ComfyUI-VideoQuality-Metrics
A comprehensive suite of video quality assessment metrics for ComfyUI including fidelity metrics, temporal metrics, distributional metrics, and deep learning-based quality evaluation.
Nodes (13)
The name is a vibe check, because that's what this node does
One number can't tell you why a video is bad. DOVER splits the answer
High-res, short, full of noise
FID is the number every image-model paper still leads with — now it runs in your graph
The old-school trio that still catches things ML metrics miss
The number video-model papers end their abstracts with, inside your workflow
The README says statistical significance testing. The code says otherwise
The glue node that turns your scores into JSON you can save, diff, and plot
Catches the robotic, jittery motion that still frames can't reveal
One number can't describe a video, so draw a fingerprint instead
The node that catches shimmer, melting objects, and strobe lighting in your video
Tells you if your video actually followed your prompt — or slowly forgot it
The name says FID, but check what it actually computes before you quote it
ComfyUI Video Quality Metrics
A comprehensive suite of video quality assessment metrics for ComfyUI.
Features
Fidelity Metrics
- PSNR - Peak Signal-to-Noise Ratio
- SSIM - Structural Similarity Index
- CIEDE2000 - Perceptually uniform color accuracy
Temporal Metrics
- Warping Error - Optical flow-based temporal consistency
- Flickering Detection - Brightness variance analysis
- Motion Smoothness - Jerk-based motion quality
Distributional Metrics
- FVD - Fréchet Video Distance
- FID - Fréchet Inception Distance
No-Reference Metrics (Deep Learning)
- CLIP-IQA - Aesthetic Scoring & Text Alignment
- DOVER - Disentangled Aesthetic & Technical Quality
- FAST-VQA - Efficient High-Res Quality Assessment
Visualization & Reporting
- Radar Charts - Multi-metric comparison
- JSON Export - Metrics logging
- Statistical Tests - T-test, Wilcoxon for workflow comparison
Installation
cd ComfyUI/custom_nodes
git clone https://github.com/yourusername/ComfyUI-VideoQuality-Metrics.git
pip install -r ComfyUI-VideoQuality-Metrics/requirements.txt
Restart ComfyUI. Nodes appear under VideoQuality/ category.
Video & Batch Handling
All nodes accept Video Tensors [T, H, W, 3] and Image Batches [N, H, W, 3].
- Fidelity Metrics (PSNR, SSIM, ΔE2000): Return the average quality across all frames in the batch.
- Temporal Metrics: Require at least 2 frames (T ≥ 2) to compute motion consistency.
- Distributional Metrics: Compare the entire distribution of the generated batch against the reference batch.
Node Reference
| Node | Inputs | Outputs | |------|--------|---------| | VQ Full-Reference Metrics | images, reference | psnr, ssim, ciede2000, summary | | VQ Temporal Consistency | video_frames | warping_error, flickering_score, summary | | VQ Motion Smoothness | video_frames | smoothness_score, mean_jerk, summary | | VQ FVD | video_generated, video_reference | fvd, summary | | VQ FID | images_generated, images_reference | fid, summary | | VQ CLIP Aesthetic | images | aesthetic_score, summary | | VQ Text Alignment | video, prompt | alignment_score, summary | | VQ DOVER Quality | video | aesthetic, technical, overall, summary | | VQ FAST-VQA | video | quality_score, summary | | VQ Radar Chart | psnr, ssim, ... | radar_chart, metrics_json | | VQ Metrics Logger | metrics | json_output |
Interpretation Guidelines
| Metric | Excellent | Good | Fair | Poor | |--------|-----------|------|------|------| | PSNR | > 35 dB | 30-35 dB | 25-30 dB | < 25 dB | | SSIM | > 0.95 | 0.90-0.95 | 0.85-0.90 | < 0.85 | | ΔE2000 | < 1.0 | 1.0-2.0 | 2.0-5.0 | > 5.0 | | FVD | < 50 | 50-150 | 150-300 | > 300 | | CLIP Aesthetic | > 0.7 | 0.6-0.7 | 0.4-0.6 | < 0.4 | | DOVER (Overall) | > 0.6 | 0.4-0.6 | 0.2-0.4 | < 0.2 | | FAST-VQA | > 0.65 | 0.5-0.65 | 0.3-0.5 | < 0.3 |
Technical Documentation
See doc.md for the complete theoretical framework.
License
MIT License