🦉 Updates from OwlBot post-processor

See https://github.com/googleapis/repo-automation-bots/blob/main/packages/owl-bot/README.md

Author: gcf-owl-bot[bot]

videointelligence/samples/analyze/analyze.py

@@ -287,7 +287,6 @@ def speech_transcription(path):
     # one video is processed.
     annotation_results = result.annotation_results[0]
     for speech_transcription in annotation_results.speech_transcriptions:
-
         # The number of alternatives for each transcription is limited by
         # SpeechTranscriptionConfig.max_alternatives.
         # Each alternative is a different possible transcription
@@ -363,7 +362,6 @@ def video_detect_text_gcs(input_uri):
 
 # [START video_detect_text]
 def video_detect_text(path):
-
     """Detect text in a local video."""
     video_client = videointelligence.VideoIntelligenceServiceClient()
     features = [videointelligence.Feature.TEXT_DETECTION]

videointelligence/samples/analyze/beta_snippets.py

@@ -79,7 +79,6 @@ def speech_transcription(input_uri, timeout=180):
     # one video is processed.
     annotation_results = result.annotation_results[0]
     for speech_transcription in annotation_results.speech_transcriptions:
-
         # The number of alternatives for each transcription is limited by
         # SpeechTranscriptionConfig.max_alternatives.
         # Each alternative is a different possible transcription

videointelligence/samples/analyze/video_detect_logo.py

@@ -69,7 +69,6 @@ def detect_logo(local_file_path="path/to/your/video.mp4"):
 
             # 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("\n\t\tLeft : {}".format(normalized_bounding_box.left))

videointelligence/samples/analyze/video_detect_logo_gcs.py

@@ -18,7 +18,6 @@
 
 
 def detect_logo_gcs(input_uri="gs://YOUR_BUCKET_ID/path/to/your/file.mp4"):
-
     client = videointelligence.VideoIntelligenceServiceClient()
 
     features = [videointelligence.Feature.LOGO_RECOGNITION]
@@ -46,7 +45,6 @@ def detect_logo_gcs(input_uri="gs://YOUR_BUCKET_ID/path/to/your/file.mp4"):
         # 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.
             print(
                 "\n\tStart Time Offset : {}.{}".format(