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| import argparse
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| import os
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| import sys
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| import cv2
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| import numpy as np
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| import json
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| from datetime import datetime
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|
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| def compute_colorfulness(frame):
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| b, g, r = cv2.split(frame.astype('float'))
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|
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| rg = r - g
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| yb = 0.5 * (r + g) - b
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|
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| std_rg, std_yb = np.std(rg), np.std(yb)
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| mean_rg, mean_yb = np.mean(rg), np.mean(yb)
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|
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| return np.sqrt(std_rg**2 + std_yb**2) + 0.3 * np.sqrt(mean_rg**2 + mean_yb**2)
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|
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| def sample_frames(video_path, max_frames=30):
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| cap = cv2.VideoCapture(video_path)
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| if not cap.isOpened():
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| return []
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| total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
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| step = max(1, total_frames // max_frames)
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| frames = []
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| for idx in range(0, total_frames, step):
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| cap.set(cv2.CAP_PROP_POS_FRAMES, idx)
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| ret, frame = cap.read()
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| if not ret:
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| break
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|
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| h, w = frame.shape[:2]
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| new_w = 256
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| new_h = int(h * (256 / w))
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| frame = cv2.resize(frame, (new_w, new_h))
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| frames.append(frame)
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| cap.release()
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| return frames
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|
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| def main():
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| parser = argparse.ArgumentParser(description="Evaluate video colorfulness (detect non-BW video).")
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| parser.add_argument("--output", type=str, required=True,
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| help="Path to the input video file.")
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| parser.add_argument("--threshold", type=float, default=10.0,
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| help="Colorfulness threshold for pass/fail (default: 10.0).")
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| parser.add_argument("--result", help="Path to append the jsonl result.")
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| args = parser.parse_args()
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|
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| input_path = args.output
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| process_ok = False
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| results_ok = False
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| comments = []
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| if not os.path.exists(input_path):
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| comments.append(f"Input file not found: {input_path}")
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| elif os.path.getsize(input_path) == 0:
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| comments.append(f"Input file is empty: {input_path}")
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| else:
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| ext = os.path.splitext(input_path)[1].lower()
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| if ext not in ['.mp4', '.avi', '.mov', '.mkv']:
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| comments.append(f"Unsupported file format: {ext}")
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| else:
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| process_ok = True
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| if process_ok:
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| frames = sample_frames(input_path)
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| if not frames:
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| comments.append("Failed to read any frames from video.")
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| else:
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| scores = [compute_colorfulness(f) for f in frames]
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| avg_score = float(np.mean(scores))
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| comments.append(f"Average colorfulness: {avg_score:.2f}")
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| results_ok = avg_score > args.threshold
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| comments.append("Pass" if results_ok else "Fail")
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| print("=== Evaluation ===")
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| print("Process OK: ", process_ok)
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| if process_ok:
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| print("Result OK: ", results_ok)
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| for c in comments:
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| print(c)
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| if args.result:
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| record = {
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| "Process": process_ok,
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| "Result": results_ok,
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| "TimePoint": datetime.now().isoformat(),
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| "comments": "; ".join(comments)
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| }
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| os.makedirs(os.path.dirname(args.result), exist_ok=True)
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| with open(args.result, 'a', encoding='utf-8') as f:
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| json_line = json.dumps(record, default=str, ensure_ascii=False)
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| f.write(json_line + "\n")
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|
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| if __name__ == "__main__":
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| main() |
