DeepLearning.Earth
Oriented object detection for Earth Observation — notes on the oriented-det package and related work.
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HRSC2016 in oriented-det — recipes, trains, and a held-out 90.41%
Native HRSC2016 ship detection in oriented-det: ImageSets trainval in, held-out test out, three 3× Hub weights. Oriented R-CNN 90.41%, Faster R-CNN 88.77%, FCOS 88.34% mAP50 on NVIDIA L4.
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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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A static demo of three oriented detectors on optical satellite imagery
A browser demo of Oriented-Det’s three 3× DOTA checkpoints — Oriented R-CNN, Rotated Faster R-CNN, and Rotated FCOS — on seven optical satellite scenes, with a side by side comparison that lands in parity with state of the art frameworks.
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Rotated FCOS vs Oriented R-CNN on macOS
Hands-on Apple Silicon comparison of Hub 1× DOTA checkpoints — Rotated FCOS (73.07% official Task 1) vs Oriented R-CNN (76.73%) — MPS latency, 1× training wall on NVIDIA L4, score thresholds, and side-by-side detections.
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Oriented-Det v0.2.0 — Rotated FCOS, decoded rIoU, and a four-family zoo
Oriented-det v0.2.0 is on PyPI — Rotated FCOS joins the zoo as the balanced one-stage detector, with a decoded rIoU 1× Hub checkpoint at 73.07% official DOTA Task 1, and the same Apache 2.0 stack.
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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.
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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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Zero-shot Ship detection on a Copernicus Sentinel-2 tile with Oriented R-CNN
A practical zero-shot experiment with a DOTA-pretrained Oriented R-CNN model on a 10 m Copernicus Sentinel-2 tile, including zoomed sliding-window inference and ship-only filtering.
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Oriented object detection on macOS, in pure Python
Run Oriented R-CNN on Apple Silicon with pip, uv, and the odet CLI — no CUDA toolchain, from demo.jpg to result.jpg in minutes.
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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.
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Oriented-Det v0.1.0 is out — sovereign oriented object detection for EO
Oriented-det v0.1.0 is on PyPI under Apache 2.0 — a lightweight PyTorch library for rotated object detection in aerial and satellite imagery, with DOTA baselines and pretrained weights.
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Oriented-det is coming: sovereign oriented detection for EO
A sovereign, Apache-licensed oriented detection stack for EO, targeting an official release in June 2026.
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Detecting ships in satellite imagery: five years later…
Revisiting ship detection in SPOT imagery — from Kaggle to MMRotate.
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Is YOLOv8 suitable for satellite imagery?
Tuning YOLOv8 for satellite imagery — what works and what to change.
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How to choose a deep learning architecture to detect aircrafts in satellite imagery?
Comparing deep learning architectures for aircraft detection in satellite imagery.
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Oil Storage Detection on Airbus Imagery with YOLOX
Detecting oil storage tanks on Airbus imagery with YOLOX.
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Detecting aircraft on Airbus Pleiades imagery with YOLOv5
Training YOLOv5 on Airbus Pleiades imagery for aircraft detection.
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Important Things you should know before Organizing a Kaggle Competition
Lessons from organizing the Airbus ship detection competition on Kaggle.