我正在尝试使用python a openCV校准全向相机。在网上找不到任何Python代码。我试图自己制作,但似乎没有起作用。
我修改了校准鱼眼镜头相机的代码。
import cv2
assert cv2.__version__[0] == '4', 'The fisheye module requires opencv version >= 3.0.0'
import numpy as np
import os
import glob
CHECKERBOARD = (5,8)
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))
xi = np.zeros(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.omnidir.calibrate(
objpoints,
imgpoints,
gray.shape[::-1],
K,
xi,
D,
calibration_flags,
(cv2.TERM_CRITERIA_EPS+cv2.TERM_CRITERIA_MAX_ITER, 30, 0.1),
rvecs,
tvecs
)
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()) + ")")
不幸的是,我遇到了这个错误。错误:(-215:断言失败((!omall.empty((&& omall.depth((== statterpoints.depth(((||omall.empty((功能"校准"
有什么想法需要改变什么?谢谢
rvecs和tvecs需要与您的模式点和图像点具有相同的深度,更改
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)]
to
rvecs = [np.zeros((1, 1, 3), dtype=np.floa32) for i in range(N_OK)]
tvecs = [np.zeros((1, 1, 3), dtype=np.float32) for i in range(N_OK)]