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- #!/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 <output path>] [--square_size] [<image mask>]
- default values:
- --debug: ./output/
- --square_size: 1.0
- <image mask> defaults to ../data/left*.jpg
- '''
- # Python 2/3 compatibility
- from __future__ import print_function
- import numpy as np
- import cv2 as cv
- # local modules
- from common import splitfn
- # built-in modules
- import os
- def main():
- import sys
- import getopt
- from glob import glob
- args, img_mask = getopt.getopt(sys.argv[1:], '', ['debug=', 'square_size=', 'threads='])
- args = dict(args)
- args.setdefault('--debug', './output/')
- args.setdefault('--square_size', 1.0)
- args.setdefault('--threads', 4)
- 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 debug_dir and 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 = cv.imread(img_names[0], cv.IMREAD_GRAYSCALE).shape[:2] # TODO: use imquery call to retrieve results
- def processImage(fn):
- print('processing %s... ' % fn)
- img = cv.imread(fn, 0)
- if img is None:
- print("Failed to load", fn)
- return None
- assert w == img.shape[1] and h == img.shape[0], ("size: %d x %d ... " % (img.shape[1], img.shape[0]))
- found, corners = cv.findChessboardCorners(img, pattern_size)
- if found:
- term = (cv.TERM_CRITERIA_EPS + cv.TERM_CRITERIA_COUNT, 30, 0.1)
- cv.cornerSubPix(img, corners, (5, 5), (-1, -1), term)
- if debug_dir:
- vis = cv.cvtColor(img, cv.COLOR_GRAY2BGR)
- cv.drawChessboardCorners(vis, pattern_size, corners, found)
- _path, name, _ext = splitfn(fn)
- outfile = os.path.join(debug_dir, name + '_chess.png')
- cv.imwrite(outfile, vis)
- if not found:
- print('chessboard not found')
- return None
- print(' %s... OK' % fn)
- return (corners.reshape(-1, 2), pattern_points)
- threads_num = int(args.get('--threads'))
- if threads_num <= 1:
- chessboards = [processImage(fn) for fn in img_names]
- else:
- print("Run with %d threads..." % threads_num)
- from multiprocessing.dummy import Pool as ThreadPool
- pool = ThreadPool(threads_num)
- chessboards = pool.map(processImage, img_names)
- chessboards = [x for x in chessboards if x is not None]
- for (corners, pattern_points) in chessboards:
- img_points.append(corners)
- obj_points.append(pattern_points)
- # calculate camera distortion
- rms, camera_matrix, dist_coefs, _rvecs, _tvecs = cv.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 fn in img_names if debug_dir else []:
- _path, name, _ext = splitfn(fn)
- img_found = os.path.join(debug_dir, name + '_chess.png')
- outfile = os.path.join(debug_dir, name + '_undistorted.png')
- img = cv.imread(img_found)
- if img is None:
- continue
- h, w = img.shape[:2]
- newcameramtx, roi = cv.getOptimalNewCameraMatrix(camera_matrix, dist_coefs, (w, h), 1, (w, h))
- dst = cv.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]
- print('Undistorted image written to: %s' % outfile)
- cv.imwrite(outfile, dst)
- print('Done')
- if __name__ == '__main__':
- print(__doc__)
- main()
- cv.destroyAllWindows()
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