generateCalibration.py

#!/usr/bin/env python
# Thank you to https://goo.gl/NDyw63

# Imports
import os
import json
from glob import glob
import numpy as np
import cv2

class GenerateCalibration(object):
    def __init__(self, directory, saveFilename):
        self.directory = directory
        self.saveFilename = saveFilename

    def run(self):
        img_names = glob(os.path.abspath(self.directory) + '/*')
        square_size = 1.0

        pattern_size = (9, 6)
        pattern_points = np.zeros((np.prod(pattern_size), 3), np.float32)
        pattern_points[:, :2] = np.indices(pattern_size).T.reshape(-1, 2)
        pattern_points *= square_size

        obj_points = []
        img_points = []
        h, w = 0, 0
        img_names_undistort = []
        for fn in img_names:
            print('processing %s... ' % fn, end='')
            img = cv2.imread(fn, 0)
            if img is None:
                print("Failed to load", fn)
                continue

            h, w = img.shape[:2]
            found, corners = cv2.findChessboardCorners(img, pattern_size)
            if found:
                term = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_COUNT, 30, 0.1)
                cv2.cornerSubPix(img, corners, (5, 5), (-1, -1), term)

                img_points.append(corners.reshape(-1, 2))
                obj_points.append(pattern_points)

        if (len(obj_points) == 0): # no images had the chessboard in them
            return False

        # calculate camera distortion
        rms, camera_matrix, dist_coefs, rvecs, tvecs = cv2.calibrateCamera(obj_points, img_points, (w, h), None, None)

        # Dump to JSON file
        with open(self.saveFilename, 'w') as f:
            json.dump({'matrix': camera_matrix.tolist(), 'distortion': dist_coefs.ravel().tolist(), 'rms': rms}, f, sort_keys = True, indent = 2)

        return True