path):
 
     # Process video/segment level label annotations
     for i, segment_label in enumerate(results.segment_label_annotations):
-        print('Video label description: {}'.format(segment_label.entity.description))
+        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))
+            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.end_time_offset.nanos / 1e9
-            end_time = segment.segment.end_time_offset.seconds + segment.segment.end_time_offset.nanos / 1e9
+            start_time = (segment.segment.start_time_offset.seconds +
+                          segment.segment.end_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))
@@ -150,13 +161,17 @@ def analyze_labels(path):
 
     # Process shot level label annotations
     for i, shot_label in enumerate(results.shot_label_annotations):
-        print('Shot label description: {}'.format(shot_label.entity.description))
+        print('Shot label description: {}'.format(
+            shot_label.entity.description))
         for category_entity in shot_label.category_entities:
-            print('\tLabel category description: {}'.format(category_entity.description))
+            print('\tLabel category description: {}'.format(
+                category_entity.description))
 
         for i, shot in enumerate(shot_label.segments):
-            start_time = shot.segment.start_time_offset.seconds + shot.segment.end_time_offset.nanos / 1e9
-            end_time = shot.segment.end_time_offset.seconds + shot.segment.end_time_offset.nanos / 1e9
+            start_time = (shot.segment.start_time_offset.seconds +
+                          shot.segment.end_time_offset.nanos / 1e9)
+            end_time = (shot.segment.end_time_offset.seconds +
+                        shot.segment.end_time_offset.nanos / 1e9)
             positions = '{}s to {}s'.format(start_time, end_time)
             confidence = shot.confidence
             print('\tSegment {}: {}'.format(i, positions))
@@ -165,14 +180,17 @@ def analyze_labels(path):
 
     # Process frame level label annotations
     for i, frame_label in enumerate(results.frame_label_annotations):
-        print('Frame label description: {}'.format(frame_label.entity.description))
+        print('Frame label description: {}'.format(
+            frame_label.entity.description))
         for category_entity in frame_label.category_entities:
-            print('\tLabel category description: {}'.format(category_entity.description))
+            print('\tLabel category description: {}'.format(
+                category_entity.description))
 
         # Each frame_label_annotation has many frames,
         # here we print information only about the first frame.
         frame = frame_label.frames[0]
-        time_offset = frame.time_offset.seconds + frame.time_offset.nanos / 1e9
+        time_offset = (frame.time_offset.seconds +
+                       frame.time_offset.nanos / 1e9)
         print('\tFirst frame time offset: {}s'.format(time_offset))
         print('\tFirst frame confidence: {}'.format(frame.confidence))
         print('\n')
@@ -202,13 +220,17 @@ def analyze_labels_file(path):
 
     # Process video/segment level label annotations
     for i, segment_label in enumerate(results.segment_label_annotations):
-        print('Video label description: {}'.format(segment_label.entity.description))
+        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))
+            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.end_time_offset.nanos / 1e9
-            end_time = segment.segment.end_time_offset.seconds + segment.segment.end_time_offset.nanos / 1e9
+            start_time = (segment.segment.start_time_offset.seconds +
+                          segment.segment.end_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))
@@ -217,13 +239,17 @@ def analyze_labels_file(path):
 
     # Process shot level label annotations
     for i, shot_label in enumerate(results.shot_label_annotations):
-        print('Shot label description: {}'.format(shot_label.entity.description))
+        print('Shot label description: {}'.format(
+            shot_label.entity.description))
         for category_entity in shot_label.category_entities:
-            print('\tLabel category description: {}'.format(category_entity.description))
+            print('\tLabel category description: {}'.format(
+                category_entity.description))
 
         for i, shot in enumerate(shot_label.segments):
-            start_time = shot.segment.start_time_offset.seconds + shot.segment.end_time_offset.nanos / 1e9
-            end_time = shot.segment.end_time_offset.seconds + shot.segment.end_time_offset.nanos / 1e9
+            start_time = (shot.segment.start_time_offset.seconds +
+                          shot.segment.end_time_offset.nanos / 1e9)
+            end_time = (shot.segment.end_time_offset.seconds +
+                        shot.segment.end_time_offset.nanos / 1e9)
             positions = '{}s to {}s'.format(start_time, end_time)
             confidence = shot.confidence
             print('\tSegment {}: {}'.format(i, positions))
@@ -232,9 +258,11 @@ def analyze_labels_file(path):
 
     # Process frame level label annotations
     for i, frame_label in enumerate(results.frame_label_annotations):
-        print('Frame label description: {}'.format(frame_label.entity.description))
+        print('Frame label description: {}'.format(
+            frame_label.entity.description))
         for category_entity in frame_label.category_entities:
-            print('\tLabel category description: {}'.format(category_entity.description))
+            print('\tLabel category description: {}'.format(
+                category_entity.description))
 
         # Each frame_label_annotation has many frames,
         # here we print information only about the first frame.
@@ -263,8 +291,10 @@ def analyze_shots(path):
     shots = operation.result().annotation_results[0].shot_annotations
 
     for i, shot in enumerate(shots):
-        start_time = shot.start_time_offset.seconds + shot.end_time_offset.nanos / 1e9
-        end_time = shot.end_time_offset.seconds + shot.end_time_offset.nanos / 1e9
+        start_time = (shot.start_time_offset.seconds +
+                      shot.end_time_offset.nanos / 1e9)
+        end_time = (shot.end_time_offset.seconds +
+                    shot.end_time_offset.nanos / 1e9)
         print('\tShot {}: {} to {}'.format(i, start_time, end_time))
 
 
diff --git a/video/cloud-client/analyze/analyze_test.py b/video/cloud-client/analyze/analyze_test.py
index bc9750c40a30..12ee0b5cd89d 100644
--- a/video/cloud-client/analyze/analyze_test.py
+++ b/video/cloud-client/analyze/analyze_test.py
@@ -15,10 +15,8 @@
 # limitations under the License.
 
 import os
-
-import pytest
-
 import analyze
+import pytest
 
 
 BUCKET = os.environ['CLOUD_STORAGE_BUCKET']

From b4073fa4a2fd546976585d0e8a9594477bcc28be Mon Sep 17 00:00:00 2001
From: Yu-Han Liu <yuhanliu@google.com>
Date: Mon, 28 Aug 2017 15:12:23 -0700
Subject: [PATCH 08/16] safe search --> explicit content

---
 video/cloud-client/analyze/README.rst      | 12 ++++++------
 video/cloud-client/analyze/analyze.py      |  4 ++--
 video/cloud-client/analyze/analyze_test.py |  4 +++-
 3 files changed, 11 insertions(+), 9 deletions(-)

diff --git a/video/cloud-client/analyze/README.rst b/video/cloud-client/analyze/README.rst
index f5ac39139e22..d68790fdf354 100644
--- a/video/cloud-client/analyze/README.rst
+++ b/video/cloud-client/analyze/README.rst
@@ -59,10 +59,10 @@ To run this sample:
 
     $ python analyze.py
 
-    usage: analyze.py [-h] {faces,labels,labels_file,safe_search,shots} ...
+    usage: analyze.py [-h] {faces,labels,labels_file,explicit_content,shots} ...
     
-    This application demonstrates face detection, label detection, safe search,
-    and shot change detection using the Google Cloud API.
+    This application demonstrates face detection, label detection,
+    explicit content, and shot change detection using the Google Cloud API.
     
     Usage Examples:
     
@@ -70,14 +70,14 @@ To run this sample:
         python analyze.py labels gs://cloud-ml-sandbox/video/chicago.mp4
         python analyze.py labels_file resources/cat.mp4
         python analyze.py shots gs://demomaker/gbikes_dinosaur.mp4
-        python analyze.py safe_search gs://demomaker/gbikes_dinosaur.mp4
+        python analyze.py explicit_content gs://demomaker/gbikes_dinosaur.mp4
     
     positional arguments:
-      {faces,labels,labels_file,safe_search,shots}
+      {faces,labels,labels_file,explicit_content,shots}
         faces               Detects faces given a GCS path.
         labels              Detects labels given a GCS path.
         labels_file         Detects labels given a file path.
-        safe_search         Detects safe search features the GCS path to a video.
+        explicit_content    Detects explicit content from the GCS path to a video.
         shots               Detects camera shot changes.
     
     optional arguments:
diff --git a/video/cloud-client/analyze/analyze.py b/video/cloud-client/analyze/analyze.py
index c5f1bab560cb..dd39eda6258e 100644
--- a/video/cloud-client/analyze/analyze.py
+++ b/video/cloud-client/analyze/analyze.py
@@ -14,8 +14,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-"""This application demonstrates face detection, label detection, safe search,
-and shot change detection using the Google Cloud API.
+"""This application demonstrates face detection, label detection,
+explicit content, and shot change detection using the Google Cloud API.
 
 Usage Examples:
 
diff --git a/video/cloud-client/analyze/analyze_test.py b/video/cloud-client/analyze/analyze_test.py
index 12ee0b5cd89d..bc9750c40a30 100644
--- a/video/cloud-client/analyze/analyze_test.py
+++ b/video/cloud-client/analyze/analyze_test.py
@@ -15,9 +15,11 @@
 # limitations under the License.
 
 import os
-import analyze
+
 import pytest
 
+import analyze
+
 
 BUCKET = os.environ['CLOUD_STORAGE_BUCKET']
 LABELS_FILE_PATH = '/video/cat.mp4'

From 331965f3a5b13a17989e371f5930c2aafec8dd8d Mon Sep 17 00:00:00 2001
From: Yu-Han Liu <yuhanliu@google.com>
Date: Tue, 29 Aug 2017 12:34:32 -0700
Subject: [PATCH 09/16] update faces tutorial

---
 video/cloud-client/faces/faces.py | 19 ++++++++++---------
 1 file changed, 10 insertions(+), 9 deletions(-)

diff --git a/video/cloud-client/faces/faces.py b/video/cloud-client/faces/faces.py
index b6221fa2e6fb..f407158ac4fd 100644
--- a/video/cloud-client/faces/faces.py
+++ b/video/cloud-client/faces/faces.py
@@ -32,17 +32,16 @@
 import sys
 import time
 
-from google.cloud.gapic.videointelligence.v1beta1 import enums
-from google.cloud.gapic.videointelligence.v1beta1 import (
-    video_intelligence_service_client)
+from google.cloud import videointelligence_v1beta2
+from google.cloud.videointelligence_v1beta2 import enums
+from google.cloud.videointelligence_v1beta2 import types
 # [END imports]
 
 
 def analyze_faces(path):
     # [START construct_request]
     """ Detects faces given a GCS path. """
-    video_client = (video_intelligence_service_client.
-                    VideoIntelligenceServiceClient())
+    video_client = videointelligence_v1beta2.VideoIntelligenceServiceClient()
     features = [enums.Feature.FACE_DETECTION]
     operation = video_client.annotate_video(path, features)
     # [END construct_request]
@@ -66,10 +65,12 @@ def analyze_faces(path):
         print('Thumbnail size: {}'.format(len(face.thumbnail)))
 
         for segment_id, segment in enumerate(face.segments):
-            print('Track {}: {} to {}'.format(
-                segment_id,
-                segment.start_time_offset,
-                segment.end_time_offset))
+            start_time = (segment.segment.start_time_offset.seconds +
+                          segment.segment.end_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)
+            print('\tSegment {}: {}'.format(segment_id, positions))
     # [END parse_response]
 
 

From 0768a7b996d5cd8bc9110440fcc2b5f4a737461a Mon Sep 17 00:00:00 2001
From: Yu-Han Liu <yuhanliu@google.com>
Date: Tue, 29 Aug 2017 12:39:14 -0700
Subject: [PATCH 10/16] update client library quickstart

---
 video/cloud-client/faces/faces.py             |  1 -
 video/cloud-client/quickstart/quickstart.py   | 35 ++++++++++---------
 .../quickstart/quickstart_test.py             |  2 +-
 3 files changed, 19 insertions(+), 19 deletions(-)

diff --git a/video/cloud-client/faces/faces.py b/video/cloud-client/faces/faces.py
index f407158ac4fd..a365d6a6bb65 100644
--- a/video/cloud-client/faces/faces.py
+++ b/video/cloud-client/faces/faces.py
@@ -34,7 +34,6 @@
 
 from google.cloud import videointelligence_v1beta2
 from google.cloud.videointelligence_v1beta2 import enums
-from google.cloud.videointelligence_v1beta2 import types
 # [END imports]
 
 
diff --git a/video/cloud-client/quickstart/quickstart.py b/video/cloud-client/quickstart/quickstart.py
index bfb5bca91161..be84b7402610 100644
--- a/video/cloud-client/quickstart/quickstart.py
+++ b/video/cloud-client/quickstart/quickstart.py
@@ -26,12 +26,10 @@ def run_quickstart():
     import sys
     import time
 
-    from google.cloud.gapic.videointelligence.v1beta1 import enums
-    from google.cloud.gapic.videointelligence.v1beta1 import (
-        video_intelligence_service_client)
+    from google.cloud import videointelligence_v1beta2
+    from google.cloud.videointelligence_v1beta2 import enums
 
-    video_client = (video_intelligence_service_client.
-                    VideoIntelligenceServiceClient())
+    video_client = videointelligence_v1beta2.VideoIntelligenceServiceClient()
     features = [enums.Feature.LABEL_DETECTION]
     operation = video_client.annotate_video('gs://demomaker/cat.mp4', features)
     print('\nProcessing video for label annotations:')
@@ -46,19 +44,22 @@ def run_quickstart():
     # first result is retrieved because a single video was processed
     results = operation.result().annotation_results[0]
 
-    for label in results.label_annotations:
-        print('Label description: {}'.format(label.description))
-        print('Locations:')
-
-        for l, location in enumerate(label.locations):
-            positions = 'Entire video'
-            if (location.segment.start_time_offset != -1 or
-                    location.segment.end_time_offset != -1):
-                positions = '{} to {}'.format(
-                    location.segment.start_time_offset / 1000000.0,
-                    location.segment.end_time_offset / 1000000.0)
-            print('\t{}: {}'.format(l, positions))
+    for i, segment_label in enumerate(results.segment_label_annotations):
+        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.end_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 videointelligence_quickstart]
 
diff --git a/video/cloud-client/quickstart/quickstart_test.py b/video/cloud-client/quickstart/quickstart_test.py
index 9712f4107621..1d1534c46cfe 100644
--- a/video/cloud-client/quickstart/quickstart_test.py
+++ b/video/cloud-client/quickstart/quickstart_test.py
@@ -23,4 +23,4 @@
 def test_quickstart(capsys):
     quickstart.run_quickstart()
     out, _ = capsys.readouterr()
-    assert 'Whiskers' in out
+    assert 'Video label description: cat' in out

From d79fc86791277b5e21c52f493c05d895484b1f4b Mon Sep 17 00:00:00 2001
From: Yu-Han Liu <yuhanliu@google.com>
Date: Tue, 29 Aug 2017 12:54:15 -0700
Subject: [PATCH 11/16] update shotchange tutorial

---
 video/cloud-client/shotchange/shotchange.py   | 23 +++++++++----------
 .../shotchange/shotchange_test.py             |  2 +-
 2 files changed, 12 insertions(+), 13 deletions(-)

diff --git a/video/cloud-client/shotchange/shotchange.py b/video/cloud-client/shotchange/shotchange.py
index 418b89fe2800..bad449f5852a 100644
--- a/video/cloud-client/shotchange/shotchange.py
+++ b/video/cloud-client/shotchange/shotchange.py
@@ -32,17 +32,15 @@
 import sys
 import time
 
-from google.cloud.gapic.videointelligence.v1beta1 import enums
-from google.cloud.gapic.videointelligence.v1beta1 import (
-    video_intelligence_service_client)
+from google.cloud import videointelligence_v1beta2
+from google.cloud.videointelligence_v1beta2 import enums
 # [END imports]
 
 
 def analyze_shots(path):
     """ Detects camera shot changes. """
     # [START construct_request]
-    video_client = (video_intelligence_service_client.
-                    VideoIntelligenceServiceClient())
+    video_client = videointelligence_v1beta2.VideoIntelligenceServiceClient()
     features = [enums.Feature.SHOT_CHANGE_DETECTION]
     operation = video_client.annotate_video(path, features)
     # [END construct_request]
@@ -58,13 +56,14 @@ def analyze_shots(path):
     # [END check_operation]
 
     # [START parse_response]
-    shots = operation.result().annotation_results[0]
-
-    for note, shot in enumerate(shots.shot_annotations):
-        print('Scene {}: {} to {}'.format(
-            note,
-            shot.start_time_offset,
-            shot.end_time_offset))
+    shots = operation.result().annotation_results[0].shot_annotations
+
+    for i, shot in enumerate(shots):
+        start_time = (shot.start_time_offset.seconds +
+                      shot.end_time_offset.nanos / 1e9)
+        end_time = (shot.end_time_offset.seconds +
+                    shot.end_time_offset.nanos / 1e9)
+        print('\tShot {}: {} to {}'.format(i, start_time, end_time))
     # [END parse_response]
 
 
diff --git a/video/cloud-client/shotchange/shotchange_test.py b/video/cloud-client/shotchange/shotchange_test.py
index 2c637036fcfa..a004f56d5cd0 100644
--- a/video/cloud-client/shotchange/shotchange_test.py
+++ b/video/cloud-client/shotchange/shotchange_test.py
@@ -29,4 +29,4 @@ def test_shots_dino(capsys):
     shotchange.analyze_shots(
         'gs://{}{}'.format(BUCKET, SHOTS_FILE_PATH))
     out, _ = capsys.readouterr()
-    assert 'Scene 1:' in out
+    assert 'Shot 1:' in out

From ac39985e584a1e4386b17437bedbd050fe57a765 Mon Sep 17 00:00:00 2001
From: Yu-Han Liu <yuhanliu@google.com>
Date: Tue, 29 Aug 2017 14:12:25 -0700
Subject: [PATCH 12/16] update labels tutorial

---
 video/cloud-client/labels/labels.py      | 34 ++++++++++++++----------
 video/cloud-client/labels/labels_test.py |  2 +-
 2 files changed, 21 insertions(+), 15 deletions(-)

diff --git a/video/cloud-client/labels/labels.py b/video/cloud-client/labels/labels.py
index 7e0f9a0e2d42..699b3930f737 100644
--- a/video/cloud-client/labels/labels.py
+++ b/video/cloud-client/labels/labels.py
@@ -32,17 +32,15 @@
 import sys
 import time
 
-from google.cloud.gapic.videointelligence.v1beta1 import enums
-from google.cloud.gapic.videointelligence.v1beta1 import (
-    video_intelligence_service_client)
+from google.cloud import videointelligence_v1beta2
+from google.cloud.videointelligence_v1beta2 import enums
 # [END imports]
 
 
 def analyze_labels(path):
     """ Detects labels given a GCS path. """
     # [START construct_request]
-    video_client = (video_intelligence_service_client.
-                    VideoIntelligenceServiceClient())
+    video_client = videointelligence_v1beta2.VideoIntelligenceServiceClient()
     features = [enums.Feature.LABEL_DETECTION]
     operation = video_client.annotate_video(path, features)
     # [END construct_request]
@@ -60,15 +58,23 @@ def analyze_labels(path):
     # [START parse_response]
     results = operation.result().annotation_results[0]
 
-    for label in results.label_annotations:
-        print('Label description: {}'.format(label.description))
-        print('Locations:')
-
-        for l, location in enumerate(label.locations):
-            print('\t{}: {} to {}'.format(
-                l,
-                location.segment.start_time_offset,
-                location.segment.end_time_offset))
+    for i, segment_label in enumerate(results.segment_label_annotations):
+        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.end_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 parse_response]
 
 
diff --git a/video/cloud-client/labels/labels_test.py b/video/cloud-client/labels/labels_test.py
index cd571b087f1e..e1c751e99b8c 100644
--- a/video/cloud-client/labels/labels_test.py
+++ b/video/cloud-client/labels/labels_test.py
@@ -29,4 +29,4 @@ def test_feline_video_labels(capsys):
     labels.analyze_labels(
         'gs://{}{}'.format(BUCKET, LABELS_FILE_PATH))
     out, _ = capsys.readouterr()
-    assert 'Whiskers' in out
+    assert 'Video label description: cat' in out

From 146686f6e6924133b8a5762823df48d289437f63 Mon Sep 17 00:00:00 2001
From: Yu-Han Liu <yuhanliu@google.com>
Date: Fri, 15 Sep 2017 15:53:50 -0700
Subject: [PATCH 13/16] correct spelling

---
 video/cloud-client/analyze/analyze_test.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/video/cloud-client/analyze/analyze_test.py b/video/cloud-client/analyze/analyze_test.py
index bc9750c40a30..f1f777384211 100644
--- a/video/cloud-client/analyze/analyze_test.py
+++ b/video/cloud-client/analyze/analyze_test.py
@@ -24,7 +24,7 @@
 BUCKET = os.environ['CLOUD_STORAGE_BUCKET']
 LABELS_FILE_PATH = '/video/cat.mp4'
 FACES_FILE_PATH = '/video/googlework.mp4'
-EXPLiCIT_CONTENT_FILE_PATH = '/video/cat.mp4'
+EXPLICIT_CONTENT_FILE_PATH = '/video/cat.mp4'
 SHOTS_FILE_PATH = '/video/gbikes_dinosaur.mp4'
 
 
@@ -55,6 +55,6 @@ def test_analyze_labels(capsys):
 @pytest.mark.slow
 def test_analyze_explicit_content(capsys):
     analyze.analyze_explicit_content(
-        'gs://{}{}'.format(BUCKET, EXPLiCIT_CONTENT_FILE_PATH))
+        'gs://{}{}'.format(BUCKET, EXPLICIT_CONTENT_FILE_PATH))
     out, _ = capsys.readouterr()
     assert 'pornography' in out

From 2f81d1de3fe211590d1188347b47f94ff059a741 Mon Sep 17 00:00:00 2001
From: Yu-Han Liu <yuhanliu@google.com>
Date: Mon, 18 Sep 2017 15:01:10 -0700
Subject: [PATCH 14/16] correction start_time_offset

---
 video/cloud-client/analyze/analyze.py       | 12 ++++++------
 video/cloud-client/faces/faces.py           |  2 +-
 video/cloud-client/labels/labels.py         |  2 +-
 video/cloud-client/quickstart/quickstart.py |  2 +-
 video/cloud-client/shotchange/shotchange.py |  2 +-
 5 files changed, 10 insertions(+), 10 deletions(-)

diff --git a/video/cloud-client/analyze/analyze.py b/video/cloud-client/analyze/analyze.py
index dd39eda6258e..738f436257f8 100644
--- a/video/cloud-client/analyze/analyze.py
+++ b/video/cloud-client/analyze/analyze.py
@@ -96,7 +96,7 @@ def analyze_faces(path):
 
         for segment_id, segment in enumerate(face.segments):
             start_time = (segment.segment.start_time_offset.seconds +
-                          segment.segment.end_time_offset.nanos / 1e9)
+                          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)
@@ -150,7 +150,7 @@ def analyze_labels(path):
 
         for i, segment in enumerate(segment_label.segments):
             start_time = (segment.segment.start_time_offset.seconds +
-                          segment.segment.end_time_offset.nanos / 1e9)
+                          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)
@@ -169,7 +169,7 @@ def analyze_labels(path):
 
         for i, shot in enumerate(shot_label.segments):
             start_time = (shot.segment.start_time_offset.seconds +
-                          shot.segment.end_time_offset.nanos / 1e9)
+                          shot.segment.start_time_offset.nanos / 1e9)
             end_time = (shot.segment.end_time_offset.seconds +
                         shot.segment.end_time_offset.nanos / 1e9)
             positions = '{}s to {}s'.format(start_time, end_time)
@@ -228,7 +228,7 @@ def analyze_labels_file(path):
 
         for i, segment in enumerate(segment_label.segments):
             start_time = (segment.segment.start_time_offset.seconds +
-                          segment.segment.end_time_offset.nanos / 1e9)
+                          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)
@@ -247,7 +247,7 @@ def analyze_labels_file(path):
 
         for i, shot in enumerate(shot_label.segments):
             start_time = (shot.segment.start_time_offset.seconds +
-                          shot.segment.end_time_offset.nanos / 1e9)
+                          shot.segment.start_time_offset.nanos / 1e9)
             end_time = (shot.segment.end_time_offset.seconds +
                         shot.segment.end_time_offset.nanos / 1e9)
             positions = '{}s to {}s'.format(start_time, end_time)
@@ -292,7 +292,7 @@ def analyze_shots(path):
 
     for i, shot in enumerate(shots):
         start_time = (shot.start_time_offset.seconds +
-                      shot.end_time_offset.nanos / 1e9)
+                      shot.start_time_offset.nanos / 1e9)
         end_time = (shot.end_time_offset.seconds +
                     shot.end_time_offset.nanos / 1e9)
         print('\tShot {}: {} to {}'.format(i, start_time, end_time))
diff --git a/video/cloud-client/faces/faces.py b/video/cloud-client/faces/faces.py
index a365d6a6bb65..3bca1510f9f4 100644
--- a/video/cloud-client/faces/faces.py
+++ b/video/cloud-client/faces/faces.py
@@ -65,7 +65,7 @@ def analyze_faces(path):
 
         for segment_id, segment in enumerate(face.segments):
             start_time = (segment.segment.start_time_offset.seconds +
-                          segment.segment.end_time_offset.nanos / 1e9)
+                          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)
diff --git a/video/cloud-client/labels/labels.py b/video/cloud-client/labels/labels.py
index 699b3930f737..5f45b8313747 100644
--- a/video/cloud-client/labels/labels.py
+++ b/video/cloud-client/labels/labels.py
@@ -67,7 +67,7 @@ def analyze_labels(path):
 
         for i, segment in enumerate(segment_label.segments):
             start_time = (segment.segment.start_time_offset.seconds +
-                          segment.segment.end_time_offset.nanos / 1e9)
+                          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)
diff --git a/video/cloud-client/quickstart/quickstart.py b/video/cloud-client/quickstart/quickstart.py
index be84b7402610..1f31d46657a9 100644
--- a/video/cloud-client/quickstart/quickstart.py
+++ b/video/cloud-client/quickstart/quickstart.py
@@ -53,7 +53,7 @@ def run_quickstart():
 
         for i, segment in enumerate(segment_label.segments):
             start_time = (segment.segment.start_time_offset.seconds +
-                          segment.segment.end_time_offset.nanos / 1e9)
+                          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)
diff --git a/video/cloud-client/shotchange/shotchange.py b/video/cloud-client/shotchange/shotchange.py
index bad449f5852a..4db4ca3bc0ac 100644
--- a/video/cloud-client/shotchange/shotchange.py
+++ b/video/cloud-client/shotchange/shotchange.py
@@ -60,7 +60,7 @@ def analyze_shots(path):
 
     for i, shot in enumerate(shots):
         start_time = (shot.start_time_offset.seconds +
-                      shot.end_time_offset.nanos / 1e9)
+                      shot.start_time_offset.nanos / 1e9)
         end_time = (shot.end_time_offset.seconds +
                     shot.end_time_offset.nanos / 1e9)
         print('\tShot {}: {} to {}'.format(i, start_time, end_time))

From 34f5001c8a3822c3b58a3fa635cfe35387a0be0f Mon Sep 17 00:00:00 2001
From: Yu-Han Liu <yuhanliu@google.com>
Date: Mon, 18 Sep 2017 15:04:58 -0700
Subject: [PATCH 15/16] import order

---
 video/cloud-client/analyze/analyze_test.py | 4 +---
 video/cloud-client/faces/faces_test.py     | 3 +--
 video/cloud-client/labels/labels_test.py   | 3 +--
 3 files changed, 3 insertions(+), 7 deletions(-)

diff --git a/video/cloud-client/analyze/analyze_test.py b/video/cloud-client/analyze/analyze_test.py
index f1f777384211..487b466dde83 100644
--- a/video/cloud-client/analyze/analyze_test.py
+++ b/video/cloud-client/analyze/analyze_test.py
@@ -15,10 +15,8 @@
 # limitations under the License.
 
 import os
-
-import pytest
-
 import analyze
+import pytest
 
 
 BUCKET = os.environ['CLOUD_STORAGE_BUCKET']
diff --git a/video/cloud-client/faces/faces_test.py b/video/cloud-client/faces/faces_test.py
index 5eb4075dedb3..9ca80920fa80 100644
--- a/video/cloud-client/faces/faces_test.py
+++ b/video/cloud-client/faces/faces_test.py
@@ -15,10 +15,9 @@
 # limitations under the License.
 
 import os
-
+import faces
 import pytest
 
-import faces
 
 BUCKET = os.environ['CLOUD_STORAGE_BUCKET']
 FACES_FILE_PATH = '/video/googlework.mp4'
diff --git a/video/cloud-client/labels/labels_test.py b/video/cloud-client/labels/labels_test.py
index e1c751e99b8c..31a68358f6fa 100644
--- a/video/cloud-client/labels/labels_test.py
+++ b/video/cloud-client/labels/labels_test.py
@@ -15,10 +15,9 @@
 # limitations under the License.
 
 import os
-
+import labels
 import pytest
 
-import labels
 
 BUCKET = os.environ['CLOUD_STORAGE_BUCKET']
 LABELS_FILE_PATH = '/video/cat.mp4'

From 64fcf6d8117c110fb67c55f922865da499fc9ec1 Mon Sep 17 00:00:00 2001
From: Yu-Han Liu <yuhanliu@google.com>
Date: Mon, 18 Sep 2017 16:00:46 -0700
Subject: [PATCH 16/16] rebased

---
 video/cloud-client/analyze/requirements.txt    | 2 +-
 video/cloud-client/faces/requirements.txt      | 2 +-
 video/cloud-client/labels/requirements.txt     | 2 +-
 video/cloud-client/quickstart/requirements.txt | 2 +-
 video/cloud-client/shotchange/requirements.txt | 2 +-
 5 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/video/cloud-client/analyze/requirements.txt b/video/cloud-client/analyze/requirements.txt
index 28c02728605f..d3b18758344b 100644
--- a/video/cloud-client/analyze/requirements.txt
+++ b/video/cloud-client/analyze/requirements.txt
@@ -1 +1 @@
-google-cloud-videointelligence==0.26.0
+google-cloud-videointelligence==0.27.2
diff --git a/video/cloud-client/faces/requirements.txt b/video/cloud-client/faces/requirements.txt
index 28c02728605f..d3b18758344b 100644
--- a/video/cloud-client/faces/requirements.txt
+++ b/video/cloud-client/faces/requirements.txt
@@ -1 +1 @@
-google-cloud-videointelligence==0.26.0
+google-cloud-videointelligence==0.27.2
diff --git a/video/cloud-client/labels/requirements.txt b/video/cloud-client/labels/requirements.txt
index 28c02728605f..d3b18758344b 100644
--- a/video/cloud-client/labels/requirements.txt
+++ b/video/cloud-client/labels/requirements.txt
@@ -1 +1 @@
-google-cloud-videointelligence==0.26.0
+google-cloud-videointelligence==0.27.2
diff --git a/video/cloud-client/quickstart/requirements.txt b/video/cloud-client/quickstart/requirements.txt
index 28c02728605f..d3b18758344b 100644
--- a/video/cloud-client/quickstart/requirements.txt
+++ b/video/cloud-client/quickstart/requirements.txt
@@ -1 +1 @@
-google-cloud-videointelligence==0.26.0
+google-cloud-videointelligence==0.27.2
diff --git a/video/cloud-client/shotchange/requirements.txt b/video/cloud-client/shotchange/requirements.txt
index 28c02728605f..d3b18758344b 100644
--- a/video/cloud-client/shotchange/requirements.txt
+++ b/video/cloud-client/shotchange/requirements.txt
@@ -1 +1 @@
-google-cloud-videointelligence==0.26.0
+google-cloud-videointelligence==0.27.2