kopia lustrzana https://github.com/OpenDroneMap/ODM
220 wiersze
9.1 KiB
Python
220 wiersze
9.1 KiB
Python
import argparse
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# parse arguments
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processopts = ['resize', 'opensfm', 'cmvs', 'pmvs',
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'odm_meshing', 'odm_texturing', 'odm_georeferencing',
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'odm_orthophoto']
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parser = argparse.ArgumentParser(description='OpenDroneMap')
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parser.add_argument('--images-src',
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metavar='<string>',
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help='Path to the images to process')
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parser.add_argument('--resize-to', # currently doesn't support 'orig'
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metavar='<integer>',
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default=2400,
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type=int,
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help='resizes images by the largest side')
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parser.add_argument('--start-with', '-s',
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metavar='<string>',
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default='resize',
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choices=processopts,
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help=('Can be one of: ' + ' | '.join(processopts)))
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parser.add_argument('--end-with', '-e',
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metavar='<string>',
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default='odm_orthophoto',
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choices=processopts,
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help=('Can be one of:' + ' | '.join(processopts)))
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parser.add_argument('--run-only',
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metavar='<string>',
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choices=processopts,
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help=('Can be one of:' + ' | '.join(processopts)))
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parser.add_argument('--force-focal',
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metavar='<positive float>',
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type=float,
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help=('Override the focal length information for the '
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'images'))
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parser.add_argument('--force-ccd',
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metavar='<positive float>',
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type=float,
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help='Override the ccd width information for the images')
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parser.add_argument('--min-num-features',
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metavar='<integer>',
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default=4000,
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type=int,
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help=('Minimum number of features to extract per image. '
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'More features leads to better results but slower '
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'execution.'))
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parser.add_argument('--matcher-threshold',
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metavar='<percent>',
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default=2.0,
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type=float,
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help=('Ignore matched keypoints if the two images share '
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'less than <float> percent of keypoints'))
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parser.add_argument('--matcher-ratio',
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metavar='<float>',
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default=0.6,
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type=float,
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help=('Ratio of the distance to the next best matched '
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'keypoint'))
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parser.add_argument('--matcher-preselect',
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type=bool,
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metavar='',
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default=False,
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help=('use GPS exif data, if available, to match each '
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'image only with its k-nearest neighbors, or all '
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'images within a certain distance threshold'))
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parser.add_argument('--matcher-useKnn',
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type=bool,
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metavar='',
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default=True,
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help=('use GPS exif data, if available, to match each '
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'image only with its k-nearest neighbors, or all '
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'images within a certain distance threshold'))
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parser.add_argument('--matcher-kDistance',
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metavar='<integer>',
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default=20,
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type=int,
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help='')
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parser.add_argument('--matcher-k',
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metavar='<integer>',
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default=8,
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type=int,
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help='Number of k-nearest images to match '
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'when using OpenSfM')
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parser.add_argument('--cmvs-maxImages',
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metavar='<integer>',
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default=500,
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type=int,
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help='The maximum number of images per cluster')
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parser.add_argument('--pmvs-level',
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metavar='<positive integer>',
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default=1,
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type=int,
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help=('The level in the image pyramid that is used '
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'for the computation. see '
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'http://www.di.ens.fr/pmvs/documentation.html for '
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'more pmvs documentation'))
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parser.add_argument('--pmvs-csize',
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metavar='< positive integer>',
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default=2,
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type=int,
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help='Cell size controls the density of reconstructions')
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parser.add_argument('--pmvs-threshold',
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metavar='<float: -1.0 <= x <= 1.0>',
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default=0.7,
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type=float,
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help=('A patch reconstruction is accepted as a success '
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'and kept, if its associcated photometric consistency '
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'measure is above this threshold.'))
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parser.add_argument('--pmvs-wsize',
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metavar='<positive integer>',
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default=7,
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type=int,
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help=('pmvs samples wsize x wsize pixel colors from '
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'each image to compute photometric consistency '
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'score. For example, when wsize=7, 7x7=49 pixel '
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'colors are sampled in each image. Increasing the '
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'value leads to more stable reconstructions, but '
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'the program becomes slower.'))
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parser.add_argument('--pmvs-minImageNum',
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metavar='<positive integer>',
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default=3,
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type=int,
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help=('Each 3D point must be visible in at least '
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'minImageNum images for being reconstructed. 3 is '
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'suggested in general.'))
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parser.add_argument('--odm_meshing-maxVertexCount',
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metavar='<positive integer>',
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default=100000,
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type=int,
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help='The maximum vertex count of the output mesh')
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parser.add_argument('--odm_meshing-octreeDepth',
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metavar='<positive integer>',
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default=9,
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type=int,
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help=('Oct-tree depth used in the mesh reconstruction, '
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'increase to get more vertices, recommended '
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'values are 8-12'))
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parser.add_argument('--odm_meshing-samplesPerNode',
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metavar='<float >= 1.0>',
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default=1,
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type=float,
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help=('Number of points per octree node, recommended '
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'value: 1.0'))
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parser.add_argument('--odm_meshing-solverDivide',
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metavar='<positive integer>',
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default=9,
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type=int,
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help=('Oct-tree depth at which the Laplacian equation '
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'is solved in the surface reconstruction step. '
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'Increasing this value increases computation '
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'times slightly but helps reduce memory usage.'))
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parser.add_argument('--odm_texturing-textureResolution',
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metavar='<positive integer>',
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default=4096,
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type=int,
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help=('The resolution of the output textures. Must be '
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'greater than textureWithSize.'))
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parser.add_argument('--odm_texturing-textureWithSize',
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metavar='<positive integer>',
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default=3600,
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type=int,
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help=('The resolution to rescale the images performing '
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'the texturing.'))
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parser.add_argument('--odm_georeferencing-gcpFile',
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metavar='<path string>',
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default='gcp_list.txt',
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help=('path to the file containing the ground control '
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'points used for georeferencing.The file needs to '
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'be on the following line format: \neasting '
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'northing height pixelrow pixelcol imagename'))
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parser.add_argument('--odm_georeferencing-useGcp',
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type = bool,
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default = False,
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help = 'set to true for enabling GCPs from the file above')
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parser.add_argument('--odm_orthophoto-resolution',
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metavar='<float > 0.0>',
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default=20.0,
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type=float,
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help=('Orthophoto ground resolution in pixels/meter'))
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parser.add_argument('--zip-results',
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action='store_true',
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default=False,
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help='compress the results using gunzip')
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parser.add_argument('--use-opensfm',
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type=bool,
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default=True,
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help='use OpenSfM instead of Bundler to find the camera positions '
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'(replaces getKeypoints, match and bundler steps)')
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args = vars(parser.parse_args()) |