- 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+
- MMCV
I ran experiments with PyTorch 1.8.0, CUDA 11.1, Python 3.7, and Ubuntu 18.04. Other settings that satisfact the requirement would work.
You can simply follow our settings:
Use Anaconda to create a conda environment:
conda create -n MDE python=3.7
conda activate MDE
Install Pytorch:
conda install pytorch==1.8.0 torchvision==0.9.0 torchaudio==0.8.0 cudatoolkit=11.1 -c pytorch -c conda-forge
Then, install MMCV and install the Monocular-Depth-Estimation-Toolbox:
pip install mmcv-full==1.5.0 -f https://download.openmmlab.com/mmcv/dist/cu111/torch1.8.0/index.html
git clone https://github.com/RuijieZhu94/HABins.git
cd HABins
pip install -e .
If training, you should install the tensorboard:
pip install future tensorboard
More information about installation can be found in docs of MMSegmentation (see get_started.md).