Is there a way to load the calibration matrix into a video feed and get the correct calibrated output video?

Question

I have calibrated the matrix and I am getting perfect calibrated image, but is there a way to do this with live video feed? Because every example in the web outputs an image but I want to know if it is possible to grab the video using VidCapture and then write the caliberated output using VidWrite. https://medium.com/@kennethjiang/calibrate-fisheye-lens-using-opencv-333b05afa0b0

How to load the calibration matrix for a live video?

I am following the above link as an inspiration.

# You should replace these 3 lines with the output in calibration step
DIM=XXX
K=np.array(YYY)
D=np.array(ZZZ)
def undistort(img_path, balance=0.0, dim2=None, dim3=None):
    img = cv2.imread(img_path)
    dim1 = img.shape[:2][::-1]  #dim1 is the dimension of input image to un-distort
    assert dim1[0]/dim1[1] == DIM[0]/DIM[1], "Image to undistort needs to have same aspect ratio as the ones used in calibration"
    if not dim2:
        dim2 = dim1
    if not dim3:
        dim3 = dim1
    scaled_K = K * dim1[0] / DIM[0]  # The values of K is to scale with image dimension.
    scaled_K[2][2] = 1.0  # Except that K[2][2] is always 1.0
    # This is how scaled_K, dim2 and balance are used to determine the final K used to un-distort image. OpenCV document failed to make this clear!
    new_K = cv2.fisheye.estimateNewCameraMatrixForUndistortRectify(scaled_K, D, dim2, np.eye(3), balance=balance)
    map1, map2 = cv2.fisheye.initUndistortRectifyMap(scaled_K, D, np.eye(3), new_K, dim3, cv2.CV_16SC2)
    undistorted_img = cv2.remap(img, map1, map2, interpolation=cv2.INTER_LINEAR, borderMode=cv2.BORDER_CONSTANT)
    cv2.imshow("undistorted", undistorted_img)
    cv2.waitKey(0)
    cv2.destroyAllWindows()
if __name__ == '__main__':
    for p in sys.argv[1:]:
        undistort(p)