Software framework for image(2D)/volumetric(3D) data processing with APIs to interface deep neural network open-source softwares, written in C++ with extensive Python supports. Originally developed for analyzing data from time-projection-chamber (TPC). It is then converted to be a generic tool to handle 2D-projected images and 3D-voxelized data.
Note This repository is re-created from LArbys/LArCV repository, referred to as larbys version. The larbys version is still under active development for analysis purpose in MicroBooNE experiment. This repository is split for more generic technical R&D work in October 2017.
- ROOT6
- Python (optional)
- OpenCV 3 (optional)
- Numpy (optional)
- Dependencies to build with are determined automatically through the following conditions.
- ROOT: determined through the ability to run rootcling
- OpenCV: the presence of OPENCV_INCDIR and OPENCV_LIBDIR environment variables
- Numpy: being able to import
numpy
- Clone & build
git clone https://github.com/DeepLearnPhysics/larcv2.git
cd larcv2
source configure.sh
make
That's it. When you want to use the built larcv from a different process, you only need to repeat source configure.sh and no need to re-make.
Checkout the Wiki for notes on using this code.