使用OpenCV校准鱼眼镜头

import cv2assert cv2.__version__[0] == '3', 'The fisheye module requires opencv version >= 3.0.0'import numpy as npimport osimport globCHECKERBOARD = (6,9)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_SKEWobjp = 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 = Noneobjpoints = [] # 3d point in real world spaceimgpoints = [] # 2d points in image plane.images = glob.glob('*.jpg')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))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()) + ")")

Found 36 images for calibrationDIM=(1600, 1200)K=np.array([[781.3524863867165, 0.0, 794.7118000552183], [0.0, 779.5071163774452, 561.3314451453386], [0.0, 0.0, 1.0]])D=np.array([[-0.042595202508066574], [0.031307765215775184], [-0.04104704724832258], [0.015343014605793324]])

# You should replace these 3 lines with the output in calibration stepDIM=XXXK=np.array(YYY)D=np.array(ZZZ)def undistort(img_path):img = cv2.imread(img_path)h,w = img.shape[:2]map1, map2 = cv2.fisheye.initUndistortRectifyMap(K, D, np.eye(3), K, DIM, 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)