Pytorch implementation of ResUnet and ResUnet ++
Unofficial Pytorch implementation of following papers :
python preprocess.py --config "config/default.yaml" --train training_files_dir --valid validation_files_dir
args
above should contain two folders input
for input images and output
for target images. And all images are of fixed square size (in this case 1500 * 1500
pixels).224 * 224
) small cropped images and saved into input_crop
and mask_crop
respectively on training and validation dump directories as in config
file.configs/default.yaml
.python train.py --name "default" --config "config/default.yaml"
For Tensorboard:
tensorboard --logdir logs/