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https://github.com/bobholamovic/fcn-cd-pytorch
Training code for https://github.com/rcdaudt/fully_convolutional_change_detection
https://github.com/bobholamovic/fcn-cd-pytorch
change-detection convolutional-siamese-networks deep-learning pytorch remote-sensing
Last synced: 6 days ago
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Training code for https://github.com/rcdaudt/fully_convolutional_change_detection
- Host: GitHub
- URL: https://github.com/bobholamovic/fcn-cd-pytorch
- Owner: Bobholamovic
- License: bsd-2-clause
- Created: 2019-12-08T15:12:43.000Z (almost 5 years ago)
- Default Branch: master
- Last Pushed: 2020-12-16T12:14:38.000Z (almost 4 years ago)
- Last Synced: 2024-10-31T05:51:40.443Z (13 days ago)
- Topics: change-detection, convolutional-siamese-networks, deep-learning, pytorch, remote-sensing
- Language: Python
- Homepage:
- Size: 128 KB
- Stars: 19
- Watchers: 2
- Forks: 8
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Fully Convolutional Siamese Networks for Change Detection
---
This repo has been deprecated. Please see [CDLab](https://github.com/Bobholamovic/CDLab), which includes more architectures and datasets.
---
This is an unofficial implementation of the paper
> Rodrigo Caye Daudt, Bertrand Le Saux, Alexandre Boulch. (2018, October). Fully convolutional siamese networks for change detection. In 2018 25th IEEE International Conference on Image Processing (ICIP) (pp. 4063-4067). IEEE.
~~as the [official repo](https://github.com/rcdaudt/fully_convolutional_change_detection) does not provide the training code.~~
[paper link](https://ieeexplore.ieee.org/abstract/document/8451652)
# Dependencies
> opencv-python==4.1.1
pytorch==1.3.1
torchvision==0.4.2
pyyaml==5.1.2
scikit-image==0.15.0
scikit-learn==0.21.3
scipy==1.3.1
tqdm==4.35.0
Tested using Python 3.7.4 on Ubuntu 16.04 and Python 3.6.8 on Windows 10.
# Basic usage
```bash
# The network definition scripts are from the original repo
git clone --recurse-submodules [email protected]:Bobholamovic/FCN-CD-PyTorch.git
cd FCN-CD-PyTorch
mkdir exp
cd src
```
In `src/constants.py`, change the dataset locations to your own. In `config_base.yaml`, set specific configurations.
For training, try
```bash
python train.py train --exp_config ../configs/config_base.yaml
```
For evaluation, try
```bash
python train.py eval --exp_config ../configs/config_base.yaml --resume path_to_checkpoint --save-on
```
You can check the model weight files in `exp/base/weights/`, the log files in `exp/base/logs`, and the output change maps in `exp/base/out`.
---
# Changed
- 2020.3.14 Add configuration files.
- 2020.4.14 Detail README.md.
- 2020.12.8 Update framework.