import glob
import pickle

import cv2
import numpy as np

# Camera calibration and storing values in pickle
# Prepare data for camera calibration
def prepareCalibrationInputs():
    # prepare object points, like (0,0,0), (1,0,0), (2,0,0) ....,(6,5,0)
    objp = np.zeros((6 * 9, 3), np.float32)
    objp[:, :2] = np.mgrid[0:9, 0:6].T.reshape(-1, 2)

    # Arrays to store object points and image points from all the images.
    objpoints = []  # 3d points in real world space
    imgpoints = []  # 2d points in image plane.

    # Make a list of calibration images
    images = glob.glob('../camera_cal/calibration*.jpg')

    # Step through the list and search for chessboard corners
    for fname in images:
        img = cv2.imread(fname)
        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

        # Find the chessboard corners
        ret, corners = cv2.findChessboardCorners(gray, (9, 6), None)

        # If found, add object points, image points
        if ret == True:
            objpoints.append(objp)
            imgpoints.append(corners)

            # Draw and display the corners
            img = cv2.drawChessboardCorners(img, (9, 6), corners, ret)
            cv2.imshow('img', img)
            cv2.waitKey(500)
            cv2.imwrite('../output_images/'+fname, img)

    cv2.destroyAllWindows()
    return objpoints, imgpoints


#Call this function once and get data from pickle later.
objpoints, imgpoints = prepareCalibrationInputs()

mydict = {"objpoints": objpoints, "imgpoints": imgpoints}

pickle.dump(mydict, open("cam_calibration_pickle.p", "wb"))


import glob
import pickle

import cv2
import numpy as np

# Camera calibration and storing values in pickle
# Prepare data for camera calibration
def prepareCalibrationInputs():
    # prepare object points, like (0,0,0), (1,0,0), (2,0,0) ....,(6,5,0)
    objp = np.zeros((6 * 9, 3), np.float32)
    objp[:, :2] = np.mgrid[0:9, 0:6].T.reshape(-1, 2)

    # Arrays to store object points and image points from all the images.
    objpoints = []  # 3d points in real world space
    imgpoints = []  # 2d points in image plane.

    # Make a list of calibration images
    images = glob.glob('../camera_cal/calibration*.jpg')

    # Step through the list and search for chessboard corners
    for fname in images:
        img = cv2.imread(fname)
        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

        # Find the chessboard corners
        ret, corners = cv2.findChessboardCorners(gray, (9, 6), None)

        # If found, add object points, image points
        if ret == True:
            objpoints.append(objp)
            imgpoints.append(corners)

            # Draw and display the corners
            img = cv2.drawChessboardCorners(img, (9, 6), corners, ret)
            cv2.imshow('img', img)
            cv2.waitKey(500)
            cv2.imwrite('../output_images/'+fname, img)

    cv2.destroyAllWindows()
    return objpoints, imgpoints


#Call this function once and get data from pickle later.
objpoints, imgpoints = prepareCalibrationInputs()

mydict = {"objpoints": objpoints, "imgpoints": imgpoints}

pickle.dump(mydict, open("cam_calibration_pickle.p", "wb"))


# Camera calibration and storing values in pickle # Prepare data for camera calibration # prepare object points, like (0,0,0), (1,0,0), (2,0,0) ....,(6,5,0) # Arrays to store object points and image points from all the images. # 3d points in real world space # 2d points in image plane. # Make a list of calibration images # Step through the list and search for chessboard corners # Find the chessboard corners # If found, add object points, image points # Draw and display the corners #Call this function once and get data from pickle later.