Update README.md

README.md

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-license: apache-2.0
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+## 🛠️ Requirements
+
+### Environment
+- **Python** 3.8+
+- **PyTorch** 1.13.0+
+- **CUDA** 11.6+
+- **Ubuntu** 18.04 or higher / Windows 10
+
+### Installation
+
+```bash
+# Create conda environment
+conda create -n dccs python=3.8 -y
+conda activate dccs
+
+# Install PyTorch
+pip install torch==1.13.0 torchvision==0.14.0 torchaudio==0.13.0
+
+# Install dependencies
+pip install packaging
+pip install timm==0.4.12
+pip install pytest chardet yacs termcolor
+pip install submitit tensorboardX
+pip install triton==2.0.0
+pip install causal_conv1d==1.0.0
+pip install mamba_ssm==1.0.1
+
+# Or simply run
+pip install -r requirements.txt
+```
+
+## 📁 Dataset Preparation
+
+We evaluate our method on three public datasets: **IRSTD-1K**, **NUAA-SIRST**, and **SIRST-Aug**.
+
+| Dataset | Link |
+|---------|------|
+| IRSTD-1K | [Download](https://github.com/RuiZhang97/ISNet) |
+| NUAA-SIRST | [Download](https://github.com/YimianDai/sirst) |
+| SIRST-Aug | [Download](https://github.com/Tianfang-Zhang/AGPCNet) |
+
+Please organize the datasets as follows:
+
+```
+├── dataset/
+│    ├── IRSTD-1K/
+│    │    ├── images/
+│    │    │    ├── XDU514png
+│    │    │    ├── XDU646.png
+│    │    │    └── ...
+│    │    ├── masks/
+│    │    │    ├── XDU514.png
+│    │    │    ├── XDU646.png
+│    │    │    └── ...
+│    │    └── trainval.txt
+│    │    └── test.txt
+│    ├── NUAA-SIRST/
+│    │    └── ...
+│    └── SIRST-Aug/
+│         └── ...
+```
+
+## 🚀 Training
+
+```bash
+python main.py --dataset-dir '/path/to/dataset' \
+               --batch-size 4 \
+               --epochs 400 \
+               --lr 0.05 \
+               --mode 'train'
+```
+
+**Example:**
+```bash
+python main.py --dataset-dir './dataset/IRSTD-1K' --batch-size 4 --epochs 400 --lr 0.05 --mode 'train'
+```
+
+## 📊 Testing
+
+```bash
+python main.py --dataset-dir '/path/to/dataset' \
+               --batch-size 4 \
+               --mode 'test' \
+               --weight-path '/path/to/weight.tar'
+```
+
+**Example:**
+```bash
+python main.py --dataset-dir './dataset/IRSTD-1K' --batch-size 4 --mode 'test' --weight-path './weight/irstd1k_weight.pkl'
+```
+
+## 📈 Results
+
+### Quantitative Results
+
+| Dataset | IoU (×10⁻²) | Pd (×10⁻²) | Fa (×10⁻⁶) | Weights |
+|:-------:|:------------:|:----------:|:----------:|:-------:|
+| IRSTD-1K | 69.64 | 95.58 | 10.48 | [Download](https://drive.google.com/file/d/1KqlOVWIktfrBrntzr53z1eGnrzjWCWSe/view?usp=sharing) |
+| NUAA-SIRST | 78.65 | 78.65 | 2.48 | [Download](https://drive.google.com/file/d/13JQ3V5xhXUcvy6h3opKs15gseuaoKrSQ/view?usp=sharing) |
+| SIRST-Aug | 75.57 | 98.90 | 33.46 | [Download](https://drive.google.com/file/d/1lcmTgft0LStM7ABWDIMRHTkcOv95p9LO/view?usp=sharing) |
+
+
+## 📂 Project Structure
+
+```
+DCCS/
+├── dataset/          # Dataset loading and preprocessing
+├── model/            # Network architecture
+├── utils/            # Utility functions
+├── weight/           # Pretrained weights
+├── main.py           # Main entry point
+├── requirements.txt  # Dependencies
+└── README.md
+```
+
+## 🙏 Acknowledgement
+
+We sincerely thank the following works for their contributions:
+
+- [BasicIRSTD](https://github.com/XinyiYing/BasicIRSTD) - A comprehensive toolbox 
+- [MSHNet](https://github.com/ying-fu/MSHNet) - Scale and Location Sensitive Loss