python opencv implements perspective transform instance code for any Angle

This paper mainly shares 1 example of python+opencv to realize perspective transformation from any Angle, specifically as follows:

# -*- coding:utf-8 -*-
import cv2
import numpy as np


def rad(x):
  return x * np.pi / 180


img = cv2.imread("6.jfif")
cv2.imshow("original", img)

#  Extend the image to keep the content within visual range 
img = cv2.copyMakeBorder(img, 200, 200, 200, 200, cv2.BORDER_CONSTANT, 0)
w, h = img.shape[0:2]

anglex = 0
angley = 30
anglez = 0 # Is rotating 
fov = 42
while 1:
  #  The distance between the lens and the image, 21 Is a semi-viewable Angle, calculate z The distance is to ensure that the entire image is displayed exactly at this visual Angle 
  z = np.sqrt(w ** 2 + h ** 2) / 2 / np.tan(rad(fov / 2))
  #  Homogeneous transformation matrix 
  rx = np.array([[1, 0, 0, 0],
          [0, np.cos(rad(anglex)), -np.sin(rad(anglex)), 0],
          [0, -np.sin(rad(anglex)), np.cos(rad(anglex)), 0, ],
          [0, 0, 0, 1]], np.float32)

  ry = np.array([[np.cos(rad(angley)), 0, np.sin(rad(angley)), 0],
          [0, 1, 0, 0],
          [-np.sin(rad(angley)), 0, np.cos(rad(angley)), 0, ],
          [0, 0, 0, 1]], np.float32)

  rz = np.array([[np.cos(rad(anglez)), np.sin(rad(anglez)), 0, 0],
          [-np.sin(rad(anglez)), np.cos(rad(anglez)), 0, 0],
          [0, 0, 1, 0],
          [0, 0, 0, 1]], np.float32)

  r = rx.dot(ry).dot(rz)

  # 4 The generation of the point 
  pcenter = np.array([h / 2, w / 2, 0, 0], np.float32)

  p1 = np.array([0, 0, 0, 0], np.float32) - pcenter
  p2 = np.array([w, 0, 0, 0], np.float32) - pcenter
  p3 = np.array([0, h, 0, 0], np.float32) - pcenter
  p4 = np.array([w, h, 0, 0], np.float32) - pcenter

  dst1 = r.dot(p1)
  dst2 = r.dot(p2)
  dst3 = r.dot(p3)
  dst4 = r.dot(p4)

  list_dst = [dst1, dst2, dst3, dst4]

  org = np.array([[0, 0],
          [w, 0],
          [0, h],
          [w, h]], np.float32)

  dst = np.zeros((4, 2), np.float32)

  #  Project onto the image plane 
  for i in range(4):
    dst[i, 0] = list_dst[i][0] * z / (z - list_dst[i][2]) + pcenter[0]
    dst[i, 1] = list_dst[i][1] * z / (z - list_dst[i][2]) + pcenter[1]

  warpR = cv2.getPerspectiveTransform(org, dst)

  result = cv2.warpPerspective(img, warpR, (h, w))
  cv2.imshow("result", result)
  c = cv2.waitKey(30)

  # anglex += 3      #auto rotate
  # anglez += 1       #auto rotate
  # angley += 2      #auto rotate

  #  Keyboard control 
  if 27 == c: # Esc quit
    break;
  if c == ord('w'):
    anglex += 1
  if c == ord('s'):
    anglex -= 1
  if c == ord('a'):
    angley += 1
    # dx=0
  if c == ord('d'):
    angley -= 1
  if c == ord('u'):
    anglez += 1
  if c == ord('p'):
    anglez -= 1
  if c == ord('t'):
    fov += 1
  if c == ord('r'):
    fov -= 1
  if c == ord(' '):
    anglex = angley = anglez = 0
  if c == ord('q'):
    print("======================================")
    print(' Rotation matrix: \n', r)
    print("angle alpha: ", anglex, 'angle beta: ', angley, "dz: ", anglez, ": ", z)

cv2.destroyAllWindows()

conclusion

That's the end of this article on the implementation of python opencv perspective transformation at any Angle of the sample code, I hope to help you. Interested friends can continue to refer to other related topics in this site, if there is any deficiency, welcome to comment out. Thank you for your support!