Nicole-Yi's picture
Upload 103 files
4a5e815 verified
#!/usr/bin/env python3
import argparse
import os
import sys
import cv2
import numpy as np
import json
from datetime import datetime
def compute_colorfulness(frame):
# Convert to float for computation
b, g, r = cv2.split(frame.astype('float'))
# Compute RG and YB components
rg = r - g
yb = 0.5 * (r + g) - b
# Compute statistics
std_rg, std_yb = np.std(rg), np.std(yb)
mean_rg, mean_yb = np.mean(rg), np.mean(yb)
# Colorfulness metric
return np.sqrt(std_rg**2 + std_yb**2) + 0.3 * np.sqrt(mean_rg**2 + mean_yb**2)
def sample_frames(video_path, max_frames=30):
cap = cv2.VideoCapture(video_path)
if not cap.isOpened():
return []
total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
step = max(1, total_frames // max_frames)
frames = []
for idx in range(0, total_frames, step):
cap.set(cv2.CAP_PROP_POS_FRAMES, idx)
ret, frame = cap.read()
if not ret:
break
# Resize frame to width=256, keep aspect ratio
h, w = frame.shape[:2]
new_w = 256
new_h = int(h * (256 / w))
frame = cv2.resize(frame, (new_w, new_h))
frames.append(frame)
cap.release()
return frames
def main():
parser = argparse.ArgumentParser(description="Evaluate video colorfulness (detect non-BW video).")
parser.add_argument("--output", type=str, required=True,
help="Path to the input video file.")
parser.add_argument("--threshold", type=float, default=10.0,
help="Colorfulness threshold for pass/fail (default: 10.0).")
parser.add_argument("--result", help="Path to append the jsonl result.")
args = parser.parse_args()
input_path = args.output
process_ok = False
results_ok = False
comments = []
# Check file existence and basic validity
if not os.path.exists(input_path):
comments.append(f"Input file not found: {input_path}")
elif os.path.getsize(input_path) == 0:
comments.append(f"Input file is empty: {input_path}")
else:
ext = os.path.splitext(input_path)[1].lower()
if ext not in ['.mp4', '.avi', '.mov', '.mkv']:
comments.append(f"Unsupported file format: {ext}")
else:
process_ok = True
if process_ok:
frames = sample_frames(input_path)
if not frames:
comments.append("Failed to read any frames from video.")
else:
scores = [compute_colorfulness(f) for f in frames]
avg_score = float(np.mean(scores))
comments.append(f"Average colorfulness: {avg_score:.2f}")
results_ok = avg_score > args.threshold
comments.append("Pass" if results_ok else "Fail")
# Print result
print("=== Evaluation ===")
print("Process OK: ", process_ok)
if process_ok:
print("Result OK: ", results_ok)
for c in comments:
print(c)
# Append to jsonl
if args.result:
record = {
"Process": process_ok,
"Result": results_ok,
"TimePoint": datetime.now().isoformat(),
"comments": "; ".join(comments)
}
os.makedirs(os.path.dirname(args.result), exist_ok=True)
with open(args.result, 'a', encoding='utf-8') as f:
json_line = json.dumps(record, default=str, ensure_ascii=False)
f.write(json_line + "\n")
if __name__ == "__main__":
main()