paulsamson18/IMAGE-TRANSFORMATIONS

IMAGE TRANSFORMATION

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.

Step2:

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: Paul samson.S

Register Number: 212222230104

i)Image Translation

import numpy as np
import cv2
import matplotlib.pyplot as plt
in_img=cv2.imread("cat.jpg")
in_img=cv2.cvtColor(in_img,cv2.COLOR_BGR2RGB)
plt.axis('off')
plt.imshow(in_img)
plt.show()

ii) Image Scaling

import cv2
import matplotlib.pyplot as plt
in_img=cv2.imread("cat.jpg")
in_img=cv2.cvtColor(in_img,cv2.COLOR_BGR2RGB)
rows,cols,dim=in_img.shape
M=np.float32([[1,0,50],
              [0,1,50],
              [0,0,1]])
trans_img=cv2.warpPerspective(in_img, M, (cols,rows))
plt.axis('off')
plt.imshow(trans_img)
plt.show() 

iii)Image shearing

import numpy as np
import cv2
import matplotlib.pyplot as plt
in_img=cv2.imread("cat.jpg")
in_img=cv2.cvtColor(in_img,cv2.COLOR_BGR2RGB)
rows,cols,dim=in_img.shape
M_x=np.float32([[1,0.5,0],
                [0,1 ,0],
                [0,0 ,1]])
M_y=np.float32([[1,  0,0],
                [0.5,1,0],
                [0,  0,1]])
sheared_img_x=cv2.warpPerspective(in_img,M_x,(int(cols),int(rows)))
sheared_img_y=cv2.warpPerspective(in_img,M_y,(int(cols),int(rows)))
plt.axis('off')
plt.imshow(sheared_img_x)
plt.show()
plt.axis('off')
plt.imshow(sheared_img_y)
plt.show()

iv)Image Reflection

import numpy as np
import cv2
import matplotlib.pyplot as plt
in_img=cv2.imread("cat.jpg")
in_img=cv2.cvtColor(in_img,cv2.COLOR_BGR2RGB)
rows,cols,dim=in_img.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  ]])
reflect_x=cv2.warpPerspective(in_img,M_x,(int(cols),int(rows)))
reflect_y=cv2.warpPerspective(in_img,M_y,(int(cols),int(rows)))
plt.axis('off')
plt.imshow(reflect_x)
plt.show()
plt.axis('off')
plt.imshow(reflect_y)
plt.show()  

v)Image Rotation

import numpy as np
import cv2
import matplotlib.pyplot as plt
in_img=cv2.imread("cat.jpg")
in_img=cv2.cvtColor(in_img,cv2.COLOR_BGR2RGB)
rows,cols,dim=in_img.shape
angle=np.radians(10)
M=np.float32([[np.cos(angle),-(np.sin(angle)),0],
              [np.sin(angle),np.cos(angle),0],
              [0,0,1]])
rotated_img=cv2.warpPerspective(in_img,M,(int(cols),int(rows)))
plt.axis('off')
plt.imshow(rotated_img)
plt.show()  

vi)Image Cropping

import numpy as np
import cv2
import matplotlib.pyplot as plt
in_img = cv2.imread("cat.jpg")
in_img = cv2.cvtColor(in_img,cv2.COLOR_BGR2RGB)
plt.imshow(in_img)
plt.show()
cropped_img=in_img[10:150 ,10:250]
plt.imshow(cropped_img)
plt.show()

Output:

i)Image Translation

ii) Image Scaling

iii)Image shearing

iv)Image Reflection

v)Image Rotation

vi)Image Cropping

Original Cropped

Result:

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