navamikairanda / R2U-Net

Pytorch Implementation of "Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) for Medical Image Segmentation" paper on cityscapes dataset

R2U-net

Pytorch Implementation of "Fully Convolutional Network", "Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net)" and "DeepLabV3" on PascalVOC and Cityscapes dataset.

Contributors

Navami Kairanda Priyanka Mohanta

Requirements

Following packages are used

• python 3.8
• pytorch 1.7
• torchvision 0.8.1
• pytorch-lightning 1.2.3

Prerequisites

For tasks 2 and 3,

Dataset preparation

Download and unzip gtFine_trainvaltest.zip (241MB) and leftImg8bit_trainvaltest.zip (11GB) from cityscapes site https://www.cityscapes-dataset.com/downloads/

Generate trainId labels for the dataset, using the scripts provided by Cityscape authors https://github.com/mcordts/cityscapesScripts

git clone https://github.com/mcordts/cityscapesScripts.git
pip install cityscapesScripts
CITYSCAPES_DATASET_PATH=/HPS/Navami/work/code/nnti/R2U-Net/cityscapes/
export CITYSCAPES_DATASET=$CITYSCAPES_DATASET_PATH
python /HPS/Navami/work/code/nnti/cityscapesScripts/cityscapesscripts/preparation/createTrainIdLabelImgs.py

Download resnet pretraineed model from https://download.pytorch.org/models/resnet50-19c8e357.pth and update corresponding path in resnet.py

Train and Test

For task 1, run Vision_task_1.ipynb jupyter notebook

For tasks 2 and 3,

python main.py /path/to/expt/logdir

Test

For tasks 2 and 3, download model from Microsoft Teams

python eval.py /path/to/expt/logdir {model_name}.tar

References

Task 1: Jonathan Long, Evan Shelhamer, and Trevor Darrell. Fully Convolutional Networks for Semantic Segmentation. arXiv e-prints, page arXiv:1411.4038, November 2014.

Task 2: Md Zahangir Alom, Mahmudul Hasan, Chris Yakopcic, Tarek M Taha, and Vijayan K Asari. Recurrent residual convolutional neural network based on u-net (r2u-net) for medical image segmentation. arXiv preprint arXiv:1802.06955, 2018.

Task 3: Liang-Chieh Chen, George Papandreou, Florian Schroff, and Hartwig Adam. Rethinking atrous convolution for semantic image segmentation. arXiv preprint arXiv:1706.05587, 2017.