-
Notifications
You must be signed in to change notification settings - Fork 208
/
calibrate_camera.py
88 lines (73 loc) · 2.14 KB
/
calibrate_camera.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
import numpy as np
import cv2
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import pickle
def calibrate_camera():
# Mapping each calibration image to number of checkerboard corners
# Everything is (9,6) for now
objp_dict = {
1: (9, 5),
2: (9, 6),
3: (9, 6),
4: (9, 6),
5: (9, 6),
6: (9, 6),
7: (9, 6),
8: (9, 6),
9: (9, 6),
10: (9, 6),
11: (9, 6),
12: (9, 6),
13: (9, 6),
14: (9, 6),
15: (9, 6),
16: (9, 6),
17: (9, 6),
18: (9, 6),
19: (9, 6),
20: (9, 6),
}
# List of object points and corners for calibration
objp_list = []
corners_list = []
# Go through all images and find corners
for k in objp_dict:
nx, ny = objp_dict[k]
# Prepare object points, like (0,0,0), (1,0,0), (2,0,0) ....,(6,5,0)
objp = np.zeros((nx*ny,3), np.float32)
objp[:,:2] = np.mgrid[0:nx, 0:ny].T.reshape(-1,2)
# Make a list of calibration images
fname = 'camera_cal/calibration%s.jpg' % str(k)
img = cv2.imread(fname)
# Convert to grayscale
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# Find the chessboard corners
ret, corners = cv2.findChessboardCorners(gray, (nx, ny), None)
# If found, save & draw corners
if ret == True:
# Save object points and corresponding corners
objp_list.append(objp)
corners_list.append(corners)
# Draw and display the corners
#cv2.drawChessboardCorners(img, (nx, ny), corners, ret)
#plt.imshow(img)
#plt.show()
#print('Found corners for %s' % fname)
else:
print('Warning: ret = %s for %s' % (ret, fname))
# Calibrate camera and undistort a test image
img = cv2.imread('test_images/straight_lines1.jpg')
img_size = (img.shape[1], img.shape[0])
ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objp_list, corners_list, img_size,None,None)
return mtx, dist
if __name__ == '__main__':
mtx, dist = calibrate_camera()
save_dict = {'mtx': mtx, 'dist': dist}
with open('calibrate_camera.p', 'wb') as f:
pickle.dump(save_dict, f)
# Undistort example calibration image
img = mpimg.imread('camera_cal/calibration5.jpg')
dst = cv2.undistort(img, mtx, dist, None, mtx)
plt.imshow(dst)
plt.savefig('example_images/undistort_calibration.png')