Gal-DETR

Journal Paper

NeurIPS 2023

Installation

Create a Python 3.8 environement with CUDA 11.3.0. Then, install PyTorch 1.5+ and torchvision 0.6+:

conda install -c pytorch pytorch torchvision

Install pycocotools and scipy:

conda install cython scipy
pip install -U 'git+https://github.com/cocodataset/cocoapi.git#subdirectory=PythonAPI'

Install packages in requirements.txt.

pip install -r requirements.txt

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 4 gpus run:

python -m torch.distributed.launch --nproc_per_node=4 --use_env main.py --output_dir ./outputs_gal/

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:

python -m torch.distributed.launch --nproc_per_node=1 --use_env main.py --eval --resume outputs_gal/checkpoint.pth

License

Apache 2.0 license.