OpenDroneMap-ODM/opendm/config.py

803 wiersze
38 KiB
Python
Executable File

import argparse
import json
from opendm import context
from opendm import io
from opendm import log
from appsettings import SettingsParser
from pyodm import Node, exceptions
import sys
# parse arguments
processopts = ['dataset', 'split', 'merge', 'opensfm', 'mve', 'odm_filterpoints',
'odm_meshing', 'mvs_texturing', 'odm_georeferencing',
'odm_dem', 'odm_orthophoto', 'odm_report']
with open(io.join_paths(context.root_path, 'VERSION')) as version_file:
__version__ = version_file.read().strip()
def alphanumeric_string(string):
import re
if re.match('^[a-zA-Z0-9_-]+$', string) is None:
msg = '{0} is not a valid name. Must use alphanumeric characters.'.format(string)
raise argparse.ArgumentTypeError(msg)
return string
def path_or_json_string(string):
try:
return io.path_or_json_string_to_dict(string)
except ValueError as e:
raise argparse.ArgumentTypeError("{0}".format(str(e)))
# Django URL validation regex
def url_string(string):
import re
regex = re.compile(
r'^(?:http|ftp)s?://' # http:// or https://
r'(?:(?:[A-Z0-9](?:[A-Z0-9-]{0,61}[A-Z0-9])?\.?)+(?:[A-Z]{2,6}\.?|[A-Z0-9-]{2,}\.?)|' #domain...
r'localhost|' #localhost...
r'\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3})' # ...or ip
r'(?::\d+)?' # optional port
r'(?:/?|[/?]\S+)$', re.IGNORECASE)
if re.match(regex, string) is None:
raise argparse.ArgumentTypeError("%s is not a valid URL. The URL must be in the format: http(s)://host[:port]/[?token=]" % string)
return string
class RerunFrom(argparse.Action):
def __call__(self, parser, namespace, values, option_string=None):
setattr(namespace, self.dest, processopts[processopts.index(values):])
setattr(namespace, self.dest + '_is_set', True)
class StoreTrue(argparse.Action):
def __call__(self, parser, namespace, values, option_string=None):
setattr(namespace, self.dest, True)
setattr(namespace, self.dest + '_is_set', True)
class StoreValue(argparse.Action):
def __call__(self, parser, namespace, values, option_string=None):
setattr(namespace, self.dest, values)
setattr(namespace, self.dest + '_is_set', True)
args = None
def config(argv=None):
global args
if args is not None and argv is None:
return args
parser = SettingsParser(description='ODM',
usage='%(prog)s [options] <project name>',
yaml_file=open(context.settings_path))
parser.add_argument('--project-path',
metavar='<path>',
action=StoreValue,
help='Path to the project folder')
parser.add_argument('name',
metavar='<project name>',
action=StoreValue,
type=alphanumeric_string,
default='code',
nargs='?',
help='Name of Project (i.e subdirectory of projects folder)')
parser.add_argument('--resize-to',
metavar='<integer>',
action=StoreValue,
default=2048,
type=int,
help='Legacy option (use --feature-quality instead). Resizes images by the largest side for feature extraction purposes only. '
'Set to -1 to disable. This does not affect the final orthophoto '
'resolution quality and will not resize the original images. Default: %(default)s')
parser.add_argument('--end-with', '-e',
metavar='<string>',
action=StoreValue,
default='odm_report',
choices=processopts,
help=('Can be one of:' + ' | '.join(processopts)))
rerun = parser.add_mutually_exclusive_group()
rerun.add_argument('--rerun', '-r',
metavar='<string>',
action=StoreValue,
choices=processopts,
help=('Can be one of:' + ' | '.join(processopts)))
rerun.add_argument('--rerun-all',
action=StoreTrue,
nargs=0,
default=False,
help='force rerun of all tasks')
rerun.add_argument('--rerun-from',
action=RerunFrom,
metavar='<string>',
choices=processopts,
help=('Can be one of:' + ' | '.join(processopts)))
# parser.add_argument('--video',
# metavar='<string>',
# help='Path to the video file to process')
# parser.add_argument('--slam-config',
# metavar='<string>',
# help='Path to config file for orb-slam')
parser.add_argument('--min-num-features',
metavar='<integer>',
action=StoreValue,
default=8000,
type=int,
help=('Minimum number of features to extract per image. '
'More features leads to better results but slower '
'execution. Default: %(default)s'))
parser.add_argument('--feature-type',
metavar='<string>',
action=StoreValue,
default='sift',
choices=['sift', 'hahog'],
help=('Choose the algorithm for extracting keypoints and computing descriptors. '
'Can be one of: %(choices)s. Default: '
'%(default)s'))
parser.add_argument('--feature-quality',
metavar='<string>',
action=StoreValue,
default='high',
choices=['ultra', 'high', 'medium', 'low', 'lowest'],
help=('Set feature extraction quality. Higher quality generates better features, but requires more memory and takes longer. '
'Can be one of: %(choices)s. Default: '
'%(default)s'))
parser.add_argument('--matcher-neighbors',
metavar='<integer>',
action=StoreValue,
default=8,
type=int,
help='Number of nearest images to pre-match based on GPS '
'exif data. Set to 0 to skip pre-matching. '
'Neighbors works together with Distance parameter, '
'set both to 0 to not use pre-matching. OpenSFM '
'uses both parameters at the same time, Bundler '
'uses only one which has value, prefering the '
'Neighbors parameter. Default: %(default)s')
parser.add_argument('--matcher-distance',
metavar='<integer>',
action=StoreValue,
default=0,
type=int,
help='Distance threshold in meters to find pre-matching '
'images based on GPS exif data. Set both '
'matcher-neighbors and this to 0 to skip '
'pre-matching. Default: %(default)s')
parser.add_argument('--use-fixed-camera-params',
action=StoreTrue,
nargs=0,
default=False,
help='Turn off camera parameter optimization during bundler')
parser.add_argument('--cameras',
default='',
metavar='<json>',
action=StoreValue,
type=path_or_json_string,
help='Use the camera parameters computed from '
'another dataset instead of calculating them. '
'Can be specified either as path to a cameras.json file or as a '
'JSON string representing the contents of a '
'cameras.json file. Default: %(default)s')
parser.add_argument('--camera-lens',
metavar='<string>',
action=StoreValue,
default='auto',
choices=['auto', 'perspective', 'brown', 'fisheye', 'spherical'],
help=('Set a camera projection type. Manually setting a value '
'can help improve geometric undistortion. By default the application '
'tries to determine a lens type from the images metadata. Can be '
'set to one of: %(choices)s. Default: '
'%(default)s'))
parser.add_argument('--radiometric-calibration',
metavar='<string>',
action=StoreValue,
default='none',
choices=['none', 'camera', 'camera+sun'],
help=('Set the radiometric calibration to perform on images. '
'When processing multispectral images you should set this option '
'to obtain reflectance values (otherwise you will get digital number values). '
'[camera] applies black level, vignetting, row gradient gain/exposure compensation (if appropriate EXIF tags are found). '
'[camera+sun] is experimental, applies all the corrections of [camera], plus compensates for spectral radiance registered via a downwelling light sensor (DLS) taking in consideration the angle of the sun. '
'Can be set to one of: %(choices)s. Default: '
'%(default)s'))
parser.add_argument('--max-concurrency',
metavar='<positive integer>',
action=StoreValue,
default=context.num_cores,
type=int,
help=('The maximum number of processes to use in various '
'processes. Peak memory requirement is ~1GB per '
'thread and 2 megapixel image resolution. Default: %(default)s'))
parser.add_argument('--depthmap-resolution',
metavar='<positive float>',
action=StoreValue,
type=float,
default=640,
help=('Controls the density of the point cloud by setting the resolution of the depthmap images. Higher values take longer to compute '
'but produce denser point clouds. '
'Default: %(default)s'))
parser.add_argument('--opensfm-depthmap-min-consistent-views',
metavar='<integer: 2 <= x <= 9>',
action=StoreValue,
type=int,
default=3,
help=('Minimum number of views that should reconstruct a point for it to be valid. Use lower values '
'if your images have less overlap. Lower values result in denser point clouds '
'but with more noise. '
'Default: %(default)s'))
parser.add_argument('--opensfm-depthmap-method',
metavar='<string>',
action=StoreValue,
default='PATCH_MATCH',
choices=['PATCH_MATCH', 'BRUTE_FORCE', 'PATCH_MATCH_SAMPLE'],
help=('Raw depthmap computation algorithm. '
'PATCH_MATCH and PATCH_MATCH_SAMPLE are faster, but might miss some valid points. '
'BRUTE_FORCE takes longer but produces denser reconstructions. '
'Default: %(default)s'))
parser.add_argument('--opensfm-depthmap-min-patch-sd',
metavar='<positive float>',
action=StoreValue,
type=float,
default=1,
help=('When using PATCH_MATCH or PATCH_MATCH_SAMPLE, controls the standard deviation threshold to include patches. '
'Patches with lower standard deviation are ignored. '
'Default: %(default)s'))
parser.add_argument('--use-hybrid-bundle-adjustment',
action=StoreTrue,
nargs=0,
default=False,
help='Run local bundle adjustment for every image added to the reconstruction and a global '
'adjustment every 100 images. Speeds up reconstruction for very large datasets.')
parser.add_argument('--mve-confidence',
metavar='<float: 0 <= x <= 1>',
action=StoreValue,
type=float,
default=0.60,
help=('Discard points that have less than a certain confidence threshold. '
'This only affects dense reconstructions performed with MVE. '
'Higher values discard more points. '
'Default: %(default)s'))
parser.add_argument('--use-3dmesh',
action=StoreTrue,
nargs=0,
default=False,
help='Use a full 3D mesh to compute the orthophoto instead of a 2.5D mesh. This option is a bit faster and provides similar results in planar areas.')
parser.add_argument('--skip-3dmodel',
action=StoreTrue,
nargs=0,
default=False,
help='Skip generation of a full 3D model. This can save time if you only need 2D results such as orthophotos and DEMs.')
parser.add_argument('--use-opensfm-dense',
action=StoreTrue,
nargs=0,
default=False,
help='Use opensfm to compute dense point cloud alternatively')
parser.add_argument('--ignore-gsd',
action=StoreTrue,
nargs=0,
default=False,
help='Ignore Ground Sampling Distance (GSD). GSD '
'caps the maximum resolution of image outputs and '
'resizes images when necessary, resulting in faster processing and '
'lower memory usage. Since GSD is an estimate, sometimes ignoring it can result in slightly better image output quality.')
parser.add_argument('--mesh-size',
metavar='<positive integer>',
action=StoreValue,
default=200000,
type=int,
help=('The maximum vertex count of the output mesh. '
'Default: %(default)s'))
parser.add_argument('--mesh-octree-depth',
metavar='<positive integer>',
action=StoreValue,
default=10,
type=int,
help=('Oct-tree depth used in the mesh reconstruction, '
'increase to get more vertices, recommended '
'values are 8-12. Default: %(default)s'))
parser.add_argument('--mesh-samples',
metavar='<float >= 1.0>',
action=StoreValue,
default=1.0,
type=float,
help=('Number of points per octree node, recommended '
'and default value: %(default)s'))
parser.add_argument('--mesh-point-weight',
metavar='<positive float>',
action=StoreValue,
default=4,
type=float,
help=('This floating point value specifies the importance'
' that interpolation of the point samples is given in the '
'formulation of the screened Poisson equation. The results '
'of the original (unscreened) Poisson Reconstruction can '
'be obtained by setting this value to 0.'
'Default= %(default)s'))
parser.add_argument('--fast-orthophoto',
action=StoreTrue,
nargs=0,
default=False,
help='Skips dense reconstruction and 3D model generation. '
'It generates an orthophoto directly from the sparse reconstruction. '
'If you just need an orthophoto and do not need a full 3D model, turn on this option.')
parser.add_argument('--crop',
metavar='<positive float>',
action=StoreValue,
default=3,
type=float,
help=('Automatically crop image outputs by creating a smooth buffer '
'around the dataset boundaries, shrinked by N meters. '
'Use 0 to disable cropping. '
'Default: %(default)s'))
parser.add_argument('--pc-classify',
action=StoreTrue,
nargs=0,
default=False,
help='Classify the point cloud outputs using a Simple Morphological Filter. '
'You can control the behavior of this option by tweaking the --dem-* parameters. '
'Default: '
'%(default)s')
parser.add_argument('--pc-csv',
action=StoreTrue,
nargs=0,
default=False,
help='Export the georeferenced point cloud in CSV format. Default: %(default)s')
parser.add_argument('--pc-las',
action=StoreTrue,
nargs=0,
default=False,
help='Export the georeferenced point cloud in LAS format. Default: %(default)s')
parser.add_argument('--pc-ept',
action=StoreTrue,
nargs=0,
default=False,
help='Export the georeferenced point cloud in Entwine Point Tile (EPT) format. Default: %(default)s')
parser.add_argument('--pc-filter',
metavar='<positive float>',
action=StoreValue,
type=float,
default=2.5,
help='Filters the point cloud by removing points that deviate more than N standard deviations from the local mean. Set to 0 to disable filtering.'
'\nDefault: '
'%(default)s')
parser.add_argument('--pc-sample',
metavar='<positive float>',
action=StoreValue,
type=float,
default=0,
help='Filters the point cloud by keeping only a single point around a radius N (in meters). This can be useful to limit the output resolution of the point cloud. Set to 0 to disable sampling.'
'\nDefault: '
'%(default)s')
parser.add_argument('--smrf-scalar',
metavar='<positive float>',
action=StoreValue,
type=float,
default=1.25,
help='Simple Morphological Filter elevation scalar parameter. '
'\nDefault: '
'%(default)s')
parser.add_argument('--smrf-slope',
metavar='<positive float>',
action=StoreValue,
type=float,
default=0.15,
help='Simple Morphological Filter slope parameter (rise over run). '
'\nDefault: '
'%(default)s')
parser.add_argument('--smrf-threshold',
metavar='<positive float>',
action=StoreValue,
type=float,
default=0.5,
help='Simple Morphological Filter elevation threshold parameter (meters). '
'\nDefault: '
'%(default)s')
parser.add_argument('--smrf-window',
metavar='<positive float>',
action=StoreValue,
type=float,
default=18.0,
help='Simple Morphological Filter window radius parameter (meters). '
'\nDefault: '
'%(default)s')
parser.add_argument('--texturing-data-term',
metavar='<string>',
action=StoreValue,
default='gmi',
choices=['gmi', 'area'],
help=('Data term: [area, gmi]. Default: '
'%(default)s'))
parser.add_argument('--texturing-nadir-weight',
metavar='<integer: 0 <= x <= 32>',
action=StoreValue,
default=16,
type=int,
help=('Affects orthophotos only. '
'Higher values result in sharper corners, but can affect color distribution and blurriness. '
'Use lower values for planar areas and higher values for urban areas. '
'The default value works well for most scenarios. Default: '
'%(default)s'))
parser.add_argument('--texturing-outlier-removal-type',
metavar='<string>',
action=StoreValue,
default='gauss_clamping',
choices=['none', 'gauss_clamping', 'gauss_damping'],
help=('Type of photometric outlier removal method: '
'[none, gauss_damping, gauss_clamping]. Default: '
'%(default)s'))
parser.add_argument('--texturing-skip-visibility-test',
action=StoreTrue,
nargs=0,
default=False,
help=('Skip geometric visibility test. Default: '
' %(default)s'))
parser.add_argument('--texturing-skip-global-seam-leveling',
action=StoreTrue,
nargs=0,
default=False,
help=('Skip global seam leveling. Useful for IR data.'
'Default: %(default)s'))
parser.add_argument('--texturing-skip-local-seam-leveling',
action=StoreTrue,
nargs=0,
default=False,
help='Skip local seam blending. Default: %(default)s')
parser.add_argument('--texturing-skip-hole-filling',
action=StoreTrue,
nargs=0,
default=False,
help=('Skip filling of holes in the mesh. Default: '
' %(default)s'))
parser.add_argument('--texturing-keep-unseen-faces',
action=StoreTrue,
nargs=0,
default=False,
help=('Keep faces in the mesh that are not seen in any camera. '
'Default: %(default)s'))
parser.add_argument('--texturing-tone-mapping',
metavar='<string>',
action=StoreValue,
choices=['none', 'gamma'],
default='none',
help='Turn on gamma tone mapping or none for no tone '
'mapping. Choices are \'gamma\' or \'none\'. '
'Default: %(default)s ')
parser.add_argument('--gcp',
metavar='<path string>',
action=StoreValue,
default=None,
help=('Path to the file containing the ground control '
'points used for georeferencing. Default: '
'%(default)s. The file needs to '
'use the following format: \n'
'EPSG:<code> or <+proj definition>\n'
'geo_x geo_y geo_z im_x im_y image_name [gcp_name] [extra1] [extra2]'))
parser.add_argument('--geo',
metavar='<path string>',
action=StoreValue,
default=None,
help=('Path to the image geolocation file containing the camera center coordinates used for georeferencing. '
'Note that omega/phi/kappa are currently not supported (you can set them to 0). '
'Default: '
'%(default)s. The file needs to '
'use the following format: \n'
'EPSG:<code> or <+proj definition>\n'
'image_name geo_x geo_y geo_z [omega (degrees)] [phi (degrees)] [kappa (degrees)] [horz accuracy (meters)] [vert accuracy (meters)]'
''))
parser.add_argument('--use-exif',
action=StoreTrue,
nargs=0,
default=False,
help=('Use this tag if you have a gcp_list.txt but '
'want to use the exif geotags instead'))
parser.add_argument('--dtm',
action=StoreTrue,
nargs=0,
default=False,
help='Use this tag to build a DTM (Digital Terrain Model, ground only) using a simple '
'morphological filter. Check the --dem* and --smrf* parameters for finer tuning.')
parser.add_argument('--dsm',
action=StoreTrue,
nargs=0,
default=False,
help='Use this tag to build a DSM (Digital Surface Model, ground + objects) using a progressive '
'morphological filter. Check the --dem* parameters for finer tuning.')
parser.add_argument('--dem-gapfill-steps',
metavar='<positive integer>',
action=StoreValue,
default=3,
type=int,
help='Number of steps used to fill areas with gaps. Set to 0 to disable gap filling. '
'Starting with a radius equal to the output resolution, N different DEMs are generated with '
'progressively bigger radius using the inverse distance weighted (IDW) algorithm '
'and merged together. Remaining gaps are then merged using nearest neighbor interpolation. '
'\nDefault=%(default)s')
parser.add_argument('--dem-resolution',
metavar='<float>',
action=StoreValue,
type=float,
default=5,
help='DSM/DTM resolution in cm / pixel. Note that this value is capped by a ground sampling distance (GSD) estimate. To remove the cap, check --ignore-gsd also.'
'\nDefault: %(default)s')
parser.add_argument('--dem-decimation',
metavar='<positive integer>',
action=StoreValue,
default=1,
type=int,
help='Decimate the points before generating the DEM. 1 is no decimation (full quality). '
'100 decimates ~99%% of the points. Useful for speeding up '
'generation.\nDefault=%(default)s')
parser.add_argument('--dem-euclidean-map',
action=StoreTrue,
nargs=0,
default=False,
help='Computes an euclidean raster map for each DEM. '
'The map reports the distance from each cell to the nearest '
'NODATA value (before any hole filling takes place). '
'This can be useful to isolate the areas that have been filled. '
'Default: '
'%(default)s')
parser.add_argument('--orthophoto-resolution',
metavar='<float > 0.0>',
action=StoreValue,
default=5,
type=float,
help=('Orthophoto resolution in cm / pixel. Note that this value is capped by a ground sampling distance (GSD) estimate. To remove the cap, check --ignore-gsd also.\n'
'Default: %(default)s'))
parser.add_argument('--orthophoto-no-tiled',
action=StoreTrue,
nargs=0,
default=False,
help='Set this parameter if you want a stripped geoTIFF.\n'
'Default: %(default)s')
parser.add_argument('--orthophoto-png',
action=StoreTrue,
nargs=0,
default=False,
help='Set this parameter if you want to generate a PNG rendering of the orthophoto.\n'
'Default: %(default)s')
parser.add_argument('--orthophoto-compression',
metavar='<string>',
action=StoreValue,
type=str,
choices=['JPEG', 'LZW', 'PACKBITS', 'DEFLATE', 'LZMA', 'NONE'],
default='DEFLATE',
help='Set the compression to use for orthophotos. Options: %(choices)s.\nDefault: %(default)s')
parser.add_argument('--orthophoto-cutline',
action=StoreTrue,
nargs=0,
default=False,
help='Generates a polygon around the cropping area '
'that cuts the orthophoto around the edges of features. This polygon '
'can be useful for stitching seamless mosaics with multiple overlapping orthophotos. '
'Default: '
'%(default)s')
parser.add_argument('--build-overviews',
action=StoreTrue,
nargs=0,
default=False,
help='Build orthophoto overviews using gdaladdo.')
parser.add_argument('--verbose', '-v',
action=StoreTrue,
nargs=0,
default=False,
help='Print additional messages to the console\n'
'Default: %(default)s')
parser.add_argument('--time',
action=StoreTrue,
nargs=0,
default=False,
help='Generates a benchmark file with runtime info\n'
'Default: %(default)s')
parser.add_argument('--debug',
action=StoreTrue,
nargs=0,
default=False,
help='Print debug messages\n'
'Default: %(default)s')
parser.add_argument('--version',
action='version',
version='ODM {0}'.format(__version__),
help='Displays version number and exits. ')
parser.add_argument('--split',
type=int,
action=StoreValue,
default=999999,
metavar='<positive integer>',
help='Average number of images per submodel. When '
'splitting a large dataset into smaller '
'submodels, images are grouped into clusters. '
'This value regulates the number of images that '
'each cluster should have on average.')
parser.add_argument('--split-overlap',
type=float,
action=StoreValue,
metavar='<positive integer>',
default=150,
help='Radius of the overlap between submodels. '
'After grouping images into clusters, images '
'that are closer than this radius to a cluster '
'are added to the cluster. This is done to ensure '
'that neighboring submodels overlap.')
parser.add_argument('--split-multitracks',
action=StoreTrue,
nargs=0,
default=False,
help='Split multi-track reconstructions.')
parser.add_argument('--sm-cluster',
metavar='<string>',
action=StoreValue,
type=url_string,
default=None,
help='URL to a ClusterODM instance '
'for distributing a split-merge workflow on '
'multiple nodes in parallel. '
'Default: %(default)s')
parser.add_argument('--merge',
metavar='<string>',
action=StoreValue,
default='all',
choices=['all', 'pointcloud', 'orthophoto', 'dem'],
help=('Choose what to merge in the merge step in a split dataset. '
'By default all available outputs are merged. '
'Options: %(choices)s. Default: '
'%(default)s'))
parser.add_argument('--force-gps',
action=StoreTrue,
nargs=0,
default=False,
help=('Use images\' GPS exif data for reconstruction, even if there are GCPs present.'
'This flag is useful if you have high precision GPS measurements. '
'If there are no GCPs, this flag does nothing. Default: %(default)s'))
parser.add_argument('--gps-accuracy',
type=float,
action=StoreValue,
metavar='<positive float>',
default=15,
help='Set a value in meters for the GPS Dilution of Precision (DOP) '
'information for all images. If your images are tagged '
'with high precision GPS information (RTK), this value will be automatically '
'set accordingly. You can use this option to manually set it in case the reconstruction '
'fails. Lowering this option can sometimes help control bowling-effects over large areas. Default: %(default)s')
parser.add_argument('--optimize-disk-space',
action=StoreTrue,
nargs=0,
default=False,
help=('Delete heavy intermediate files to optimize disk space usage. This '
'affects the ability to restart the pipeline from an intermediate stage, '
'but allows datasets to be processed on machines that don\'t have sufficient '
'disk space available. Default: %(default)s'))
parser.add_argument('--pc-rectify',
action=StoreTrue,
nargs=0,
default=False,
help=('Perform ground rectification on the point cloud. This means that wrongly classified ground '
'points will be re-classified and gaps will be filled. Useful for generating DTMs. '
'Default: %(default)s'))
args = parser.parse_args(argv)
# check that the project path setting has been set properly
if not args.project_path:
log.ODM_ERROR('You need to set the project path in the '
'settings.yaml file before you can run ODM, '
'or use `--project-path <path>`. Run `python3 '
'run.py --help` for more information. ')
sys.exit(1)
if args.fast_orthophoto:
log.ODM_INFO('Fast orthophoto is turned on, automatically setting --skip-3dmodel')
args.skip_3dmodel = True
if args.pc_rectify and not args.pc_classify:
log.ODM_INFO("Ground rectify is turned on, automatically turning on point cloud classification")
args.pc_classify = True
if args.dtm and not args.pc_classify:
log.ODM_INFO("DTM is turned on, automatically turning on point cloud classification")
args.pc_classify = True
if args.skip_3dmodel and args.use_3dmesh:
log.ODM_WARNING('--skip-3dmodel is set, but so is --use-3dmesh. --skip-3dmodel will be ignored.')
args.skip_3dmodel = False
if args.orthophoto_cutline and not args.crop:
log.ODM_WARNING("--orthophoto-cutline is set, but --crop is not. --crop will be set to 0.01")
args.crop = 0.01
if args.sm_cluster:
try:
Node.from_url(args.sm_cluster).info()
except exceptions.NodeConnectionError as e:
log.ODM_ERROR("Cluster node seems to be offline: %s" % str(e))
sys.exit(1)
# if args.radiometric_calibration != "none" and not args.texturing_skip_global_seam_leveling:
# log.ODM_WARNING("radiometric-calibration is turned on, automatically setting --texturing-skip-global-seam-leveling")
# args.texturing_skip_global_seam_leveling = True
return args