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main.py
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main.py
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#!usr/bin/env/ python
# _*_ coding:utf-8 _*_
import cv2 as cv
import numpy as np
import os
import glob
from homography import get_homography
from intrinsics import get_intrinsics_param
from extrinsics import get_extrinsics_param
from distortion import get_distortion
from refine_all import refinall_all_param
def calibrate(pic_points, real_points_x_y):
# 求单应矩阵
H = get_homography(pic_points, real_points_x_y)
# 求内参
intrinsics_param = get_intrinsics_param(H)
# 求对应每幅图外参
extrinsics_param = get_extrinsics_param(H, intrinsics_param)
# 畸变矫正
k = get_distortion(intrinsics_param, extrinsics_param, pic_points, real_points_x_y)
# 微调所有参数
max_raial_error, [new_intrinsics_param, new_k, new_extrinsics_param] = refinall_all_param(intrinsics_param, k, extrinsics_param, real_points, pic_points)
#print("total max error:\t", max_raial_error)
#print("intrinsics_parm:\t", new_intrinsics_param)
#print("distortionk:\t", new_k)
#print("extrinsics_parm:\t", new_extrinsics_param)
MyRecord.write("total max error:\n")
MyRecord.write(str(max_raial_error))
MyRecord.write("\n")
MyRecord.write("intrinsics_parm:\n")
MyRecord.write(str(new_intrinsics_param))
MyRecord.write("\n")
MyRecord.write("distortionk:\n")
MyRecord.write(str(new_k))
MyRecord.write("\n")
MyRecord.write("extrinsics_parm:\n")
MyRecord.write(str(new_extrinsics_param))
MyRecord.write("\n")
if __name__ == "__main__":
# 定义记录输出数据的文件目录
record_dir = r"record"
MyRecord = open(os.path.join(record_dir, r"myrecord.txt"), "w")
StandardRecord = open(os.path.join(record_dir, r"standardrecord.txt"), "w")
file_dir = r'images'
# 标定所用图像
pic_name = os.listdir(file_dir)
# 由于棋盘为二维平面，设定世界坐标系在棋盘上，一个单位代表一个棋盘宽度，产生世界坐标系三维坐标
cross_corners = [9, 6] # 棋盘方块交界点排列
real_coor = np.zeros((cross_corners[0] * cross_corners[1], 3), np.float32)
real_coor[:, :2] = np.mgrid[0:9*30:30, 0:6*30:30].T.reshape(-1, 2)
real_points = []
real_points_x_y = []
pic_points = []
flag = True
for pic in pic_name:
pic_path = os.path.join(file_dir, pic)
pic_data = cv.imread(pic_path)
# 寻找到棋盘角点
succ, pic_coor = cv.findChessboardCorners(pic_data, (cross_corners[0], cross_corners[1]), None)
if succ:
# 灰度化
pic_data = cv.cvtColor(pic_data, cv.COLOR_RGB2GRAY)
#获取图像大小
if flag:
size = pic_data.shape[::-1]
flag = False
# 亚像素精细化
cv.cornerSubPix(
pic_data,
pic_coor,
(11, 11),
(-1, -1),
(cv.TermCriteria_MAX_ITER + cv.TermCriteria_EPS, 30, 0.01)
)
# 添加每幅图的对应3D-2D坐标
pic_coor = pic_coor.reshape(-1, 2)
pic_points.append(pic_coor)
real_points.append(real_coor)
real_points_x_y.append(real_coor[:, :2])
pic_points1 = pic_points.copy()
real_points_x_y1 = real_points_x_y.copy()
#调用自己定义的标定函数
calibrate(pic_points, real_points_x_y)
MyRecord.close()
#使用OpenCV库函数标定
ret, mtx, dist, rvecs, tvecs = cv.calibrateCamera(real_points, pic_points, size, None, None)
W = []#外参矩阵
for i in range(len(tvecs)):
Rotate_M = (cv.Rodrigues(rvecs[i]))[0]
w = np.concatenate((Rotate_M, tvecs[i]), axis=1)
w = np.array(w)
W.append(w)
StandardRecord.write("Reprojection error:\n")
StandardRecord.write(str(ret))
StandardRecord.write("\n")
StandardRecord.write("intrinsics_parm:\n")
StandardRecord.write(str(mtx))
StandardRecord.write("\n")
StandardRecord.write("distortionk:\n")
StandardRecord.write(str(dist))
StandardRecord.write("\n")
StandardRecord.write("extrinsics_parm:\n")
for i in range(len(W)):
StandardRecord.write(str(W[i]))
StandardRecord.write("\n\n")