mahotas 0.6.2

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)

Recent Changes

For version 0.6.2:

Bugfix releas:

• Fix memory leak in _surf

• More robust searching for freeimage

• More functions in mahotas.surf() to retrieve intermediate results

• Improve compilation on Windows (patches by Christoph Gohlke)

For version 0.6.1:

• Release the GIL in morphological functions

• Convolution

• just_filter option in edge.sobel()

• mahotas.labeled functions

• SURF local features

For version 0.6:

• Improve Local Binary patterns (faster and better interface)

• Much faster erode() (10x faster)

• Faster dilate() (2x faster)

• TAS for 3D images

• Haralick for 3D images

Support

Website: http://luispedro.org/software/mahotas

API Docs: http://packages.python.org/mahotas/

Mailing List: Use the pythonvision mailing list for questions, bug submissions, etc.