In [12]:

    

import cv2
import numpy as np
import matplotlib.pyplot as plt

%matplotlib inline
plt.rcParams["figure.figsize"] = (8,6)


    

In [16]:

    

np_bgr_image = cv2.imread('./lena2.png', 1)
np_rgb_image = cv2.cvtColor(np_bgr_image, cv2.COLOR_BGR2RGB)
plt.imshow(np_rgb_image)
plt.show()


    

In [18]:

    

np_bgr_image.shape


    

    
Out[18]:





(407, 288, 3)

In [19]:

    

np_bgr_image.dtype


    

    
Out[19]:





dtype('uint8')

In [24]:

    

height, width = np_rgb_image.shape[:2]
resized_image = cv2.resize(np_rgb_image, (int(width/2), int(height/2)))


    

In [25]:

    

print ('resized image shape:', resized_image.shape)
plt.imshow(resized_image)
plt.show()


    

    




resized image shape: (203, 144, 3)






    

In [28]:

    

M = np.float32([[1,0,20],[0,1,40]])
translated_image = cv2.warpAffine(np_rgb_image, M,(width, height))

print ('translated image shape:', translated_image.shape)
plt.imshow(translated_image)
plt.show()


    

    




translated image shape: (407, 288, 3)






    

In [29]:

    

M= cv2.getRotationMatrix2D((width/2, height/2), 45, 1)
rotated_image = cv2.warpAffine(np_rgb_image, M, (width, height))

print ('rotated image shape:',rotated_image.shape)
plt.imshow(rotated_image)
plt.show()


    

    




rotated image shape: (407, 288, 3)






    

In [30]:

    

np_gray_image = cv2.cvtColor(np_bgr_image, cv2.COLOR_BGR2GRAY)
laplacian = cv2.Laplacian(np_gray_image, cv2.CV_8U)
print ('gradient image shape:',laplacian.shape)
plt.imshow(laplacian, cmap='gray')
plt.show()


    

    




gradient image shape: (407, 288)






    

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