"""
Credits : https://medium.com/@kennethjiang/calibrate-fisheye-lens-using-opencv-333b05afa0b0
"""

import cv2
# assert cv2.__version__[0] == '3', 'The fisheye module requires opencv version >= 3.0.0'

import numpy as np
import os
import glob
import pickle

CHECKERBOARD = (6,9)

subpix_criteria = (cv2.TERM_CRITERIA_EPS+cv2.TERM_CRITERIA_MAX_ITER, 30, 0.1)
calibration_flags = cv2.fisheye.CALIB_RECOMPUTE_EXTRINSIC + cv2.fisheye.CALIB_CHECK_COND + cv2.fisheye.CALIB_FIX_SKEW

objp = np.zeros((1, CHECKERBOARD[0]*CHECKERBOARD[1], 3), np.float32)
objp[0, :, :2] = np.mgrid[0:CHECKERBOARD[0], 0:CHECKERBOARD[1]].T.reshape(-1, 2)
_img_shape = None
objpoints = [] # 3d point in real world space
imgpoints = [] # 2d points in image plane.

images = glob.glob('Callibration_fisheye/*.jpg')
for fname in images:
    img = cv2.imread(fname)
    if _img_shape == None:
        _img_shape = img.shape[:2]
    else:
        assert _img_shape == img.shape[:2], "All images must share the same size."

    gray_image = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    # Find the chess board corners
    ret, corners = cv2.findChessboardCorners(gray_image, CHECKERBOARD, cv2.CALIB_CB_ADAPTIVE_THRESH + cv2.CALIB_CB_FAST_CHECK + cv2.CALIB_CB_NORMALIZE_IMAGE)
    # If found, add object points, image points (after refining them)
    if ret == True:
        objpoints.append(objp)
        cv2.cornerSubPix(gray_image, corners, (3, 3), (-1, -1), subpix_criteria)
        imgpoints.append(corners)

N_OK = len(objpoints)
K = np.zeros((3, 3))
D = np.zeros((4, 1))
rvecs = [np.zeros((1, 1, 3), dtype=np.float64) for i in range(N_OK)]
tvecs = [np.zeros((1, 1, 3), dtype=np.float64) for i in range(N_OK)]
rms, _, _, _, _ = \
    cv2.fisheye.calibrate(
        objpoints,
        imgpoints,
        gray_image.shape[::-1],
        K,
        D,
        rvecs,
        tvecs,
        calibration_flags,
        (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 1e-6)
    )
print("Found " + str(N_OK) + " valid images for calibration")
print("DIM = " + str(_img_shape[::-1]))
print("K = np.array(" + str(K.tolist()) + ")")
print("D = np.array(" + str(D.tolist()) + ")")

with open(f'../output/Fisheye_KD_matrix', 'wb') as handle:
    pickle.dump([DIM, K, D], handle)