def main():
from optparse import OptionParser, OptionGroup
parser = OptionParser("%prog --size SIZE1 --square SQUARE1 [ --size SIZE2 --square SQUARE2 ]",
description=None)
parser.add_option("-c", "--camera_name",
type="string", default='narrow_stereo',
help="name of the camera to appear in the calibration file")
group = OptionGroup(parser, "Chessboard Options",
"You must specify one or more chessboards as pairs of --size and --square options.")
group.add_option("-p", "--pattern",
type="string", default="chessboard",
help="calibration pattern to detect - 'chessboard', 'circles', 'acircles', 'charuco'\n" +
" if 'charuco' is used, a --charuco_marker_size and --aruco_dict argument must be supplied\n" +
" with each --size and --square argument")
group.add_option("-s", "--size",
action="append", default=[],
help="chessboard size as NxM, counting interior corners (e.g. a standard chessboard is 7x7)")
group.add_option("-q", "--square",
action="append", default=[],
help="chessboard square size in meters")
group.add_option("-m", "--charuco_marker_size",
action="append", default=[],
help="ArUco marker size (meters); only valid with `-p charuco`")
group.add_option("-d", "--aruco_dict",
action="append", default=[],
help="ArUco marker dictionary; only valid with `-p charuco`; one of 'aruco_orig', '4x4_250', " +
"'5x5_250', '6x6_250', '7x7_250'")
parser.add_option_group(group)
group = OptionGroup(parser, "ROS Communication Options")
group.add_option("--approximate",
type="float", default=0.0,
help="allow specified slop (in seconds) when pairing images from unsynchronized stereo cameras")
group.add_option("--no-service-check",
action="store_false", dest="service_check", default=True,
help="disable check for set_camera_info services at startup")
group.add_option("--queue-size",
type="int", default=1,
help="image queue size (default %default, set to 0 for unlimited)")
parser.add_option_group(group)
group = OptionGroup(parser, "Calibration Optimizer Options")
group.add_option("--fix-principal-point",
action="store_true", default=False,
help="for pinhole, fix the principal point at the image center")
group.add_option("--fix-aspect-ratio",
action="store_true", default=False,
help="for pinhole, enforce focal lengths (fx, fy) are equal")
group.add_option("--zero-tangent-dist",
action="store_true", default=False,
help="for pinhole, set tangential distortion coefficients (p1, p2) to zero")
group.add_option("-k", "--k-coefficients",
type="int", default=2, metavar="NUM_COEFFS",
help="for pinhole, number of radial distortion coefficients to use (up to 6, default %default)")
group.add_option("--fisheye-recompute-extrinsicsts",
action="store_true", default=False,
help="for fisheye, extrinsic will be recomputed after each iteration of intrinsic optimization")
group.add_option("--fisheye-fix-skew",
action="store_true", default=False,
help="for fisheye, skew coefficient (alpha) is set to zero and stay zero")
group.add_option("--fisheye-fix-principal-point",
action="store_true", default=False,
help="for fisheye,fix the principal point at the image center")
group.add_option("--fisheye-k-coefficients",
type="int", default=4, metavar="NUM_COEFFS",
help="for fisheye, number of radial distortion coefficients to use fixing to zero the rest (up to 4, default %default)")
group.add_option("--fisheye-check-conditions",
action="store_true", default=False,
help="for fisheye, the functions will check validity of condition number")
group.add_option("--disable_calib_cb_fast_check", action='store_true', default=False,
help="uses the CALIB_CB_FAST_CHECK flag for findChessboardCorners")
group.add_option("--max-chessboard-speed", type="float", default=-1.0,
help="Do not use samples where the calibration pattern is moving faster \
than this speed in px/frame. Set to eg. 0.5 for rolling shutter cameras.")
parser.add_option_group(group)
options, args = parser.parse_args()
if (len(options.size) != len(options.square)):
parser.error("Number of size and square inputs must be the same!")
if not options.square:
options.square.append("0.108")
options.size.append("8x6")
boards = []
if options.pattern == "charuco" and optionsValidCharuco(options, parser):
for (sz, sq, ms, ad) in zip(options.size, options.square, options.charuco_marker_size, options.aruco_dict):
size = tuple([int(c) for c in sz.split('x')])
boards.append(ChessboardInfo('charuco', size[0], size[1], float(sq), float(ms), ad))
else:
for (sz, sq) in zip(options.size, options.square):
size = tuple([int(c) for c in sz.split('x')])
boards.append(ChessboardInfo(options.pattern, size[0], size[1], float(sq)))
if options.approximate == 0.0:
sync = message_filters.TimeSynchronizer
else:
sync = functools.partial(ApproximateTimeSynchronizer, slop=options.approximate)
# Pinhole opencv calibration options parsing
num_ks = options.k_coefficients
calib_flags = 0
if options.fix_principal_point:
calib_flags |= cv2.CALIB_FIX_PRINCIPAL_POINT
if options.fix_aspect_ratio:
calib_flags |= cv2.CALIB_FIX_ASPECT_RATIO
if options.zero_tangent_dist:
calib_flags |= cv2.CALIB_ZERO_TANGENT_DIST
if (num_ks > 3):
calib_flags |= cv2.CALIB_RATIONAL_MODEL
if (num_ks < 6):
calib_flags |= cv2.CALIB_FIX_K6
if (num_ks < 5):
calib_flags |= cv2.CALIB_FIX_K5
if (num_ks < 4):
calib_flags |= cv2.CALIB_FIX_K4
if (num_ks < 3):
calib_flags |= cv2.CALIB_FIX_K3
if (num_ks < 2):
calib_flags |= cv2.CALIB_FIX_K2
if (num_ks < 1):
calib_flags |= cv2.CALIB_FIX_K1
# Opencv calibration flags parsing:
num_ks = options.fisheye_k_coefficients
fisheye_calib_flags = 0
if options.fisheye_fix_principal_point:
fisheye_calib_flags |= cv2.fisheye.CALIB_FIX_PRINCIPAL_POINT
if options.fisheye_fix_skew:
fisheye_calib_flags |= cv2.fisheye.CALIB_FIX_SKEW
if options.fisheye_recompute_extrinsicsts:
fisheye_calib_flags |= cv2.fisheye.CALIB_RECOMPUTE_EXTRINSIC
if options.fisheye_check_conditions:
fisheye_calib_flags |= cv2.fisheye.CALIB_CHECK_COND
if (num_ks < 4):
fisheye_calib_flags |= cv2.fisheye.CALIB_FIX_K4
if (num_ks < 3):
fisheye_calib_flags |= cv2.fisheye.CALIB_FIX_K3
if (num_ks < 2):
fisheye_calib_flags |= cv2.fisheye.CALIB_FIX_K2
if (num_ks < 1):
fisheye_calib_flags |= cv2.fisheye.CALIB_FIX_K1
pattern = Patterns.Chessboard
if options.pattern == 'circles':
pattern = Patterns.Circles
elif options.pattern == 'acircles':
pattern = Patterns.ACircles
elif options.pattern == 'charuco':
pattern = Patterns.ChArUco
elif options.pattern != 'chessboard':
print('Unrecognized pattern %s, defaulting to chessboard' % options.pattern)
if options.disable_calib_cb_fast_check:
checkerboard_flags = 0
else:
checkerboard_flags = cv2.CALIB_CB_FAST_CHECK
rospy.init_node('cameracalibrator')
node = OpenCVCalibrationNode(boards, options.service_check, sync, calib_flags, fisheye_calib_flags, pattern, options.camera_name,
checkerboard_flags=checkerboard_flags, max_chessboard_speed=options.max_chessboard_speed,
queue_size=options.queue_size)
rospy.spin()
def main():
from optparse import OptionParser, OptionGroup
parser = OptionParser("%prog --size SIZE1 --square SQUARE1 [ --size SIZE2 --square SQUARE2 ]",
description=None)
parser.add_option("-c", "--camera_name",
type="string", default='autoware_camera_calibration',
help="name of the camera to appear in the calibration file")
parser.add_option("-o", "--output",
type="string", default="yaml",
help="type of output - 'yaml' or 'tar'")
parser.add_option("-d", "--detection",
type="string", default="cv2",
help="Chessboard detection algorithm, OpenCV2 or Matlab (python matlab engine) - 'cv2', 'matlab'")
group = OptionGroup(parser, "Chessboard Options",
"You must specify one or more chessboards as pairs of --size and --square options.")
group.add_option("-p", "--pattern",
type="string", default="chessboard",
help="calibration pattern to detect - 'chessboard', 'circles', 'acircles'")
group.add_option("-s", "--size",
action="append", default=[],
help="chessboard size as NxM, counting interior corners (e.g. a standard chessboard is 7x7)")
group.add_option("-q", "--square",
action="append", default=[],
help="chessboard square size in meters")
group.add_option("--min_samples",
type="int", default=40,
help="defines the minimum number of samples before allowing to calibrate regardless of the status")
parser.add_option_group(group)
group = OptionGroup(parser, "ROS Communication Options")
group.add_option("--approximate",
type="float", default=0.0,
help="allow specified slop (in seconds) when pairing images from unsynchronized stereo cameras")
group.add_option("--no-service-check",
action="store_false", dest="service_check", default=True,
help="disable check for set_camera_info services at startup")
parser.add_option_group(group)
group = OptionGroup(parser, "Calibration Optimizer Options")
group.add_option("--fix-principal-point",
action="store_true", default=False,
help="fix the principal point at the image center")
group.add_option("--fix-aspect-ratio",
action="store_true", default=False,
help="enforce focal lengths (fx, fy) are equal")
group.add_option("--zero-tangent-dist",
action="store_true", default=False,
help="set tangential distortion coefficients (p1, p2) to zero")
group.add_option("-k", "--k-coefficients",
type="int", default=3, metavar="NUM_COEFFS",
help="number of radial distortion coefficients to use (up to 6, default %default)")
group.add_option("--disable_calib_cb_fast_check", action='store_true', default=False,
help="uses the CALIB_CB_FAST_CHECK flag for findChessboardCorners")
parser.add_option_group(group)
options, args = parser.parse_args()
if len(options.size) != len(options.square):
parser.error("Number of size and square inputs must be the same!")
if options.detection == "cv2":
print('Using OpenCV 2 for chessboard corner detection')
elif options.detection == "matlab":
print('Using matlab for chessboard corner detection')
else:
print('Unrecognized detection method %s, defaulting to OpenCV 2' % options.detection)
options.detection = "cv2"
if options.output == "yaml":
print('Saving as autoware yaml')
elif options.output == "tar":
print('Saving as tar')
else:
print('Unrecognized output method %s, defaulting to Autoware Yaml' % options.output)
options.output = "yaml"
if not options.square:
options.square.append("0.108")
options.size.append("8x6")
boards = []
for (sz, sq) in zip(options.size, options.square):
size = tuple([int(c) for c in sz.split('x')])
boards.append(ChessboardInfo(size[0], size[1], float(sq)))
if options.approximate == 0.0:
sync = message_filters.TimeSynchronizer
else:
sync = functools.partial(ApproximateTimeSynchronizer, slop=options.approximate)
num_ks = options.k_coefficients
calib_flags = 0
if options.fix_principal_point:
calib_flags |= cv2.CALIB_FIX_PRINCIPAL_POINT
if options.fix_aspect_ratio:
calib_flags |= cv2.CALIB_FIX_ASPECT_RATIO
if options.zero_tangent_dist:
calib_flags |= cv2.CALIB_ZERO_TANGENT_DIST
if (num_ks > 3):
calib_flags |= cv2.CALIB_RATIONAL_MODEL
if (num_ks < 6):
calib_flags |= cv2.CALIB_FIX_K6
if (num_ks < 5):
calib_flags |= cv2.CALIB_FIX_K5
if (num_ks < 4):
calib_flags |= cv2.CALIB_FIX_K4
if (num_ks < 3):
calib_flags |= cv2.CALIB_FIX_K3
if (num_ks < 2):
calib_flags |= cv2.CALIB_FIX_K2
if (num_ks < 1):
calib_flags |= cv2.CALIB_FIX_K1
pattern = Patterns.Chessboard
if options.pattern == 'circles':
pattern = Patterns.Circles
elif options.pattern == 'acircles':
pattern = Patterns.ACircles
elif options.pattern != 'chessboard':
print('Unrecognized pattern %s, defaulting to chessboard' % options.pattern)
if options.disable_calib_cb_fast_check:
checkerboard_flags = 0
else:
checkerboard_flags = cv2.CALIB_CB_FAST_CHECK
rospy.init_node('cameracalibrator')
node = OpenCVCalibrationNode(boards, options.service_check, sync, calib_flags, pattern, options.camera_name,
options.detection, options.output, min_good_enough=options.min_samples, checkerboard_flags=checkerboard_flags)
rospy.spin()
def main(args=None):
from optparse import OptionParser, OptionGroup
parser = OptionParser(
"%prog --size SIZE1 --square SQUARE1 [ --size SIZE2 --square SQUARE2 ]",
description=None)
parser.add_option(
"-c",
"--camera_name",
type="string",
default='narrow_stereo',
help="name of the camera to appear in the calibration file")
parser.add_option(
"--image",
type="string",
default='image',
help="name of the image topic to appear in the calibration file")
parser.add_option(
"--camera",
type="string",
default='camera',
help="name of the camera topic to appear in the calibration file")
parser.add_option(
"--left_camera",
type="string",
default='left_camera',
help="name of the left camera to appear in the calibration file")
parser.add_option(
"--right_camera",
type="string",
default='right_camera',
help="name of the right camera to appear in the calibration file")
group = OptionGroup(
parser, "Chessboard Options",
"You must specify one or more chessboards as pairs of --size and --square options."
)
group.add_option(
"-p",
"--pattern",
type="string",
default="chessboard",
help=
"calibration pattern to detect - 'chessboard', 'circles', 'acircles'")
group.add_option(
"-s",
"--size",
action="append",
default=[],
help=
"chessboard size as NxM, counting interior corners (e.g. a standard chessboard is 7x7)"
)
group.add_option("-q",
"--square",
action="append",
default=[],
help="chessboard square size in meters")
parser.add_option_group(group)
group = OptionGroup(parser, "ROS Communication Options")
group.add_option(
"--approximate",
type="float",
default=0.0,
help=
"allow specified slop (in seconds) when pairing images from unsynchronized stereo cameras"
)
group.add_option(
"--no-service-check",
action="store_false",
dest="service_check",
default=False,
help="disable check for set_camera_info services at startup")
parser.add_option_group(group)
group = OptionGroup(parser, "Calibration Optimizer Options")
group.add_option("--fix-principal-point",
action="store_true",
default=False,
help="fix the principal point at the image center")
group.add_option("--fix-aspect-ratio",
action="store_true",
default=False,
help="enforce focal lengths (fx, fy) are equal")
group.add_option(
"--zero-tangent-dist",
action="store_true",
default=False,
help="set tangential distortion coefficients (p1, p2) to zero")
group.add_option(
"-k",
"--k-coefficients",
type="int",
default=2,
metavar="NUM_COEFFS",
help=
"number of radial distortion coefficients to use (up to 6, default %default)"
)
group.add_option(
"--disable_calib_cb_fast_check",
action='store_true',
default=False,
help="uses the CALIB_CB_FAST_CHECK flag for findChessboardCorners")
parser.add_option_group(group)
options, args = parser.parse_args()
if len(options.size) != len(options.square):
parser.error("Number of size and square inputs must be the same!")
if not options.square:
options.square.append("0.108")
options.size.append("8x6")
boards = []
for (sz, sq) in zip(options.size, options.square):
size = tuple([int(c) for c in sz.split('x')])
boards.append(ChessboardInfo(size[0], size[1], float(sq)))
if options.approximate == 0.0:
sync = message_filters.TimeSynchronizer
else:
sync = functools.partial(ApproximateTimeSynchronizer,
slop=options.approximate)
num_ks = options.k_coefficients
calib_flags = 0
if options.fix_principal_point:
calib_flags |= cv2.CALIB_FIX_PRINCIPAL_POINT
if options.fix_aspect_ratio:
calib_flags |= cv2.CALIB_FIX_ASPECT_RATIO
if options.zero_tangent_dist:
calib_flags |= cv2.CALIB_ZERO_TANGENT_DIST
if (num_ks > 3):
calib_flags |= cv2.CALIB_RATIONAL_MODEL
if (num_ks < 6):
calib_flags |= cv2.CALIB_FIX_K6
if (num_ks < 5):
calib_flags |= cv2.CALIB_FIX_K5
if (num_ks < 4):
calib_flags |= cv2.CALIB_FIX_K4
if (num_ks < 3):
calib_flags |= cv2.CALIB_FIX_K3
if (num_ks < 2):
calib_flags |= cv2.CALIB_FIX_K2
if (num_ks < 1):
calib_flags |= cv2.CALIB_FIX_K1
pattern = Patterns.Chessboard
if options.pattern == 'circles':
pattern = Patterns.Circles
elif options.pattern == 'acircles':
pattern = Patterns.ACircles
elif options.pattern != 'chessboard':
print('Unrecognized pattern %s, defaulting to chessboard' %
options.pattern)
if options.disable_calib_cb_fast_check:
checkerboard_flags = 0
else:
checkerboard_flags = cv2.CALIB_CB_FAST_CHECK
rclpy.init(args=args)
node = OpenCVCalibrationNode(boards,
options.service_check,
sync,
calib_flags,
pattern,
camera_name=options.camera_name,
camera=options.camera,
left_camera=options.left_camera,
right_camera=options.right_camera,
image=options.image,
checkerboard_flags=checkerboard_flags)
rclpy.spin(node)
node.destroy_node()
rclpy.shutdown()