Mahotas is a library of fast computer vision algorithms (all implemented in C++ for speed) operating over NumPy arrays.
It includes many algorithms implemented in C++ for speed while operating in numpy arrays and with a very clean Python interface.
Mahotas currently has over 100 functions for image processing and computer vision and it keeps growing. This is free and open source software.
Key Features
- Watershed.
- Convex points calculations.
- Hit & miss. thinning.
- Zernike & Haralick, local binary patterns, and TAS features.
- Morphological processing.
- Speeded-Up Robust Features (SURF), a form of local features.
- Thresholding.
- Convolution.
- Sobel edge detection.
Website: mahotas.readthedocs.io
Support: GitHub Code Repository
Developer: Luis Pedro Coelho, Zachary Pincus, Peter J. Verveer, Davis King
License: Open source
Mahotas is written in Python and C++. Learn Python with our recommended free books and free tutorials. Learn C++ with our recommended free books and free tutorials.
Related Software
| Image Processing Libraries | |
|---|---|
| matplotlib | Python 2D plotting library |
| OpenCV | Library that includes several hundreds of computer vision algorithms |
| VIPS | Fast image processing library with low memory requirements |
| SciPy | Scientific Computing Tools for Python |
| Pillow | Fork of the Python Imaging Library |
| Pillow-SIMD | Highly optimized downstream Pillow fork |
| scikit-image | Collection of algorithms for image processing |
| ImageMagick | Uses multiple computational threads to increase performance |
| GraphicsMagick | Billed as the Swiss army knife of image processing. |
| GEGL | Generic Graphics Library |
| Mahotas | Library of fast computer vision algorithms |
| SimpleITK | Image analysis toolkit with a large number of components |
| Netpbm | Toolkit for manipulation of graphic images |
| LibGD | Library for the dynamic creation of images by developers |
Read our verdict in the software roundup.
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