I'm trying to use OpenCV 2.3 python bindings to calibrate a camera. I've used the data below in matlab and the calibration worked, but I can't seem to get it to work in OpenCV. The camera matrix I setup as an initial guess is very close to the answer calculated from the matlab toolbox.
import cv2
import numpy as np
obj_points = [[-9.7,3.0,4.5],[-11.1,0.5,3.1],[-8.5,0.9,2.4],[-5.8,4.4,2.7],[-4.8,1.5,0.2],[-6.7,-1.6,-0.4],[-8.7,-3.3,-0.6],[-4.3,-1.2,-2.4],[-12.4,-2.3,0.9], [-14.1,-3.8,-0.6],[-18.9,2.9,2.9],[-14.6,2.3,4.6],[-16.0,0.8,3.0],[-18.9,-0.1,0.3], [-16.3,-1.7,0.5],[-18.6,-2.7,-2.2]]
img_points = [[993.0,623.0],[942.0,705.0],[1023.0,720.0],[1116.0,645.0],[1136.0,764.0],[1071.0,847.0],[1003.0,885.0],[1142.0,887.0],[886.0,816.0],[827.0,883.0],[710.0,636.0],[837.0,621.0],[789.0,688.0],[699.0,759.0],[768.0,800.0],[697.0,873.0]]
obj_points = np.array(obj_points)
img_points = np.array(img_points)
w = 1680
h = 1050
size = (w,h)
camera_matrix = np.zeros((3, 3))
camera_matrix[0,0]= 2200.0
camera_matrix[1,1]= 2200.0
camera_matrix[2,2]=1.0
camera_matrix[2,0]=750.0
camera_matrix[2,1]=750.0
dist_coefs = np.zeros(4)
results = cv2.calibrateCamera(obj_points, img_points,size,
camera_matrix, dist_coefs)
First off, your camera matrix is wrong. If you read the documentation, it should look like:
fx 0 cx
0 fy cy
0 0 1
If you look at yours, you've got it the wrong way round:
fx 0 0
0 fy 0
cx cy 1
So first, set camera_matrix to camera_matrix.T (or change how you construct camera_matrix. Remember that camera_matrix[i,j] is row i, column j).
camera_matrix = camera_matrix.T
Next, I ran your code and I see that "can't seem to get it to work" means the following error (by the way - always say what you mean by "can't seem to get it to work" in your questions - if it's an error, post the error. If it runs but gives you weirdo numbers, say so):
OpenCV Error: Assertion failed (ni >= 0) in collectCalibrationData, file /home/cha66i/Downloads/OpenCV-2.3.1/modules/calib3d/src/calibration.cpp, line 3161
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
cv2.error: /home/cha66i/Downloads/OpenCV-2.3.1/modules/calib3d/src/calibration.cpp:3161: error: (-215) ni >= 0 in function collectCalibrationData
I then read the documentation (very useful by the way) and noticed that obj_points and img_points have to be vectors of vectors, because it is possible to feed in sets of object/image points for multiple images of the same chessboard(/calibration points).
Hence:
cv2.calibrateCamera([obj_points], [img_points],size, camera_matrix, dist_coefs)
What? I still get the same error?!
Then, I had a look at the OpenCV python2 samples (in the folder OpenCV-2.x.x/samples/python2), and noticed a calibration.py showing me how to use the calibration functions (never underestimate the samples, they're often better than the documentation!).
I tried to run calibration.py but it doesn't run because it doesn't supply the camera_matrix and distCoeffs arguments, which are necessary. So I modified it to feed in a dummy camera_matrix and distCoeffs, and hey, it works!
The only difference I can see between my obj_points/img_points and theirs, is that theirs has dtype=float32, while mine doesn't.
So, I change my obj_points and img_points to also have dtype float32 (the python2 interface to OpenCV is funny like that; often functions don't work when matrices don't have a dtype):
obj_points = obj_points.astype('float32')
img_points = img_points.astype('float32')
Then I try again:
>>> cv2.calibrateCamera([obj_points], [img_points],size, camera_matrix, dist_coefs)
OpenCV Error: Bad argument
(For non-planar calibration rigs the initial intrinsic matrix must be specified)
in cvCalibrateCamera2, file ....
What?! A different error at least. But I did supply an initial intrinsic matrix!
So I go back to the documentation, and notice the flags parameter:
flags – Different flags that may be zero or a combination of the following values:
CV_CALIB_USE_INTRINSIC_GUESScameraMatrix contains valid initial values of fx, fy, cx, cy that are optimized further...
Aha, so I have to tell the function explicitly to use the initial guesses I provided:
cv2.calibrateCamera([obj_points], [img_points],size, camera_matrix.T, dist_coefs,
flags=cv2.CALIB_USE_INTRINSIC_GUESS)
Hurrah! It works!
(Moral of the story - read the OpenCV documentation carefully, and use the newest version (i.e. on opencv.itseez.com) if you're using the Python cv2 interface. Also, consult the examples in the samples/python2 directory to supplement the documentation. With these two things you should be able to work out most problems.)
For what it is worth, the following code snippet currently works under 2.4.6.1:
pattern_size = (16, 12)
pattern_points = np.zeros( (np.prod(pattern_size), 3), np.float32)
pattern_points[:, :2] = np.indices(pattern_size).T.reshape(-1, 2).astype(np.float32)
img_points = pattern_points[:, :2] * 2 + np.array([40, 30], np.float32)
print(cv2.calibrateCamera([pattern_points], [img_points], (400, 400), flags=cv2.CALIB_USE_INTRINSIC_GUESS))
Note that camera_matrix and dist_coefs are not needed.
After the help from mathematical.coffee I have got this 3d calibration to run.
import cv2
from cv2 import cv
import numpy as np
obj_points = [[-9.7,3.0,4.5],[-11.1,0.5,3.1],[-8.5,0.9,2.4],[-5.8,4.4,2.7],[-4.8,1.5,0.2],[-6.7,-1.6,-0.4],[-8.7,-3.3,-0.6],[-4.3,-1.2,-2.4],[-12.4,-2.3,0.9],[-14.1,-3.8,-0.6],[-18.9,2.9,2.9],[-14.6,2.3,4.6],[-16.0,0.8,3.0],[-18.9,-0.1,0.3],[-16.3,-1.7,0.5],[-18.6,-2.7,-2.2]]
img_points = [[993.0,623.0],[942.0,705.0],[1023.0,720.0],[1116.0,645.0],[1136.0,764.0],[1071.0,847.0],[1003.0,885.0],[1142.0,887.0],[886.0,816.0],[827.0,883.0],[710.0,636.0],[837.0,621.0],[789.0,688.0],[699.0,759.0],[768.0,800.0],[697.0,873.0]]
obj_points = np.array(obj_points,'float32')
img_points = np.array(img_points,'float32')
w = 1680
h = 1050
size = (w,h)
camera_matrix = np.zeros((3, 3),'float32')
camera_matrix[0,0]= 2200.0
camera_matrix[1,1]= 2200.0
camera_matrix[2,2]=1.0
camera_matrix[0,2]=750.0
camera_matrix[1,2]=750.0
dist_coefs = np.zeros(4,'float32')
retval,camera_matrix,dist_coefs,rvecs,tvecs = cv2.calibrateCamera([obj_points],[img_points],size,camera_matrix,dist_coefs,flags=cv.CV_CALIB_USE_INTRINSIC_GUESS)
The only problem I have now is why is the dist_coefs vector is 5 elements long when returned from the calibration function. the documentation says " if the vector contains four elements, it means that K3=0". But in fact K3 is is used, no matter the length of dist_coefs (4 or 5). Furthermore I can't seem to get flag CV_CALIB_FIX_K3 to work, tied to use that flag to force K3 to be zero. cashes saying an integer is required. this could be because I don't know how to do multiple flags at once, I'm just doing this, flags = (cv.CV..., cv.CV...).
Just to compare, from the matlab camera cal routine the results are...
Focal length: 2210. 2207.
principal point: 781. 738.
Distortions: 4.65e-2 -9.74e+0 3.9e-3 6.74e-3 0.0e+0
Rotation vector: 2.36 0.178 -0.131
Translation vector: 16.016 2.527 69.549
From this code,
Focal length: 1647. 1629.
principal point: 761. 711.
Distortions: -2.3e-1 2.0e+1 1.4e-2 -9.5e-2 -172e+2
Rotation vector: 2.357 0.199 -0.193
Translation vector: 16.511 3.307 48.946
I think if I could figure out how to force k3=0, the rest of the values would align right up.
Make dist_coeffs vector as 5 dimensional zero vector and then use CV_CALIB_FIX_K3 flag. You can see that last element in the vector (K3) will be zero.
When it comes to using multiple flags, you can OR them.
Example : cv.CV_CALIB_USE_INTRINSIC_GUESS | cv.CV_CALIB_FIX_K3
Use Point3f and Point2f instead of Point3d and Point2d to define object_points and image_points and it will work.
来源：https://stackoverflow.com/questions/10022568/opencv-2-3-camera-calibration