-
Notifications
You must be signed in to change notification settings - Fork 0
/
camera_in_ex_para.py
69 lines (60 loc) · 2.87 KB
/
camera_in_ex_para.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
import numpy as np
import cv2
distortion_coefficients1 = np.array([-0.145834, 0.197798, -0.001340, -0.000277, 0.000000])
distortion_coefficients2 = np.array([-0.1377, 0.1915, -0.002118, -0.000510, 0.000000])
distortion_coefficients6 = np.array([-0.148392, 0.208062, -0.000187, 0.000458, 0.000000])
distortion_coefficients = np.array([0,0,0,0,0])
'''
This can be used for projcet the pc on the images, we only use front three cameras
(cam1,cam2,cam6,cam1 is the center camera)
'''
h, w = 1200, 1920
ex_matrix_cam1 = np.array([ # cam1
[0.017452406437283574, -0.999847695156391, -5.551115123125783e-17, -0.024703597383298997],
[-0.012215140126845492, -0.00021321606402130433, -0.999925369660452, 0.03975440225788578],
[0.9997730761834054, 0.01745110395826527, -0.012217000835247127, -0.09080308692722944]
])
ex_matrix_cam2 = np.array([ # cam2
[-0.8598522715968737, -0.5105429179116056, 0.0, -0.009863877519666886],
[0.004455270896599028, -0.0075035313714476234, -0.9999619230641715, -0.06082809641205974],
[0.5105234780016824, -0.8598195310571061, 0.008726535498373912, -0.08629482217741014]
])
ex_matrix_cam6 = np.array([ # cam6
[0.8720692724321204, -0.4893824517488462, 0.0, -0.00012454852885848515],
[8.326672684688674e-17, 1.6653345369377348e-16, -0.9999999999999998, -0.04931984031870221],
[0.48938245174884615, 0.8720692724321204, 1.6653345369377348e-16, -0.08243496651085405]
])
in_matrix_cam1 = np.array([
[1288.27043, 0. , 944.73479],
[0. , 1288.57055, 617.01932],
[0. , 0. , 1. ]
])
in_matrix_cam2 = np.array([[1293.11391, 0. , 974.14537],
[0. , 1295.19251, 644.25513],
[0. , 0. , 1. ]
])
in_matrix_cam6 = np.array([
[1294.81375, 0. , 926.57962],
[0. , 1295.83987, 624.76414],
[0. , 0. , 1. ]
])
# in_matrix
newcameramtx_cam1, _ = cv2.getOptimalNewCameraMatrix(in_matrix_cam1, distortion_coefficients1, (w,h), 0, (w,h))
newcameramtx_cam2, _ = cv2.getOptimalNewCameraMatrix(in_matrix_cam2, distortion_coefficients2, (w,h), 0, (w,h))
newcameramtx_cam6, _ = cv2.getOptimalNewCameraMatrix(in_matrix_cam6, distortion_coefficients, (w,h), 0, (w,h))
''' sample code
# lidar2camera
points = np.fromfile(data_path, dtype=np.float32).reshape([-1,3])
points = np.concatenate((points,np.ones((points.shape[0],1))),1)
points_T = np.transpose(points)
points_T_camera = np.dot(ex_matrix_cam, points_T)
# camera2pixel
pixel = np.dot(in_matrix_cam, points_T_camera).T
pixel_xy = np.array([x / x[2] for x in pixel])[:, 0:2]
pixel_xy = np.around(pixel_xy).astype(int)
image = np.array(cv2.imread(image_path))
mask = (pixel_xy[:, 0] >= 0) & (pixel_xy[:, 0] < 1920) & \
(pixel_xy[:, 1] >= 0) & (pixel_xy[:, 1] < 1200) & \
(points_T_camera[2, :] > 0)
filtered_coords = pixel_xy[mask]
'''