Mahotas is a computer vision and image processing and manipulation library for Python. A library is a collection of functions and methods that allows you to perform many actions without having to write hundreds of lines of code. Mahotas includes many algorithms that operates with arrays, mahotas currently has over 100 functions for image processing and computer vision and is constantly growing.
Mahotas provides a good solution in finding patterns in the image for example “Where’s Wally Problem” can be solved easily using Mahotas.
How to install Mahotas :
pip install mahotas
Notable algorithms available in Mahotas :
2. Convex points calculations.
3. Hit & miss, thinning.
4. Zernike & Haralick, LBP, and TAS features.
5. Speeded-Up Robust Features (SURF), a form of local features.
8. Sobel edge detection.
9. Spline interpolation
10. SLIC super pixels.
Example 1: Loading Image
Example 2: Creating distance transform
Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.
To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course.
- Labeled Image Function in Python Mahotas
- Loading Image using Mahotas - Python
- Mahotas - Re-Labeling
- Mahotas - Labelled Image from the Normal Image
- Mahotas - Getting Mean Value of Image
- Mahotas - Element Structure for Eroding Image
- Mahotas - RGB to Gray Conversion
- Mahotas - Dilating Image
- Mahotas - Eroding Image
- Mahotas - Opening Process on Image
- Mahotas - Element Structure for Dilating Image
- Where's Wally Problem using Mahotas
- Mahotas - Sizes of Labeled Region
- Mahotas - Weight of Labeled Region
- Mahotas - Filtering Region
- Mahotas - Removing Bordered Labeled
- Mahotas - Filtering Labels
- Mahotas - Setting Threshold
- Mahotas - Gaussian filtering
- Mahotas - Transforming image using Daubechies wavelet
If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to firstname.lastname@example.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.
Please Improve this article if you find anything incorrect by clicking on the "Improve Article" button below.