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
cd ./models/ops
sh ./make.sh
# unit test (should see all checking is True)
python test.py
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
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.
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
Apache 2.0 license.