06.mp4 — Casal Tk

import cv2 import librosa import numpy as np

def extract_features(video_path): # Initialize video capture cap = cv2.VideoCapture(video_path) # Metadata frame_count = 0 width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)) height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT)) fps = cap.get(cv2.CAP_PROP_FPS) # Visual Features Example: Just count frames, similar to duration while cap.isOpened(): ret, frame = cap.read() if not ret: break frame_count += 1 cap.release() # Duration duration = frame_count / fps print(f"Metadata:") print(f"Resolution: {width}x{height}") print(f"FPS: {fps}") print(f"Duration (seconds): {duration}") # Simple Audio Feature Extraction (Using Librosa) try: y, sr = librosa.load(video_path, sr=None) tempo, beats = librosa.beat.beat_track(y=y, sr=sr) print(f"Audio Tempo: {tempo}") except Exception as e: print(f"Failed to extract audio features: {e}") CASAL TK 06.mp4

# Example usage video_path = "CASAL TK 06.mp4" extract_features(video_path) This example provides a basic entry point into feature extraction. The actual features you choose to extract depend on your specific requirements or application, which might involve more sophisticated video analysis techniques. import cv2 import librosa import numpy as np