Datasets

Docker Setup

docker build -t dafne.

Training

With Docker

./tools/run.py --gpus 0,1,2,3 --config-file ./configs/dota-1.0/1024.yaml

Without Docker

NVIDIA_VISIBLE_DEVICES=0,1,2,3 ./tools/plain_train_net.py --num-gpus 4 --config-file ./configs/dota-1.0/1024.yaml

Pre-Trained Weights

Pre-Trained Weights Usage with Docker

./tools/run.py --gpus 0 --config-file<CONFIG_PATH> --opts"MODEL.WEIGHTS <WEIGHTS_PATH>"

Pre-Trained Weights Usage without Docker

NVIDIA_VISIBLE_DEVICES=0 ./tools/plain_train_net.py --num-gpus 1 --config-file<CONFIG_PATH> MODEL.WEIGHTS<WEIGHTS_PATH>

Cite

@misc{lang2021dafne,title={DAFNe: A One-Stage Anchor-Free Approach for Oriented Object Detection},author={Steven Lang and Fabrizio Ventola and Kristian Kersting},year={2021},eprint={2109.06148},archivePrefix={arXiv},primaryClass={cs.CV}}

Acknowledgments