1.9 KiB
1.9 KiB
Installation instructions
Ubuntu 18.04
-
Make sure CUDA and cuDNN are installed. One configuration has been tested:
- PyTorch 1.4.0, CUDA 10.1 and cuDNN 7.6
-
Ensure all python packages are installed :
sudo apt update sudo apt install python3-dev python3-pip python3-tk
-
Follow PyTorch installation procedure.
-
Install the other dependencies with pip:
- numpy
- scikit-learn
- PyYAML
- matplotlib (for visualization)
- mayavi (for visualization)
- PyQt5 (for visualization)
-
Compile the C++ extension modules for python located in
cpp_wrappers
. Open a terminal in this folder, and run:sh compile_wrappers.sh
You should now be able to train Kernel-Point Convolution models
Windows 10
-
Make sure CUDA and cuDNN are installed. One configuration has been tested:
- PyTorch 1.4.0, CUDA 10.1 and cuDNN 7.5
-
Follow PyTorch installation procedure.
-
We used the PyCharm IDE to pip install all python dependencies (including PyTorch):
- numpy
- scikit-learn
- PyYAML
- matplotlib (for visualization)
- mayavi (for visualization)
- PyQt5 (for visualization)
-
Compile the C++ extension modules for python located in
cpp_wrappers
. You just have to execute two .bat files:cpp_wrappers/cpp_neighbors/build.bat
and
cpp_wrappers/cpp_subsampling/build.bat
You should now be able to train Kernel-Point Convolution models