mahotas 0.5.3

Mahotas: Python Image Processing Library

Image Processing Library for Python.

It includes a couple of algorithms implemented in C++ for speed while operating
in numpy arrays.

Notable algorithms:
- watershed.
- thresholding.
- convex points calculations.
- hit & miss. thinning.
- Zernike & Haralick features.
- freeimage based numpy image loading (requires freeimage libraries to be
installed).


Examples
--------

This is a simple example of loading a file (called `test.jpeg`) and calling
`watershed` using above threshold regions as a seed (we use Otsu to define
threshold).

::

import numpy as np
from scipy import ndimage
import mahotas
import pylab

img = mahotas.imread('test.jpeg')
T_otsu = mahotas.thresholding.otsu(img)
seeds,_ = ndimage.label(img > T_otsu)
labeled = mahotas.cwatershed(img.max() - img, seeds)

pylab.imshow(labeled)


Support
-------

*Website*: `http://luispedro.org/software/mahotas
<http://luispedro.org/software/mahotas>`_

*API Docs*: `http://packages.python.org/mahotas/
<http://packages.python.org/mahotas/>`_

*Mailing List*: Use the `pythonvision mailing list
<http://groups.google.com/group/pythonvision?pli=1>`_ for questions, bug
submissions, etc.