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import argparse
import os
from pathlib import Path
import cv2
import numpy as np
IMAGE_EXTS = {".png", ".jpg", ".jpeg", ".webp"}
VIDEO_EXTS = {".mp4", ".mov", ".webm", ".mkv", ".avi"}
def _frame_stats(frame: np.ndarray) -> tuple[float, float]:
if frame is None:
return 0.0, 0.0
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
return float(np.std(gray)), float(np.max(gray) - np.min(gray))
def _check_image(path: Path, min_std: float, min_range: float) -> tuple[bool, str]:
img = cv2.imread(str(path), cv2.IMREAD_COLOR)
if img is None:
return False, "unable to decode image"
std, rng = _frame_stats(img)
if std < min_std or rng < min_range:
return False, f"low variance (std={std:.2f}, range={rng:.2f})"
return True, f"ok (std={std:.2f}, range={rng:.2f})"
def _sample_video_frames(cap: cv2.VideoCapture, indices: list[int]) -> list[np.ndarray]:
frames = []
for idx in indices:
cap.set(cv2.CAP_PROP_POS_FRAMES, idx)
ok, frame = cap.read()
if ok:
frames.append(frame)
return frames
def _check_video(path: Path, min_std: float, min_range: float) -> tuple[bool, str]:
cap = cv2.VideoCapture(str(path))
if not cap.isOpened():
return False, "unable to open video"
frame_count = int(cap.get(cv2.CAP_PROP_FRAME_COUNT) or 0)
if frame_count <= 0:
cap.release()
return False, "no frames detected"
indices = [0, frame_count // 2, max(frame_count - 1, 0)]
frames = _sample_video_frames(cap, indices)
cap.release()
if not frames:
return False, "failed to read sample frames"
stats = [_frame_stats(frame) for frame in frames]
avg_std = sum(s[0] for s in stats) / len(stats)
avg_rng = sum(s[1] for s in stats) / len(stats)
if avg_std < min_std or avg_rng < min_range:
return False, f"low variance (avg std={avg_std:.2f}, avg range={avg_rng:.2f})"
return True, f"ok (avg std={avg_std:.2f}, avg range={avg_rng:.2f})"
def main() -> None:
parser = argparse.ArgumentParser(description="Validate generated outputs are not garbage.")
parser.add_argument("output_dir", help="Output directory to scan.")
parser.add_argument("--min-std", type=float, default=2.0, help="Minimum grayscale stddev.")
parser.add_argument("--min-range", type=float, default=10.0, help="Minimum grayscale range.")
args = parser.parse_args()
root = Path(args.output_dir)
if not root.exists():
raise SystemExit(f"Output directory not found: {root}")
files = [p for p in root.rglob("*") if p.suffix.lower() in IMAGE_EXTS.union(VIDEO_EXTS)]
if not files:
raise SystemExit(f"No output media files found in {root}")
failures = []
for path in sorted(files):
if path.suffix.lower() in IMAGE_EXTS:
ok, detail = _check_image(path, args.min_std, args.min_range)
else:
ok, detail = _check_video(path, args.min_std, args.min_range)
status = "ok" if ok else "fail"
print(f"[{status}] {path}: {detail}")
if not ok:
failures.append(path)
if failures:
raise SystemExit(f"{len(failures)} file(s) failed validation.")
print(f"Validated {len(files)} file(s).")
if __name__ == "__main__":
main()
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