Image processing with Scikitimage in Python (original) (raw)

Last Updated : 19 Jan, 2023

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 in set of information and its 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 :

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 :

Python3 `

Python3 program to process

images using scikit-image

importing data from skimage

from skimage import data

camera = data.camera()

An image with 512 rows

and 512 columns

type(camera)

print(camera.shape)

`

Output :

numpy.ndarray (512, 512)

Code #2 : skimage.data submodule provides a set of functions returning example images.

Python `

Python3 program to process

images using scikit-image

importing filters and

data from skimage

from skimage import filters from skimage import data

Predefined function to fetch data

coins = data.coins()

way to find threshold

threshold_value = filters.threshold_otsu(coins)

print(threshold_value)

`

Output :

107

Code #3 : Load own images as NumPy arrays from image files.

Python `

Python3 program to process

images using scikit-image

import os

importing io from skimage

import skimage from skimage import io

way to load car image from file

file = os.path.join(skimage.data_dir, 'cc.jpg')

cars = io.imread(file)

way to show the input image

io.imshow(cars) io.show()

`

Output :

Applications :