- Linux
- Python 3.6+
- PyTorch 1.3+
- CUDA 9.2+ (If you build PyTorch from source, CUDA 9.0 is also compatible)
- GCC 4.9+
- mmcv
a. Create a conda virtual environment and activate it.
conda create -n open-mmlab python=3.7 -y
conda activate open-mmlab
b. Install PyTorch and torchvision following the official instructions, e.g.,
conda install pytorch torchvision -c pytorch
Note: Make sure that your compilation CUDA version and runtime CUDA version match. You can check the supported CUDA version for precompiled packages on the PyTorch website.
E.g.1
If you have CUDA 10.1 installed under /usr/local/cuda
and would like to install
PyTorch 1.5, you need to install the prebuilt PyTorch with CUDA 10.1.
conda install pytorch cudatoolkit=10.1 torchvision -c pytorch
E.g. 2
If you have CUDA 9.2 installed under /usr/local/cuda
and would like to install
PyTorch 1.3.1., you need to install the prebuilt PyTorch with CUDA 9.2.
conda install pytorch=1.3.1 cudatoolkit=9.2 torchvision=0.4.2 -c pytorch
If you build PyTorch from source instead of installing the prebuilt pacakge, you can use more CUDA versions such as 9.0.
c. Clone the mmdetection repository.
git clone https://github.com/aliyun/conditional-lane-detection.git
cd conditional-lane-detection
d. Install build requirements and then install mmdetection. (We install pycocotools via the github repo instead of pypi because the pypi version is old and not compatible with the latest numpy.)
pip install -r requirements/build.txt
python setup.py develop