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README.md

autotres

Build Status

What is it?

autotres is a collection of tools to analyze tongue surface contours in ultrasound images.

Where did it come from?

autotres is a direct descendant of AutoTrace (AutoTrace III). Read about the original in Jeff Berry's dissertation:

@phdthesis{berry2012diss,
  title={Machine learning methods for articulatory data},
  author={Berry, Jeffrey James},
  year={2012},
  school={The University of Arizona.}
}

Installation

Dependencies

We recommend running the project using a virtual environment. virtualenv can be installed with pip install virtualenv.

  1. virtualenv -p python3 venv
  2. source venv/bin/activate

Installation instructions:

System dependencies

OSX

The system dependencies can be installed via homebrew:

brew update;
brew install python3;
brew install gfortran;
brew tap homebrew/science;
brew install openblas;
brew install hdf5;

Linux

sudo apt-get update;
sudo apt-get install build-essential;
sudo apt-get install gcc;
sudo apt-get install python3-dev;
sudo apt-get install libhdf5-dev;
sudo apt-get install gfortran;
sudo apt-get build-dep libopenblas-dev;
sudo apt-get build-dep nvidia-cuda-toolkit;

Installing autotres and its Python dependencies:

pip install -e .

Using autotres

We provide network training and usage tutorials under examples.

Example data

You will need git-lfs to pull the example data.

Once you've installed git-lfs, simply run this command:

git-lfs fetch

Training networks

Networks can be trained using either a GPU or CPU. GPU training will save a great deal of time.

GPU-based training

The code for training deep networks uses Lasagne, a wrapper for Theano. One of the advantages of relying on these libraries is that networks can easily be trained on a CUDA-capable GPU, if present (with limited support for open-cl).

CPU-based training

If no GPU is present, Theano will use the CPU. For best results, a BLAS library with multithreading support is suggested, such as 'BLAS' or OpenBLAS.

What's missing?

Currently, the project lacks a graphical interface, and has only been tested on Ubuntu 14.04 and OSX 10.11. With luck, future versions will rectify these shortcomings.