SU
Fanghua-Yu/SUPIR
SUPIR aims at developing Practical Algorithms for Photo-Realistic Image Restoration In the Wild. Our new online demo is also released at suppixel.ai.
5.5k 472 +0/wk
GitHub
deep-learning diffusion-models llava pytorch pytorch-lightning restoration sdxl stable-diffusion super-resolution
Trend
3
Star & Fork Trend (21 data points)
Stars
Forks
Multi-Source Signals
Growth Velocity
Fanghua-Yu/SUPIR has +0 stars this period . 7-day velocity: 0.0%.
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Signal-backed technical analysis will be available soon.
| Metric | SUPIR | seq2seq-couplet | deep-learning-v2-pytorch | composer |
|---|---|---|---|---|
| Stars | 5.5k | 5.5k | 5.5k | 5.5k |
| Forks | 472 | 1.1k | 5.3k | 464 |
| Weekly Growth | +0 | +0 | +0 | +0 |
| Language | Python | Python | Jupyter Notebook | Python |
| Sources | 1 | 1 | 1 | 1 |
| License | NOASSERTION | AGPL-3.0 | MIT | Apache-2.0 |
Capability Radar vs seq2seq-couplet
SUPIR
seq2seq-couplet
Maintenance Activity 0
Last code push 332 days ago.
Community Engagement 43
Fork-to-star ratio: 8.6%. Lower fork ratio may indicate passive usage.
Issue Burden 70
Issue data not yet available.
Growth Momentum 30
No measurable growth in the current period (first-day cold start expected).
License Clarity 30
No clear license detected — proceed with caution.
Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.