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.
# storing image path fname = r 'g4g.png'
# opening image using pil image = Image. open (fname).convert( "L" )
# mapping image to gray scale plt.imshow(image, cmap = 'gray' )
plt.show() |
Output:
Example 1:
# importing libraries. import numpy as np
import matplotlib.pyplot as plt
from PIL import Image
# storing image path fname = r 'gfg.png'
# opening image using pil image = Image. open (fname).convert( "L" )
# mapping image to gray scale plt.imshow(image, cmap = 'gray' )
plt.show() |
Output:
Example 2:
# importing libraries. import numpy as np
import matplotlib.pyplot as plt
from PIL import Image
# storing image path fname = r 'geeks.png'
# opening image using pil image = Image. open (fname).convert( "L" )
# mapping image to gray scale plt.imshow(image, cmap = 'gray' )
plt.show() |
Output: