code: def test_opencv_five_coeff(self, device, dtype):
      # Test using 5 distortion coefficients
      pts = torch.tensor(
          [
              [1028.0374, 788.7520],
              [1025.1218, 716.8726],
              [1022.1792, 645.1857],
          ],
          device=device,
          dtype=dtype,
      )
  
      K = torch.tensor(
          [
              [1.7315e03, 0.0000e00, 6.2289e02],
              [0.0000e00, 1.7320e03, 5.3537e02],
              [0.0000e00, 0.0000e00, 1.0000e00],
          ],
          device=device,
          dtype=dtype,
      )
  
      dist = torch.tensor(
          [-0.1007, 0.2650, -0.0018, 0.0007, -0.2597],
          device=device,
          dtype=dtype,
      )
  
      # Expected output generated with OpenCV:
      # import cv2
      # ptsu_expected = cv2.undistortPoints(pts.numpy().reshape(-1,1,2), K.numpy(),
      #                               dist1.numpy(), None, None, K.numpy()).reshape(-1,2)
      ptsu_expected = torch.tensor(
          [
              [1030.5992, 790.65533],
              [1027.3059, 718.10020],
              [1024.0700, 645.90600],
          ],
          device=device,
          dtype=dtype,
      )
      ptsu = undistort_points(pts, K, dist)
      assert_close(ptsu, ptsu_expected, rtol=1e-4, atol=1e-4)
  
      new_K = K * 2
      new_K[2, 2] = 1
      # Expected output generated with OpenCV:
      # import cv2
      # ptsu_expected = cv2.undistortPoints(pts.numpy().reshape(-1,1,2), K.numpy(),
      #                                    dist.numpy(), None, None, new_K.numpy()).reshape(-1,2)
      print(ptsu_expected)
      ptsu_expected = 2 * torch.tensor(
          [
              [1030.5992, 790.65533],
              [1027.3059, 718.10020],
              [1024.0700, 645.90600],
          ],
          device=device,
          dtype=dtype,
      )
      print(ptsu_expected)
      ptsu = undistort_points(pts, K, dist, new_K)
      assert_close(ptsu, ptsu_expected, rtol=1e-4, atol=1e-4)
  
imports: import pytest
  import torch
  from kornia.geometry.calibration.undistort import undistort_image, undistort_points
  from kornia.testing import assert_close, gradcheck
label_desc: Use image node_id 4 for calling the TestUndistortPoints obj's underlying member method code with example usage: obj.test_opencv_five_coeff(device, dtype) without return types