# BoundaryNets

**Repository Path**: kang_wu/boundary-nets

## Basic Information

- **Project Name**: BoundaryNets
- **Description**: This implementation is for the article titled "Cloud detection with BoundaryNets".
- **Primary Language**: Python
- **License**: GPL-3.0
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 7
- **Forks**: 3
- **Created**: 2021-08-27
- **Last Updated**: 2025-05-08

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Cloud detection with BoundaryNets

This implementation is for the article titled "Cloud detection with BoundaryNets", also see in [Github]()

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## Environemnt

### Our environment

- CentOS 7.9
- Intel Xeon Gold 5218R CPU
- 2 NVIDIA Geforce 2080Ti GPUs

### Requirements

- Python 3.6
- Pytorch 0.4.1
- Gdal

---

## Train

### Trained model

The trained model can be downloaded from: [Google Driver](https://drive.google.com/file/d/1sCHbDIcAHOt_IqdOTnNokECkrIUYVX9K/view?usp=drive_link).

### Training details

1. config the training details in the file: `boundarynets_train_sparcs.py`
2. train the nets by:
   ```shell
   python boundarynets_train_sparcs.py
   ```

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## Test

1. config the model_dir and saved_dir on the file: `boundarynets_test_sparcs.py`
2. inference the nets by:
   ```shell
   python boundarynets_test_sparcs.py
   ```

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## Todo

- [X] Test Code release
- [X] Trained model release
- [X] Train Code release
- [X] Crop Code release
- [x] [Eval Code](https://gitee.com/kang_wu/in-extensive-nets/blob/master/utils/metrics.py) release 

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## BibTex

```
@article{WU2022218,
title = {Cloud detection with boundary nets},
journal = {ISPRS Journal of Photogrammetry and Remote Sensing},
volume = {186},
pages = {218-231},
year = {2022},
issn = {0924-2716},
doi = {https://doi.org/10.1016/j.isprsjprs.2022.02.010},
url = {https://www.sciencedirect.com/science/article/pii/S0924271622000521},
author = {Kang Wu and Zunxiao Xu and Xinrong Lyu and Peng Ren}
}
```

---

## Contact

kang_wu@foxmail.com