- Linux OS: Ubuntu 16.04
- Python 3.5+
- PyTorch 1.1 or higher
- CUDA 9.0 or higher
- NCCL 2
- GCC 4.9 or higher
- mmcv
Clone the Pytorch-Uodac repository.
git clone https://github.com/ChenYingpeng/Pytorch-Uodac
cd Pytorch-UodacInstall build requirements and then install pytorch-uodac. Note:(We install pycocotools via the github repo instead of pypi because the pypi version is old and not compatible with the latest numpy.)
pip install -r requirements.txt
pip install "git+https://github.com/cocodataset/cocoapi.git#subdirectory=PythonAPI"
python3 setup.py developGenerate tran json data
python3 tools/data_process/generate_train_json.py --xml-dir [xxx] --json [xxx]Example
python3 tools/data_process/generate_train_json.py --xml-dir ../underwater/optics/data/train/box/ --json ../underwater/optics/data/train/train_data_annotations.jsonGenerate test json data
python3 tools/data_process/generate_test_json.py --test-image-dir [xxx] --save-json-path [xxx]Example
python3 tools/data_process/generate_test_json.py --test-image-dir ../underwater/optics/data/test-A-image/ --save-json-path ../underwater/optics/data/annotations/test-A-image.json./tools/dist_train.sh configs/underwater/optics/xxxx.py 2download model link passwd : rf0n
./tools/dist_submit.sh configs/underwater/optics/xxxx.py ../underwater/optics/output/xxxx/latest.pth 2 --format_onlyYou could find test_A_image_submission.csv on submit/.