Roadmap
August 10, 2026 · View on GitHub
High-level plan for Oriented-Det after v0.1 (geometry, IoU/NMS, DOTA, three ResNet-FPN detectors, config training, Hub weights).
Maintainers: a longer planning doc lives at
docs/roadmap-detailed.md(gitignored, local only).
Releases
| Version | Focus |
|---|---|
| v0.1 | Shipped — Oriented R-CNN, Rotated Faster R-CNN, Rotated RetinaNet; DOTA; odet train; Hub |
| v0.1.1 | Shipped — ProbIoU Faster R-CNN 1×/3× on Hub (77.57% / 83.42% eval-val mAP50) |
| v0.2 | Rotated FCOS — anchor-free single-stage; DOTA le90 1×/3× configs |
| v0.3 | HRSC2016 and FAIR1M dataset loaders; cross-dataset benchmarks |
| v0.4 | Production speed tier: RTMDet-R, then native YOLO-OBB |
| v0.5–v0.8 | Swin-FPN backbone; Oriented R-CNN + Swin-T on Hub; extend to FCOS / speed models |
| v1.0 | Stable API, hosted docs, complete model zoo (accuracy / balanced / speed tiers) |
Model tiers (target v1.0)
| Tier | Models |
|---|---|
| Accuracy | Oriented R-CNN, Rotated Faster R-CNN (probiou) — ResNet50 and Swin-T |
| Balanced | Rotated FCOS |
| Speed | RTMDet-R, native Rotated YOLO-OBB |
| Legacy | Rotated RetinaNet (L1; MMRotate parity) |
| Datasets | DOTA, HRSC2016, FAIR1M |
Closed ablations (not Hub)
- RetinaNet ProbIoU 1× — no zoo-worthy gain vs L1 (~63% vs 64% eval-val); keep L1 RetinaNet only
- Extra FRCNN angle / rIoU-aux recipes — did not beat the published ProbIoU 1.0 / 0.1 recipe
Ongoing
- Hosted MkDocs site and dataset tutorials
- Optional GPU / fused CUDA rotated IoU/NMS after single-stage models land (profiling-driven; not a v0.2 blocker)
- Export parity for new detectors (ONNX head wrappers + postprocess)
Out of scope (for now)
- Ultralytics wrapper or AGPL dependencies
- End-to-end DETR-style detectors in core
odet train - MMCV / MMDet as runtime dependencies
- RetinaNet ProbIoU Hub weights; FRCNN angle-fine-tune Hub twin without a clear eval-val win
See Contributing for areas where help is welcome.