Tag: Dota
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Oriented-Det v0.4.0 — Rotated RTMDet, 77.60% Task 1
Oriented-det v0.4.0 is on PyPI — Rotated RTMDet-S at 77.60% official DOTA Task 1 (AP75 52.01), ahead of Oriented R-CNN, with the 3090 Ti training wall and the MMRotate latency next to it.
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Lessons learned on DOTA: official Task 1, leaky val, and the last mile
What I would keep from four months on DOTA: the official Task 1 number, MMRotate as a neighbour in the same band, and a better box loss when ships are still a few degrees off.
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Apache 2.0 covers oriented-det. It does not cover DOTA or HRSC.
The oriented-det framework is Apache 2.0. DOTA and HRSC are research datasets with no commercial grant. Production detectors are trained on your own licensed imagery — this is not legal advice.
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Rotated Faster R-CNN on DOTA without custom CUDA: sampled rIoU, ProbIoU, and a 74.42% Task 1 checkpoint
Why OrientedDet avoids MMRotate's exact CUDA IoU kernels, how ProbIoU trains oriented boxes in pure PyTorch, and why the 1× Rotated Faster R-CNN Hub weight beats MMRotate on official DOTA Task 1.
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Sliding-window inference on images larger than the DOTA canvas
How odet image-demo tiles images larger than 1024×1024, merges overlapping windows, and filters classes — using the Oriented R-CNN 1× Hub checkpoint retrained after a diagonal-flip bug.
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Oriented R-CNN detections for the 15 DOTA classes
A visual tour of Oriented R-CNN detections across the 15 original DOTA v1.0 aerial object classes.