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Linux or macOS with Python ≥ 3.6
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PyTorch ≥ 1.9 and torchvision that matches the PyTorch installation. Install them together at pytorch.org to make sure of this. Note, please check PyTorch version matches that is required by Detectron2.
Recommended:
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
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Detectron2: follow Detectron2 installation instructions.
Recommended:
python -m pip install detectron2 -f \ https://dl.fbaipublicfiles.com/detectron2/wheels/cu111/torch1.9/index.html
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OpenCV is optional but needed by demo and visualization
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pip install -r requirements.txt
After preparing the required environment, run the following command to compile CUDA kernel for MSDeformAttn:
CUDA_HOME
must be defined and points to the directory of the installed CUDA toolkit.
cd mask2former/modeling/pixel_decoder/ops
sh make.sh
To build on a system that does not have a GPU device but provide the drivers:
TORCH_CUDA_ARCH_LIST='8.0' FORCE_CUDA=1 python setup.py build install
conda create --name mask2former python=3.8 -y
conda activate mask2former
conda install pytorch==1.9.0 torchvision==0.10.0 cudatoolkit=11.1 -c pytorch -c nvidia
pip install -U opencv-python
pip install easydict
# under your working directory
git clone [email protected]:facebookresearch/detectron2.git
cd detectron2
pip install -e .
pip install git+https://github.com/cocodataset/panopticapi.git
pip install git+https://github.com/mcordts/cityscapesScripts.git
cd ..
git clone [email protected]:facebookresearch/Mask2Former.git
cd Mask2Former
pip install -r requirements.txt
cd mask2former/modeling/pixel_decoder/ops
sh make.sh