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+

If you are experienced with PyTorch and have already installed it, just skip this part and jump to the [next section](#installation). 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.