This repository is for DFU challenge (https://dfu2020.grand-challenge.org/evaluation/submissions/create/). This challenge will be held in MICCAI 2020 (https://www.miccai2020.org/).
This repository is based on mmdetection. Please follow the instruction guide on installation
If you want to test with your image, download the one of the pretrained weights of any model (e.g. Deformable Convolution) from the link and save to the MODEL_PATH. And assume that the image is placed at IMG_PATH. And run the following command.
python demo/image_demo.py IMG_PATH configs/feet/deform_low.py MODEL_PATH
This will visualize the bounding boxes of the wound.
Faster R-CNN, Deformable Conv2, Cascade R-CNN, pisa
python tools/train.py configs/feet/feet_low.py
python tools/train.py configs/feet/deform_low.py
python tools/train.py configs/feet/cascade.py
python tools/train.py configs/feet/pisa.py
The pretrained models can be downloaded from the link
python demo/inference.py configs/feet/feet_low.py work_dirs/feet_low/epoch_17.pth --score-thr=0.7
python demo/inference.py configs/feet/deform_low.py work_dirs/deform_low/epoch_25.pth --score-thr=0.7
python demo/inference.py configs/feet/cascade.py work_dirs/cascade/epoch_23.pth --score-thr=0.7
python demo/inference.py configs/feet/pisa.py work_dirs/pisa/epoch_19.pth --score-thr=0.7
python demo/ensemble_nms.py