#!/usr/bin/env python ''' camera calibration for distorted images with chess board samples reads distorted images, calculates the calibration and write undistorted images usage: calibrate.py [--debug ] [--square_size] [] default values: --debug: ./output/ --square_size: 1.0 defaults to ../data/left*.jpg ''' # Python 2/3 compatibility from __future__ import print_function import numpy as np import cv2 # local modules from common import splitfn # built-in modules import os if __name__ == '__main__': import sys import getopt from glob import glob args, img_mask = getopt.getopt(sys.argv[1:], '', ['debug=', 'square_size=']) args = dict(args) args.setdefault('--debug', './output/') args.setdefault('--square_size', 1.0) if not img_mask: img_mask = '../data/left*.jpg' # default else: img_mask = img_mask[0] img_names = glob(img_mask) debug_dir = args.get('--debug') if not os.path.isdir(debug_dir): os.mkdir(debug_dir) square_size = float(args.get('--square_size')) 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) if debug_dir: vis = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR) cv2.drawChessboardCorners(vis, pattern_size, corners, found) path, name, ext = splitfn(fn) outfile = debug_dir + name + '_chess.png' cv2.imwrite(outfile, vis) if found: img_names_undistort.append(outfile) if not found: print('chessboard not found') continue img_points.append(corners.reshape(-1, 2)) obj_points.append(pattern_points) print('ok') # calculate camera distortion rms, camera_matrix, dist_coefs, rvecs, tvecs = cv2.calibrateCamera(obj_points, img_points, (w, h), None, None) print("\nRMS:", rms) print("camera matrix:\n", camera_matrix) print("distortion coefficients: ", dist_coefs.ravel()) # undistort the image with the calibration print('') for img_found in img_names_undistort: img = cv2.imread(img_found) h, w = img.shape[:2] newcameramtx, roi = cv2.getOptimalNewCameraMatrix(camera_matrix, dist_coefs, (w, h), 1, (w, h)) dst = cv2.undistort(img, camera_matrix, dist_coefs, None, newcameramtx) # crop and save the image x, y, w, h = roi dst = dst[y:y+h, x:x+w] outfile = img_found + '_undistorted.png' print('Undistorted image written to: %s' % outfile) cv2.imwrite(outfile, dst) cv2.destroyAllWindows()