kopia lustrzana https://github.com/OpenDroneMap/ODM
Piero Toffanin
GitHub
commit
c1cd2456b1
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@ -209,7 +209,7 @@ externalproject_add(poissonrecon
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externalproject_add(dem2mesh
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GIT_REPOSITORY https://github.com/OpenDroneMap/dem2mesh.git
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GIT_TAG master
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GIT_TAG 300
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PREFIX ${SB_BINARY_DIR}/dem2mesh
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SOURCE_DIR ${SB_SOURCE_DIR}/dem2mesh
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CMAKE_ARGS -DCMAKE_INSTALL_PREFIX:PATH=${SB_INSTALL_DIR}
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@ -53,7 +53,7 @@ ExternalProject_Add(${_proj_name}
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#--Download step--------------
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DOWNLOAD_DIR ${SB_DOWNLOAD_DIR}
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GIT_REPOSITORY https://github.com/OpenDroneMap/openMVS
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GIT_TAG 291
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GIT_TAG 300
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#--Update/Patch step----------
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UPDATE_COMMAND ""
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#--Configure step-------------
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2
VERSION
2
VERSION
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@ -1 +1 @@
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2.9.2
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3.0.0
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@ -51,7 +51,6 @@ commands.create_dem(args.point_cloud,
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outdir=outdir,
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resolution=args.resolution,
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decimation=1,
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verbose=True,
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max_workers=multiprocessing.cpu_count(),
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keep_unfilled_copy=False
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)
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@ -83,15 +83,6 @@ def config(argv=None, parser=None):
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nargs='?',
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help='Name of dataset (i.e subfolder name within project folder). Default: %(default)s')
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parser.add_argument('--resize-to',
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metavar='<integer>',
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action=StoreValue,
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default=2048,
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type=int,
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help='Legacy option (use --feature-quality instead). Resizes images by the largest side for feature extraction purposes only. '
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'Set to -1 to disable. This does not affect the final orthophoto '
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'resolution quality and will not resize the original images. Default: %(default)s')
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parser.add_argument('--end-with', '-e',
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metavar='<string>',
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action=StoreValue,
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@ -212,15 +203,6 @@ def config(argv=None, parser=None):
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'processes. Peak memory requirement is ~1GB per '
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'thread and 2 megapixel image resolution. Default: %(default)s'))
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parser.add_argument('--depthmap-resolution',
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metavar='<positive float>',
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action=StoreValue,
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type=float,
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default=640,
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help=('Controls the density of the point cloud by setting the resolution of the depthmap images. Higher values take longer to compute '
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'but produce denser point clouds. Overrides the value calculated by --pc-quality.'
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'Default: %(default)s'))
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parser.add_argument('--use-hybrid-bundle-adjustment',
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action=StoreTrue,
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nargs=0,
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@ -414,13 +396,6 @@ def config(argv=None, parser=None):
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help='Reduce the memory usage needed for depthmap fusion by splitting large scenes into tiles. Turn this on if your machine doesn\'t have much RAM and/or you\'ve set --pc-quality to high or ultra. Experimental. '
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'Default: %(default)s')
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parser.add_argument('--pc-geometric',
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action=StoreTrue,
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nargs=0,
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default=False,
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help='Improve the accuracy of the point cloud by computing geometrically consistent depthmaps. This increases processing time, but can improve results in urban scenes. '
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'Default: %(default)s')
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parser.add_argument('--smrf-scalar',
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metavar='<positive float>',
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action=StoreValue,
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@ -453,20 +428,6 @@ def config(argv=None, parser=None):
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help='Simple Morphological Filter window radius parameter (meters). '
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'Default: %(default)s')
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parser.add_argument('--texturing-data-term',
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metavar='<string>',
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action=StoreValue,
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default='gmi',
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choices=['gmi', 'area'],
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help=('When texturing the 3D mesh, for each triangle, choose to prioritize images with sharp features (gmi) or those that cover the largest area (area). Default: %(default)s'))
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parser.add_argument('--texturing-outlier-removal-type',
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metavar='<string>',
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action=StoreValue,
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default='gauss_clamping',
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choices=['none', 'gauss_clamping', 'gauss_damping'],
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help=('Type of photometric outlier removal method. Can be one of: %(choices)s. Default: %(default)s'))
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parser.add_argument('--texturing-skip-global-seam-leveling',
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action=StoreTrue,
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nargs=0,
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@ -486,15 +447,6 @@ def config(argv=None, parser=None):
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help=('Keep faces in the mesh that are not seen in any camera. '
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'Default: %(default)s'))
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parser.add_argument('--texturing-tone-mapping',
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metavar='<string>',
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action=StoreValue,
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choices=['none', 'gamma'],
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default='none',
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help='Turn on gamma tone mapping or none for no tone '
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'mapping. Can be one of %(choices)s. '
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'Default: %(default)s ')
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parser.add_argument('--gcp',
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metavar='<path string>',
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action=StoreValue,
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@ -512,7 +464,7 @@ def config(argv=None, parser=None):
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action=StoreValue,
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default=None,
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help=('Path to the image geolocation file containing the camera center coordinates used for georeferencing. '
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'Note that omega/phi/kappa are currently not supported (you can set them to 0). '
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'If you don''t have values for omega/phi/kappa you can set them to 0. '
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'The file needs to '
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'use the following format: \n'
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'EPSG:<code> or <+proj definition>\n'
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@ -592,7 +544,7 @@ def config(argv=None, parser=None):
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default=False,
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help='Set this parameter if you want a striped GeoTIFF. '
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'Default: %(default)s')
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parser.add_argument('--orthophoto-png',
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action=StoreTrue,
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nargs=0,
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@ -606,7 +558,6 @@ def config(argv=None, parser=None):
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default=False,
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help='Set this parameter if you want to generate a Google Earth (KMZ) rendering of the orthophoto. '
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'Default: %(default)s')
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parser.add_argument('--orthophoto-compression',
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metavar='<string>',
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@ -670,32 +621,11 @@ def config(argv=None, parser=None):
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default=False,
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help='Create Cloud-Optimized GeoTIFFs instead of normal GeoTIFFs. Default: %(default)s')
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parser.add_argument('--verbose', '-v',
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action=StoreTrue,
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nargs=0,
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default=False,
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help='Print additional messages to the console. '
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'Default: %(default)s')
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parser.add_argument('--copy-to',
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metavar='<path>',
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action=StoreValue,
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help='Copy output results to this folder after processing.')
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parser.add_argument('--time',
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action=StoreTrue,
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nargs=0,
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default=False,
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help='Generates a benchmark file with runtime info. '
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'Default: %(default)s')
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parser.add_argument('--debug',
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action=StoreTrue,
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nargs=0,
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default=False,
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help='Print debug messages. Default: %(default)s')
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parser.add_argument('--version',
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action='version',
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version='ODM {0}'.format(__version__),
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@ -811,7 +741,15 @@ def config(argv=None, parser=None):
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'If the images have been postprocessed and are already aligned, use this option. '
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'Default: %(default)s'))
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args = parser.parse_args(argv)
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args, unknown = parser.parse_known_args(argv)
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DEPRECATED = ["--verbose", "--debug", "--time", "--resize-to", "--depthmap-resolution", "--pc-geometric", "--texturing-data-term", "--texturing-outlier-removal-type", "--texturing-tone-mapping"]
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unknown_e = [p for p in unknown if p not in DEPRECATED]
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if len(unknown_e) > 0:
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raise parser.error("unrecognized arguments: %s" % " ".join(unknown_e))
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for p in unknown:
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if p in DEPRECATED:
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log.ODM_WARNING("%s is no longer a valid argument and will be ignored!" % p)
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# check that the project path setting has been set properly
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if not args.project_path:
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@ -35,11 +35,11 @@ except ModuleNotFoundError:
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except:
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pass
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def classify(lasFile, scalar, slope, threshold, window, verbose=False):
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def classify(lasFile, scalar, slope, threshold, window):
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start = datetime.now()
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try:
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pdal.run_pdaltranslate_smrf(lasFile, lasFile, scalar, slope, threshold, window, verbose)
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pdal.run_pdaltranslate_smrf(lasFile, lasFile, scalar, slope, threshold, window)
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except:
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log.ODM_WARNING("Error creating classified file %s" % lasFile)
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@ -90,7 +90,7 @@ error = None
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def create_dem(input_point_cloud, dem_type, output_type='max', radiuses=['0.56'], gapfill=True,
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outdir='', resolution=0.1, max_workers=1, max_tile_size=4096,
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verbose=False, decimation=None, keep_unfilled_copy=False,
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decimation=None, keep_unfilled_copy=False,
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apply_smoothing=True):
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""" Create DEM from multiple radii, and optionally gapfill """
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@ -187,7 +187,7 @@ def create_dem(input_point_cloud, dem_type, output_type='max', radiuses=['0.56']
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d = pdal.json_add_decimation_filter(d, decimation)
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pdal.json_add_readers(d, [input_point_cloud])
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pdal.run_pipeline(d, verbose=verbose)
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pdal.run_pipeline(d)
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parallel_map(process_tile, tiles, max_workers)
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@ -380,5 +380,4 @@ def window_filter_2d(arr, nodata, window, kernel_size, filter):
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win_arr = filter(win_arr)
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win_arr[nodata_locs] = nodata
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win_arr = win_arr[window[0] - expanded_window[0] : window[2] - expanded_window[0], window[1] - expanded_window[1] : window[3] - expanded_window[1]]
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log.ODM_DEBUG("Filtered window: %s" % str(window))
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return win_arr
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@ -133,22 +133,13 @@ def json_add_readers(json, filenames):
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return json
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def json_print(json):
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""" Pretty print JSON """
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log.ODM_DEBUG(jsonlib.dumps(json, indent=4, separators=(',', ': ')))
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""" Run PDAL commands """
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def run_pipeline(json, verbose=False):
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def run_pipeline(json):
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""" Run PDAL Pipeline with provided JSON """
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if verbose:
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json_print(json)
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# write to temp file
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f, jsonfile = tempfile.mkstemp(suffix='.json')
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if verbose:
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log.ODM_INFO('Pipeline file: %s' % jsonfile)
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os.write(f, jsonlib.dumps(json).encode('utf8'))
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os.close(f)
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@ -157,14 +148,11 @@ def run_pipeline(json, verbose=False):
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'pipeline',
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'-i %s' % double_quote(jsonfile)
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]
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if verbose or sys.platform == 'win32':
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system.run(' '.join(cmd))
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else:
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system.run(' '.join(cmd) + ' > /dev/null 2>&1')
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system.run(' '.join(cmd))
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os.remove(jsonfile)
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def run_pdaltranslate_smrf(fin, fout, scalar, slope, threshold, window, verbose=False):
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def run_pdaltranslate_smrf(fin, fout, scalar, slope, threshold, window):
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""" Run PDAL translate """
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cmd = [
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'pdal',
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@ -178,12 +166,9 @@ def run_pdaltranslate_smrf(fin, fout, scalar, slope, threshold, window, verbose=
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'--filters.smrf.window=%s' % window,
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]
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if verbose:
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log.ODM_INFO(' '.join(cmd))
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system.run(' '.join(cmd))
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def merge_point_clouds(input_files, output_file, verbose=False):
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def merge_point_clouds(input_files, output_file):
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if len(input_files) == 0:
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log.ODM_WARNING("Cannot merge point clouds, no point clouds to merge.")
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return
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@ -194,8 +179,5 @@ def merge_point_clouds(input_files, output_file, verbose=False):
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' '.join(map(double_quote, input_files + [output_file])),
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]
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if verbose:
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log.ODM_INFO(' '.join(cmd))
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system.run(' '.join(cmd))
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@ -43,7 +43,6 @@ def memory():
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class ODMLogger:
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def __init__(self):
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self.show_debug = False
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self.json = None
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self.json_output_file = None
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self.start_time = datetime.datetime.now()
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@ -134,10 +133,6 @@ class ODMLogger:
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def exception(self, msg):
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self.log(FAIL, msg, "EXCEPTION")
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def debug(self, msg):
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if self.show_debug:
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self.log(OKGREEN, msg, "DEBUG")
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def close(self):
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if self.json is not None and self.json_output_file is not None:
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try:
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@ -154,4 +149,3 @@ ODM_INFO = logger.info
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ODM_WARNING = logger.warning
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ODM_ERROR = logger.error
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ODM_EXCEPTION = logger.exception
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ODM_DEBUG = logger.debug
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@ -8,7 +8,7 @@ from opendm import concurrency
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from scipy import signal
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import numpy as np
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def create_25dmesh(inPointCloud, outMesh, dsm_radius=0.07, dsm_resolution=0.05, depth=8, samples=1, maxVertexCount=100000, verbose=False, available_cores=None, method='gridded', smooth_dsm=True):
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def create_25dmesh(inPointCloud, outMesh, dsm_radius=0.07, dsm_resolution=0.05, depth=8, samples=1, maxVertexCount=100000, available_cores=None, method='gridded', smooth_dsm=True):
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# Create DSM from point cloud
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# Create temporary directory
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@ -21,7 +21,7 @@ def create_25dmesh(inPointCloud, outMesh, dsm_radius=0.07, dsm_resolution=0.05,
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radius_steps = [dsm_radius]
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for _ in range(2):
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radius_steps.append(radius_steps[-1] * 2) # 2 is arbitrary
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radius_steps.append(radius_steps[-1] * math.sqrt(2)) # sqrt(2) is arbitrary
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log.ODM_INFO('Creating DSM for 2.5D mesh')
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@ -33,20 +33,18 @@ def create_25dmesh(inPointCloud, outMesh, dsm_radius=0.07, dsm_resolution=0.05,
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gapfill=True,
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outdir=tmp_directory,
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resolution=dsm_resolution,
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verbose=verbose,
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max_workers=available_cores,
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apply_smoothing=smooth_dsm
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)
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if method == 'gridded':
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mesh = dem_to_mesh_gridded(os.path.join(tmp_directory, 'mesh_dsm.tif'), outMesh, maxVertexCount, verbose, maxConcurrency=max(1, available_cores))
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mesh = dem_to_mesh_gridded(os.path.join(tmp_directory, 'mesh_dsm.tif'), outMesh, maxVertexCount, maxConcurrency=max(1, available_cores))
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elif method == 'poisson':
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dsm_points = dem_to_points(os.path.join(tmp_directory, 'mesh_dsm.tif'), os.path.join(tmp_directory, 'dsm_points.ply'), verbose)
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dsm_points = dem_to_points(os.path.join(tmp_directory, 'mesh_dsm.tif'), os.path.join(tmp_directory, 'dsm_points.ply'))
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mesh = screened_poisson_reconstruction(dsm_points, outMesh, depth=depth,
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samples=samples,
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maxVertexCount=maxVertexCount,
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threads=max(1, available_cores - 1), # poissonrecon can get stuck on some machines if --threads == all cores
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verbose=verbose)
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threads=max(1, available_cores - 1)), # poissonrecon can get stuck on some machines if --threads == all cores
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else:
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raise 'Not a valid method: ' + method
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@ -57,14 +55,13 @@ def create_25dmesh(inPointCloud, outMesh, dsm_radius=0.07, dsm_resolution=0.05,
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return mesh
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def dem_to_points(inGeotiff, outPointCloud, verbose=False):
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def dem_to_points(inGeotiff, outPointCloud):
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log.ODM_INFO('Sampling points from DSM: %s' % inGeotiff)
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kwargs = {
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'bin': context.dem2points_path,
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'outfile': outPointCloud,
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'infile': inGeotiff,
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'verbose': '-verbose' if verbose else ''
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'infile': inGeotiff
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}
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system.run('"{bin}" -inputFile "{infile}" '
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@ -72,12 +69,12 @@ def dem_to_points(inGeotiff, outPointCloud, verbose=False):
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'-skirtHeightThreshold 1.5 '
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'-skirtIncrements 0.2 '
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'-skirtHeightCap 100 '
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' {verbose} '.format(**kwargs))
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'-verbose '.format(**kwargs))
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return outPointCloud
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def dem_to_mesh_gridded(inGeotiff, outMesh, maxVertexCount, verbose=False, maxConcurrency=1):
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def dem_to_mesh_gridded(inGeotiff, outMesh, maxVertexCount, maxConcurrency=1):
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log.ODM_INFO('Creating mesh from DSM: %s' % inGeotiff)
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mesh_path, mesh_filename = os.path.split(outMesh)
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@ -99,8 +96,7 @@ def dem_to_mesh_gridded(inGeotiff, outMesh, maxVertexCount, verbose=False, maxCo
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'outfile': outMeshDirty,
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'infile': inGeotiff,
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'maxVertexCount': maxVertexCount,
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'maxConcurrency': maxConcurrency,
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'verbose': '-verbose' if verbose else ''
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'maxConcurrency': maxConcurrency
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}
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system.run('"{bin}" -inputFile "{infile}" '
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'-outputFile "{outfile}" '
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@ -108,7 +104,7 @@ def dem_to_mesh_gridded(inGeotiff, outMesh, maxVertexCount, verbose=False, maxCo
|
|||
'-maxVertexCount {maxVertexCount} '
|
||||
'-maxConcurrency {maxConcurrency} '
|
||||
'-edgeSwapThreshold 0.15 '
|
||||
' {verbose} '.format(**kwargs))
|
||||
'-verbose '.format(**kwargs))
|
||||
break
|
||||
except Exception as e:
|
||||
maxConcurrency = math.floor(maxConcurrency / 2)
|
||||
|
|
@ -138,7 +134,7 @@ def dem_to_mesh_gridded(inGeotiff, outMesh, maxVertexCount, verbose=False, maxCo
|
|||
return outMesh
|
||||
|
||||
|
||||
def screened_poisson_reconstruction(inPointCloud, outMesh, depth = 8, samples = 1, maxVertexCount=100000, pointWeight=4, threads=context.num_cores, verbose=False):
|
||||
def screened_poisson_reconstruction(inPointCloud, outMesh, depth = 8, samples = 1, maxVertexCount=100000, pointWeight=4, threads=context.num_cores):
|
||||
|
||||
mesh_path, mesh_filename = os.path.split(outMesh)
|
||||
# mesh_path = path/to
|
||||
|
|
@ -165,8 +161,7 @@ def screened_poisson_reconstruction(inPointCloud, outMesh, depth = 8, samples =
|
|||
'depth': depth,
|
||||
'samples': samples,
|
||||
'pointWeight': pointWeight,
|
||||
'threads': int(threads),
|
||||
'verbose': '--verbose' if verbose else ''
|
||||
'threads': int(threads)
|
||||
}
|
||||
|
||||
# Run PoissonRecon
|
||||
|
|
@ -178,8 +173,7 @@ def screened_poisson_reconstruction(inPointCloud, outMesh, depth = 8, samples =
|
|||
'--samplesPerNode {samples} '
|
||||
'--threads {threads} '
|
||||
'--bType 2 '
|
||||
'--linearFit '
|
||||
'{verbose}'.format(**poissonReconArgs))
|
||||
'--linearFit '.format(**poissonReconArgs))
|
||||
except Exception as e:
|
||||
log.ODM_WARNING(str(e))
|
||||
|
||||
|
|
|
|||
|
|
@ -202,27 +202,22 @@ class OSFMContext:
|
|||
# Compute feature_process_size
|
||||
feature_process_size = 2048 # default
|
||||
|
||||
if ('resize_to_is_set' in args) and args.resize_to > 0:
|
||||
# Legacy
|
||||
log.ODM_WARNING("Legacy option --resize-to (this might be removed in a future version). Use --feature-quality instead.")
|
||||
feature_process_size = int(args.resize_to)
|
||||
feature_quality_scale = {
|
||||
'ultra': 1,
|
||||
'high': 0.5,
|
||||
'medium': 0.25,
|
||||
'low': 0.125,
|
||||
'lowest': 0.0675,
|
||||
}
|
||||
|
||||
max_dim = find_largest_photo_dim(photos)
|
||||
|
||||
if max_dim > 0:
|
||||
log.ODM_INFO("Maximum photo dimensions: %spx" % str(max_dim))
|
||||
feature_process_size = int(max_dim * feature_quality_scale[args.feature_quality])
|
||||
log.ODM_INFO("Photo dimensions for feature extraction: %ipx" % feature_process_size)
|
||||
else:
|
||||
feature_quality_scale = {
|
||||
'ultra': 1,
|
||||
'high': 0.5,
|
||||
'medium': 0.25,
|
||||
'low': 0.125,
|
||||
'lowest': 0.0675,
|
||||
}
|
||||
|
||||
max_dim = find_largest_photo_dim(photos)
|
||||
|
||||
if max_dim > 0:
|
||||
log.ODM_INFO("Maximum photo dimensions: %spx" % str(max_dim))
|
||||
feature_process_size = int(max_dim * feature_quality_scale[args.feature_quality])
|
||||
log.ODM_INFO("Photo dimensions for feature extraction: %ipx" % feature_process_size)
|
||||
else:
|
||||
log.ODM_WARNING("Cannot compute max image dimensions, going with defaults")
|
||||
log.ODM_WARNING("Cannot compute max image dimensions, going with defaults")
|
||||
|
||||
# create config file for OpenSfM
|
||||
if args.matcher_neighbors > 0:
|
||||
|
|
|
|||
|
|
@ -166,10 +166,6 @@ class ODM_Photo:
|
|||
# parse values from metadata
|
||||
self.parse_exif_values(path_file)
|
||||
|
||||
# print log message
|
||||
log.ODM_DEBUG('Loaded {}'.format(self))
|
||||
|
||||
|
||||
def __str__(self):
|
||||
return '{} | camera: {} {} | dimensions: {} x {} | lat: {} | lon: {} | alt: {} | band: {} ({})'.format(
|
||||
self.filename, self.camera_make, self.camera_model, self.width, self.height,
|
||||
|
|
|
|||
|
|
@ -71,7 +71,7 @@ def split(input_point_cloud, outdir, filename_template, capacity, dims=None):
|
|||
return [os.path.join(outdir, f) for f in os.listdir(outdir)]
|
||||
|
||||
|
||||
def filter(input_point_cloud, output_point_cloud, standard_deviation=2.5, meank=16, sample_radius=0, boundary=None, verbose=False, max_concurrency=1):
|
||||
def filter(input_point_cloud, output_point_cloud, standard_deviation=2.5, meank=16, sample_radius=0, boundary=None, max_concurrency=1):
|
||||
"""
|
||||
Filters a point cloud
|
||||
"""
|
||||
|
|
@ -82,8 +82,7 @@ def filter(input_point_cloud, output_point_cloud, standard_deviation=2.5, meank=
|
|||
args = [
|
||||
'--input "%s"' % input_point_cloud,
|
||||
'--output "%s"' % output_point_cloud,
|
||||
'--concurrency %s' % max_concurrency,
|
||||
'--verbose' if verbose else '',
|
||||
'--concurrency %s' % max_concurrency
|
||||
]
|
||||
|
||||
if sample_radius > 0:
|
||||
|
|
|
|||
|
|
@ -41,7 +41,7 @@ def extract_temperatures_dji(photo, image, dataset_tree):
|
|||
except ValueError as e:
|
||||
log.ODM_ERROR("Error during extracting temperature values for file %s : %s" % photo.filename, e)
|
||||
else:
|
||||
log.ODM_DEBUG("Only DJI M2EA currently supported, please wait for new updates")
|
||||
log.ODM_WARNING("Only DJI M2EA currently supported, please wait for new updates")
|
||||
return image
|
||||
# Extract raw sensor values from generated image into numpy array
|
||||
raw_sensor_np = np.array(img)
|
||||
|
|
|
|||
|
|
@ -364,8 +364,10 @@ class ODM_Stage:
|
|||
if outputs.get('tree') is None:
|
||||
raise Exception("Assert violation: tree variable is missing from outputs dictionary.")
|
||||
|
||||
if self.args.time:
|
||||
try:
|
||||
system.benchmark(start_time, outputs['tree'].benchmarking, self.name)
|
||||
except Exception as e:
|
||||
log.ODM_WARNING("Cannot write benchmark file: %s" % str(e))
|
||||
|
||||
log.ODM_INFO('Finished %s stage' % self.name)
|
||||
self.update_progress_end()
|
||||
|
|
|
|||
|
|
@ -5,37 +5,33 @@ from osgeo import gdal
|
|||
from opendm.loghelpers import double_quote
|
||||
|
||||
def get_depthmap_resolution(args, photos):
|
||||
if 'depthmap_resolution_is_set' in args:
|
||||
# Override pc-quality
|
||||
return int(args.depthmap_resolution)
|
||||
max_dims = find_largest_photo_dims(photos)
|
||||
min_dim = 320 # Never go lower than this
|
||||
|
||||
if max_dims is not None:
|
||||
w, h = max_dims
|
||||
max_dim = max(w, h)
|
||||
|
||||
megapixels = (w * h) / 1e6
|
||||
multiplier = 1
|
||||
|
||||
if megapixels < 6:
|
||||
multiplier = 2
|
||||
elif megapixels > 42:
|
||||
multiplier = 0.5
|
||||
|
||||
pc_quality_scale = {
|
||||
'ultra': 0.5,
|
||||
'high': 0.25,
|
||||
'medium': 0.125,
|
||||
'low': 0.0675,
|
||||
'lowest': 0.03375
|
||||
}
|
||||
|
||||
return max(min_dim, int(max_dim * pc_quality_scale[args.pc_quality] * multiplier))
|
||||
else:
|
||||
max_dims = find_largest_photo_dims(photos)
|
||||
min_dim = 320 # Never go lower than this
|
||||
|
||||
if max_dims is not None:
|
||||
w, h = max_dims
|
||||
max_dim = max(w, h)
|
||||
|
||||
megapixels = (w * h) / 1e6
|
||||
multiplier = 1
|
||||
|
||||
if megapixels < 6:
|
||||
multiplier = 2
|
||||
elif megapixels > 42:
|
||||
multiplier = 0.5
|
||||
|
||||
pc_quality_scale = {
|
||||
'ultra': 0.5,
|
||||
'high': 0.25,
|
||||
'medium': 0.125,
|
||||
'low': 0.0675,
|
||||
'lowest': 0.03375
|
||||
}
|
||||
|
||||
return max(min_dim, int(max_dim * pc_quality_scale[args.pc_quality] * multiplier))
|
||||
else:
|
||||
log.ODM_WARNING("Cannot compute max image dimensions, going with default depthmap_resolution of 640")
|
||||
return 640 # Sensible default
|
||||
log.ODM_WARNING("Cannot compute max image dimensions, going with default depthmap_resolution of 640")
|
||||
return 640 # Sensible default
|
||||
|
||||
def get_raster_stats(geotiff):
|
||||
stats = []
|
||||
|
|
|
|||
|
|
@ -49,12 +49,15 @@ class ODMLoadDatasetStage(types.ODM_Stage):
|
|||
tree = types.ODM_Tree(args.project_path, args.gcp, args.geo)
|
||||
outputs['tree'] = tree
|
||||
|
||||
if args.time and io.file_exists(tree.benchmarking):
|
||||
if io.file_exists(tree.benchmarking):
|
||||
# Delete the previously made file
|
||||
os.remove(tree.benchmarking)
|
||||
with open(tree.benchmarking, 'a') as b:
|
||||
b.write('ODM Benchmarking file created %s\nNumber of Cores: %s\n\n' % (system.now(), context.num_cores))
|
||||
|
||||
try:
|
||||
os.remove(tree.benchmarking)
|
||||
with open(tree.benchmarking, 'a') as b:
|
||||
b.write('ODM Benchmarking file created %s\nNumber of Cores: %s\n\n' % (system.now(), context.num_cores))
|
||||
except Exception as e:
|
||||
log.ODM_WARNING("Cannot write benchmark file: %s" % str(e))
|
||||
|
||||
# check if the image filename is supported
|
||||
def valid_image_filename(filename):
|
||||
(pathfn, ext) = os.path.splitext(filename)
|
||||
|
|
@ -62,7 +65,6 @@ class ODMLoadDatasetStage(types.ODM_Stage):
|
|||
|
||||
# Get supported images from dir
|
||||
def get_images(in_dir):
|
||||
log.ODM_DEBUG(in_dir)
|
||||
entries = os.listdir(in_dir)
|
||||
valid, rejects = [], []
|
||||
for f in entries:
|
||||
|
|
|
|||
|
|
@ -93,12 +93,12 @@ class ODMMvsTexStage(types.ODM_Stage):
|
|||
'bin': context.mvstex_path,
|
||||
'out_dir': os.path.join(r['out_dir'], "odm_textured_model_geo"),
|
||||
'model': r['model'],
|
||||
'dataTerm': args.texturing_data_term,
|
||||
'outlierRemovalType': args.texturing_outlier_removal_type,
|
||||
'dataTerm': 'gmi',
|
||||
'outlierRemovalType': 'gauss_clamping',
|
||||
'skipGlobalSeamLeveling': skipGlobalSeamLeveling,
|
||||
'skipLocalSeamLeveling': skipLocalSeamLeveling,
|
||||
'keepUnseenFaces': keepUnseenFaces,
|
||||
'toneMapping': args.texturing_tone_mapping,
|
||||
'toneMapping': 'none',
|
||||
'nadirMode': nadir,
|
||||
'maxTextureSize': '--max_texture_size=%s' % max_texture_size,
|
||||
'nvm_file': r['nvm_file'],
|
||||
|
|
|
|||
|
|
@ -26,17 +26,13 @@ class ODMApp:
|
|||
"""
|
||||
Initializes the application and defines the ODM application pipeline stages
|
||||
"""
|
||||
if args.debug:
|
||||
log.logger.show_debug = True
|
||||
|
||||
json_log_paths = [os.path.join(args.project_path, "log.json")]
|
||||
if args.copy_to:
|
||||
json_log_paths.append(args.copy_to)
|
||||
|
||||
log.logger.init_json_output(json_log_paths, args)
|
||||
|
||||
dataset = ODMLoadDatasetStage('dataset', args, progress=5.0,
|
||||
verbose=args.verbose)
|
||||
dataset = ODMLoadDatasetStage('dataset', args, progress=5.0)
|
||||
split = ODMSplitStage('split', args, progress=75.0)
|
||||
merge = ODMMergeStage('merge', args, progress=100.0)
|
||||
opensfm = ODMOpenSfMStage('opensfm', args, progress=25.0)
|
||||
|
|
@ -47,15 +43,12 @@ class ODMApp:
|
|||
oct_tree=max(1, min(14, args.mesh_octree_depth)),
|
||||
samples=1.0,
|
||||
point_weight=4.0,
|
||||
max_concurrency=args.max_concurrency,
|
||||
verbose=args.verbose)
|
||||
max_concurrency=args.max_concurrency)
|
||||
texturing = ODMMvsTexStage('mvs_texturing', args, progress=70.0)
|
||||
georeferencing = ODMGeoreferencingStage('odm_georeferencing', args, progress=80.0,
|
||||
gcp_file=args.gcp,
|
||||
verbose=args.verbose)
|
||||
gcp_file=args.gcp)
|
||||
dem = ODMDEMStage('odm_dem', args, progress=90.0,
|
||||
max_concurrency=args.max_concurrency,
|
||||
verbose=args.verbose)
|
||||
max_concurrency=args.max_concurrency)
|
||||
orthophoto = ODMOrthoPhotoStage('odm_orthophoto', args, progress=98.0)
|
||||
report = ODMReport('odm_report', args, progress=99.0)
|
||||
postprocess = ODMPostProcess('odm_postprocess', args, progress=100.0)
|
||||
|
|
|
|||
|
|
@ -1,4 +1,4 @@
|
|||
import os, json
|
||||
import os, json, math
|
||||
from shutil import copyfile
|
||||
|
||||
from opendm import io
|
||||
|
|
@ -58,8 +58,7 @@ class ODMDEMStage(types.ODM_Stage):
|
|||
args.smrf_scalar,
|
||||
args.smrf_slope,
|
||||
args.smrf_threshold,
|
||||
args.smrf_window,
|
||||
verbose=args.verbose
|
||||
args.smrf_window
|
||||
)
|
||||
|
||||
with open(pc_classify_marker, 'w') as f:
|
||||
|
|
@ -91,7 +90,7 @@ class ODMDEMStage(types.ODM_Stage):
|
|||
|
||||
radius_steps = [(resolution / 100.0) / 2.0]
|
||||
for _ in range(args.dem_gapfill_steps - 1):
|
||||
radius_steps.append(radius_steps[-1] * 2) # 2 is arbitrary, maybe there's a better value?
|
||||
radius_steps.append(radius_steps[-1] * math.sqrt(2)) # sqrt(2) is arbitrary, maybe there's a better value?
|
||||
|
||||
for product in products:
|
||||
commands.create_dem(
|
||||
|
|
@ -103,7 +102,6 @@ class ODMDEMStage(types.ODM_Stage):
|
|||
outdir=odm_dem_root,
|
||||
resolution=resolution / 100.0,
|
||||
decimation=args.dem_decimation,
|
||||
verbose=args.verbose,
|
||||
max_workers=args.max_concurrency,
|
||||
keep_unfilled_copy=args.dem_euclidean_map
|
||||
)
|
||||
|
|
|
|||
|
|
@ -53,7 +53,6 @@ class ODMFilterPoints(types.ODM_Stage):
|
|||
standard_deviation=args.pc_filter,
|
||||
sample_radius=args.pc_sample,
|
||||
boundary=boundary_offset(outputs.get('boundary'), reconstruction.get_proj_offset()),
|
||||
verbose=args.verbose,
|
||||
max_concurrency=args.max_concurrency)
|
||||
|
||||
# Quick check
|
||||
|
|
|
|||
|
|
@ -27,9 +27,7 @@ class ODMeshingStage(types.ODM_Stage):
|
|||
samples=self.params.get('samples'),
|
||||
maxVertexCount=self.params.get('max_vertex'),
|
||||
pointWeight=self.params.get('point_weight'),
|
||||
threads=max(1, self.params.get('max_concurrency') - 1), # poissonrecon can get stuck on some machines if --threads == all cores
|
||||
verbose=self.params.get('verbose'))
|
||||
|
||||
threads=max(1, self.params.get('max_concurrency') - 1)), # poissonrecon can get stuck on some machines if --threads == all cores
|
||||
else:
|
||||
log.ODM_WARNING('Found a valid ODM Mesh file in: %s' %
|
||||
tree.odm_mesh)
|
||||
|
|
@ -68,7 +66,6 @@ class ODMeshingStage(types.ODM_Stage):
|
|||
depth=self.params.get('oct_tree'),
|
||||
maxVertexCount=self.params.get('max_vertex'),
|
||||
samples=self.params.get('samples'),
|
||||
verbose=self.params.get('verbose'),
|
||||
available_cores=args.max_concurrency,
|
||||
method='poisson' if args.fast_orthophoto else 'gridded',
|
||||
smooth_dsm=True)
|
||||
|
|
|
|||
|
|
@ -18,7 +18,6 @@ class ODMOrthoPhotoStage(types.ODM_Stage):
|
|||
def process(self, args, outputs):
|
||||
tree = outputs['tree']
|
||||
reconstruction = outputs['reconstruction']
|
||||
verbose = '-verbose' if args.verbose else ''
|
||||
|
||||
# define paths and create working directories
|
||||
system.mkdir_p(tree.odm_orthophoto)
|
||||
|
|
@ -42,8 +41,7 @@ class ODMOrthoPhotoStage(types.ODM_Stage):
|
|||
'corners': tree.odm_orthophoto_corners,
|
||||
'res': resolution,
|
||||
'bands': '',
|
||||
'depth_idx': '',
|
||||
'verbose': verbose
|
||||
'depth_idx': ''
|
||||
}
|
||||
|
||||
models = []
|
||||
|
|
@ -85,7 +83,7 @@ class ODMOrthoPhotoStage(types.ODM_Stage):
|
|||
|
||||
# run odm_orthophoto
|
||||
system.run('"{odm_ortho_bin}" -inputFiles {models} '
|
||||
'-logFile "{log}" -outputFile "{ortho}" -resolution {res} {verbose} '
|
||||
'-logFile "{log}" -outputFile "{ortho}" -resolution {res} -verbose '
|
||||
'-outputCornerFile "{corners}" {bands} {depth_idx}'.format(**kwargs))
|
||||
|
||||
# Create georeferenced GeoTiff
|
||||
|
|
|
|||
|
|
@ -77,8 +77,8 @@ class ODMOpenMVSStage(types.ODM_Stage):
|
|||
gpu_config = []
|
||||
use_gpu = has_gpu(args)
|
||||
if use_gpu:
|
||||
# gpu_config.append("--cuda-device -3")
|
||||
gpu_config.append("--cuda-device -1")
|
||||
gpu_config.append("--cuda-device -3")
|
||||
# gpu_config.append("--cuda-device -1")
|
||||
else:
|
||||
gpu_config.append("--cuda-device -2")
|
||||
|
||||
|
|
@ -87,17 +87,13 @@ class ODMOpenMVSStage(types.ODM_Stage):
|
|||
|
||||
extra_config = []
|
||||
|
||||
if not args.pc_geometric:
|
||||
extra_config.append("--geometric-iters 0")
|
||||
|
||||
masks_dir = os.path.join(tree.opensfm, "undistorted", "masks")
|
||||
masks = os.path.exists(masks_dir) and len(os.listdir(masks_dir)) > 0
|
||||
if masks:
|
||||
extra_config.append("--ignore-mask-label 0")
|
||||
|
||||
sharp = args.pc_geometric
|
||||
with open(densify_ini_file, 'w+') as f:
|
||||
f.write("Optimize = %s\n" % (7 if sharp else 3))
|
||||
f.write("Optimize = 7\n")
|
||||
|
||||
def run_densify():
|
||||
system.run('"%s" "%s" %s' % (context.omvs_densify_path,
|
||||
|
|
@ -173,27 +169,22 @@ class ODMOpenMVSStage(types.ODM_Stage):
|
|||
|
||||
try:
|
||||
system.run('"%s" "%s" %s' % (context.omvs_densify_path, sf, ' '.join(config + gpu_config + extra_config)))
|
||||
|
||||
# Filter
|
||||
if args.pc_filter > 0:
|
||||
system.run('"%s" "%s" --filter-point-cloud -1 -v 0 %s' % (context.omvs_densify_path, scene_dense_mvs, ' '.join(gpu_config)))
|
||||
else:
|
||||
# Just rename
|
||||
log.ODM_INFO("Skipped filtering, %s --> %s" % (scene_ply_unfiltered, scene_ply))
|
||||
os.rename(scene_ply_unfiltered, scene_ply)
|
||||
except:
|
||||
log.ODM_WARNING("Sub-scene %s could not be reconstructed, skipping..." % sf)
|
||||
|
||||
if not io.file_exists(scene_ply):
|
||||
if not io.file_exists(scene_ply_unfiltered):
|
||||
scene_ply_files.pop()
|
||||
log.ODM_WARNING("Could not compute PLY for subscene %s" % sf)
|
||||
else:
|
||||
# Do not filter
|
||||
os.rename(scene_ply_unfiltered, scene_ply)
|
||||
else:
|
||||
log.ODM_WARNING("Found existing dense scene file %s" % scene_ply)
|
||||
|
||||
# Merge
|
||||
log.ODM_INFO("Merging %s scene files" % len(scene_ply_files))
|
||||
if len(scene_ply_files) == 0:
|
||||
log.ODM_ERROR("Could not compute dense point cloud (no PLY files available).")
|
||||
raise system.ExitException("Could not compute dense point cloud (no PLY files available).")
|
||||
if len(scene_ply_files) == 1:
|
||||
# Simply rename
|
||||
os.replace(scene_ply_files[0], tree.openmvs_model)
|
||||
|
|
@ -202,32 +193,12 @@ class ODMOpenMVSStage(types.ODM_Stage):
|
|||
# Merge
|
||||
fast_merge_ply(scene_ply_files, tree.openmvs_model)
|
||||
else:
|
||||
def skip_filtering():
|
||||
# Just rename
|
||||
scene_dense_ply = os.path.join(tree.openmvs, 'scene_dense.ply')
|
||||
log.ODM_INFO("Skipped filtering, %s --> %s" % (scene_dense_ply, tree.openmvs_model))
|
||||
os.rename(scene_dense_ply, tree.openmvs_model)
|
||||
|
||||
# Filter all at once
|
||||
if args.pc_filter > 0:
|
||||
if os.path.exists(scene_dense):
|
||||
config = [
|
||||
"--filter-point-cloud -1",
|
||||
'-i "%s"' % scene_dense,
|
||||
"-v 0"
|
||||
]
|
||||
try:
|
||||
system.run('"%s" %s' % (context.omvs_densify_path, ' '.join(config + gpu_config + extra_config)))
|
||||
except system.SubprocessException as e:
|
||||
if e.errorCode == 137 or e.errorCode == 3221226505:
|
||||
log.ODM_WARNING("OpenMVS filtering ran out of memory, visibility checks will be skipped.")
|
||||
skip_filtering()
|
||||
else:
|
||||
raise e
|
||||
else:
|
||||
raise system.ExitException("Cannot find scene_dense.mvs, dense reconstruction probably failed. Exiting...")
|
||||
else:
|
||||
skip_filtering()
|
||||
scene_dense_ply = os.path.join(tree.openmvs, 'scene_dense.ply')
|
||||
|
||||
if not os.path.exists(scene_dense_ply):
|
||||
raise system.ExitException("Dense reconstruction failed. This could be due to poor georeferencing or insufficient image overlap.")
|
||||
|
||||
os.rename(scene_dense_ply, tree.openmvs_model)
|
||||
|
||||
self.update_progress(95)
|
||||
|
||||
|
|
|
|||
Ładowanie…
Reference in New Issue