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+
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 .