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This commit is contained in:
Prince Canuma
2026-03-18 17:40:05 +01:00
parent 78bcfba31b
commit 17397da70c
77 changed files with 4125 additions and 1655 deletions
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85
scripts/video/compare_videos.py
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@@ -170,19 +170,33 @@ def print_report(results, ref_path, test_path):
print("AGGREGATE METRICS")
print("-" * 40)
print(f" PSNR (dB): mean={np.mean(psnr):6.2f} min={np.min(psnr):6.2f} max={np.max(psnr):6.2f}")
print(f" SSIM: mean={np.mean(ssim):.4f} min={np.min(ssim):.4f} max={np.max(ssim):.4f}")
print(f" Mean diff: mean={np.mean(md):6.2f} min={np.min(md):6.2f} max={np.max(md):6.2f}")
print(f" Max diff: mean={np.mean(mx):6.1f} min={np.min(mx):6.1f} max={np.max(mx):6.1f}")
print(f" Color dist: mean={np.mean(cd):.4f} min={np.min(cd):.4f} max={np.max(cd):.4f}")
print(
f" PSNR (dB): mean={np.mean(psnr):6.2f} min={np.min(psnr):6.2f} max={np.max(psnr):6.2f}"
)
print(
f" SSIM: mean={np.mean(ssim):.4f} min={np.min(ssim):.4f} max={np.max(ssim):.4f}"
)
print(
f" Mean diff: mean={np.mean(md):6.2f} min={np.min(md):6.2f} max={np.max(md):6.2f}"
)
print(
f" Max diff: mean={np.mean(mx):6.1f} min={np.min(mx):6.1f} max={np.max(mx):6.1f}"
)
print(
f" Color dist: mean={np.mean(cd):.4f} min={np.min(cd):.4f} max={np.max(cd):.4f}"
)
print()
print("TEMPORAL COHERENCE (mean frame-to-frame diff, lower = smoother)")
print("-" * 40)
print(f" Reference: {results['ref_temporal_coherence']:.2f}")
print(f" Test: {results['test_temporal_coherence']:.2f}")
ratio = results["test_temporal_coherence"] / (results["ref_temporal_coherence"] + 1e-10)
print(f" Ratio: {ratio:.2f}x {'(test is smoother)' if ratio < 1 else '(test is jerkier)' if ratio > 1.05 else '(similar)'}")
ratio = results["test_temporal_coherence"] / (
results["ref_temporal_coherence"] + 1e-10
)
print(
f" Ratio: {ratio:.2f}x {'(test is smoother)' if ratio < 1 else '(test is jerkier)' if ratio > 1.05 else '(similar)'}"
)
print()
# Identify worst frames
@@ -190,7 +204,9 @@ def print_report(results, ref_path, test_path):
print("-" * 40)
worst_idx = np.argsort(psnr)[:5]
for i in worst_idx:
print(f" Frame {i:4d}: PSNR={psnr[i]:6.2f} dB SSIM={ssim[i]:.4f} mean_diff={md[i]:.2f}")
print(
f" Frame {i:4d}: PSNR={psnr[i]:6.2f} dB SSIM={ssim[i]:.4f} mean_diff={md[i]:.2f}"
)
print()
# Quality assessment
@@ -210,7 +226,9 @@ def print_report(results, ref_path, test_path):
grade = "Very different"
print(f" Overall: {grade} (PSNR={mean_psnr:.1f} dB, SSIM={mean_ssim:.4f})")
if mean_psnr < 30:
print(" ⚠ Videos differ significantly — likely a bug or different generation seed")
print(
" ⚠ Videos differ significantly — likely a bug or different generation seed"
)
print("=" * 72)
@@ -242,9 +260,7 @@ def main():
parser.add_argument(
"--diff-video", help="Save side-by-side diff visualization to this path"
)
parser.add_argument(
"--max-frames", type=int, help="Compare only first N frames"
)
parser.add_argument("--max-frames", type=int, help="Compare only first N frames")
parser.add_argument(
"--ssim-win", type=int, default=7, help="SSIM window size (default: 7)"
)
@@ -254,26 +270,29 @@ def main():
default=5.0,
help="Diff heatmap amplification (default: 5.0)",
)
parser.add_argument(
"--csv", help="Export per-frame metrics to CSV file"
)
parser.add_argument("--csv", help="Export per-frame metrics to CSV file")
args = parser.parse_args()
print(f"Loading reference: {args.reference}")
ref_frames, ref_fps = load_video(args.reference, args.max_frames)
print(f" → {len(ref_frames)} frames, {ref_fps:.1f} fps, {ref_frames[0].shape[1]}x{ref_frames[0].shape[0]}")
print(
f" → {len(ref_frames)} frames, {ref_fps:.1f} fps, {ref_frames[0].shape[1]}x{ref_frames[0].shape[0]}"
)
print(f"Loading test: {args.test}")
test_frames, test_fps = load_video(args.test, args.max_frames)
print(f" → {len(test_frames)} frames, {test_fps:.1f} fps, {test_frames[0].shape[1]}x{test_frames[0].shape[0]}")
print(
f" → {len(test_frames)} frames, {test_fps:.1f} fps, {test_frames[0].shape[1]}x{test_frames[0].shape[0]}"
)
if ref_frames[0].shape != test_frames[0].shape:
print(f"Warning: resolution mismatch {ref_frames[0].shape} vs {test_frames[0].shape}")
print(
f"Warning: resolution mismatch {ref_frames[0].shape} vs {test_frames[0].shape}"
)
print("Resizing test frames to match reference...")
h, w = ref_frames[0].shape[:2]
test_frames = [
cv2.resize(f, (w, h), interpolation=cv2.INTER_LANCZOS4)
for f in test_frames
cv2.resize(f, (w, h), interpolation=cv2.INTER_LANCZOS4) for f in test_frames
]
print("Computing metrics...")
@@ -282,23 +301,29 @@ def main():
print_report(results, args.reference, args.test)
if args.diff_video:
save_diff_video(ref_frames, test_frames, args.diff_video, ref_fps, args.diff_scale)
save_diff_video(
ref_frames, test_frames, args.diff_video, ref_fps, args.diff_scale
)
if args.csv:
import csv
with open(args.csv, "w", newline="") as f:
writer = csv.writer(f)
writer.writerow(["frame", "psnr", "ssim", "mean_diff", "max_diff", "color_dist"])
writer.writerow(
["frame", "psnr", "ssim", "mean_diff", "max_diff", "color_dist"]
)
for i in range(results["num_frames"]):
writer.writerow([
i,
f"{results['psnr'][i]:.4f}",
f"{results['ssim'][i]:.6f}",
f"{results['mean_diff'][i]:.4f}",
f"{results['max_diff'][i]:.1f}",
f"{results['color_dist'][i]:.6f}",
])
writer.writerow(
[
i,
f"{results['psnr'][i]:.4f}",
f"{results['ssim'][i]:.6f}",
f"{results['mean_diff'][i]:.4f}",
f"{results['max_diff'][i]:.1f}",
f"{results['color_dist'][i]:.6f}",
]
)
print(f"Per-frame metrics saved to {args.csv}")