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+ ## Requirements
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+
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+ ### Environment
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+
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+ - Python 3.8+
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+ - PyTorch 2.0.1+
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+ - CUDA 11.8+
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+ - Ubuntu 22.04 or higher / Windows 10
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+
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+ ### Installation
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+ ```bash
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+ conda create --name rscd python=3.8
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+ conda activate rscd
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+ conda install pytorch==2.0.1 torchvision==0.15.2 torchaudio==2.0.2 pytorch-cuda=11.8 -c pytorch -c nvidia
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+ pip install pytorch-lightning==2.0.5
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+ pip install scikit-image==0.19.3 numpy==1.24.4
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+ pip install torchmetrics==1.0.1
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+ pip install -U catalyst==20.09
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+ pip install albumentations==1.3.1
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+ pip install einops==0.6.1
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+ pip install timm==0.6.7
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+ pip install addict==2.4.0
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+ pip install soundfile==0.12.1
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+ pip install ttach==0.0.3
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+ pip install prettytable==3.8.0
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+ pip install -U openmim
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+ pip install triton==2.0.0
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+ mim install mmcv
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+ pip install -U fvcore
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+
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+
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+ ## Dataset Preparation
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+ We evaluate our method on three public datasets: **LEVIR-CD**, **WHU-CD**, and **CLCD**.[Download](https://drive.google.com/drive/folders/1zxhJ7v3UPgNsKkdvkYCOW7DdKDAAy_ll) |