使用OpenCV校准鱼眼镜头的方法

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 = (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_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('*.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 calibration
DIM=(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]])

DIM=XXX
K=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)