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Prerequisites

  • Linux & Windows
  • Python 3.7+
  • PyTorch 1.6+
  • CUDA 9.2+
  • GCC 5+
  • mmcv 1.4.5+
  • mmdet 2.22.0+

Compatible MMCV, MMClassification and MMDetection versions are shown as below. Please install the correct version of them to avoid installation issues.

MMRotate version MMCV version MMDetection version
main mmcv-full>=1.4.5, <1.6.0 mmdet >= 2.22.0
0.3.1 mmcv-full>=1.4.5, <1.6.0 mmdet >= 2.22.0
0.3.0 mmcv-full>=1.4.5, <1.6.0 mmdet >= 2.22.0
0.2.0 mmcv-full>=1.4.5, <1.5.0 mmdet >= 2.19.0
0.1.1 mmcv-full>=1.4.5, <1.5.0 mmdet >= 2.19.0
0.1.0 mmcv-full>=1.4.5, <1.5.0 mmdet >= 2.19.0

Note: You need to run pip uninstall mmcv first if you have mmcv installed. If mmcv and mmcv-full are both installed, there will be ModuleNotFoundError.

Installation

A from-scratch setup script

Assuming that you already have CUDA 10.1 installed, here is a full script for setting up MMRotate with conda. You can refer to the step-by-step installation instructions in the next section.

conda create -n open-mmlab python=3.7 pytorch==1.7.0 cudatoolkit=10.1 torchvision -c pytorch -y
conda activate open-mmlab
pip install openmim
mim install mmcv-full
mim install mmdet
git clone https://github.com/open-mmlab/mmrotate.git
cd mmrotate
pip install -r requirements/build.txt
pip install -v -e .

Prepare environment

  1. Create a conda virtual environment and activate it.

    conda create -n openmmlab python=3.7 -y
conda activate openmmlab

  2. 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 If you have CUDA 10.1 installed under /usr/local/cuda and would like to install PyTorch 1.7, you need to install the prebuilt PyTorch with CUDA 10.1.

    conda install pytorch==1.7.0 torchvision==0.8.0 cudatoolkit=10.1 -c pytorch

Install MMRotate

It is recommended to install MMRotate with MIM, which automatically handle the dependencies of OpenMMLab projects, including mmcv and other python packages.

pip install openmim
mim install mmrotate

Or you can still install MMRotate manually:

  1. Install mmcv-full.

    pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/{cu_version}/{torch_version}/index.html

    Please replace {cu_version} and {torch_version} in the url to your desired one. For example, to install the latest mmcv-full with CUDA 11.0 and PyTorch 1.7.0, use the following command:

    pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cu110/torch1.7.0/index.html

    See here for different versions of MMCV compatible to different PyTorch and CUDA versions.

    Optionally you can compile mmcv from source if you need to develop both mmcv and mmrotate. Refer to the guide for details.

  2. Install MMDetection.

    You can simply install mmdetection with the following command:

    pip install mmdet

  3. Install MMRotate.

    You can simply install MMRotate with the following command:

    pip install mmrotate

    or clone the repository and then install it:

    git clone https://github.com/open-mmlab/mmrotate.git
cd mmrotate
pip install -r requirements/build.txt
pip install -v -e .  # or "python setup.py develop"

Note:

a. When specifying -e or develop, MMRotate is installed on dev mode , any local modifications made to the code will take effect without reinstallation.

b. If you would like to use opencv-python-headless instead of opencv-python, you can install it before installing MMCV.

c. Some dependencies are optional. Simply running pip install -v -e . will only install the minimum runtime requirements. To use optional dependencies like albumentations and imagecorruptions either install them manually with pip install -r requirements/optional.txt or specify desired extras when calling pip (e.g. pip install -v -e .[optional]). Valid keys for the extras field are: all, tests, build, and optional.

Another option: Docker Image

We provide a Dockerfile to build an image. Ensure that you are using docker version >=19.03.

# build an image with PyTorch 1.6, CUDA 10.1
docker build -t mmrotate docker/

Run it with

docker run --gpus all --shm-size=8g -it -v {DATA_DIR}:/mmrotate/data mmrotate

Verification

To verify whether MMRotate is installed correctly, we can run the demo code and inference a demo image.

Please refer to demo for more details. The demo code is supposed to run successfully upon you finish the installation.

Dataset Preparation

Please refer to data preparation for dataset preparation.