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import cv2
import numpy as np
import glob
# termination criteria
criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)
# prepare object points, like (0,0,0), (1,0,0), (2,0,0) ....,(6,5,0)
objp = np.zeros((6*7,3), np.float32)
objp[:,:2] = np.mgrid[0:7,0:6].T.reshape(-1,2) * 2
# Arrays to store object points and image points from all the images.
objpoints = [] # 3d point in real world space
imgpoints = [] # 2d points in i
cap = cv2.VideoCapture(0)
i = 0
while cap.isOpened() and i < 12:
_, img = cap.read()
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
# Find the chess board corners
ret, corners = cv2.findChessboardCorners(gray, (7,6),None)
print(ret)
# If found, add object points, image points (after refining them)
if ret == True:
i += 1
objpoints.append(objp)
cv2.cornerSubPix(gray,corners,(11,11),(-1,-1),criteria)
imgpoints.append(corners)
# Draw and display the corners
cv2.drawChessboardCorners(img, (7,6), corners,ret)
#cv2.imshow('img',img)
#cv2.waitKey(250)
cap.release()
print("Trying to calibrate")
ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, gray.shape[::-1],None,None)
img = cv2.imread('calibration/IMG_20170613_130645.jpg')
h, w = img.shape[:2]
newcameramtx, roi=cv2.getOptimalNewCameraMatrix(mtx,dist,(w,h),1,(w,h))
# undistort
dst = cv2.undistort(img, mtx, dist, None, newcameramtx)
# crop the image
x,y,w,h = roi
dst = dst[y:y+h, x:x+w]
cv2.imwrite('calibration/calibresult.png',dst)
np.savez("calibrationM/matrices", cameraMatrix=mtx, distortion=dist)
print("Done")
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