This repository contains the implementation of our paper, "ERN: Edge Loss Reinforced Semantic Segmentation Network for Remote Sensing Images".

In this repository you will find:

• ERN prototxt and caffemodel;
• Python codes for training and testing;
• C++ code (VS2013 + OpenCV3.0) for simple shadow detection;

• Please follow Yu Liu's instruction and install the modified version of Caffe from following link: https://github.com/Walkerlikesfish/CaffeGeo.git.
• Notice that if you use Caffe, please cite their papers.

• Prepare the data;
• Make sure the file path in solver.prototxt & train.prototxt & run_training.py is correct;
• Run python run_training.py in terminal.

• Prepare the data;(In our experiments, we first splited the original image into 256*256 )
• Make sure the file path in infer.prototxt & VH_infer.py & UAV_infer.py is correct;
• Run python VH_infer.py in terminal.

• We have split the images using https://github.com/Walkerlikesfish/HSNRS/tree/master/script/data_preprocessing
  • Make sure the file path in VH_assemble.py & UAV_assemble.py is correct;
  • Run python VH_assemble.py in terminal.

• Shadow detection for ISPRS Vaihingen Dataset (Windows)
  • VS2013 + OpenCV3.0
  • The contrast preserving decolorization has been used.
• Evaluation (Linux)
  • Make sure the file path in testperformance.py (def xf_set_test_vh())is correct;
  • Run python testperformance.py (def xf_set_test_vh()) in terminal.

Please cite the following paper if you find the project helpful to your research.

@article{Liu2018ERN,
title={ERN: Edge Loss Reinforced Semantic Segmentation Network for Remote Sensing Images},
author={Liu, Shuo and Ding, Wenrui and Liu, Chunhui and Liu, Yu and Li, Hongguang},
journal={Remote Sensing},
volume={10},
number={9},
pages={1339},
year={2018}
}

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