Prerequisites

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

MMYOLO version	MMDetection version	MMEngine version	MMCV version
main	mmdet>=3.0.0, \<3.1.0	mmengine>=0.7.1, \<1.0.0	mmcv>=2.0.0rc4, \<2.1.0
0.6.0	mmdet>=3.0.0, \<3.1.0	mmengine>=0.7.1, \<1.0.0	mmcv>=2.0.0rc4, \<2.1.0
0.5.0	mmdet>=3.0.0rc6, \<3.1.0	mmengine>=0.6.0, \<1.0.0	mmcv>=2.0.0rc4, \<2.1.0
0.4.0	mmdet>=3.0.0rc5, \<3.1.0	mmengine>=0.3.1, \<1.0.0	mmcv>=2.0.0rc0, \<2.1.0
0.3.0	mmdet>=3.0.0rc5, \<3.1.0	mmengine>=0.3.1, \<1.0.0	mmcv>=2.0.0rc0, \<2.1.0
0.2.0	mmdet>=3.0.0rc3, \<3.1.0	mmengine>=0.3.1, \<1.0.0	mmcv>=2.0.0rc0, \<2.1.0
0.1.3	mmdet>=3.0.0rc3, \<3.1.0	mmengine>=0.3.1, \<1.0.0	mmcv>=2.0.0rc0, \<2.1.0
0.1.2	mmdet>=3.0.0rc2, \<3.1.0	mmengine>=0.3.0, \<1.0.0	mmcv>=2.0.0rc0, \<2.1.0
0.1.1	mmdet==3.0.0rc1	mmengine>=0.1.0, \<0.2.0	mmcv>=2.0.0rc0, \<2.1.0
0.1.0	mmdet==3.0.0rc0	mmengine>=0.1.0, \<0.2.0	mmcv>=2.0.0rc0, \<2.1.0

In this section, we demonstrate how to prepare an environment with PyTorch.

MMDetection works on Linux, Windows, and macOS. It requires:

• Python 3.7+

• PyTorch 1.7+

• CUDA 9.2+

• GCC 5.4+

Note

If you are experienced with PyTorch and have already installed it, just skip this part and jump to the next section. Otherwise, you can follow these steps for the preparation.

Step 0. Download and install Miniconda from the official website.

Step 1. Create a conda environment and activate it.

conda create --name openmmlab python=3.8 -y
conda activate openmmlab

Step 2. Install PyTorch following official commands, e.g.

On GPU platforms:

conda install pytorch torchvision -c pytorch

On CPU platforms:

conda install pytorch torchvision cpuonly -c pytorch

Step 3. Verify PyTorch installation

python -c "import torch; print(torch.__version__); print(torch.cuda.is_available())"

If the GPU is used, the version information and True are printed; otherwise, the version information and False are printed.