Mahotas is an image processing library for Python. It includes a couple of algorithms implemented in C++ for speed while operating in numpy arrays. The main algorithms are watershed and Otsu thresholding.
| Tags | Image Processing Scientific computer vision |
|---|---|
| Licenses | MIT |
| Operating Systems | Cross Platform |
| Implementation | Python C C++ |
Recent releases


Release Notes: This release reduces the dependencies needed at runtime. matplotlib is now only needed in certain cases (instead of being imported at the start). Similarly, tests no longer depend on an image IO library. Compared to the previously-released beta versions, there were only a few small changes.


Release Notes: A minor release that adds dense SURF calculation and post-filtering SLIC segmentation as well as several documentation fixes.


Release Notes: This release adds several new functions: haralick_features, circle_se, bernsen (local thresholding). It adds an out parameter to morph functions that were missing it. It uses a direct implementation of binary erosion/dilation in two-dimensional C arrays.


Release Notes: This release adds a color conversion module (mahotas.color) as well as a basic SLIC super-pixels implementation and a few extra label handling functions: relabel and remove_regions. There are bugfixes for distance function and median_filter.


Release Notes: This version adds several new morphological functions: subm, cdilate, and tophat transforms. It adds border handling to functions where it was missing, such as border, euler, and bwperim. It includes a few fixes for older compilers.