diff --git a/samples/python/calibrate.py b/samples/python/calibrate.py index 991a531ede..9528f67aa4 100755 --- a/samples/python/calibrate.py +++ b/samples/python/calibrate.py @@ -5,11 +5,21 @@ 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] [] + calibrate.py [--debug ] [-w ] [-h ] [-t ] [--square_size=] + [--marker_size=] [--aruco_dict=] [] + +usage example: + calibrate.py -w 4 -h 6 -t chessboard --square_size=50 ../data/left*.jpg default values: --debug: ./output/ - --square_size: 1.0 + -w: 4 + -h: 6 + -t: chessboard + --square_size: 50 + --marker_size: 25 + --aruco_dict: DICT_4X4_50 + --threads: 4 defaults to ../data/left*.jpg ''' @@ -30,31 +40,81 @@ def main(): import getopt from glob import glob - args, img_mask = getopt.getopt(sys.argv[1:], '', ['debug=', 'square_size=', 'threads=']) + 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('--square_size', 1.0) + 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_mask: - img_mask = '../data/left??.jpg' # default - else: - img_mask = img_mask[0] - img_names = glob(img_mask) + 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) - 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 + 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 = (height, width) + 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 + elif pattern_type == 'charucoboard': + pattern_points = np.zeros((np.prod((height-1, width-1)), 3), np.float32) + pattern_points[:, :2] = np.indices((height-1, width-1)).T.reshape(-1, 2) + pattern_points *= square_size + else: + print("unknown pattern") + return None 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) @@ -63,10 +123,20 @@ def main(): 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) + 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) + elif pattern_type == 'charucoboard': + corners, _charucoIds, _markerCorners_svg, _markerIds_svg = charuco_detector.detectBoard(img) + if (len(corners) == (height-1)*(width-1)): + found = True + else: + print("unknown pattern type", pattern_type) + return None if debug_dir: vis = cv.cvtColor(img, cv.COLOR_GRAY2BGR) @@ -76,7 +146,7 @@ def main(): cv.imwrite(outfile, vis) if not found: - print('chessboard not found') + print('pattern not found') return None print(' %s... OK' % fn)