Project comparison
Compare adoption, momentum, maintenance health, and project basics before choosing which tool to evaluate deeper.
Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
Best matched with other framework tools.
Ultralytics YOLOv5 in PyTorch for object detection, instance segmentation, classification, training, and export.
Best matched with other framework tools.
Yolov5 has the larger GitHub footprint with 57.7K stars.
Yolov5 is currently growing faster at +354 stars this week.
Segmentation Models.pytorch has the stronger automated maintenance signal at 66/100. This is not a security or fit verdict.
Use these signals to narrow your choice, then confirm setup, license, and fit upstream.
| Signal | Segmentation Models.pytorch | Yolov5 |
|---|---|---|
| Evidence status | Basic listing· 2026-10-04 09:18 UTC | Basic listing· 2026-10-04 09:18 UTC |
| GitHub stars | 11.7K | 57.7K |
| Weekly growth | +138 | +354 |
| Health score | Healthy66/100 | Healthy64/100 |
| Contributors | 79 | 348 |
| Commits per week | 9.7 | 3.6 |
| Open issues | 82 | 30 |
| Language | Python | Python |
| License | MIT | AGPL-3.0 |
| Last commit | 2026-08-03 01:43 UTC | 2026-07-21 10:14 UTC |
| Last release | v0.5.0 | v7.0 |
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