In this article, we are going to depict images using the Matplotlib module in grayscale representation using PIL, i.e. image representation using two colors only i.e. black and white.
Syntax: matplotlib.pyplot.imshow(X, cmap=None)
Displaying Grayscale image
Displaying Grayscale image, store the image path here let’s say it fname. Now open the image using PIL image method and convert it to L mode If you have an L mode image, that means it is a single-channel image – normally interpreted as grayscale. It only stores a grayscale, not color. Plotting the image as cmap = ‘gray’ converts the colors. All the work is done you can now see your image.
Python3
# storing image pathfname = r'g4g.png'# opening image using pilimage = Image.open(fname).convert("L")# mapping image to gray scaleplt.imshow(image, cmap='gray')plt.show() |
Output:
Example 1:
Python3
# importing libraries.import numpy as npimport matplotlib.pyplot as pltfrom PIL import Image# storing image pathfname = r'gfg.png'# opening image using pilimage = Image.open(fname).convert("L")# mapping image to gray scaleplt.imshow(image, cmap='gray')plt.show() |
Output:
Image used
Example 2:
Python3
# importing libraries.import numpy as npimport matplotlib.pyplot as pltfrom PIL import Image# storing image pathfname = r'Lazyroar.png'# opening image using pilimage = Image.open(fname).convert("L")# mapping image to gray scaleplt.imshow(image, cmap='gray')plt.show() |
Output:
Image Used
