def video_labels_result()

in experiments/notebooks/cloudstory-api/cloudstory.py [0:0]

• 25 lines of code
• 5 McCabe index (conditional complexity)

def video_labels_result(jobId):
    display('In Progress...')
    response_label = rekognition.get_label_detection(JobId=jobId)
    while response_label['JobStatus'] == 'IN_PROGRESS':
        time.sleep(5)
        response_label = rekognition.get_label_detection(JobId=jobId)

    display('Getting Labels...')
    display(f"Video Duration (ms): {response_label['VideoMetadata']['DurationMillis']}")
    display(f"FrameRate: {int(response_label['VideoMetadata']['FrameRate'])}")

    labels = []
    while response_label:
        labels.extend(response_label['Labels'])
        if 'NextToken' in response_label:
            response_label = rekognition.get_label_detection(JobId=jobId, NextToken=response_label['NextToken']) 
        else:
            response_label = None
    
    display(f'Succeeded in detecting {len(labels)} labels.')
    
    df = pd.DataFrame(labels)
    df['LabelName'] = df['Label'].apply(lambda x: x['Name'])
    df['Score'] = df['Label'].apply(lambda x: round(float(x['Confidence']), 2))
    df['Instances'] = df['Label'].apply(lambda x: len(x['Instances']) if x['Instances'] else 0)
    df['ParentsCount'] = df['Label'].apply(lambda x: len(x['Parents']))
    df['Parents'] = df['Label'].apply(lambda x: ', '.join(map(lambda x : x['Name'], x['Parents'])))
    df = df.drop(columns=['Label'])
    return df