DerProp

Getting Started

Installation

git clone git@github.com:BBBBchan/CorrMatch.git
cd CorrMatch
conda create -n corrmatch python=3.9
conda activate corrmatch
conda install pytorch==1.13.1 torchvision==0.14.1 torchaudio==0.13.1 pytorch-cuda=11.7 -c pytorch -c nvidia
pip install opencv-python tqdm einops pyyaml

Pretrained Backbone:

ResNet-101

mkdir pretrained

Please put the pretrained model under pretrained dictionary.

Dataset:

• Pascal VOC 2012: JPEGImages | SegmentationClass
• Cityscapes: leftImg8bit | gtFine

Please modify the dataset path in configuration files.The groundtruth mask ids have already been pre-processed. You may use them directly.

Your dataset path may look like:

├── [Your Pascal Path]
    ├── JPEGImages
    └── SegmentationClass
    
├── [Your Cityscapes Path]
    ├── leftImg8bit
    └── gtFine

Usage

Training

sh tools/train.sh <num_gpu> <port>

To run on different labeled data partitions or different datasets, please modify:

config, labeled_id_path, unlabeled_id_path, and save_path in train.sh.

Evaluation

sh tools/val.sh <num_gpu> <port>

To evaluate your checkpoint, please modify checkpoint_path in val.sh.

License

This code is licensed under the Creative Commons Attribution-NonCommercial 4.0 International for non-commercial use only. Please note that any commercial use of this code requires formal permission prior to use.

Contact

For technical questions, please contact yuanbinfu@tju.edu.cn.

Acknowledgement

We thank CorrMatch, UniMatch, CPS, CutMix-Seg, DeepLabv3Plus, U²PL and other excellent works (see this project) for their amazing projects!