calibration.py

import numpy as np
import cv2
import glob


def calculateCalibration():
    
    pattern_size = (8,6)
    # 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((pattern_size[0]*pattern_size[1],3), np.float32)
    objp[:,:2] = np.mgrid[0:pattern_size[0],0:pattern_size[1]].T.reshape(-1,2)

    # Arrays to store object points and image points from all the images.
    objpoints = [] # 3d point in real world space
    imgpoints = [] # 2d points in image plane.

    images = glob.glob('images/calibration/*.png')


    for fname in images:
        img = cv2.imread(fname)
        gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
        # Find the chess board corners
        ret, corners = cv2.findChessboardCorners(gray,pattern_size, cv2.cv.CV_CALIB_CB_ADAPTIVE_THRESH)
        # If found, add object points, image points (after refining them)
        if ret == True:
            objpoints.append(objp)
            cv2.cornerSubPix(gray,corners,(22,22),(-1,-1), criteria)
            imgpoints.append(corners)
            # Draw and display the corners
            #cv2.drawChessboardCorners(img, pattern_size, corners,ret)
            #cv2.imshow('img',img)
            #cv2.waitKey(500)

    cv2.destroyAllWindows()
    
    ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, gray.shape[::-1],None,None)
    print(str(ret) + "\n" + str(mtx))

    return (ret,mtx,dist,rvecs,tvecs)