calibrate.py

import cv2
import numpy as np
import os
import glob

# Define the dimensions of the chessboard
chessboard_size = (10, 7)
square_size = 25  # 25 mm

# Define the criteria for the termination of the iterative algorithm for corner refinement
criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)

# Prepare object points, like (0,0,0), (1,0,0), (2,0,0) ....,(9,6,0)
objp = np.zeros((chessboard_size[0] * chessboard_size[1], 3), np.float32)
objp[:, :2] = np.mgrid[0:chessboard_size[0], 0:chessboard_size[1]].T.reshape(-1, 2)
objp = objp * square_size

# 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

# Load images
images = glob.glob('converted_images/*.jpg')

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

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

    # If found, add object points, image points (after refining them)
    if ret:
        objpoints.append(objp)
        corners2 = cv2.cornerSubPix(gray, corners, (11, 11), (-1, -1), criteria)
        imgpoints.append(corners2)

        # Draw and display the corners
        cv2.drawChessboardCorners(img, chessboard_size, corners2, ret)
        cv2.imshow('img', img)
        cv2.waitKey(500)

cv2.destroyAllWindows()

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

# Save the calibration results
np.savez('calibration.npz', mtx=mtx, dist=dist, rvecs=rvecs, tvecs=tvecs)

# Print the calibration results
print("Camera matrix:")
print(mtx)
print("Distortion coefficients:")
print(dist)