06_translating_images.py

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#                   BASICS 0.6: Translating Images OpenCV                     #
#                              by: Todd Farr                                  #
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# imports
import numpy as np
import cv2

# Translation is the shifting of objects location. If you know the shift in
# (x,y) direction, let it be (t_x,t_y), you can create the transformation matrix
# M as follows:
#
#      M =  | 1  0  t_x |
#           | 0  1  t_y |
#
# You'll need to make it into a Numpy array of type np.float32 and pass it into
# cv2.warpAffine() function.

# read in an image
img = cv2.imread('images/saturn.png', 0) # the second argument 0 will set mono
rows, cols = img.shape[:2] # get the number of rows and columns
translate_x = 50 # translate in the x direction by 50 pixels
translate_y = 50 # translate in the y direction by 50 pixels
M = np.float32([[1, 0, translate_x], [0, 1, translate_y]]) # create M

# translate the image and show
img_translated = cv2.warpAffine(img, M, (cols, rows))
cv2.imshow('Translated Image', img_translated)
cv2.waitKey(0)
cv2.destroyAllWindows()

# WARNING: Third argument of the cv2.warpAffine() function is the size of the
# output image, which should be in the form of (width, height).
# Remember width = number of columns, and height = number of rows.