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;
1. Caffe
- 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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