Projet_RT/incubateur/Aruco_opencv_python/calibrate.py

import numpy as np
import cv2
import glob


def calculareCameraCalibration():
    # termination criteria
    criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 23, 0.001)

    # prepare object points, like (0,0,0), (1,0,0), (2,0,0) ....,(6,5,0)
    objp = np.zeros((6*7,3), np.float32)
    objp[:,:2] = np.mgrid[0:7,0:6].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.

    images = glob.glob('./img_calibrate/*.jpg')

    for fname in images:
        img = cv2.imread(fname)
        gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

        # Find the chess board corners
        ret, corners = cv2.findChessboardCorners(gray, (7,6),None)

        # If found, add object points, image points (after refining them)
        if ret == True:
            objpoints.append(objp)

            corners2 = cv2.cornerSubPix(gray,corners,(11,11),(-1,-1),criteria)
            imgpoints.append(corners2)

            ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, gray.shape[::-1], None, None)
            return ret, mtx, dist, rvecs, tvecs