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228 lines
7.6 KiB
Python
Executable File
228 lines
7.6 KiB
Python
Executable File
#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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# Python 2/3 compatibility
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from __future__ import print_function
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import numpy as np
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import cv2 as cv
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from numpy import linspace
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def inverse_homogeneoux_matrix(M):
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R = M[0:3, 0:3]
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T = M[0:3, 3]
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M_inv = np.identity(4)
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M_inv[0:3, 0:3] = R.T
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M_inv[0:3, 3] = -(R.T).dot(T)
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return M_inv
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def transform_to_matplotlib_frame(cMo, X, inverse=False):
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M = np.identity(4)
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M[1,1] = 0
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M[1,2] = 1
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M[2,1] = -1
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M[2,2] = 0
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if inverse:
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return M.dot(inverse_homogeneoux_matrix(cMo).dot(X))
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else:
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return M.dot(cMo.dot(X))
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def create_camera_model(camera_matrix, width, height, scale_focal, draw_frame_axis=False):
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fx = camera_matrix[0,0]
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fy = camera_matrix[1,1]
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focal = 2 / (fx + fy)
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f_scale = scale_focal * focal
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# draw image plane
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X_img_plane = np.ones((4,5))
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X_img_plane[0:3,0] = [-width, height, f_scale]
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X_img_plane[0:3,1] = [width, height, f_scale]
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X_img_plane[0:3,2] = [width, -height, f_scale]
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X_img_plane[0:3,3] = [-width, -height, f_scale]
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X_img_plane[0:3,4] = [-width, height, f_scale]
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# draw triangle above the image plane
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X_triangle = np.ones((4,3))
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X_triangle[0:3,0] = [-width, -height, f_scale]
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X_triangle[0:3,1] = [0, -2*height, f_scale]
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X_triangle[0:3,2] = [width, -height, f_scale]
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# draw camera
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X_center1 = np.ones((4,2))
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X_center1[0:3,0] = [0, 0, 0]
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X_center1[0:3,1] = [-width, height, f_scale]
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X_center2 = np.ones((4,2))
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X_center2[0:3,0] = [0, 0, 0]
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X_center2[0:3,1] = [width, height, f_scale]
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X_center3 = np.ones((4,2))
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X_center3[0:3,0] = [0, 0, 0]
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X_center3[0:3,1] = [width, -height, f_scale]
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X_center4 = np.ones((4,2))
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X_center4[0:3,0] = [0, 0, 0]
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X_center4[0:3,1] = [-width, -height, f_scale]
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# draw camera frame axis
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X_frame1 = np.ones((4,2))
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X_frame1[0:3,0] = [0, 0, 0]
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X_frame1[0:3,1] = [f_scale/2, 0, 0]
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X_frame2 = np.ones((4,2))
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X_frame2[0:3,0] = [0, 0, 0]
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X_frame2[0:3,1] = [0, f_scale/2, 0]
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X_frame3 = np.ones((4,2))
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X_frame3[0:3,0] = [0, 0, 0]
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X_frame3[0:3,1] = [0, 0, f_scale/2]
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if draw_frame_axis:
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return [X_img_plane, X_triangle, X_center1, X_center2, X_center3, X_center4, X_frame1, X_frame2, X_frame3]
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else:
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return [X_img_plane, X_triangle, X_center1, X_center2, X_center3, X_center4]
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def create_board_model(extrinsics, board_width, board_height, square_size, draw_frame_axis=False):
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width = board_width*square_size
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height = board_height*square_size
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# draw calibration board
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X_board = np.ones((4,5))
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#X_board_cam = np.ones((extrinsics.shape[0],4,5))
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X_board[0:3,0] = [0,0,0]
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X_board[0:3,1] = [width,0,0]
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X_board[0:3,2] = [width,height,0]
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X_board[0:3,3] = [0,height,0]
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X_board[0:3,4] = [0,0,0]
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# draw board frame axis
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X_frame1 = np.ones((4,2))
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X_frame1[0:3,0] = [0, 0, 0]
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X_frame1[0:3,1] = [height/2, 0, 0]
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X_frame2 = np.ones((4,2))
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X_frame2[0:3,0] = [0, 0, 0]
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X_frame2[0:3,1] = [0, height/2, 0]
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X_frame3 = np.ones((4,2))
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X_frame3[0:3,0] = [0, 0, 0]
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X_frame3[0:3,1] = [0, 0, height/2]
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if draw_frame_axis:
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return [X_board, X_frame1, X_frame2, X_frame3]
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else:
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return [X_board]
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def draw_camera_boards(ax, camera_matrix, cam_width, cam_height, scale_focal,
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extrinsics, board_width, board_height, square_size,
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patternCentric):
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from matplotlib import cm
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min_values = np.zeros((3,1))
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min_values = np.inf
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max_values = np.zeros((3,1))
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max_values = -np.inf
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if patternCentric:
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X_moving = create_camera_model(camera_matrix, cam_width, cam_height, scale_focal)
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X_static = create_board_model(extrinsics, board_width, board_height, square_size)
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else:
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X_static = create_camera_model(camera_matrix, cam_width, cam_height, scale_focal, True)
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X_moving = create_board_model(extrinsics, board_width, board_height, square_size)
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cm_subsection = linspace(0.0, 1.0, extrinsics.shape[0])
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colors = [ cm.jet(x) for x in cm_subsection ]
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for i in range(len(X_static)):
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X = np.zeros(X_static[i].shape)
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for j in range(X_static[i].shape[1]):
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X[:,j] = transform_to_matplotlib_frame(np.eye(4), X_static[i][:,j])
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ax.plot3D(X[0,:], X[1,:], X[2,:], color='r')
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min_values = np.minimum(min_values, X[0:3,:].min(1))
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max_values = np.maximum(max_values, X[0:3,:].max(1))
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for idx in range(extrinsics.shape[0]):
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R, _ = cv.Rodrigues(extrinsics[idx,0:3])
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cMo = np.eye(4,4)
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cMo[0:3,0:3] = R
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cMo[0:3,3] = extrinsics[idx,3:6]
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for i in range(len(X_moving)):
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X = np.zeros(X_moving[i].shape)
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for j in range(X_moving[i].shape[1]):
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X[0:4,j] = transform_to_matplotlib_frame(cMo, X_moving[i][0:4,j], patternCentric)
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ax.plot3D(X[0,:], X[1,:], X[2,:], color=colors[idx])
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min_values = np.minimum(min_values, X[0:3,:].min(1))
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max_values = np.maximum(max_values, X[0:3,:].max(1))
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return min_values, max_values
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def main():
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import argparse
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parser = argparse.ArgumentParser(description='Plot camera calibration extrinsics.',
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formatter_class=argparse.ArgumentDefaultsHelpFormatter)
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parser.add_argument('--calibration', type=str, default='left_intrinsics.yml',
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help='YAML camera calibration file.')
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parser.add_argument('--cam_width', type=float, default=0.064/2,
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help='Width/2 of the displayed camera.')
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parser.add_argument('--cam_height', type=float, default=0.048/2,
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help='Height/2 of the displayed camera.')
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parser.add_argument('--scale_focal', type=float, default=40,
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help='Value to scale the focal length.')
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parser.add_argument('--patternCentric', action='store_true',
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help='The calibration board is static and the camera is moving.')
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args = parser.parse_args()
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fs = cv.FileStorage(cv.samples.findFile(args.calibration), cv.FILE_STORAGE_READ)
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board_width = int(fs.getNode('board_width').real())
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board_height = int(fs.getNode('board_height').real())
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square_size = fs.getNode('square_size').real()
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camera_matrix = fs.getNode('camera_matrix').mat()
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extrinsics = fs.getNode('extrinsic_parameters').mat()
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import matplotlib.pyplot as plt
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from mpl_toolkits.mplot3d import Axes3D
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fig = plt.figure()
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ax = fig.gca(projection='3d')
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ax.set_aspect("equal")
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cam_width = args.cam_width
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cam_height = args.cam_height
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scale_focal = args.scale_focal
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min_values, max_values = draw_camera_boards(ax, camera_matrix, cam_width, cam_height,
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scale_focal, extrinsics, board_width,
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board_height, square_size, args.patternCentric)
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X_min = min_values[0]
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X_max = max_values[0]
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Y_min = min_values[1]
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Y_max = max_values[1]
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Z_min = min_values[2]
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Z_max = max_values[2]
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max_range = np.array([X_max-X_min, Y_max-Y_min, Z_max-Z_min]).max() / 2.0
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mid_x = (X_max+X_min) * 0.5
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mid_y = (Y_max+Y_min) * 0.5
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mid_z = (Z_max+Z_min) * 0.5
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ax.set_xlim(mid_x - max_range, mid_x + max_range)
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ax.set_ylim(mid_y - max_range, mid_y + max_range)
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ax.set_zlim(mid_z - max_range, mid_z + max_range)
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ax.set_xlabel('x')
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ax.set_ylabel('z')
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ax.set_zlabel('-y')
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ax.set_title('Extrinsic Parameters Visualization')
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plt.show()
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print('Done')
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if __name__ == '__main__':
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print(__doc__)
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main()
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cv.destroyAllWindows()
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