HOOLOOVOO

Image analysis toolbox based on a deep learning networks.

Code Author: Sam De Meyer

🔹🔷🔹

Contains tools to:

• Manipulate image and tensor objects.
• simplify the setup of an image augmentation pipeline.
• simplify setting up a training pipeline.
• parse settings files in json or yaml format.
• do piece-wise image segmentation for images that don't fit into memory.

Installation

pip install

The easiest way to install this package is using pip. First set up a python environment, preferably using conda or a pip virtualenv. Then inside the conda/venv environment execute the following command:

# fresh install
pip install git+https://github.com/MMichaelVdV/hooloovoo.git
# upgrade to newer version
pip install --upgrade git+https://github.com/MMichaelVdV/hooloovoo.git

This will automatically pull in all python dependencies. Note that a fresh install will take over a gigabyte of disk space, this is mainly due to the huge torch binaries.

manual install

Clone this repository, then make sure the contents of the hooloovoo and hooloovoo_applications folder at the root of this repository are available on your PYTHONPATH, then manually install all the dependencies listed in setup.py of this repository.

Usage

Once installed, the hooloovoo package can be used as a library.

To run one of the applications, invoke the hooloovoo command inside the conda/venv invironment.