Software repository for the "Approximate Nearest-Neighbour Fields via Massively-Parallel Propagation-Assisted K-D Trees" paper, presented at IEEE BigData 2020, MLBD special session.
The annfmp package provides a highly-efficient parallel implementation for computing nearest neighbor fields.
See the documentation for details and examples.
The annfmp package has been tested under Python 3.6 to 3.9. The required Python dependencies are:
- numpy==1.16.3
- pyopencl==2018.2.5
- sklearn
Furthermore, OpenCL needs to be available. When installed from source, SWIG is required.
The package can easily be installed via pip via:
pip install annfmp
To install the package from the sources, first get the current stable release via:
git clone https://github.com/diku-dk/annfmp.git
We recommand to use virtualenv for installing the dependencies, for example:
$ virtualenv -p python3 annfield
$ source annfield/bin/activate
$ pip install -r requirements.txt
Afterwards, on Linux systems, you can install the package locally for the current user via:
python setup.py install --user
The source code is published under the GNU General Public License (GPLv3). The authors are not responsible for any implications that stem from the use of this software.