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# Prerequisites

- Linux or macOS (Windows is in experimental support)

- Python 3.6+

- PyTorch 1.3+

- CUDA 9.2+ (If you build PyTorch from source, CUDA 9.0 is also compatible)

- GCC 5+

- Dataset4EO

- MMCV

# Installation

(Install Prerequisites)

Step 0. Download and install Miniconda from the official website.

Step 1. Create a conda environment and activate it.

    conda create --name earthnets -y
    conda activate earthnets

Step 2. Install required libraries. Core libraries: `torch`, `torchvision`, `torchdata`.

    conda install pytorch torchvision cudatoolkit=11.3 -c pytorch
    pip install torchdata
    pip install mmcv-full==1.6.0
    pip install prettytable
    pip install pycocotools
    pip install wandb

(Install Dataset4EO)

Step 3. Install Dataset4EO.

    git clone git@github.com:DeepAI4EO/Dataset4EO.git
    python -m pip install -e .

(Install RSI-Segmentation)

Step 4. Install RSI-Segmentation.

    git clone https://github.com/EarthNets/RSI-Segmentation.git
    cd RSI-Segmentation
    pip install -e .