scikit-image is an image processing Python package that works with NumPy arrays which is a collection of algorithms for image processing. Let’s discuss how to deal with images into set of information and it’s some application in the real world.
Important features of scikit-image :
Simple and efficient tools for image processing and computer vision techniques.
Accessible to everybody and reusable in various contexts.
Built on the top of NumPy, SciPy, and matplotlib.
Open source, commercially usable – BSD license.
Note : Before installing scikit-image, ensure that NumPy and SciPy are pre-installed. Now, the easiest way to install scikit-image is using
pip install -U scikit-image
Most functions of skimage are found within submodules. Images are represented as NumPy arrays, for example 2-D arrays for grayscale 2-D images.
Code #1 :
numpy.ndarray (512, 512)
Code #2 : skimage.data submodule provides a set of functions returning example images.
Code #3 : Load own images as NumPy arrays from image files.
- Analysis of Medical images.
- Classification of images for detection.
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