## 🛠️ Requirements

### Environment
- **Linux system**, Windows is not tested, depending on whether and can be installed `causal-conv1d` and `mamba-ssm`
- **Python** 3.8+, recommended 3.10
- **PyTorch** 2.0 or higher, recommended 2.1.0
- **CUDA** 11.7 or higher, recommended 12.1

### Environment Installation

It is recommended to use Miniconda for installation. The following commands will create a virtual environment named `stnr` and install PyTorch. In the following installation steps, the default installed CUDA version is 12.1. If your CUDA version is not 12.1, please modify it according to the actual situation.

```bash
# Create conda environment
conda create -n stnr python=3.8 -y
conda activate stnr

# Install PyTorch
pip install torch==2.1.0 torchvision==0.14.0 torchaudio==0.13.0

# Install dependencies
pip install causal_conv1d mamba_ssm packaging
pip install timm==0.4.12
pip install pytest chardet yacs termcolor
pip install submitit tensorboardX
pip install triton==2.0.0

# Or simply run
pip install -r requirements.txt
```

## 📁 Dataset Preparation

We evaluate our method on five remote sensing change detection datasets: **WHU-CD**, **LEVIR-CD**, **LEVIR-CD+**, **SYSU-CD**, and **SVCD**.

| Dataset | Link |
|---------|------|
| WHU-CD | [Download](https://aistudio.baidu.com/datasetdetail/251669) |
| LEVIR-CD | [Download](https://opendatalab.org.cn/OpenDataLab/LEVIR-CD) |
| LEVIR-CD+ | [Download](https://www.cvmart.net/dataSets/detail/1385) |
| SYSU-CD | [Download](https://mail2sysueducn-my.sharepoint.com/personal/liumx23_mail2_sysu_edu_cn/_layouts/15/onedrive.aspx?id=%2Fpersonal%2Fliumx23%5Fmail2%5Fsysu%5Fedu%5Fcn%2FDocuments%2FSYSU%2DCD&ga=1) |
| SVCD | [Download](https://aistudio.baidu.com/datasetdetail/78676) |

Please organize the datasets as follows:

```
${DATASET_ROOT} # Dataset root directory, for example: /home/username/data/LEVIR-CD
├── A
│   ├── train_1_1.png
│   ├── train_1_2.png
│   ├──...
│   ├── val_1_1.png
│   ├── val_1_2.png
│   ├──...
│   ├── test_1_1.png
│   ├── test_1_2.png
│   └── ...
├── B
│   ├── train_1_1.png
│   ├── train_1_2.png
│   ├──...
│   ├── val_1_1.png
│   ├── val_1_2.png
│   ├──...
│   ├── test_1_1.png
│   ├── test_1_2.png
│   └── ...
├── label
│   ├── train_1_1.png
│   ├── train_1_2.png
│   ├──...
│   ├── val_1_1.png
│   ├── val_1_2.png
│   ├──...
│   ├── test_1_1.png
│   ├── test_1_2.png
│   └── ...
├── list
│   ├── train.txt
│   ├── val.txt
│   └── test.txt
```


## 🔧 Model Training and Testing

All configuration for model training and testing is stored in the local folder `config`. Below are the example commands to train and test the model on the **LEVIR-CD** dataset.

### Example of Training on LEVIR-CD Dataset

```bash
python train_cd.py --config/levir/levir.json
```

### Example of Training on LEVIR-CD Dataset

```bash
python test_cd.py --config/levir/levir_test.json
```

## 📂 Project Structure

```
STNR-Det/
├── config/          # Configuration files for training/testing
│ ├── levir_cd_mamba.json
│ ├── levir_test_cd_mamba.json
│ └── ...
├── core/            # Core functionality (e.g., models, loss functions)
│ └── ...
├── data/            # Data loading and preprocessing scripts
│ └── ...
├── misc/            # Miscellaneous utility scripts
│ └── ...
├── models/          # Model architectures and components
│ └── ...
├── .gitattributes   # Git attributes for version control
├── README.md        # Project README (this file)
├── requirement.txt  # Python package dependencies
├── test_cd.py       # Testing script for the model
└── train_cd.py      # Training script for the model
```

## 🙏 Acknowledgement

We sincerely thank the following works for their contributions:

- [CDMamba](https://github.com/zmoka-zht/CDMamba) – A state-of-the-art method for remote sensing change detection that inspired and influenced parts of this work.
- [MambaDFuse](https://github.com/Lizhe1228/MambaDFuse) – A valuable method for feature fusion that informed our approach.