#!/usr/bin/python
#
# This file is part of fluid3d - a software for image registration
#
# Copyright (c) Madrid 2013 Gert Wollny
#
# fluid3d is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with fluid3d; if not, see <http://www.gnu.org/licenses/>.
#
#
import nibabel
import pyopencl as cl
import registration
from argparse import ArgumentParser
from argparse import RawTextHelpFormatter
from OpenCLHelpers import get_cl_devices
parser = ArgumentParser(description='Fluid dynamics registration of two 3D images.',
formatter_class=RawTextHelpFormatter)
group = parser.add_argument_group('File I/O')
group.add_argument("-s", "--study", action="store", required=True, help="study image to be registered")
group.add_argument("-r", "--ref", action="store", required=True, help="reference image to be registered to")
group.add_argument("-o", "--outimage", action="store", required=True, help="registered and transformed study image")
(devchoices, devhelp, devices) = get_cl_devices()
group = parser.add_argument_group('Processing')
group.add_argument("-d", "--device", action="store", choices= devchoices,
help="Device to be used for computations:\n" + devhelp)
group = parser.add_argument_group('Registration')
group.add_argument("-S", "--min-start-size", action="store", type=int, default=16, dest='minstartsize'
help="Minimum start size for multi-resolution processing")
options = parser.parse_args()
try:
study = nibabel.load(options.study)
ref = nibabel.load(options.ref)
device_to_use = [devices[options.device]]
ctx = cl.Contex(device_to_use)
registration = C3DNRRegistration(ctx, options.min_start_size)
(transform, deformed) = registration.run(study, ref)
except ValueError as verror:
print (