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Installation

Below are the key dependencies for running MVCTrack:

Dependency Version
Python 3.9.0
PyTorch 2.0.1
MMEngine 0.7.4
MMCV 2.0.0
MMDet 3.0.0
MMDet3D 1.1.0
SpConv 2.3.6
YAPF 0.40.0

Preparation

Clone the repository to your local directory:

git clone https://github.com/StiphyJay/MVCTrack.git

We recommend using conda to manage the environment.

Step 1: Create and activate a new conda environment

conda create -n mvc python=3.9 conda activate mvc

Step 2: Install the key dependencies

  • Install PyTorch and related libraries:

pip install torch==2.0.1 torchvision==0.15.2 torchaudio==2.0.2 --index-url https://download.pytorch.org/whl/cu118

  • Install MMCV:

pip install mmcv==2.0.0 -f https://download.openmmlab.com/mmcv/dist/cu118/torch2.0/index.html

  • Install SpConv:

pip install spconv-cu118==2.3.6

Additional Notes

  • Ensure your system has CUDA 11.8 installed to match the dependencies listed above.
  • Other dependencies like MMEngine, MMDet, MMDet3D, and YAPF will be installed automatically when running the setup or can be installed manually using pip.
  • For detailed instructions on environment setup, please refer to the project documentation.

Step 3: Install segmentor CenterNet2

Please install CenterNet2. Make sure to add a link to CenterNet2 folder in your Python path. We will use CenterNet2 for 2D instance segmentation and use the segmentation results to generate the virtual points.