picam_calibration.py

"""
Reference:
OpenCV-Python Tutorials - Camera Calibration and 3D Reconstruction
http://opencv-python-tutroals.readthedocs.org/en/latest/py_tutorials/py_calib3d/py_calibration/py_calibration.html
"""
def calibrate_KBD():
    import cv2
    import numpy as np
    import glob

    # termination criteria
    criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)

    # 6x9 chess board, prepare object points, like (0,0,0), (1,0,0), (2,0,0) ....,(6,5,0)
    object_point = np.zeros((6*9, 3), np.float32)
    object_point[:, :2] = np.mgrid[0:9, 0:6].T.reshape(-1, 2)

    # 3d point in real world space
    object_points = []
    # 2d points in image plane
    image_points = []
    h, w = 0, 0

    images = glob.glob('chess_board/*.jpg')

    for file_name in images:
        image = cv2.imread(file_name)
        gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
        h, w = gray.shape[:2]

        # find chess board corners
        ret, corners = cv2.findChessboardCorners(gray, (9, 6), None)
        print(ret,corners)
        # add object points, image points
        if ret:
            object_points.append(object_point)
            cv2.cornerSubPix(gray, corners, (11, 11), (-1, -1), criteria)
            image_points.append(corners)

            # draw and display the corners
            cv2.drawChessboardCorners(image, (9, 6), corners, ret)
            cv2.imshow('image', image)
            cv2.waitKey(500)

    # calibration
    retval, cameraMatrix, distCoeffs, rvecs, tvecs = cv2.calibrateCamera(object_points, image_points, (w, h), None, None)

    #print "camera matrix:\n", cameraMatrix
    # pi camera intrinsic parameters
    ay = cameraMatrix[1, 1]
    u0 = cameraMatrix[0, 2]
    v0 = cameraMatrix[1, 2]
    #print "Ay:", ay
    #print "u0:", u0
    #print "v0:", v0
    print cameraMatrix
    print distCoeffs
    cv2.destroyAllWindows()

    return cameraMatrix,distCoeffs
#calibrationKBD()