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# ----------------------------------------------------------------------------
# - Open3D: www.open3d.org -
# ----------------------------------------------------------------------------
# The MIT License (MIT)
#
# Copyright (c) 2018-2021 www.open3d.org
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
# FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
# IN THE SOFTWARE.
# ----------------------------------------------------------------------------
import os
import configargparse
class ConfigParser(configargparse.ArgParser):
def __init__(self):
super().__init__(default_config_files=[
os.path.join(os.path.dirname(__file__), 'default_config.yml')
],
conflict_handler='resolve')
# yapf:disable
# Default arguments
self.add(
'--name', type=str,
help='Name of the config for the offline reconstruction system.')
self.add(
'--fragment_size', type=int,
help='Number of RGBD frames to construct a fragment.')
self.add(
'--device', type=str,
help='Device to run the system.')
self.add(
'--engine', type=str,
choices=['tensor', 'legacy'],
help='Open3D engine to reconstruct.')
self.add(
'--multiprocessing', action='store_true',
help='Use multiprocessing in operations. Only available for the legacy engine.')
input_parser = self.add_argument_group('input')
input_parser.add(
'--path_dataset', type=str,
help='Path to the dataset folder. It should contain a folder with depth and a folder with color images.')
input_parser.add(
'--depth_folder', type=str,
help='Path that stores depth images.')
input_parser.add(
'--color_folder', type=str,
help='Path that stores color images.')
input_parser.add(
'--path_intrinsic', type=str,
help='Path to the intrinsic.json config file.'
'If the intrinsic matrix for color image is different,'
'specify it by --path_color_intrinsic.'
'By default PrimeSense intrinsics is used.')
input_parser.add(
'--path_color_intrinsic', type=str,
help='Path to the intrinsic.json config file.'
'If the intrinsic matrix for color image is different,'
'specify it by --path_color_intrinsic.'
'By default PrimeSense intrinsics is used.')
input_parser.add(
'--depth_min', type=float,
help='Min clipping distance (in meter) for input depth data.')
input_parser.add(
'--depth_max', type=float,
help='Max clipping distance (in meter) for input depth data.')
input_parser.add(
'--depth_scale', type=float,
help='Scale factor to convert raw input depth data to meters.')
odometry_parser = self.add_argument_group('odometry')
odometry_parser.add(
'--odometry_method', type=str,
choices=['point2plane', 'intensity', 'hybrid', 'frame2model'],
help='Method used in pose estimation between RGBD images.'
'Frame2model only available for the tensor engine.')
odometry_parser.add(
'--odometry_loop_interval', type=int,
help='Intervals to check loop closures between RGBD images.')
odometry_parser.add(
'--odometry_loop_weight', type=float,
help='Weight of loop closure edges when optimizing pose graphs for odometry.')
odometry_parser.add(
'--odometry_distance_thr', type=float,
help='Default distance threshold to filter outliers in odometry correspondences.')
registration_parser = self.add_argument_group('registration')
registration_parser.add(
'--icp_method', type=str,
choices=['colored', 'point2point', 'point2plane', 'generalized'],
help='Method used in registration between fragment point clouds with a good initial pose estimate.'
'Generalized ICP only available for the tensor engine.')
registration_parser.add(
'--icp_voxelsize', type=float,
help='Voxel size used to down sample point cloud for fast/multiscale ICP.')
registration_parser.add(
'--icp_distance_thr', type=float,
help='Default distance threshold to filter outliers in ICP correspondences.')
registration_parser.add(
'--global_registration_method', type=str,
choices=['fgr', 'ransac'],
help='Method used in global registration of two fragment point clouds without an initial pose estimate.')
registration_parser.add(
'--registration_loop_weight', type=float,
help='Weight of loop closure edges when optimizing pose graphs for registration.')
integration_parser = self.add_argument_group('integration')
integration_parser.add(
'--integration_mode',type=str,
choices=['color', 'depth'],
help='Volumetric integration mode.')
integration_parser.add(
'--voxel_size', type=float,
help='Voxel size in meter for volumetric integration.')
integration_parser.add(
'--trunc_voxel_multiplier', type=float,
help='Truncation distance multiplier in voxel size for signed distance. For instance, --trunc_voxel_multiplier=8 with --voxel_size=0.006(m) creates a truncation distance of 0.048(m).')
integration_parser.add(
'--est_point_count', type=int,
help='Estimated point cloud size for surface extraction.')
integration_parser.add(
'--block_count', type=int,
help='Pre-allocated voxel block count for volumetric integration.')
integration_parser.add(
'--surface_weight_thr', type=float,
help='Weight threshold to filter outliers during volumetric surface reconstruction.')
# yapf:enable
def get_config(self):
config = self.parse_args()
# Resolve conflicts
if config.engine == 'legacy':
if config.device.lower().startswith('cuda'):
print('Legacy engine only supports CPU.', 'Fallback to CPU.')
config.device = 'CPU:0'
if config.odometry_method == 'frame2model':
print('Legacy engine does not supports frame2model tracking.',
'Fallback to hybrid odometry.')
config.odometry_method = 'hybrid'
if config.engine == 'tensor':
if config.icp_method == 'generalized':
print('Tensor engine does not support generalized ICP.',
'Fallback to colored ICP.')
config.icp_method = 'colored'
if config.multiprocessing:
print('Tensor engine does not support multiprocessing.',
'Disabled.')
config.multiprocessing = False
return config
if __name__ == '__main__':
# Priority: command line > custom config file > default config file
parser = ConfigParser()
parser.add(
'--config',
is_config_file=True,
help='YAML config file path. Please refer to default_config.yml as a '
'reference. It overrides the default config file, but will be '
'overridden by other command line inputs.')
config = parser.get_config()
print(config)
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