calibrate_fisheye_camera using KB8 for VI

calibrate_fisheye_camera.py

import cv2
#assert cv2.__version__[0] == '3', 'The fisheye module requires opencv version >= 3.0.0'
import numpy as np
import os
import glob
CHECKERBOARD = (7,10)
subpix_criteria = (cv2.TERM_CRITERIA_EPS+cv2.TERM_CRITERIA_MAX_ITER, 30, 0.1)
calibration_flags = cv2.fisheye.CALIB_RECOMPUTE_EXTRINSIC+cv2.fisheye.CALIB_CHECK_COND+cv2.fisheye.CALIB_FIX_SKEW
# calibration_flags = cv2.fisheye.CALIB_RECOMPUTE_EXTRINSIC+cv2.fisheye.CALIB_FIX_SKEW
objp = np.zeros((1, CHECKERBOARD[0]*CHECKERBOARD[1], 3), np.float32)
objp[0,:,:2] = np.mgrid[0:CHECKERBOARD[0], 0:CHECKERBOARD[1]].T.reshape(-1, 2)
_img_shape = None
objpoints = [] # 3d point in real world space
imgpoints = [] # 2d points in image plane.
images = glob.glob('*.png')
images.sort()

for fname in images:
   
    img = cv2.imread(fname)
    if _img_shape == None:
        _img_shape = img.shape[:2]
    else:
        assert _img_shape == img.shape[:2], "All images must share the same size."
    gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    # Find the chess board corners

    ret, corners = cv2.findChessboardCorners(gray, CHECKERBOARD, cv2.CALIB_CB_ADAPTIVE_THRESH+cv2.CALIB_CB_FAST_CHECK+cv2.CALIB_CB_NORMALIZE_IMAGE)
    # If found, add object points, image points (after refining them)

    if ret == True:
        objpoints.append(objp)
        cv2.cornerSubPix(gray,corners,(3,3),(-1,-1),subpix_criteria)
        imgpoints.append(corners)
    

N_OK = len(objpoints)
K = np.zeros((3, 3))
D = np.zeros((4, 1))
print("finished processing images")
rvecs = [np.zeros((1, 1, 3), dtype=np.float64) for i in range(N_OK)]
tvecs = [np.zeros((1, 1, 3), dtype=np.float64) for i in range(N_OK)]
rms, _, _, _, _ = \
    cv2.fisheye.calibrate(
        objpoints,
        imgpoints,
        gray.shape[::-1],
        K,
        D,
        rvecs,
        tvecs,
        calibration_flags,
        (cv2.TERM_CRITERIA_EPS+cv2.TERM_CRITERIA_MAX_ITER, 30, 1e-6)
    )
print("Found " + str(N_OK) + " valid images for calibration")
print("DIM=" + str(_img_shape[::-1]))
print("K=np.array(" + str(K.tolist()) + ")")
print("D=np.array(" + str(D.tolist()) + ")")
 

K2=np.array([[2.4734003025545465e+02, 0.0, 3.3626570042116441e+02], [0.0, 2.4738056560443138e+02, 2.0050730427749909e+02], [0.0, 0.0, 1.0]])
D2=np.array([[5.5420483333080472e-01], [3.4851549830571299e-01], [-8.5237465089897979e-01], [3.9202413479288289e-01]])
 
def draw_lines(img, corners, pattern_size):
    for i in range(pattern_size[1]):
        cv2.line(img, tuple(corners[i*pattern_size[0]].ravel()), tuple(corners[(i+1)*pattern_size[0]-1].ravel()), (0, 255, 0), 2)

    for i in range(pattern_size[0]):
        cv2.line(img, tuple(corners[i].ravel()), tuple(corners[pattern_size[0]*(pattern_size[1]-1)+i].ravel()), (0, 255, 0), 2)


map1, map2 = cv2.fisheye.initUndistortRectifyMap(K, D, np.eye(3), K, _img_shape[::-1], cv2.CV_16SC2)
map12, map22 = cv2.fisheye.initUndistortRectifyMap(K2, D2, np.eye(3), K2, _img_shape[::-1], cv2.CV_16SC2)
for fname in images:
    img = cv2.imread(fname)
    undistorted_img = cv2.remap(img, map1, map2, interpolation=cv2.INTER_LINEAR, borderMode=cv2.BORDER_CONSTANT)
    undistorted_img2 = cv2.remap(img, map12, map22, interpolation=cv2.INTER_LINEAR, borderMode=cv2.BORDER_CONSTANT)
    


    gray = cv2.cvtColor(undistorted_img,cv2.COLOR_BGR2GRAY)
    gray2 = cv2.cvtColor(undistorted_img2,cv2.COLOR_BGR2GRAY)



    ret, corners = cv2.findChessboardCorners(gray, CHECKERBOARD, cv2.CALIB_CB_ADAPTIVE_THRESH+cv2.CALIB_CB_FAST_CHECK+cv2.CALIB_CB_NORMALIZE_IMAGE)
    ret2, corners2 = cv2.findChessboardCorners(gray2, CHECKERBOARD, cv2.CALIB_CB_ADAPTIVE_THRESH+cv2.CALIB_CB_FAST_CHECK+cv2.CALIB_CB_NORMALIZE_IMAGE)

    # Draw lines on the undistorted images
    if corners is not None and corners2 is not None:

        draw_lines(undistorted_img, corners, CHECKERBOARD)
        draw_lines(undistorted_img2, corners2, CHECKERBOARD)


    if ret and ret2:  # If the checkerboard is found
        cv2.cornerSubPix(gray, corners, (3, 3), (-1, -1), subpix_criteria)
        cv2.drawChessboardCorners(undistorted_img, CHECKERBOARD, corners, ret)

        cv2.cornerSubPix(gray2, corners2, (3, 3), (-1, -1), subpix_criteria)
        cv2.drawChessboardCorners(undistorted_img2, CHECKERBOARD, corners2, ret2)

        # Display the rectified image with the checkerboard pattern
        cv2.imshow('Rectified Image with Checkerboard', np.hstack((undistorted_img, undistorted_img2)))
        cv2.waitKey(0)

cv2.destroyAllWindows()