## Installation ### Requirements - Linux (Windows is not officially supported) - Python 3.6+ - PyTorch 1.3 or higher - [mmcv](https://github.com/open-mmlab/mmcv) ### Install mmsegmentation a. Create a conda virtual environment and activate it. ```shell conda create -n open-mmlab python=3.7 -y conda activate open-mmlab ``` b. Install PyTorch and torchvision following the [official instructions](https://pytorch.org/). Here we use PyTorch 1.5.0 and CUDA 10.1. You may also switch to other version by specifying the version number. ```shell conda install pytorch=1.5.0 torchvision cudatoolkit=10.1 -c pytorch ``` c. Install [MMCV](https://mmcv.readthedocs.io/en/latest/) following the [official instructions](https://mmcv.readthedocs.io/en/latest/#installation). Either `mmcv` or `mmcv-full` is compatible with MMSegmentation, but for methods like CCNet and PSANet, CUDA ops in `mmcv-full` is required The pre-build mmcv-full (with PyTorch 1.5 and CUDA 10.1) can be installed by running: (other available versions could be found [here](https://mmcv.readthedocs.io/en/latest/#install-with-pip)) ```shell pip install mmcv-full==latest+torch1.5.0+cu101 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html ``` d. Install MMSegmentation. ```shell pip install mmsegmentation # install the latest release ``` or ```shell pip install git+https://github.com/open-mmlab/mmsegmentation.git # install the master branch ``` Instead, if you would like to install MMSegmentation in `dev` mode, run following ```shell git clone https://github.com/open-mmlab/mmsegmentation cd mmsegmentation pip install -e . # or "python setup.py develop" ``` Note: 1. The `version+git_hash` will also be saved in trained models meta, e.g. 0.5.0+c415a2e. 2. When MMsegmentation is installed on `dev` mode, any local modifications made to the code will take effect without the need to reinstall it. 3. If you would like to use `opencv-python-headless` instead of `opencv-python`, you can install it before installing MMCV. 4. Some dependencies are optional. Simply running `pip install -e .` will only install the minimum runtime requirements. To use optional dependencies like `cityscapessripts` either install them manually with `pip install -r requirements/optional.txt` or specify desired extras when calling `pip` (e.g. `pip install -e .[optional]`). Valid keys for the extras field are: `all`, `tests`, `build`, and `optional`. ### A from-scratch setup script Here is a full script for setting up mmsegmentation with conda and link the dataset path (supposing that your dataset path is $DATA_ROOT). ```shell conda create -n open-mmlab python=3.7 -y conda activate open-mmlab conda install pytorch=1.5.0 torchvision cudatoolkit=10.1 -c pytorch pip install mmcv-full==latest+torch1.5.0+cu101 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html git clone https://github.com/open-mmlab/mmsegmentation cd mmsegmentation pip install -e . # or "python setup.py develop" mkdir data ln -s $DATA_ROOT data ```