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Data checked 2026-08-13. Data may be stale - beyond the review cycle. Review cycles are documented on the Methodology page. Methodology

open-mmlab/mmrotate

Software Tool Tier A perception_ai Apache-2.0
Official confirmed

OpenMMLab Rotated Object Detection Toolbox and Benchmark

Engineering Snapshot

Use cases & tasks 7
Best suited for
  • aerial imagery analysis
  • satellite imagery object detection
  • oriented object detection research
  • benchmarking rotated detectors
Primary tasks
  • training rotated detectors on DOTA, HRSC2016, UCAS-AOD datasets
  • evaluating oriented bounding box (OBB) models
  • deploying rotated detection pipelines in PyTorch
Stack & ecosystem
Resource type
Software Tool
Ecosystem
detection · openmmlab · pytorch · rotated-object
License & compliance
License
Apache-2.0 (Inferred)
Lifecycle & freshness Show
Maintenance
Active
Latest version
Not recorded
Last activity
2026-08-11
Last checked
2026-08-13
Verification
Official confirmed

What It Solves

Rotated object detection for aerial/satellite imagery where objects have arbitrary orientations; standard horizontal bounding boxes insufficient for dense, oriented targets like vehicles, ships, aircraft.

Primary use cases

  • training rotated detectors on DOTA, HRSC2016, UCAS-AOD datasets
  • evaluating oriented bounding box (OBB) models
  • deploying rotated detection pipelines in PyTorch

Secondary use cases

  • data augmentation for oriented objects
  • model conversion to ONNX/TensorRT for edge deployment
  • synthetic data generation for rotated objects

When to Use

Consider when

  • need oriented bounding boxes not horizontal boxes
  • working with aerial/satellite datasets (DOTA, HRSC)
  • require OpenMMLab ecosystem integration
  • need reproducible benchmarks for rotated detection

Verify before adopting

  • PyTorch version compatibility (check mmrotate release notes)
  • CUDA/cuDNN version for training speed
  • dataset license compliance for commercial use
  • inference latency on target hardware (Jetson, x86)

Where It Fits

Stack layer perception_localization

Upstream / depends on

Start Here

repo https://github.com/open-mmlab/mmrotate Docs https://mmrotate.readthedocs.io/en/latest/

Adoption Checklist

  • Needs verification PyTorch version compatibility (check mmrotate release notes)
  • Needs verification CUDA/cuDNN version for training speed
  • Needs verification dataset license compliance for commercial use
  • Needs verification inference latency on target hardware (Jetson, x86)

Each check stays "needs verification" until an official source confirms it; unconfirmed items are never marked verified.

Known Limitations & Unknowns

Known limitations

  • horizontal box detectors cannot be directly reused without modification
  • OBB annotation tools less mature than horizontal box tools
  • fewer pre-trained rotated models vs horizontal detection
  • evaluation metrics ([email protected] OBB) differ from standard COCO metrics

Not publicly verified

  • real-time performance on embedded targets (Jetson Orin, Snapdragon Flight)
  • long-term maintenance cadence after OpenMMLab 3.x migration
  • support for rotated instance segmentation vs detection only

Alternatives & Related Tools

Related tools

How is it used?

Start from the recorded entry points below, then validate against the technical checklist.

Technical checklist

  • OK License identified Recorded: Apache-2.0
  • OK Maintenance signal Active
  • OK Verification status Official confirmed
  • OK Source evidence attached 1 source record(s)
  • NEEDS REVIEW Latest version recorded Not recorded

Official Links

Metadata & Governance

License Apache-2.0 — Inferred
Commercial modelUnknown
Maintenance statusActive
Verification status Official confirmed — Confirmed via the official repository API responses in SourceRefs below.
Latest versionNot recorded
Latest releaseNot recorded
Last activity2026-08-11
Last checked2026-08-13
First seenNot recorded

Dataset facts

Facts above come from the official dataset card only; unconfirmed fields stay unknown.

Related Resources & Dependencies

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