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IRAOD

IRAOD is an oriented object detection workspace for DIOR/RSAR source-free adaptation and corruption robustness experiments.

Quick Start

bash scripts/setup_env_iraod.sh
conda activate iraod

python tools/verify_dataset_layout.py --dior dataset/DIOR --rsar dataset/RSAR
DRY_RUN=1 SOURCE_CKPT=auto WORK_ROOT=work_dirs/smoke_refactor \
  CUDA_VISIBLE_DEVICES=0,1,2 NGPUS=3 bash scripts/run/rsar_sfodrs_full.sh

Use DRY_RUN=1 first on any launcher to verify paths, env, and generated commands without starting training or evaluation.

Recommended RSAR Entries

# Full SFOD-RS protocol. SOURCE_CKPT=auto trains the clean source detector first.
SOURCE_CKPT=auto WORK_ROOT=work_dirs/<run> CUDA_VISIBLE_DEVICES=0,1,2 NGPUS=3 \
  bash scripts/run/rsar_sfodrs_full.sh

# One corruption domain.
CORR=chaff SOURCE_CKPT=work_dirs/<source>/latest.pth WORK_ROOT=work_dirs/<run> \
  bash scripts/run/rsar_sfodrs_domain.sh

# TENT adapt/eval/fusion.
TENT_MODE=adapt SOURCE_CKPT=work_dirs/<source>/latest.pth WORK_ROOT=work_dirs/<tent> \
  bash scripts/run/rsar_tent.sh

# Collect SFOD-RS result tables.
WORK_ROOT=work_dirs/<run> bash scripts/run/collect_results.sh

Compatibility wrappers remain for older commands such as:

bash scripts/run_rsar_sfodrs_full_3gpu.sh auto work_dirs/<run>
bash scripts/run_rsar_sfodrs_7corr.sh work_dirs/<source>/latest.pth
bash scripts/exp_rsar_sfodrs_adapt.sh chaff work_dirs/<source>/latest.pth

Datasets

Default local layout:

dataset/DIOR/
dataset/RSAR/
  train/{images,annfiles}
  val/{images,annfiles}
  test/{images,annfiles}
  corruptions/<corruption>/{val,test}/images

Override RSAR location with either RSAR_DATA_ROOT=/path/to/RSAR or DATA_ROOT=/path/to/RSAR.

Prepare the RSAR corruption layout when needed:

python tools/prepare_rsar_corruption.py --data-root dataset/RSAR --workers 8

Documentation Map

  • docs/commands.md: current smoke/full/eval/collect command cookbook.
  • docs/project_map.md: directory responsibilities and active vs archived entrypoints.
  • docs/experiment.md: full experiment ledger and recorded metrics.
  • configs/README.md: current config aliases and historical config locations.
  • MODEL_ZOO.md: checkpoint and external weight notes.

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Interference-Resistant Aerial Image Object Detection

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