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Reworked calibrate.py

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- Fixed width and height swap in board size
- Fixed defaults in command line hint
- Fixed board visualization for Charuco case
- Used matchImagePoints method to handle partially detected Charuco boards
This commit is contained in:
Alexander Smorkalov 2023-06-23 22:04:02 +03:00
parent bf06bc92aa
commit 85ea247cc6
1 changed files with 40 additions and 37 deletions
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77
samples/python/calibrate.py
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@ -16,11 +16,13 @@ default values:
-w: 4 -w: 4
-h: 6 -h: 6
-t: chessboard -t: chessboard
--square_size: 50 --square_size: 10
--marker_size: 25 --marker_size: 5
--aruco_dict: DICT_4X4_50 --aruco_dict: DICT_4X4_50
--threads: 4 --threads: 4
<image mask> defaults to ../data/left*.jpg <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 # Python 2/3 compatibility
@ -67,45 +69,38 @@ def main():
marker_size = float(args.get('--marker_size')) marker_size = float(args.get('--marker_size'))
aruco_dict_name = str(args.get('--aruco_dict')) aruco_dict_name = str(args.get('--aruco_dict'))
pattern_size = (height, width) pattern_size = (width, height)
if pattern_type == 'chessboard': if pattern_type == 'chessboard':
pattern_points = np.zeros((np.prod(pattern_size), 3), np.float32) pattern_points = np.zeros((np.prod(pattern_size), 3), np.float32)
pattern_points[:, :2] = np.indices(pattern_size).T.reshape(-1, 2) pattern_points[:, :2] = np.indices(pattern_size).T.reshape(-1, 2)
pattern_points *= square_size 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 = [] obj_points = []
img_points = [] img_points = []
h, w = cv.imread(img_names[0], cv.IMREAD_GRAYSCALE).shape[:2] # TODO: use imquery call to retrieve results h, w = cv.imread(img_names[0], cv.IMREAD_GRAYSCALE).shape[:2] # TODO: use imquery call to retrieve results
aruco_dicts = { aruco_dicts = {
'DICT_4X4_50':cv.aruco.DICT_4X4_50, 'DICT_4X4_50': cv.aruco.DICT_4X4_50,
'DICT_4X4_100':cv.aruco.DICT_4X4_100, 'DICT_4X4_100': cv.aruco.DICT_4X4_100,
'DICT_4X4_250':cv.aruco.DICT_4X4_250, 'DICT_4X4_250': cv.aruco.DICT_4X4_250,
'DICT_4X4_1000':cv.aruco.DICT_4X4_1000, 'DICT_4X4_1000': cv.aruco.DICT_4X4_1000,
'DICT_5X5_50':cv.aruco.DICT_5X5_50, 'DICT_5X5_50': cv.aruco.DICT_5X5_50,
'DICT_5X5_100':cv.aruco.DICT_5X5_100, 'DICT_5X5_100': cv.aruco.DICT_5X5_100,
'DICT_5X5_250':cv.aruco.DICT_5X5_250, 'DICT_5X5_250': cv.aruco.DICT_5X5_250,
'DICT_5X5_1000':cv.aruco.DICT_5X5_1000, 'DICT_5X5_1000': cv.aruco.DICT_5X5_1000,
'DICT_6X6_50':cv.aruco.DICT_6X6_50, 'DICT_6X6_50': cv.aruco.DICT_6X6_50,
'DICT_6X6_100':cv.aruco.DICT_6X6_100, 'DICT_6X6_100': cv.aruco.DICT_6X6_100,
'DICT_6X6_250':cv.aruco.DICT_6X6_250, 'DICT_6X6_250': cv.aruco.DICT_6X6_250,
'DICT_6X6_1000':cv.aruco.DICT_6X6_1000, 'DICT_6X6_1000': cv.aruco.DICT_6X6_1000,
'DICT_7X7_50':cv.aruco.DICT_7X7_50, 'DICT_7X7_50': cv.aruco.DICT_7X7_50,
'DICT_7X7_100':cv.aruco.DICT_7X7_100, 'DICT_7X7_100': cv.aruco.DICT_7X7_100,
'DICT_7X7_250':cv.aruco.DICT_7X7_250, 'DICT_7X7_250': cv.aruco.DICT_7X7_250,
'DICT_7X7_1000':cv.aruco.DICT_7X7_1000, 'DICT_7X7_1000': cv.aruco.DICT_7X7_1000,
'DICT_ARUCO_ORIGINAL':cv.aruco.DICT_ARUCO_ORIGINAL, 'DICT_ARUCO_ORIGINAL': cv.aruco.DICT_ARUCO_ORIGINAL,
'DICT_APRILTAG_16h5':cv.aruco.DICT_APRILTAG_16h5, 'DICT_APRILTAG_16h5': cv.aruco.DICT_APRILTAG_16h5,
'DICT_APRILTAG_25h9':cv.aruco.DICT_APRILTAG_25h9, 'DICT_APRILTAG_25h9': cv.aruco.DICT_APRILTAG_25h9,
'DICT_APRILTAG_36h10':cv.aruco.DICT_APRILTAG_36h10, 'DICT_APRILTAG_36h10': cv.aruco.DICT_APRILTAG_36h10,
'DICT_APRILTAG_36h11':cv.aruco.DICT_APRILTAG_36h11 'DICT_APRILTAG_36h11': cv.aruco.DICT_APRILTAG_36h11
} }
if (aruco_dict_name not in set(aruco_dicts.keys())): if (aruco_dict_name not in set(aruco_dicts.keys())):
@ -130,19 +125,27 @@ def main():
if found: if found:
term = (cv.TERM_CRITERIA_EPS + cv.TERM_CRITERIA_COUNT, 30, 0.1) term = (cv.TERM_CRITERIA_EPS + cv.TERM_CRITERIA_COUNT, 30, 0.1)
cv.cornerSubPix(img, corners, (5, 5), (-1, -1), term) 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': elif pattern_type == 'charucoboard':
corners, _charucoIds, _markerCorners_svg, _markerIds_svg = charuco_detector.detectBoard(img) corners, charucoIds, _, _ = charuco_detector.detectBoard(img)
if (len(corners) == (height-1)*(width-1)): if (len(corners) > 0):
frame_obj_points, frame_img_points = board.matchImagePoints(corners, charucoIds)
found = True found = True
else:
found = False
else: else:
print("unknown pattern type", pattern_type) print("unknown pattern type", pattern_type)
return None return None
if debug_dir: if debug_dir:
vis = cv.cvtColor(img, cv.COLOR_GRAY2BGR) vis = cv.cvtColor(img, cv.COLOR_GRAY2BGR)
cv.drawChessboardCorners(vis, pattern_size, corners, found) 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) _path, name, _ext = splitfn(fn)
outfile = os.path.join(debug_dir, name + '_chess.png') outfile = os.path.join(debug_dir, name + '_board.png')
cv.imwrite(outfile, vis) cv.imwrite(outfile, vis)
if not found: if not found:
@ -150,7 +153,7 @@ def main():
return None return None
print(' %s... OK' % fn) print(' %s... OK' % fn)
return (corners.reshape(-1, 2), pattern_points) return (frame_img_points, frame_obj_points)
threads_num = int(args.get('--threads')) threads_num = int(args.get('--threads'))
if threads_num <= 1: if threads_num <= 1:
@ -177,7 +180,7 @@ def main():
print('') print('')
for fn in img_names if debug_dir else []: for fn in img_names if debug_dir else []:
_path, name, _ext = splitfn(fn) _path, name, _ext = splitfn(fn)
img_found = os.path.join(debug_dir, name + '_chess.png') img_found = os.path.join(debug_dir, name + '_board.png')
outfile = os.path.join(debug_dir, name + '_undistorted.png') outfile = os.path.join(debug_dir, name + '_undistorted.png')
img = cv.imread(img_found) img = cv.imread(img_found)