import numpy as np
import cv2
import cv2.aruco as aruco
import glob

def calibrateKd(im_fpath, aruco_len=60.0):
    (w, h) = (6, 4)
    criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.01)
    objp = np.zeros((w*h, 3), np.float32)
    objp[:, :2] = np.mgrid[0:w, 0:h].T.reshape(-1, 2)
    objp *= aruco_len
    objpoints, imgpoints = [], []
    images = glob.glob(f'{im_fpath}/*')
    for fname in images:
        img = cv2.imread(fname)
        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
        ret, corners = cv2.findChessboardCorners(gray, (w, h), None)
        if ret == True:
            objpoints.append(objp)
            corners2 = cv2.cornerSubPix(gray, corners, (11, 11), (-1, -1), criteria)
            imgpoints.append(corners2)
            img = cv2.drawChessboardCorners(img, (6, 4), corners2, ret)

    ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, gray.shap[::-1], None, None)
    tot_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)
        tot_error += error
    print(tot_error)
    return mtx, dist