#提取所有检测图片
import glob
images = glob.glob("E:\Test_imges/*.jpg")
#棋盘标定
# coding=utf-8
import cv2
import numpy as np
# 设置寻找亚像素角点的参数，采用的停止准则是最大循环次数30和最大误差容限0.001
criteria = (cv2.TERM_CRITERIA_MAX_ITER | cv2.TERM_CRITERIA_EPS, 30, 0.001)
#设定棋盘横纵参数
x,y=11,8
# 获取标定板角点的位置
objp = np.zeros((x * y, 3), np.float32)
objp[:, :2] = np.mgrid[0:x, 0:y].T.reshape(-1, 2) # 将世界坐标系建在标定板上，所有点的Z坐标全部为0，所以只需要赋值x和y
obj_points = [] # 存储3D点
img_points = [] # 存储2D点
i=0
for fname in images:
img = cv2.imread(fname)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
size = gray.shape[::-1]
ret, corners = cv2.findChessboardCorners(gray, (x, y), None)
#print(corners)
if ret:
obj_points.append(objp)
#在原角点的基础上寻找亚像素角点
corners2 = cv2.cornerSubPix(gray, corners, (5, 5), (-1, -1), criteria)
#print(corners2)
if [corners2]:
img_points.append(corners2)
else:
img_points.append(corners)
cv2.drawChessboardCorners(img, (x, y), corners, ret) # OpenCV的绘制函数一般无返回值
i+=1
cv2.imwrite('chessboard'+str(i)+'.jpg', img)
cv2.waitKey(1500)
print(len(img_points))
cv2.destroyAllWindows()
# 标定
ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(obj_points, img_points, (3000,4000), None, None)#size图片尺寸，未设置，tuple类型
print("ret:", ret)
print("mtx:", mtx) # 内参数矩阵
print("dist:", dist) # 畸变系数 distortion cofficients = (k_1,k_2,p_1,p_2,k_3)
print("rvecs:", rvecs) # 旋转向量 # 外参数
print("tvecs:", tvecs ) # 平移向量 # 外参数
10
ret: 0.6034656484375196
mtx: [[3.46706020e+03 0.00000000e+00 1.53076867e+03]
[0.00000000e+00 3.46612170e+03 2.01506578e+03]
[0.00000000e+00 0.00000000e+00 1.00000000e+00]]
dist: [[ 2.98747578e-01 -2.38376967e+00 -1.91990369e-04 7.75053363e-04
5.24296009e+00]]
rvecs: [array([[-0.04814146],
[-0.19805164],
[-0.01611279]]), array([[-0.05857207],
[ 0.25726468],
[-0.03622482]]), array([[-0.26283773],
[ 0.00406836],
[-0.02836761]]), array([[ 0.11325151],
[-0.29267606],
[-0.24485429]]), array([[0.03654181],
[0.36617318],
[0.30823712]]), array([[-0.2279373 ],
[ 0.24614305],
[ 0.39151749]]), array([[-0.37970194],
[-0.06548714],
[-0.40256486]]), array([[-0.11043704],
[ 0.41937632],
[-0.06089215]]), array([[-0.1349403 ],
[-0.48651913],
[ 0.28989606]]), array([[-0.14343477],
[ 0.25002587],
[-0.06997245]])]
tvecs: [array([[-3.14943299],
[-2.68881339],
[28.24934916]]), array([[-7.64596377],
[-3.59689334],
[30.44712761]]), array([[ -5.69152288],
[-10.3377668 ],
[ 30.3679679 ]]), array([[-3.56758529],
[-0.45837763],
[29.09574447]]), array([[-7.85523525],
[-4.06623205],
[30.06502994]]), array([[ -7.78091572],
[-11.30186817],
[ 36.00030819]]), array([[-4.29531013],
[-6.94139307],
[34.55544274]]), array([[-9.86432222],
[-2.13682508],
[34.93451369]]), array([[-2.4666996 ],
[-5.25780146],
[28.46556912]]), array([[-8.83054719],
[-5.21811431],
[29.64621938]])]
#结果预存
import numpy as np
ret = 0.6034656484375196
mtx = np.array([[3.46706020e+03, 0.00000000e+00, 1.53076867e+03],
[0.00000000e+00, 3.46612170e+03, 2.01506578e+03],
[0.00000000e+00, 0.00000000e+00, 1.00000000e+00]])
dist = np.array([[ 2.98747578e-01, -2.38376967e+00, -1.91990369e-04, 7.75053363e-04,
5.24296009e+00]])
rvecs = [np.array([[-0.04814146],
[-0.19805164],
[-0.01611279]]), np.array([[-0.05857207],
[ 0.25726468],
[-0.03622482]]), np.array([[-0.26283773],
[ 0.00406836],
[-0.02836761]]), np.array([[ 0.11325151],
[-0.29267606],
[-0.24485429]]), np.array([[0.03654181],
[0.36617318],
[0.30823712]]), np.array([[-0.2279373 ],
[ 0.24614305],
[ 0.39151749]]), np.array([[-0.37970194],
[-0.06548714],
[-0.40256486]]), np.array([[-0.11043704],
[ 0.41937632],
[-0.06089215]]), np.array([[-0.1349403 ],
[-0.48651913],
[ 0.28989606]]), np.array([[-0.14343477],
[ 0.25002587],
[-0.06997245]])]
tvecs: [np.array([[-3.14943299],
[-2.68881339],
[28.24934916]]), np.array([[-7.64596377],
[-3.59689334],
[30.44712761]]), np.array([[ -5.69152288],
[-10.3377668 ],
[ 30.3679679 ]]), np.array([[-3.56758529],
[-0.45837763],
[29.09574447]]), np.array([[-7.85523525],
[-4.06623205],
[30.06502994]]), np.array([[ -7.78091572],
[-11.30186817],
[ 36.00030819]]), np.array([[-4.29531013],
[-6.94139307],
[34.55544274]]), np.array([[-9.86432222],
[-2.13682508],
[34.93451369]]), np.array([[-2.4666996 ],
[-5.25780146],
[28.46556912]]), np.array([[-8.83054719],
[-5.21811431],
[29.64621938]])]
#单一尝试
import numpy as np
import cv2
x,y = 11,8
def draw(img, corners, imgpts):
corner = tuple(corners[0].ravel())
img = cv2.line(img, corner, tuple(imgpts[0].ravel()), (255,0,0), 5)
img = cv2.line(img, corner, tuple(imgpts[1].ravel()), (0,255,0), 5)
img = cv2.line(img, corner, tuple(imgpts[2].ravel()), (0,0,255), 5)
return img
criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)
objp = np.zeros((x * y, 3), np.float32)
objp[:,:2] = np.mgrid[0:x,0:y].T.reshape(-1,2)
axis = np.float32([[3,0,0], [0,3,0], [0,0,-3]]).reshape(-1,3)
img = cv2.imread(images[2])
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
ret, corners = cv2.findChessboardCorners(gray, (x, y),None)
if ret == True:
corners2 = cv2.cornerSubPix(gray,corners,(5, 5),(-1,-1),criteria)
# Find the rotation and translation vectors.
ret, rvecs, tvecs, inliers = cv2.solvePnPRansac(objp, corners2, mtx, dist)
# project 3D points to image plane
imgpts, jac = cv2.projectPoints(axis, rvecs, tvecs, mtx, dist)
img = draw(img,corners2,imgpts)
cv2.imwrite("review2"+ '.jpg', img)
cv2.imshow('showme',img)
cv2.waitKey(0)
cv2.destroyAllWindows()
<ipython-input-16-ae4098a9d9e4>:7: DeprecationWarning: an integer is required (got type numpy.float32). Implicit conversion to integers using __int__ is deprecated, and may be removed in a future version of Python. img = cv2.line(img, corner, tuple(imgpts[0].ravel()), (255,0,0), 5) <ipython-input-16-ae4098a9d9e4>:8: DeprecationWarning: an integer is required (got type numpy.float32). Implicit conversion to integers using __int__ is deprecated, and may be removed in a future version of Python. img = cv2.line(img, corner, tuple(imgpts[1].ravel()), (0,255,0), 5) <ipython-input-16-ae4098a9d9e4>:9: DeprecationWarning: an integer is required (got type numpy.float32). Implicit conversion to integers using __int__ is deprecated, and may be removed in a future version of Python. img = cv2.line(img, corner, tuple(imgpts[2].ravel()), (0,0,255), 5)
#相机姿态重构 P2
#创建一个函数：draw, 它的参数有棋盘上的角点（使用cv2.findChessboardCorners() 得到）和要绘制的 3D 坐标轴上的点。
import cv2
import numpy as np
def draw(img, corners, imgpts):
corner = tuple(corners[0].ravel())
img = cv2.line(img, corner, tuple(imgpts[0].ravel()), (255,0,0), 5)
img = cv2.line(img, corner, tuple(imgpts[1].ravel()), (0,255,0), 5)
img = cv2.line(img, corner, tuple(imgpts[2].ravel()), (0,0,255), 5)
return img
criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)
objp = np.zeros((x * y, 3), np.float32)
objp[:,:2] = np.mgrid[0:x,0:y].T.reshape(-1,2)
axis = np.float32([[3,0,0], [0,3,0], [0,0,-3]]).reshape(-1,3)
j=0
for fname in images:
img = cv2.imread(fname)
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
ret, corners = cv2.findChessboardCorners(gray, (x, y),None)
if ret == True:
corners2 = cv2.cornerSubPix(gray,corners,(5, 5),(-1,-1),criteria)
# Find the rotation and translation vectors.
ret, rvecs, tvecs, inliers = cv2.solvePnPRansac(objp, corners2, mtx, dist)
# project 3D points to image plane
imgpts, jac = cv2.projectPoints(axis, rvecs, tvecs, mtx, dist)
img = draw(img,corners2,imgpts)
j+=1
cv2.imwrite("review"+ str(j)+ '.jpg', img)
cv2.imshow('showme',img)
cv2.waitKey(1500)
cv2.destroyAllWindows()
#畸变矫正
import cv2
img = cv2.imread(images[1])#随便从有畸变的图片中挑一张进行矫正
h, w = img.shape[:2]
newcameramtx, roi = cv2.getOptimalNewCameraMatrix(mtx,dist,(w,h),1,(w,h))#显示更大范围的图片（正常重映射之后会删掉一部分图像）
print (newcameramtx)
dst = cv2.undistort(img,mtx,dist,None,newcameramtx)
x,y,w,h = roi
dst1 = dst[y:y+h,x:x+w]
cv2.imwrite('calibresult.jpg', dst1)
print ("dst的大小为:", dst1.shape)
[[3.48711987e+03 0.00000000e+00 1.53191442e+03] [0.00000000e+00 3.54943628e+03 2.01423843e+03] [0.00000000e+00 0.00000000e+00 1.00000000e+00]] dst的大小为: (3461, 2570, 3)
#相机姿态重构 P1
def draw(img, corners, imgpts):
corner = tuple(corners[0].ravel())
img = cv2.line(img, corner, tuple(imgpts[0].ravel()), (255,0,0), 5)
img = cv2.line(img, corner, tuple(imgpts[1].ravel()), (0,255,0), 5)
img = cv2.line(img, corner, tuple(imgpts[2].ravel()), (0,0,255), 5)
return img
# criteria = (cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)
# objp = np.zeros((x * y,3), np.float32)
# objp[:,:2] = np.mgrid[0:x,0:y].T.reshape(-1,2)
axis = np.float32([[3,0,0], [0,3,0], [0,0,-3]]).reshape(-1,3)
for fname in images:
img2 = cv2.imread(fname)
gray = cv2.cvtColor(img2,cv2.COLOR_BGR2GRAY)
ret, corners = cv2.findChessboardCorners(gray, (x, y),None)
if ret == True:
corners2 = cv2.cornerSubPix(gray,corners,(5, 5),(-1,-1),criteria)
# 找到旋转和平移矢量。
ret,rvecs, tvecs = cv2.solvePnP(objp, corners2, mtx, dist)
# 将3D点投影到图像平面
imgpts, jac = cv2.projectPoints(axis, rvecs, tvecs, mtx, dist)
img2 = draw(img2,corners2,imgpts)
cv2.imwrite(fname[:6]+'.png', img2)
cv2.destroyAllWindows()
<ipython-input-3-5f61c7c85e06>:4: DeprecationWarning: an integer is required (got type numpy.float32). Implicit conversion to integers using __int__ is deprecated, and may be removed in a future version of Python. img = cv2.line(img, corner, tuple(imgpts[0].ravel()), (255,0,0), 5) <ipython-input-3-5f61c7c85e06>:5: DeprecationWarning: an integer is required (got type numpy.float32). Implicit conversion to integers using __int__ is deprecated, and may be removed in a future version of Python. img = cv2.line(img, corner, tuple(imgpts[1].ravel()), (0,255,0), 5) <ipython-input-3-5f61c7c85e06>:6: DeprecationWarning: an integer is required (got type numpy.float32). Implicit conversion to integers using __int__ is deprecated, and may be removed in a future version of Python. img = cv2.line(img, corner, tuple(imgpts[2].ravel()), (0,0,255), 5)