我正在尝试按照以下说明来校准鱼眼镜头https://medium.com/@kennethjiang/calibrate-fisheye-lens-usis-using-opencv-333b05afa0b0您可以在哪里找到我用于校准部分的完整代码。
我到达了：
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-3)
)
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()) + ")")
我得到此错误：
Traceback (most recent call last)
<ipython-input-10-deaca9981fe4> in <module>()
13 tvecs,
14 calibration_flags,
---> 15 (cv2.TERM_CRITERIA_EPS+cv2.TERM_CRITERIA_MAX_ITER, 30, 1e-3)
16 )
17 print("Found " + str(N_OK) + " valid images for calibration")
error: C:ciopencv_1512688052760workmodulescalib3dsrcfisheye.cpp:1414:
error: (-3) CALIB_CHECK_COND - Ill-conditioned matrix for input array 0 in
function cv::internal::CalibrateExtrinsics
我不明白发生了什么，我只能在互联网周围找到如此少的信息，有人经历了类似的事情并知道如何解决这个问题吗？
谢谢
这些是我正在使用的棋盘板的图像：
- https://i.stack.imgur.com/gohig.jpg
- https://i.stack.imgur.com/kja3o.jpg
- https://i.stack.imgur.com/xbizh.jpg
- https://i.stack.imgur.com/uq9gr.jpg
- https://i.stack.imgur.com/n8alj.jpg
- https://i.stack.imgur.com/jmmmz.jpg
- https://i.stack.imgur.com/qj8wn.jpg
- https://i.stack.imgur.com/nmifq.jpg
- https://i.stack.imgur.com/sqhdd.jpg
- https://i.stack.imgur.com/dnbud.jpg
- https://i.stack.imgur.com/vftoo.jpg
- https://i.stack.imgur.com/lhkf5.jpg
我认为这是因为您的变量校准_flags具有calib_check_cond集。尝试禁用此标志。没有它，我就可以不介绍您的图像(请参见下面的链接(。
我不确定此检查是什么(文档不是很明确(。该旗帜拒绝我的GoPro Hero 3的一些图像。即使可以看到棋盘并检测到棋盘。在我的情况下，20个图像不是通过此测试。此图像在靠近左边框的棋盘上。
- https://i.stack.imgur.com/m2wf6.jpg
- https://i.stack.imgur.com/kitrz.jpg
- https://i.stack.imgur.com/mhhyn.jpg
- https://i.stack.imgur.com/psiyg.jpg
- https://i.stack.imgur.com/drxsl.jpg
- https://i.stack.imgur.com/ddze1.jpg
- https://i.stack.imgur.com/b6l8f.jpg
- https://i.stack.imgur.com/9mrak.jpg
- https://i.stack.imgur.com/wymg5.jpg
- https://i.stack.imgur.com/rmj5q.jpg
- https://i.stack.imgur.com/k8k8y.jpg
- https://i.stack.imgur.com/miber.jpg
¹在OPENCV版本中> = 3.4.1错误消息告诉您哪个图像未通过测试
我没有在python中找到代码，因此我在边缘上用棋盘手动检查图像，然后一个一个删除它们，直到错误消失。
正如@Ahmadiah所述，当棋盘落在图像边缘附近时，"条件疾病"的事情可能发生。处理此操作的一种方法是，一一删除图像，并在导致校准失败时重试。这是我们这样做的示例：
def calibrate_fisheye(all_image_points, all_true_points, image_size):
""" Calibrate a fisheye camera from matching points.
:param all_image_points: Sequence[Array(N, 2)[float32]] of (x, y) image coordinates of the points. (see cv2.findChessboardCorners)
:param all_true_points: Sequence[Array(N, 3)[float32]] of (x,y,z) points. (If from a grid, just put (x,y) on a regular grid and z=0)
Note that each of these sets of points can be in its own reference frame,
:param image_size: The (size_y, size_x) of the image.
:return: (rms, mtx, dist, rvecs, tvecs) where
rms: float - The root-mean-squared error
mtx: array[3x3] A 3x3 camera intrinsics matrix
dst: array[4x1] A (4x1) array of distortion coefficients
rvecs: Sequence[array[N,3,1]] of estimated rotation vectors for each set of true points
tvecs: Sequence[array[N,3,1]] of estimated translation vectors for each set of true points
"""
assert len(all_true_points) == len(all_image_points)
all_true_points = list(all_true_points) # Because we'll modify it in place
all_image_points = list(all_image_points)
while True:
assert len(all_true_points) > 0, "There are no valid images from which to calibrate."
try:
rms, mtx, dist, rvecs, tvecs = cv2.fisheye.calibrate(
objectPoints=[p[None, :, :] for p in all_true_points],
imagePoints=[p[:, None, :] for p in all_image_points],
image_size=image_size,
K=np.zeros((3, 3)),
D=np.zeros((4, 1)),
flags=cv2.fisheye.CALIB_RECOMPUTE_EXTRINSIC + cv2.fisheye.CALIB_CHECK_COND + cv2.fisheye.CALIB_FIX_SKEW,
criteria=(cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 1e-6),
)
print('Found a calibration based on {} well-conditioned images.'.format(len(all_true_points)))
return rms, mtx, dist, rvecs, tvecs
except cv2.error as err:
try:
idx = int(err.message.split('array ')[1][0]) # Parse index of invalid image from error message
all_true_points.pop(idx)
all_image_points.pop(idx)
print("Removed ill-conditioned image {} from the data. Trying again...".format(idx))
except IndexError:
raise err
我的openCV版本是4.0 ，我通过此方法
将其滑过rms, _, _, _, _ =
cv2.fisheye.calibrate(
objpoints,
imgpoints,
#gray.shape[::-1],
gray.shape,
K,
D,
rvecs,
tvecs,
calibration_flags,
(cv2.TERM_CRITERIA_EPS+cv2.TERM_CRITERIA_MAX_ITER, 30, 1e-3)
)