Translation refers to shifting of object from one point to another.

Transformation matrix for translation is given by, T = 

10tx
01ty

Where,

 tx and ty are the amount of translation in x and y axis respectively.

cv2.warpAffine():

To perform linear mapping, we can use cv2.warpAffine(image, transformation_matrix, shape) function which takes a 2×3 matrix and convert the image based on the passed transformation matrix. It has three arguments:

  1. image: the image which we want to transform.
  2. transformation_matrix: it is a 2×3 matrix which is used to transform the input image. We can perform rotation, translation and other transformations by changing the transformation matrix.
  3. shape: it defines the shape(width, height) of the resultant image. 

Implemented code in Python:

import cv2
import numpy as np

img = cv2.imread('birds.jpg',1);
rows = img.shape[0];
cols = img.shape[1];

T = np.float32([[1,0,50],[0,1,25]]); #translation matrix

output_img = cv2.warpAffine(img, T, (cols,rows));

cv2.imshow('Original', img);
cv2.imshow('Output Image',output_img);

#wait for 10 seconds
cv2.waitKey(10000);
cv2.destroyAllWindows();

Output:


Implemented code in Python:

import cv2
import numpy as np

img = cv2.imread('birds.jpg',1);
rows = 100;
cols = 350;

T = np.float32([[1,0,50],[0,1,25]]); #translation matrix

output_img = cv2.warpAffine(img, T, (cols,rows));

cv2.imshow('Original', img);
cv2.imshow('Output Image',output_img);

#wait for 10 seconds
cv2.waitKey(10000);
cv2.destroyAllWindows();

Output:

Thank you Rishika Gupta for this article.


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