mirror of
https://github.com/opencv/opencv.git
synced 2024-12-05 01:39:13 +08:00
241 lines
8.0 KiB
Python
Executable File
241 lines
8.0 KiB
Python
Executable File
#!/usr/bin/env python
|
|
|
|
'''
|
|
Plot camera calibration extrinsics.
|
|
|
|
usage:
|
|
camera_calibration_show_extrinsics.py [--calibration <input path>] [--cam_width] [--cam_height] [--scale_focal] [--patternCentric ]
|
|
|
|
default values:
|
|
--calibration : left_intrinsics.yml
|
|
--cam_width : 0.064/2
|
|
--cam_height : 0.048/2
|
|
--scale_focal : 40
|
|
--patternCentric : True
|
|
'''
|
|
|
|
# Python 2/3 compatibility
|
|
from __future__ import print_function
|
|
|
|
import numpy as np
|
|
import cv2 as cv
|
|
|
|
from numpy import linspace
|
|
|
|
def inverse_homogeneoux_matrix(M):
|
|
R = M[0:3, 0:3]
|
|
T = M[0:3, 3]
|
|
M_inv = np.identity(4)
|
|
M_inv[0:3, 0:3] = R.T
|
|
M_inv[0:3, 3] = -(R.T).dot(T)
|
|
|
|
return M_inv
|
|
|
|
def transform_to_matplotlib_frame(cMo, X, inverse=False):
|
|
M = np.identity(4)
|
|
M[1,1] = 0
|
|
M[1,2] = 1
|
|
M[2,1] = -1
|
|
M[2,2] = 0
|
|
|
|
if inverse:
|
|
return M.dot(inverse_homogeneoux_matrix(cMo).dot(X))
|
|
else:
|
|
return M.dot(cMo.dot(X))
|
|
|
|
def create_camera_model(camera_matrix, width, height, scale_focal, draw_frame_axis=False):
|
|
fx = camera_matrix[0,0]
|
|
fy = camera_matrix[1,1]
|
|
focal = 2 / (fx + fy)
|
|
f_scale = scale_focal * focal
|
|
|
|
# draw image plane
|
|
X_img_plane = np.ones((4,5))
|
|
X_img_plane[0:3,0] = [-width, height, f_scale]
|
|
X_img_plane[0:3,1] = [width, height, f_scale]
|
|
X_img_plane[0:3,2] = [width, -height, f_scale]
|
|
X_img_plane[0:3,3] = [-width, -height, f_scale]
|
|
X_img_plane[0:3,4] = [-width, height, f_scale]
|
|
|
|
# draw triangle above the image plane
|
|
X_triangle = np.ones((4,3))
|
|
X_triangle[0:3,0] = [-width, -height, f_scale]
|
|
X_triangle[0:3,1] = [0, -2*height, f_scale]
|
|
X_triangle[0:3,2] = [width, -height, f_scale]
|
|
|
|
# draw camera
|
|
X_center1 = np.ones((4,2))
|
|
X_center1[0:3,0] = [0, 0, 0]
|
|
X_center1[0:3,1] = [-width, height, f_scale]
|
|
|
|
X_center2 = np.ones((4,2))
|
|
X_center2[0:3,0] = [0, 0, 0]
|
|
X_center2[0:3,1] = [width, height, f_scale]
|
|
|
|
X_center3 = np.ones((4,2))
|
|
X_center3[0:3,0] = [0, 0, 0]
|
|
X_center3[0:3,1] = [width, -height, f_scale]
|
|
|
|
X_center4 = np.ones((4,2))
|
|
X_center4[0:3,0] = [0, 0, 0]
|
|
X_center4[0:3,1] = [-width, -height, f_scale]
|
|
|
|
# draw camera frame axis
|
|
X_frame1 = np.ones((4,2))
|
|
X_frame1[0:3,0] = [0, 0, 0]
|
|
X_frame1[0:3,1] = [f_scale/2, 0, 0]
|
|
|
|
X_frame2 = np.ones((4,2))
|
|
X_frame2[0:3,0] = [0, 0, 0]
|
|
X_frame2[0:3,1] = [0, f_scale/2, 0]
|
|
|
|
X_frame3 = np.ones((4,2))
|
|
X_frame3[0:3,0] = [0, 0, 0]
|
|
X_frame3[0:3,1] = [0, 0, f_scale/2]
|
|
|
|
if draw_frame_axis:
|
|
return [X_img_plane, X_triangle, X_center1, X_center2, X_center3, X_center4, X_frame1, X_frame2, X_frame3]
|
|
else:
|
|
return [X_img_plane, X_triangle, X_center1, X_center2, X_center3, X_center4]
|
|
|
|
def create_board_model(extrinsics, board_width, board_height, square_size, draw_frame_axis=False):
|
|
width = board_width*square_size
|
|
height = board_height*square_size
|
|
|
|
# draw calibration board
|
|
X_board = np.ones((4,5))
|
|
#X_board_cam = np.ones((extrinsics.shape[0],4,5))
|
|
X_board[0:3,0] = [0,0,0]
|
|
X_board[0:3,1] = [width,0,0]
|
|
X_board[0:3,2] = [width,height,0]
|
|
X_board[0:3,3] = [0,height,0]
|
|
X_board[0:3,4] = [0,0,0]
|
|
|
|
# draw board frame axis
|
|
X_frame1 = np.ones((4,2))
|
|
X_frame1[0:3,0] = [0, 0, 0]
|
|
X_frame1[0:3,1] = [height/2, 0, 0]
|
|
|
|
X_frame2 = np.ones((4,2))
|
|
X_frame2[0:3,0] = [0, 0, 0]
|
|
X_frame2[0:3,1] = [0, height/2, 0]
|
|
|
|
X_frame3 = np.ones((4,2))
|
|
X_frame3[0:3,0] = [0, 0, 0]
|
|
X_frame3[0:3,1] = [0, 0, height/2]
|
|
|
|
if draw_frame_axis:
|
|
return [X_board, X_frame1, X_frame2, X_frame3]
|
|
else:
|
|
return [X_board]
|
|
|
|
def draw_camera_boards(ax, camera_matrix, cam_width, cam_height, scale_focal,
|
|
extrinsics, board_width, board_height, square_size,
|
|
patternCentric):
|
|
from matplotlib import cm
|
|
|
|
min_values = np.zeros((3,1))
|
|
min_values = np.inf
|
|
max_values = np.zeros((3,1))
|
|
max_values = -np.inf
|
|
|
|
if patternCentric:
|
|
X_moving = create_camera_model(camera_matrix, cam_width, cam_height, scale_focal)
|
|
X_static = create_board_model(extrinsics, board_width, board_height, square_size)
|
|
else:
|
|
X_static = create_camera_model(camera_matrix, cam_width, cam_height, scale_focal, True)
|
|
X_moving = create_board_model(extrinsics, board_width, board_height, square_size)
|
|
|
|
cm_subsection = linspace(0.0, 1.0, extrinsics.shape[0])
|
|
colors = [ cm.jet(x) for x in cm_subsection ]
|
|
|
|
for i in range(len(X_static)):
|
|
X = np.zeros(X_static[i].shape)
|
|
for j in range(X_static[i].shape[1]):
|
|
X[:,j] = transform_to_matplotlib_frame(np.eye(4), X_static[i][:,j])
|
|
ax.plot3D(X[0,:], X[1,:], X[2,:], color='r')
|
|
min_values = np.minimum(min_values, X[0:3,:].min(1))
|
|
max_values = np.maximum(max_values, X[0:3,:].max(1))
|
|
|
|
for idx in range(extrinsics.shape[0]):
|
|
R, _ = cv.Rodrigues(extrinsics[idx,0:3])
|
|
cMo = np.eye(4,4)
|
|
cMo[0:3,0:3] = R
|
|
cMo[0:3,3] = extrinsics[idx,3:6]
|
|
for i in range(len(X_moving)):
|
|
X = np.zeros(X_moving[i].shape)
|
|
for j in range(X_moving[i].shape[1]):
|
|
X[0:4,j] = transform_to_matplotlib_frame(cMo, X_moving[i][0:4,j], patternCentric)
|
|
ax.plot3D(X[0,:], X[1,:], X[2,:], color=colors[idx])
|
|
min_values = np.minimum(min_values, X[0:3,:].min(1))
|
|
max_values = np.maximum(max_values, X[0:3,:].max(1))
|
|
|
|
return min_values, max_values
|
|
|
|
def main():
|
|
import argparse
|
|
|
|
parser = argparse.ArgumentParser(description='Plot camera calibration extrinsics.',
|
|
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
|
|
parser.add_argument('--calibration', type=str, default='left_intrinsics.yml',
|
|
help='YAML camera calibration file.')
|
|
parser.add_argument('--cam_width', type=float, default=0.064/2,
|
|
help='Width/2 of the displayed camera.')
|
|
parser.add_argument('--cam_height', type=float, default=0.048/2,
|
|
help='Height/2 of the displayed camera.')
|
|
parser.add_argument('--scale_focal', type=float, default=40,
|
|
help='Value to scale the focal length.')
|
|
parser.add_argument('--patternCentric', action='store_true',
|
|
help='The calibration board is static and the camera is moving.')
|
|
args = parser.parse_args()
|
|
|
|
fs = cv.FileStorage(cv.samples.findFile(args.calibration), cv.FILE_STORAGE_READ)
|
|
board_width = int(fs.getNode('board_width').real())
|
|
board_height = int(fs.getNode('board_height').real())
|
|
square_size = fs.getNode('square_size').real()
|
|
camera_matrix = fs.getNode('camera_matrix').mat()
|
|
extrinsics = fs.getNode('extrinsic_parameters').mat()
|
|
|
|
import matplotlib.pyplot as plt
|
|
from mpl_toolkits.mplot3d import Axes3D # pylint: disable=unused-variable
|
|
|
|
fig = plt.figure()
|
|
ax = fig.gca(projection='3d')
|
|
ax.set_aspect("auto")
|
|
|
|
cam_width = args.cam_width
|
|
cam_height = args.cam_height
|
|
scale_focal = args.scale_focal
|
|
min_values, max_values = draw_camera_boards(ax, camera_matrix, cam_width, cam_height,
|
|
scale_focal, extrinsics, board_width,
|
|
board_height, square_size, args.patternCentric)
|
|
|
|
X_min = min_values[0]
|
|
X_max = max_values[0]
|
|
Y_min = min_values[1]
|
|
Y_max = max_values[1]
|
|
Z_min = min_values[2]
|
|
Z_max = max_values[2]
|
|
max_range = np.array([X_max-X_min, Y_max-Y_min, Z_max-Z_min]).max() / 2.0
|
|
|
|
mid_x = (X_max+X_min) * 0.5
|
|
mid_y = (Y_max+Y_min) * 0.5
|
|
mid_z = (Z_max+Z_min) * 0.5
|
|
ax.set_xlim(mid_x - max_range, mid_x + max_range)
|
|
ax.set_ylim(mid_y - max_range, mid_y + max_range)
|
|
ax.set_zlim(mid_z - max_range, mid_z + max_range)
|
|
|
|
ax.set_xlabel('x')
|
|
ax.set_ylabel('z')
|
|
ax.set_zlabel('-y')
|
|
ax.set_title('Extrinsic Parameters Visualization')
|
|
|
|
plt.show()
|
|
print('Done')
|
|
|
|
|
|
if __name__ == '__main__':
|
|
print(__doc__)
|
|
main()
|
|
cv.destroyAllWindows()
|