This repository contains code which implements the Stochastic Gaussian Mixture Model (S-GMM) for event-based datasets
- Generate time-surfaces using: time_surfaces.ipynb (look at tonic for more details on what datasets are support)
- Compile C++14 source code
premake4 gmake && cd build && make
- Main entry point for clustering and classification: variational-gmm.ipynb
pip install tonic
You can install cmake and premake via the homebrew package manager
/usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
brew install cmake premake
sudo apt-get install cmake premake4
Make sure you have BLAS and LAPACK installed first
sudo apt-get install libopenblas-dev
Proceed to the blaze installation
git clone https://bitbucket.org/blaze-lib/blaze.git
cd blaze && cmake -DCMAKE_INSTALL_PREFIX=/usr/local/
sudo make install
You can install intel TBB via the homebrew package manager
brew install tbb
sudo apt install libtbb-dev