Tag: Rotated-Faster-Rcnn
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Which oriented detector should you train?
Start with Rotated RTMDet-S (77.60% on DOTA, tight-box score 52.01). Switch to Oriented R-CNN for a diagonal row of long vehicles, Faster R-CNN when finding the object matters more, or FCOS for that row on a shorter ResNet train.
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Does MMRotate Faster R-CNN also mess up the bus lot?
Official MMRotate Rotated Faster R-CNN 1× is as messy as OrientedDet Faster R-CNN on the DOTA bus-lot demo tile. The failure is architectural and rare (dense ~45° objects). Oriented R-CNN is clean but heavy to finetune; FCOS follows the heading on this tile. RTMDet was not re-run here.
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Oriented-Det v0.1.1 — ProbIoU, MMRotate parity, and the updated zoo
Oriented-det v0.1.1 is on PyPI — ProbIoU ROI regression, MMRotate-aligned training fixes, a DOTA le90 zoo on official Task 1 led by Oriented R-CNN 1× at 76.73%, and a hands-on harbor-scene demo of the Faster R-CNN throughput pick.
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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.