camera_calibration.py

import numpy as np
import cv2
import glob


def calibrate_camera():
    # 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((20*11, 3), np.float32)
    objp[:, :2] = np.mgrid[0:20, 0:11].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('./first_calibration/*.png')

    for fname in images:
        img = cv2.imread(fname)
        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
        # cv.imshow('img', gray)
        # cv.waitKey(500)

        # Find the chess board corners
        ret, corners = cv2.findChessboardCorners(gray, (20, 11), None)
        # If found, add object points, image points (after refining them)

        if ret:
            objpoints.append(objp)
            corners2 = cv2.cornerSubPix(gray, corners, (11, 11), (-1, -1), criteria)
            imgpoints.append(corners2)
            # Draw and display the corners
            cv2.drawChessboardCorners(img, (20, 11), corners2, ret)
            key = ''
    #         while key != 113:
    #             cv2.imshow('img', img)
    #             key = cv2.waitKey(5)
    #         cv2.waitKey(5)
    #
    #
    # cv2.destroyAllWindows()

    ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, gray.shape[::-1], None, None)


    mean_error = 0
    for i in range(len(objpoints)):
        imgpoints2, _ = cv2.projectPoints(objpoints[i], rvecs[i], tvecs[i], mtx, dist)
        error = cv2.norm(imgpoints[i], imgpoints2, cv2.NORM_L2)/len(imgpoints2)
        mean_error += error
    print( "total error: {}".format(mean_error/len(objpoints)) )

    return dist, mtx