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roboflow/rf-detr
[ICLR 2026] RF-DETR is a real-time object detection and segmentation model architecture developed by Roboflow, SOTA on COCO, designed for fine-tuning.
6.3k 758 +14/wk
GitHub
computer-vision detr instance-segmentation machine-learning object-detection rf-detr sota
Trend
3
Star & Fork Trend (34 data points)
Stars
Forks
Multi-Source Signals
Growth Velocity
roboflow/rf-detr has +14 stars this period . 7-day velocity: 0.6%.
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| Metric | rf-detr | machine-learning-mindmap | tensorflow_cookbook | pyAudioAnalysis |
|---|---|---|---|---|
| Stars | 6.3k | 6.3k | 6.2k | 6.2k |
| Forks | 758 | 1.0k | 2.4k | 1.2k |
| Weekly Growth | +14 | +0 | -1 | +0 |
| Language | Python | N/A | Jupyter Notebook | Python |
| Sources | 1 | 1 | 1 | 1 |
| License | Apache-2.0 | Apache-2.0 | MIT | Apache-2.0 |
Capability Radar vs machine-learning-mindmap
rf-detr
machine-learning-mindmap
Maintenance Activity 100
Last code push 2 days ago.
Community Engagement 61
Fork-to-star ratio: 12.1%. Active community forking and contributing.
Issue Burden 70
Issue data not yet available.
Growth Momentum 53
+14 stars this period — 0.22% growth rate.
License Clarity 95
Licensed under Apache-2.0. Permissive — safe for commercial use.
Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.