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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>] [-w <width>] [-h <height>] [-t <pattern type>] [--square_size=<square size>]
[--marker_size=<aruco marker size>] [--aruco_dict=<aruco dictionary name>] [<image mask>]
usage example:
calibrate.py -w 4 -h 6 -t chessboard --square_size=50 ../data/left*.jpg
default values:
--debug: ./output/
-w: 4
-h: 6
-t: chessboard
--square_size: 10
--marker_size: 5
--aruco_dict: DICT_4X4_50
--threads: 4
<image mask> defaults to ../data/left*.jpg
NOTE: Chessboard size is defined in inner corners. Charuco board size is defined in units.
'''
# 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_names = getopt.getopt(sys.argv[1:], 'w:h:t:', ['debug=','square_size=', 'marker_size=',
'aruco_dict=', 'threads=', ])
args = dict(args)
args.setdefault('--debug', './output/')
args.setdefault('-w', 4)
args.setdefault('-h', 6)
args.setdefault('-t', 'chessboard')
args.setdefault('--square_size', 10)
args.setdefault('--marker_size', 5)
args.setdefault('--aruco_dict', 'DICT_4X4_50')
args.setdefault('--threads', 4)
if not img_names:
img_mask = '../data/left??.jpg' # default
img_names = glob(img_mask)
debug_dir = args.get('--debug')
if debug_dir and not os.path.isdir(debug_dir):
os.mkdir(debug_dir)
height = int(args.get('-h'))
width = int(args.get('-w'))
pattern_type = str(args.get('-t'))
square_size = float(args.get('--square_size'))
marker_size = float(args.get('--marker_size'))
aruco_dict_name = str(args.get('--aruco_dict'))
pattern_size = (width, height)
if pattern_type == 'chessboard':
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
aruco_dicts = {
'DICT_4X4_50': cv.aruco.DICT_4X4_50,
'DICT_4X4_100': cv.aruco.DICT_4X4_100,
'DICT_4X4_250': cv.aruco.DICT_4X4_250,
'DICT_4X4_1000': cv.aruco.DICT_4X4_1000,
'DICT_5X5_50': cv.aruco.DICT_5X5_50,
'DICT_5X5_100': cv.aruco.DICT_5X5_100,
'DICT_5X5_250': cv.aruco.DICT_5X5_250,
'DICT_5X5_1000': cv.aruco.DICT_5X5_1000,
'DICT_6X6_50': cv.aruco.DICT_6X6_50,
'DICT_6X6_100': cv.aruco.DICT_6X6_100,
'DICT_6X6_250': cv.aruco.DICT_6X6_250,
'DICT_6X6_1000': cv.aruco.DICT_6X6_1000,
'DICT_7X7_50': cv.aruco.DICT_7X7_50,
'DICT_7X7_100': cv.aruco.DICT_7X7_100,
'DICT_7X7_250': cv.aruco.DICT_7X7_250,
'DICT_7X7_1000': cv.aruco.DICT_7X7_1000,
'DICT_ARUCO_ORIGINAL': cv.aruco.DICT_ARUCO_ORIGINAL,
'DICT_APRILTAG_16h5': cv.aruco.DICT_APRILTAG_16h5,
'DICT_APRILTAG_25h9': cv.aruco.DICT_APRILTAG_25h9,
'DICT_APRILTAG_36h10': cv.aruco.DICT_APRILTAG_36h10,
'DICT_APRILTAG_36h11': cv.aruco.DICT_APRILTAG_36h11
}
if (aruco_dict_name not in set(aruco_dicts.keys())):
print("unknown aruco dictionary name")
return None
aruco_dict = cv.aruco.getPredefinedDictionary(aruco_dicts[aruco_dict_name])
board = cv.aruco.CharucoBoard(pattern_size, square_size, marker_size, aruco_dict)
charuco_detector = cv.aruco.CharucoDetector(board)
def processImage(fn):
print('processing %s... ' % fn)
img = cv.imread(fn, cv.IMREAD_GRAYSCALE)
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 = False
corners = 0
if pattern_type == 'chessboard':
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)
frame_img_points = corners.reshape(-1, 2)
frame_obj_points = pattern_points
elif pattern_type == 'charucoboard':
corners, charucoIds, _, _ = charuco_detector.detectBoard(img)
if (len(corners) > 0):
frame_obj_points, frame_img_points = board.matchImagePoints(corners, charucoIds)
found = True
else:
found = False
else:
print("unknown pattern type", pattern_type)
return None
if debug_dir:
vis = cv.cvtColor(img, cv.COLOR_GRAY2BGR)
if pattern_type == 'chessboard':
cv.drawChessboardCorners(vis, pattern_size, corners, found)
elif pattern_type == 'charucoboard':
cv.aruco.drawDetectedCornersCharuco(vis, corners, charucoIds=charucoIds)
_path, name, _ext = splitfn(fn)
outfile = os.path.join(debug_dir, name + '_board.png')
cv.imwrite(outfile, vis)
if not found:
print('pattern not found')
return None
print(' %s... OK' % fn)
return (frame_img_points, frame_obj_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 + '_board.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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