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# カメラ内部パラメータ(内部パラメータ行列)
# ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, gray.shape[::-1], None, None)
# -----reading camera intrinsic matrix
cameraMatrix = np.loadtxt("calib/cameraMatrix.csv",delimiter=",")
distCoeffs = np.loadtxt("calib/distCoeffs.csv",delimiter=",")


# 外部パラメータ行列
# https://gist.github.com/shks/e3cd5fc22ad9f4ddbccd5312a64803c3

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retval, rvec, tvec = aruco.estimatePoseBoard(corners, ids, board, cameraMatrix, distCoeffs, None, None)

#rvec, tvec  : 3 float vector 

#ロドリゲス公式で、rvecから回転行列へ変換する
Rmatrix, Jacob = cv2.Rodrigues(rvec)

# [3 x 4 matrix]で、R|t マトリクスを作成
RTmatrix34_L = np.concatenate([Rmatrix, tvec],  axis=1)

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# -load camera instrinsic matrix
cameraMatrix = np.loadtxt("calib/cameraMatrix.csv",delimiter=",")
distCoeffs = np.loadtxt("calib/distCoeffs.csv",delimiter=",")


# prepare the 'same' aruco board
aruco = cv2.aruco
dictionary = aruco.getPredefinedDictionary(aruco.DICT_4X4_50)
board = cv2.aruco.GridBoard_create(5, 5, 0.2,0.1,dictionary)
# retval	=	cv.aruco.GridBoard_create(	markersX, markersY, markerLength, markerSeparation, dictionary[

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from cv2 import aruco
import cv2

aruco_dict = aruco.Dictionary_get(aruco.DICT_6X6_250)
board = aruco.CharucoBoard_create(28, 16, 200, 140, aruco_dict)

imboard = board.draw((1920,1080))
cv2.imwrite('CharucoBoard.png', imboard)

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import cv2
import numpy as np

arr = op('td_top').numpyArray('delayed=True')
gray = arr[:, :, 0]
gray = gray * 255.0
gray = gray.astype(np.uint8)

#flip
gray = cv2.flip(gray, 0)

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import sys
import cv2
import glob


_list =  glob.glob("./some/*", recursive=True)
_list.sort()

fourcc = cv2.VideoWriter_fourcc('m', 'p', '4', 'v')    
video = cv2.VideoWriter('./some/video.mp4',fourcc, 60.0, (1024, 1024))

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import glob
_list =  glob.glob("*.mov", recursive=True)
for fname in _list:
    sampleName = os.path.basename(fname).split('.', 1)[0]
    print(sampleName)   

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import cv2
import os

def save_all_frames(video_path, dir_path, basename, ext='jpg'):
    cap = cv2.VideoCapture(video_path)

    if not cap.isOpened():
        return

    os.makedirs(dir_path, exist_ok=True)

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# me - this DAT
# scriptOp - the OP which is cooking

import numpy as np
import cv2
import io
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
matplotlib.use('Agg')

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from scipy.stats import shapiro

#https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.shapiro.html
def doShapirotest(data):
    stat, p = shapiro(data)
    print("Shapirotest Wstat , p-value", stat, p)
    if(p < 0.05):
        print("USE NON-PARAMETRIC TEST :(p < 0.05)")
    else:
        print("USE PARAMETRIC TEST  : (p > 0.05)")