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Environments

  • Linux or macOS
  • Python 3.6+ (Python 3.8 in our envs)
  • PyTorch 1.7+ (1.9.0 in our envs)
  • CUDA 9.2+ (CUDA 11.1 in our envs)
  • GCC 5+
  • mmdet==2.25.0
  • mmcv-full==1.5.0 (MMCV)

Installation

  1. Create a conda virtual environment and activate it.

    conda create -n boxinstseg python=3.8 -y
    conda activate boxinstseg
  2. Install PyTorch and torchvision following the official instructions, e.g.,

    pip install torch==1.9.0+cu111 torchvision==0.10.0+cu111 torchaudio==0.9.0 -f https://download.pytorch.org/whl/torch_stable.html

    Note: Make sure that your compilation CUDA version and runtime CUDA version match.

  3. Install mmcv using mim

    pip install -U openmim
    mim install mmcv-full==1.5.0
  4. Clone the this repository.

    git clone https://github.com/CircleRadon/APro.git
    cd APro
  5. Install build requirements and then install MMDetection.

    bash setup.sh   #compile the whole envs 

    Or

    pip install -v -e .
    # "-v" means verbose, or more output
    # "-e" means installing a project in editable mode,
    
    cd apro/gp_cuda #compile for the global affinity propagation
    python setup.py build develop