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Image Translation

Unsolved
Computer Vision

Difficulty: 6 | Problem written by Sakar Ghimire
Problem reported in interviews at

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We can use the following transformation matrix: 

\(\begin{pmatrix} 1 & 0 & t_x\\ 0 & 1 & t_y \end{pmatrix} \)

To translate an image, we then need to calculate the dot product of every pixel and this matrix. 

For a given grayscale input image represented by a NumPy array with shape (h,w), shift distance tuple (tx,ty), and the shape of output image as a tuple (h,w), calculate and return the translated output image. 

Sample Input:
<class 'numpy.ndarray'>
src_img: [[ 1 2 3 4 5] [ 1 1 1 1 1] [ 5 66 6 5 5]]
<class 'tuple'>
shift_distance: (0, 0)
<class 'tuple'>
shape_of_out_img: (5, 5)

Expected Output:
<class 'numpy.ndarray'>
[[ 0 0 0 0 0] [ 0 1 1 1 1] [ 0 66 6 5 5] [ 0 0 0 0 0] [ 0 0 0 0 0]]

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Comments
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mo_venouziou • 2¬†months, 1¬†week ago

0

There appears to be an error in the test case. Shift distance is (0,0) but the solution has its first row and first column turned to zeros.

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numpy has been already imported as np (import numpy as np)