praveenv23013808 / IMAGE-TRANSFORMATIONS

IMAGE-TRANSFORMATIONS

Aim

To perform image transformation such as Translation, Scaling, Shearing, Reflection, Rotation and Cropping using OpenCV and Python.

Software Required:

Anaconda - Python 3.7

Algorithm:

Step1:

Import the required packages.

Step 2:

Load the image file in the program.

Step3:

Use the techniques for Translation, Scaling, Shearing, Reflection, Rotation and Cropping using OpenCV and Python.

Step4:

Display the modified image output.

Step5:

End the program.

Program:

Developed By: praveen v Register Number: 212222233004 i)Image Translation

import numpy as np
import cv2
import matplotlib.pyplot as plt
input_image=cv2.imread("book cover.jpeg") 
input_image=cv2.cvtColor(input_image,cv2.COLOR_BGR2RGB) 
plt.axis("off") 
plt.imshow(input_image)
plt.show()
rows, cols, dim = input_image.shape
M_x=np.float32([[1,0,0 ],
                [0,-1,rows],
                [0,0,1 ]])
M_y=np.float32([[-1,0,cols ],
                [0,1,0],
                [0,0,1 ]])
reflected_img_xaxis=cv2.warpPerspective(input_image,M_x,(cols,rows))
reflected_img_yaxis=cv2.warpPerspective(input_image,M_y,(cols,rows))
plt.imshow(reflected_img_xaxis)
plt.show()

ii) Image Scaling

import numpy as np
import cv2
import matplotlib.pyplot as plt
input_image=cv2.imread("book cover.jpeg") 
input_image=cv2.cvtColor(input_image, cv2.COLOR_BGR2RGB)
angle=np.radians(45)
M=np.float32([[np.cos(angle),-(np.sin(angle)),0],
               [np.sin(angle),(np.cos(angle)),0],
               [0,0,1]])
rotated_img=cv2.warpPerspective(input_image, M, (int(cols),int(rows)))

iii)Image shearing

import numpy as np
import cv2
import matplotlib.pyplot as plt
input_image=cv2.imread("download.jpeg") 
input_image=cv2.cvtColor(input_image,cv2.COLOR_BGR2RGB) 
plt.axis("off") 
plt.imshow(input_image)
plt.show()
rows, cols, dim = input_image.shape
M_x=np.float32([[1,0.2,0],
               [0,1,0],
               [0,0,1]])
M_y=np.float32([[1, 0, 0],
                [0.5, 1, 0],
                [0,0,1]])
sheared_img_xaxis=cv2.warpPerspective(input_img,M_x,(cols,rows))
sheared_img_yaxis=cv2.warpPerspective(input_img,M_y,(cols,rows))
plt.axis('off')
plt.imshow(sheared_img_xaxis)
plt.show()
plt.axis
plt.show()

iv)Image Reflection

import numpy as np
import cv2
import matplotlib.pyplot as plt
input_image=cv2.imread("download.jpeg") 
input_image=cv2.cvtColor(input_image,cv2.COLOR_BGR2RGB) 
plt.axis("off") 
plt.imshow(input_image)
plt.show()
rows, cols, dim = input_image.shape
M_x=np.float32([[1,0,0 ],
                [0,-1,rows],
                [0,0,1 ]])
M_y=np.float32([[-1,0,cols ],
                [0,1,0],
                [0,0,1 ]])
reflected_img_xaxis=cv2.warpPerspective(input_image,M_x,(cols,rows))
reflected_img_yaxis=cv2.warpPerspective(input_image,M_y,(cols,rows))
plt.imshow(reflected_img_xaxis)
plt.show()
plt.imshow(reflected_img_yaxis)
plt.show()

v)Image Rotation

import numpy as np
import cv2
import matplotlib.pyplot as plt
input_image=cv2.imread("book cover.jpeg") 
input_image=cv2.cvtColor(input_image, cv2.COLOR_BGR2RGB)
angle=np.radians(45)
M=np.float32([[np.cos(angle),-(np.sin(angle)),0],
               [np.sin(angle),(np.cos(angle)),0],
               [0,0,1]])
rotated_img=cv2.warpPerspective(input_image, M, (int(cols),int(rows)))

vi)Image Cropping

import numpy as np
import cv2
import matplotlib.pyplot as plt
input_image=cv2.imread("download.jpeg") 
input_image=cv2.cvtColor(input_image,cv2.COLOR_BGR2RGB)
cropped_img=input_image[100:300, 100:300]
plt.imshow(cropped_img)

Output:

i)Image Translation

ii) Image Scaling

iii)Image shearing

iv)Image Reflection

v)Image Rotation

vi)Image Cropping

Result:

Thus the different image transformations such as Translation, Scaling, Shearing, Reflection, Rotation and Cropping are done using OpenCV and python programming.