Friday 20 August 2021

Opencv cv.calibrateCamera returns "argument for calibrateCamera() given by name ('flags') and position (8)"

I am trying to calibrate a camera using known data from a image (pixel positions) and realworld positions.

Here is what I know about:

Camera

focal_length  = 3.9
image_height  = 3456 
image_width   = 4608
esl_height    = 35  
sensor_height = 4.69
sensor_width  = 6.26
pixel_size    = 1.34/1000
FOV_x         = 71.9
FOV_y         = 56.7

F_x = image_width /(2 * tan(FOV_x* pi / 360))
F_y = image_height /(2 * tan(FOV_y* pi / 360))

C_x = image_width / 2
C_y = image_height / 2

row1 = [F_x,0,C_x]
row2 = [0,F_y, C_y]
row3 = [0,0,1]


camera_matrix = np.matrix([row1,row2,row3])

which gives:

matrix([[3.17701054e+03, 0.00000000e+00, 2.30400000e+03],
        [0.00000000e+00, 3.20254589e+03, 1.72800000e+03],
        [0.00000000e+00, 0.00000000e+00, 1.00000000e+00]])

Data

I have a dataset containing 49 points for which I have both the real-world (x,y) positions (I also have the z values, but I am really only interested in the (x,y) position. Also, I have the pixel positions for all these points in an image (They are the bounding box centers in the object deterction I perform.

  id  manual.location.x  manual.location.y  manual.location.z  \
0    0            32.9878            41.9033              0.215   
1    1            32.9878            44.4404              0.215   
2    2            32.9878            44.4404              0.215   
3    3            32.9878            44.4404              0.565   
4    4            32.9878            44.4404              0.565   
5    5            32.9878            44.4404              0.565   
6    6            32.9878            44.4404              0.565   
7    7            32.9878            44.4404              0.565   
8    8            32.9878            41.9033              0.753   
9    9            32.9878            44.4404              0.779   
10  10            32.9878            44.4404              0.779   
11  11            32.9878            44.4404              0.779   
12  12            32.9878            41.9033              1.024   
13  13            32.9878            44.4404              1.024   
14  14            32.9878            42.7490              1.100   
15  15            32.9878            43.5947              1.100   
16  16            32.9878            43.5947              1.100   
17  17            32.9878            43.5947              1.100   
18  18            32.9878            43.5947              1.100   
19  19            32.9878            44.4404              1.231   
20  20            32.9878            44.4404              1.231   
21  21            32.9878            44.4404              1.231   
22  22            32.9878            44.4404              1.231   
23  23            32.9878            42.7490              1.320   
24  24            32.9878            43.5947              1.412   
25  25            32.9878            42.7490              1.412   
26  26            32.9878            43.5947              1.412   
27  27            32.9878            44.4404              1.412   
28  28            32.9878            44.4404              1.458   
29  29            32.9878            44.4404              1.458   
30  30            32.9878            44.4404              1.458   
31  31            32.9878            44.4404              1.458   
32  32            32.9878            42.7490              1.620   
33  33            32.9878            42.7490              1.620   
34  34            32.9878            43.5947              1.620   
35  35            32.9878            43.5947              1.620   
36  36            32.9878            42.7490              1.620   
37  37            32.9878            44.4404              1.651   
38  38            32.9878            44.4404              1.651   
39  39            32.9878            44.4404              1.651   
40  40            32.9878            44.4404              1.651   
41  41            32.9878            44.4404              1.651   
42  42            32.9878            42.7490              1.850   
43  43            32.9878            42.7490                NaN   
44  44            32.9878            44.4404                NaN   
45  45            32.9878            44.4404                NaN   
46  46            32.9878            44.4404              1.850   
47  47            32.9878            43.5947              1.850   
48  48            32.9878            44.4404              1.850   

    bbox_center_x  bbox_center_y  
0          4269.5         2914.0  
1          1035.0         2883.5  
2           843.5         2880.0  
3          1516.5         2529.0  
4          1247.5         2527.0  
5          1730.0         2525.5  
6           987.0         2522.0  
7           765.5         2520.0  
8          4435.0         2356.5  
9          1196.0         2257.0  
10          938.5         2255.0  
11          704.5         2250.0  
12         4547.0         1998.0  
13         1291.0         1980.0  
14         3681.0         1864.5  
15         2394.0         1856.0  
16         1931.5         1854.0  
17         2043.0         1853.5  
18         2043.0         1853.5  
19         1620.0         1676.0  
20         1267.0         1675.5  
21          847.0         1672.5  
22          593.5         1669.5  
23         3783.5         1452.0  
24         1931.5         1446.5  
25         3346.5         1443.5  
26         2878.0         1443.0  
27         1632.0         1350.0  
28         1409.0         1346.5  
29          945.0         1339.5  
30          727.0         1334.0  
31          534.5         1332.0  
32         4349.0         1109.0  
33         3859.0         1101.0  
34         1920.5         1097.5  
35         2878.0         1090.5  
36         3364.0         1087.0  
37         1460.5         1037.0  
38         1290.5         1036.0  
39         1065.5         1034.0  
40          748.0         1032.5  
41          473.0         1029.0  
42         4262.0          726.0  
43         3683.5          713.0  
44         1375.0          710.0  
45         1094.5          708.0  
46          850.0          705.0  
47         3103.5          702.5  
48          375.5          701.5  

To make things easier, I am willing to let the z-coordinate (manual.location.z) of realworld positions be 0.

Now, I trried the following thing using cv.calibrateCamera on data with z-coordinate = 0. So, I did the following:

manual.location.x  manual.location.y  manual.location.z  bbox_center_x  \
0             32.9878            41.9033                  0         4269.5   
1             32.9878            44.4404                  0         1035.0   
2             32.9878            44.4404                  0          843.5   
3             32.9878            44.4404                  0         1516.5   
4             32.9878            44.4404                  0         1247.5   
5             32.9878            44.4404                  0         1730.0   
6             32.9878            44.4404                  0          987.0   
7             32.9878            44.4404                  0          765.5   
8             32.9878            41.9033                  0         4435.0   
9             32.9878            44.4404                  0         1196.0   
10            32.9878            44.4404                  0          938.5   
11            32.9878            44.4404                  0          704.5   
12            32.9878            41.9033                  0         4547.0   
13            32.9878            44.4404                  0         1291.0   
14            32.9878            42.7490                  0         3681.0   
15            32.9878            43.5947                  0         2394.0   
16            32.9878            43.5947                  0         1931.5   
17            32.9878            43.5947                  0         2043.0   
18            32.9878            43.5947                  0         2043.0   
19            32.9878            44.4404                  0         1620.0   
20            32.9878            44.4404                  0         1267.0   
21            32.9878            44.4404                  0          847.0   
22            32.9878            44.4404                  0          593.5   
23            32.9878            42.7490                  0         3783.5   
24            32.9878            43.5947                  0         1931.5   
25            32.9878            42.7490                  0         3346.5   
26            32.9878            43.5947                  0         2878.0   
27            32.9878            44.4404                  0         1632.0   
28            32.9878            44.4404                  0         1409.0   
29            32.9878            44.4404                  0          945.0   
30            32.9878            44.4404                  0          727.0   
31            32.9878            44.4404                  0          534.5   
32            32.9878            42.7490                  0         4349.0   
33            32.9878            42.7490                  0         3859.0   
34            32.9878            43.5947                  0         1920.5   
35            32.9878            43.5947                  0         2878.0   
36            32.9878            42.7490                  0         3364.0   
37            32.9878            44.4404                  0         1460.5   
38            32.9878            44.4404                  0         1290.5   
39            32.9878            44.4404                  0         1065.5   
40            32.9878            44.4404                  0          748.0   
41            32.9878            44.4404                  0          473.0   
42            32.9878            42.7490                  0         4262.0   
46            32.9878            44.4404                  0          850.0   
47            32.9878            43.5947                  0         3103.5   
48            32.9878            44.4404                  0          375.5   

    bbox_center_y  
0          2914.0  
1          2883.5  
2          2880.0  
3          2529.0  
4          2527.0  
5          2525.5  
6          2522.0  
7          2520.0  
8          2356.5  
9          2257.0  
10         2255.0  
11         2250.0  
12         1998.0  
13         1980.0  
14         1864.5  
15         1856.0  
16         1854.0  
17         1853.5  
18         1853.5  
19         1676.0  
20         1675.5  
21         1672.5  
22         1669.5  
23         1452.0  
24         1446.5  
25         1443.5  
26         1443.0  
27         1350.0  
28         1346.5  
29         1339.5  
30         1334.0  
31         1332.0  
32         1109.0  
33         1101.0  
34         1097.5  
35         1090.5  
36         1087.0  
37         1037.0  
38         1036.0  
39         1034.0  
40         1032.5  
41         1029.0  
42          726.0  
46          705.0  
47          702.5  
48          701.5  

and prepared the data for calibration of the cammera:

data = df_p.to_numpy()

pts3d = data[:, 0:3] 
pts2d = data[:, 3:5] 
pts3d = pts3d.reshape(1,-1, 3) 
pts2d = pts2d.reshape(1,-1, 2)

image_height  = 3456 
image_width   = 4608

w = image_width
h = image_height

pts3d = pts3d.astype('float32')
pts2d = pts2d.astype('float32')

size = (w,h)

and finally:

image_height  = 3456 
image_width   = 4608

tvec = np.array([0, 0, 0], dtype=np.float32)  #Camera is static
rvec = np.array([0, 0, 0], dtype=np.float32)  #Camera is static

distCoeffs =np.array([0,0,0,0,0], dtype=np.float32)

cv.calibrateCamera([pts3d], [pts2d],size,camera_matrix,None,None,None,None,flags=cv.CALIB_FIX_K1+cv.CALIB_FIX_K2+cv.CALIB_FIX_K3+cv.CALIB_FIX_K4+cv.CALIB_FIX_K5)

But this returns:

---------------------------------------------------------------------------
error                                     Traceback (most recent call last)
<ipython-input-374-406d179adbf6> in <module>
     17 distCoeffs =np.array([0, 0, 0,0,0], dtype=np.float32)
     18 
---> 19 cv.calibrateCamera([pts3d], [pts2d],size,camera_matrix,None,None,None,None,flags=cv.CALIB_FIX_K1+cv.CALIB_FIX_K2+cv.CALIB_FIX_K3+cv.CALIB_FIX_K4+cv.CALIB_FIX_K5)

error: OpenCV(4.5.3) :-1: error: (-5:Bad argument) in function 'calibrateCamera'
> Overload resolution failed:
>  - argument for calibrateCamera() given by name ('flags') and position (8)
>  - argument for calibrateCamera() given by name ('flags') and position (8)

Even this:

cv.calibrateCamera([pts3d], [pts2d],size,camera_matrix,distCoeffs,None,None,None,flags=cv.CALIB_FIX_K1+cv.CALIB_FIX_K2+cv.CALIB_FIX_K3+cv.CALIB_FIX_K4+cv.CALIB_FIX_K5)

returns the same error.

I have no clue about what I do wrong.

What do I want? I want to be able to get the distortion coefficients for my camera. This way or any other way that gives me satisfactory results.



from Opencv cv.calibrateCamera returns "argument for calibrateCamera() given by name ('flags') and position (8)"

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