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

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) in a venv:
- torch
- torchvision
- 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