Page 306 - AI Computer 10

Dispaly an image in Jupyter notebook with the help of the following code:

import cv2 from matplotlib Output
import pyplot as plt
import numpy as np
image = cv2.imread(‘F:\Softwares\Setups\
DataScience\
Deepa\img1.jpg’)
plt.imshow(cv2.cvtColor(image,cv2.COLOR_
BGR2RGB))
plt.title(‘Summer Camp 2025’)
plt.axis(‘on’)
plt.show( )
Now, copy a specific part of an image i.e. the Dance Callout. To do so, we can write the following code:
import cv2 from matplotlib Output
import pyplot as plt
import numpy as np
image = cv2.imread(‘F:\Softwares\Setups\
DataScience\
Deepa\img1.jpg’)
extract_part = image[150:300,50:260]
plt.imshow(cv2.cvtColor(extract_part,
cv2.COLOR_BGR2RGB))
plt.axis(‘on’)
plt.show( )
Now, we want to insert the extracted part in the image at a particular location. To do this, we can write the
following code:

import cv2 from matplotlib Output
import pyplot as plt
import numpy as np
image = cv2.imread(‘F:\Softwares\Setups\
DataScience\Deepa\img1.jpg’)
extract_part = image[150:300,50:260]
image[50:200,0:210] = extract_part
plt.imshow(cv2.cvtColor(image, cv2.COLOR_
BGR2RGB))
plt.axis(‘on’)
plt.show( )
Resizing An Image

Resizing an image is an important part of image processing technique because on resizing an image, its pixel
information is changed. For example, when an image is reduced in size, any unneeded pixel information will be
discarded by the photo editor like Photoshop. When an image is enlarged, the photo editor must create and add
new pixel information on the basis of its best guesses to achieve a larger size which typically results in either a
very pixelated or very soft and blurry looking image. In case of AI systems, resizing images is important especially
when we want to train a model having the same size and aspect ratio.

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