Gal-Deformable DETR

Journal Paper

NeurIPS 2023

Installation

Create a Python 3.10.9 environement with CUDA 11.6.2 and GCC>=5.4. Then, install PyTorch 1.5.1 and torchvision 0.6.1:

conda install pytorch=1.5.1 torchvision=0.6.1 -c pytorch

Install packages in requirements.txt.

pip install -r requirements.txt

Compiling CUDA operators

cd ./models/ops
sh ./make.sh
# unit test (should see all checking is True)
python test.py

Data preparation

Download and extract RadioGalaxyNET data from here. We expect the directory structure to be the following:

./RadioGalaxyNET/
  annotations/  # annotation json files
  train/    # train images
  val/      # val images
  test/     # test images

Training

To train on a single node with single gpu run:

GPUS_PER_NODE=1 ./tools/run_dist_launch.sh 1 ./configs/r50_deformable_detr.sh

To ease reproduction of our results we provide model checkpoint here. Place the model in ./outputs_gal/ directory.

Evaluation

To evaluate on test images with a single GPU run:

GPUS_PER_NODE=1 ./tools/run_dist_launch.sh 1 ./configs/r50_deformable_detr.sh --eval --resume outputs_gal/checkpoint.pth

License

Apache 2.0 license.