cv2.perspectiveTransform() not performing the operation

Question

I want to apply a transformation matrix to a set of points. So the set of points:

points = np.array([[0 ,20], [0, 575], [0, 460]])

And I want to use the matrix I calculated with cv2.getPerspectiveTransform() which is a 3x3 matrix.

matrix = np.array([
   [  -4.       ,   -3.       , 1920.     ],
   [  -2.25     ,   -1.6875   , 1080.     ],
   [  -0.0020833,   -0.0015625,    1.     ]])

Then I pass the array and a matrix to the following function:

def poly_points_transform(poly_points, matrix):
  poly_points_transformed = np.empty_like(poly_points)
  for i in range(len(poly_points)):
    point = np.array([[poly_points[i]]])
    transformed_point = cv2.perspectiveTransform(point, matrix)
    np.append(poly_points_transformed, transformed_point)

  return poly_points_transformed

Now It doesn't throw an error, but it just copies the src array to the poly_points_transformed. It might be something really rudimentary and stupid. If it is the case, I am sorry, but could someone give me a hint on what is wrong? Thanks in advance

Not sure about python, but in c++ cv2.perspectiveTransform takes a list of points as input, maybe that's the problem? So you could try poly_points_transformed=cv2.perspectiveTransform(poly_points, matrix) — Micka, Sep 08 '22 at 18:18

score 1 · Accepted Answer · answered Sep 08 '22 at 20:36

We may solve it with one line of code:

transformed_point = cv2.perspectiveTransform(np.array([points], np.float64), matrix)[0]

As Micka commented cv2.perspectiveTransform takes a list of points (and returns a list of points as output).

np.array([points]) is used because cv2.perspectiveTransform expects 3D array.
For details see trouble getting cv.transform to work.
np.float64 is used in case the dtype of points is int32 (the method accepts float64 and float32 types).
[0] is used for removing the redundant dimension (convert from 3D to 2D).

For fixing the loop, replace np.append(poly_points_transformed, transformed_point) with:
poly_points_transformed[i] = transformed_point[0].

Since the array is initialized to poly_points_transformed = np.empty_like(poly_points), we can't use np.append().

Code sample:

import cv2
import numpy as np

points = np.array([[0.0 ,20.0], [0.0, 575.0], [0.0, 460.0]])

matrix = np.array([
   [  -4.       ,   -3.       , 1920.     ],
   [  -2.25     ,   -1.6875   , 1080.     ],
   [  -0.0020833,   -0.0015625,    1.     ]])

# transformed_point = cv2.perspectiveTransform(np.array([points], np.float64), matrix)[0]

def poly_points_transform(poly_points, matrix):
    poly_points_transformed = np.empty_like(poly_points)
    for i in range(len(poly_points)):
        point = np.array([[poly_points[i]]])
        transformed_point = cv2.perspectiveTransform(point, matrix)
        poly_points_transformed[i] = transformed_point[0] #np.append(poly_points_transformed, transformed_point)

    return poly_points_transformed


poly_points_transformed = poly_points_transform(points, matrix)

The result is:

poly_points_transformed = 
    array([[1920., 1080.],
           [1920., 1080.],
           [1920., 1080.]])

Why are we getting [1920.0, 1080.0] value for all the transformed points?

Lets transform the middle point mathematically:

Multiply matrix by point (with 1 in the third index)

[  -4.       ,   -3.       , 1920.     ]   [  0]
[  -2.25     ,   -1.6875   , 1080.     ] * [575] = 
[  -0.0020833,   -0.0015625,    1.     ]   [  1]

p = matrix @ np.array([[0.0], [575.0], [1.0]]) = 

[1.950000e+02]
[1.096875e+02]
[1.015625e-01]

Now divide the coordinates by the last element (converting homogeneous coordinates to Euclidian coordinates):

[1.950000e+02/1.015625e-01]              [1920]
[1.096875e+02/1.015625e-01] = p / p[2] = [1080]
[1.015625e-01/1.015625e-01]              [   1]

The equivalent Euclidian point is [1920, 1080].

The transformation matrix may be wrong, because it transforms all the input points (with x coordinate equals 0) to the same output point...

cv2.perspectiveTransform() not performing the operation

1 Answers1