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| from fer import Video | |
| import pandas as pd | |
| def analyze_video_emotions(video_file_path, face_detector): | |
| """ | |
| Analyzes the emotions in a given video file and returns a dataframe of scores. | |
| """ | |
| input_video = Video(video_file_path) | |
| processing_data = input_video.analyze(face_detector, display=False) | |
| if not processing_data: | |
| print("No faces detected in the video.") | |
| return pd.DataFrame() | |
| vid_df = input_video.to_pandas(processing_data) | |
| vid_df = input_video.get_first_face(vid_df) | |
| vid_df = input_video.get_emotions(vid_df) | |
| emotions = ['angry', 'disgust', 'fear', 'happy', 'sad', 'surprise', 'neutral'] | |
| emotions_values = [sum(vid_df[emotion]) for emotion in emotions] | |
| score_comparisons = pd.DataFrame({ | |
| 'Human Emotions': [emotion.capitalize() for emotion in emotions], | |
| 'Emotion Value from the Video': emotions_values | |
| }) | |
| return score_comparisons | |