Belief-propagation for binary tomography reconstruction
This Python code implements belief-propagation iterations for solving the tomography reconstruction problem for binary images with a spatial regularization.
A zipball of the source code is available on https://github.com/eddam/bp-for-tomo/zipball/demo
If you wish to download the whole versioned project, you can clone it with git (http://git-scm.com/):
$ git clone https://github.com/eddam/bp-for-tomo.git
to use this code, you will need the Python language, together with several Python modules
- python >=2.6
- numpy >= 1.4
- a C compiler
- optional: matplotlib (to plot the demo results) and scikit-image (for utility functions to preprocess real data).
Go to the bptomo directory
$ cd bptomo
And execute one of the following commands:
If you wish to use the code inside the source directory:
$ python setup.py build_ext --inplace
(this will build the compiled parts of the code, using cython).
Or you can install the package in order to import it from anywhere in the system:
$ python setup.py install --user
run the script
$ python demo_bp_flavors.py
(or, better, run the script inside the Ipython interpreter)