google/diffseg
DiffSeg is an unsupervised zero-shot segmentation method using attention information from a stable-diffusion model. This repo implements the main DiffSeg algorithm and additionally includes an experimental feature to add semantic labels to the masks based on a generated caption.
Star & Fork Trend (18 data points)
Multi-Source Signals
Growth Velocity
google/diffseg has +0 stars this period . Velocity data will be available after more historical data is collected.
Deep analysis is being generated for this repository.
Signal-backed technical analysis will be available soon.
| Metric | diffseg | vision_tutorial | VisionReasoner | VIAME |
|---|---|---|---|---|
| Stars | 330 | 330 | 332 | 332 |
| Forks | 28 | 44 | 15 | 86 |
| Weekly Growth | +0 | +0 | +0 | +0 |
| Language | Jupyter Notebook | Shell | Python | Python |
| Sources | 1 | 1 | 1 | 1 |
| License | MIT | MIT | Apache-2.0 | NOASSERTION |
Capability Radar vs vision_tutorial
Last code push 638 days ago.
Fork-to-star ratio: 8.5%. Lower fork ratio may indicate passive usage.
Issue data not yet available.
No measurable growth in the current period (first-day cold start expected).
Licensed under MIT. Permissive — safe for commercial use.
Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.