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import numpy as np
import cv2 as cv
import mtutils as mt
# termination criteria
criteria = (cv.TERM_CRITERIA_EPS + cv.TERM_CRITERIA_MAX_ITER, 30, 0.001)
# prepare object points, like (0,0,0), (1,0,0), (2,0,0) ....,(6,6,0)
W_num = 7
H_num = 7
objp = np.zeros((W_num*H_num,3), np.float32)
objp[:,:2] = np.mgrid[0:W_num,0:H_num].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.
img = mt.cv_rgb_imread('undistort.png', 1)
another = img.copy()
# Find the chess board corners
ret, corners = cv.findChessboardCorners(img, (W_num,H_num), None)
# If found, add object points, image points (after refining them)
if ret == True:
    objpoints.append(objp)
    corners2 = cv.cornerSubPix(img,corners, (11,11), (-1,-1), criteria)
    imgpoints.append(corners2)
    # Draw and display the corners
    cv.drawChessboardCorners(img, (W_num, H_num), corners2, ret)
    mt.PIS(img)
ret, mtx, dist, rvecs, tvecs = cv.calibrateCamera(objpoints, imgpoints, img.shape[::-1], None, None)
h,  w = img.shape[:2]
newcameramtx, roi = cv.getOptimalNewCameraMatrix(mtx, dist, (w,h), 1, (w,h))
# 原始 mtx 效果会好一些
# dst = cv.undistort(another, mtx, dist, None, newcameramtx)
dst = cv.undistort(another, mtx, dist, None, mtx)
# 点校正
undis_corners2 = cv.undistortPoints(corners2, mtx, dist, None, mtx)
# build map matrix
# 原始 mtx 效果会好一些
# map1, map2 = cv.initUndistortRectifyMap(mtx, dist, None, newcameramtx, img.shape[::-1], cv.CV_32FC1)
map1, map2 = cv.initUndistortRectifyMap(mtx, dist, None, mtx, img.shape[::-1], cv.CV_32FC1)
frame2 = cv.remap(another2, map1, map2, cv.INTER_LINEAR)
mt.PIS([another, 'origin'], [img, 'marked'], [dst, 'undistort'], row_num=1)
pass