PyTorch implementation of Fully Convolutional Networks, for VGG and RESNET backbones.
- pytorch >= 1.1.0
- torchvision >= 0.3.0
- fcn
- Jupyter Notebook
pip install -r requirements.txt
sh download_dataset.sh
will download the PascalVOC dataset inside data folder.
python main.py --gpu_id=0 --backbone=vgg --fcn=32s --root_dataset=./data/Pascal_VOC --mode=train
- backbone: vgg or resnet [vgg default].
- fcn: 32s, 16s, 8s for vgg, and 101, 50 for resnet [32s default].
- mode: train, val, demo [train default].
- gpu_id: [-1 default (cpu)].
- resume: For val and demo, if no resume path is given, code will use original FCN pre-trained weights.
This repo is built upon wkentaro's code and some snippets can be just a mirror.