: Oriented-Det

Technical notes on oriented-det: announcements, releases, training, evaluation, and parity work against research frameworks.

Start here

  1. Oriented-det is coming — motivation and design goals
  2. Oriented-Det v0.1.0 is out — install, docs, and getting started
  3. Oriented object detection on macOS, in pure Python — hands-on inference with odet image-demo on Apple Silicon
  4. Oriented R-CNN detections for the 15 DOTA classes — qualitative gallery on the DOTA taxonomy
  5. Zero-shot ships on Sentinel-2 — public checkpoint on a Copernicus tile
  6. Announcing the Oriented R-CNN 3× pretrained model — first DOTA le90 zoo chapter
  7. Rotated Faster R-CNN on DOTA without custom CUDA — ProbIoU, sampled rIoU, 83.42% eval-val
  8. Oriented-Det v0.1.1 — ProbIoU packaged, MMRotate parity, harbor-scene demo
  9. Oriented-Det v0.2.0 — Rotated FCOS, decoded rIoU, four-family zoo
  10. Rotated FCOS vs Oriented R-CNN on macOS — Apple Silicon MPS latency, L4 training wall (~5.7×), side-by-side demos
  11. A static demo of three oriented detectors — Rotated Faster R-CNN, FCOS, and Oriented R-CNN on seven optical scenes, in parity with MMRotate

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