kopia lustrzana https://github.com/OpenDroneMap/ODM
Started adding odm_dem module
Piero Toffanin
rodzic
fed4cb95dc
commit
af0c2c986f
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@ -14,7 +14,7 @@ RUN apt-get install --no-install-recommends -y git cmake python-pip build-essent
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libgtk2.0-dev libavcodec-dev libavformat-dev libswscale-dev python-dev python-numpy libtbb2 libtbb-dev libjpeg-dev libpng-dev libtiff-dev libjasper-dev libflann-dev \
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libproj-dev libxext-dev liblapack-dev libeigen3-dev libvtk5-dev python-networkx libgoogle-glog-dev libsuitesparse-dev libboost-filesystem-dev libboost-iostreams-dev \
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libboost-regex-dev libboost-python-dev libboost-date-time-dev libboost-thread-dev python-pyproj python-empy python-nose python-pyside python-pyexiv2 python-scipy \
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jhead liblas-bin python-matplotlib libatlas-base-dev libgmp-dev libmpfr-dev swig2.0 python-wheel libboost-log-dev libxslt-dev
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jhead liblas-bin python-matplotlib libatlas-base-dev libgmp-dev libmpfr-dev swig2.0 python-wheel libboost-log-dev
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RUN apt-get remove libdc1394-22-dev
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RUN pip install --upgrade pip
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@ -89,8 +89,7 @@ install() {
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echo "Installing lidar2dems Dependencies"
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sudo apt-get install -y -qq swig2.0 \
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python-wheel \
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libboost-log-dev \
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libxslt-dev
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libboost-log-dev
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sudo pip install -U https://github.com/pierotofy/gippy/archive/v0.3.9.tar.gz
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@ -10,7 +10,7 @@ import sys
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# parse arguments
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processopts = ['resize', 'opensfm', 'slam', 'cmvs', 'pmvs',
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'odm_meshing', 'odm_25dmeshing', 'mvs_texturing', 'odm_georeferencing',
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'odm_orthophoto']
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'odm_dem', 'odm_orthophoto']
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with open(io.join_paths(context.root_path, 'VERSION')) as version_file:
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__version__ = version_file.read().strip()
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@ -341,34 +341,77 @@ def config():
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help=('Use this tag if you have a gcp_list.txt but '
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'want to use the exif geotags instead'))
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parser.add_argument('--dem',
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parser.add_argument('--dtm',
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action='store_true',
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default=False,
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help='Use this tag to build a DEM using a progressive '
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'morphological filter in PDAL.')
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help='Use this tag to build a DTM (Digital Terrain Model, ground only) using a progressive '
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'morphological filter in PDAL. Check the --dem* parameters for fine tuning.')
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parser.add_argument('--dsm',
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action='store_true',
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default=False,
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help='Use this tag to build a DSM (Digital Surface Model, ground + objects) using a progressive '
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'morphological filter in PDAL. Check the --dem* parameters for fine tuning.')
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parser.add_argument('--dem-sample-radius',
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metavar='<float>',
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default=1.0,
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type=float,
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help='Minimum distance between samples for DEM '
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parser.add_argument('--dem-gapfill-steps',
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metavar='<positive integer>',
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default=4,
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type=int,
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help='Number of steps used to fill areas with gaps. Set to 0 to disable gap filling. '
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'Starting with a radius equal to the output resolution, N different DEMs are generated with '
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'progressively bigger radius using the inverse distance weighted (IDW) algorithm '
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'and merged together. Remaining gaps are then merged using linear interpolation. '
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'generation.\nDefault=%(default)s')
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parser.add_argument('--dem-resolution',
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metavar='<float>',
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type=float,
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default=2,
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default=0.1,
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help='Length of raster cell edges in X/Y units.'
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'\nDefault: %(default)s')
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parser.add_argument('--dem-radius',
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metavar='<float>',
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parser.add_argument('--dem-maxangle',
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metavar='<positive float>',
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type=float,
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default=0.5,
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help='Radius about cell center bounding points to '
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'use to calculate a cell value.\nDefault: '
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default=20,
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help='Points that are more than maxangle degrees off-nadir are discarded. '
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'\nDefault: '
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'%(default)s')
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parser.add_argument('--dem-maxsd',
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metavar='<positive float>',
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type=float,
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default=2.5,
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help='Points that deviate more than maxsd standard deviations from the local mean '
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'are discarded. \nDefault: '
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'%(default)s')
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parser.add_argument('--dem-approximate',
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action='store_true',
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default=False,
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help='Use this tag use the approximate progressive '
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'morphological filter in PDAL, which computes DEMs faster '
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'but is not as accurate.')
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parser.add_argument('--dem-decimation',
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metavar='<positive integer>',
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default=1,
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type=int,
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help='Decimate the points before generating the DEM. 1 is no decimation (full quality). '
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'100 decimates ~99% of the points. Useful for speeding up '
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'generation.\nDefault=%(default)s')
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parser.add_argument('--dem-terrain-type',
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metavar='<string>',
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choices=['FlatNonForest', 'FlatForest', 'ComplexNonForest', 'ComplexForest'],
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default='ComplexForest',
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help='Specifies the type of terrain. This mainly helps reduce processing time. '
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'FlatNonForest: Relatively flat region with little to no vegetation (slope 1, cell size 3)'
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'FlatForest: Relatively flat region that is forested (slope 1, cell size 2)'
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'ComplexNonForest: Varied terrain with little to no vegetation (slope 5, cell size 2)'
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'ComplexForest: Varied terrain that is forested (slope 10, cell size 2)'
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'\nDefault=%(default)s')
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parser.add_argument('--orthophoto-resolution',
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metavar='<float > 0.0>',
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default=20.0,
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@ -15,8 +15,9 @@ tasks_dict = {'1': 'resize',
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'5': 'odm_meshing',
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'6': 'mvs_texturing',
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'7': 'odm_georeferencing',
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'8': 'odm_orthophoto',
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'9': 'zip_results'}
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'8': 'odm_dem',
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'9': 'odm_orthophoto',
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'10': 'zip_results'}
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class ODMTaskManager(object):
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@ -435,3 +435,6 @@ class ODM_Tree(object):
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self.odm_orthophoto_log = io.join_paths(self.odm_orthophoto, 'odm_orthophoto_log.txt')
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self.odm_orthophoto_tif_log = io.join_paths(self.odm_orthophoto, 'gdal_translate_log.txt')
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self.odm_orthophoto_gdaladdo_log = io.join_paths(self.odm_orthophoto, 'gdaladdo_log.txt')
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def path(self, **args):
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return io.join_paths(self.root_path, **args)
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@ -16,6 +16,7 @@ from odm_meshing import ODMeshingCell
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from mvstex import ODMMvsTexCell
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from odm_georeferencing import ODMGeoreferencingCell
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from odm_orthophoto import ODMOrthoPhotoCell
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from odm_dem import ODMDEMCell
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class ODMApp(ecto.BlackBox):
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@ -73,11 +74,8 @@ class ODMApp(ecto.BlackBox):
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'georeferencing': ODMGeoreferencingCell(img_size=p.args.resize_to,
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gcp_file=p.args.gcp,
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use_exif=p.args.use_exif,
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dem=p.args.dem,
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sample_radius=p.args.dem_sample_radius,
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gdal_res=p.args.dem_resolution,
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gdal_radius=p.args.dem_radius,
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verbose=p.args.verbose),
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'dem': ODMDEMCell(verbose=p.args.verbose),
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'orthophoto': ODMOrthoPhotoCell(resolution=p.args.orthophoto_resolution,
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t_srs=p.args.orthophoto_target_srs,
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no_tiled=p.args.orthophoto_no_tiled,
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@ -0,0 +1,148 @@
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import ecto, os
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from opendm import io
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from opendm import log
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from opendm import system
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from opendm import context
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from opendm import types
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class ODMDemCell(ecto.Cell):
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def declare_params(self, params):
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params.declare("verbose", 'print additional messages to console', False)
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def declare_io(self, params, inputs, outputs):
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inputs.declare("args", "The application arguments.", {})
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def process(self, inputs, outputs):
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# Benchmarking
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start_time = system.now_raw()
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log.ODM_INFO('Running ODM DEM Cell')
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# get inputs
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args = self.inputs.args
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verbose = '-v' if self.params.verbose else ''
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# define paths and create working directories
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odm_dem_root = tree.path('odm_dem')
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system.mkdir_p(odm_dem_root)
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dsm_output_filename = os.path.join(odm_dem_root, )
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# check if we rerun cell or not
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rerun_cell = (args.rerun is not None and
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args.rerun == 'odm_dem') or \
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(args.rerun_all) or \
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(args.rerun_from is not None and
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'odm_dem' in args.rerun_from)
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if not io.file_exists(tree.odm_orthophoto_file) or rerun_cell:
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# odm_orthophoto definitions
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kwargs = {
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'bin': context.odm_modules_path,
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'log': tree.odm_orthophoto_log,
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'ortho': tree.odm_orthophoto_file,
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'corners': tree.odm_orthophoto_corners,
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'res': self.params.resolution,
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'verbose': verbose
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}
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# Have geo coordinates?
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if io.file_exists(tree.odm_georeferencing_coords):
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if args.use_25dmesh:
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kwargs['model_geo'] = os.path.join(tree.odm_25dtexturing, tree.odm_georeferencing_model_obj_geo)
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else:
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kwargs['model_geo'] = os.path.join(tree.odm_texturing, tree.odm_georeferencing_model_obj_geo)
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else:
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if args.use_25dmesh:
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kwargs['model_geo'] = os.path.join(tree.odm_25dtexturing, tree.odm_textured_model_obj)
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else:
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kwargs['model_geo'] = os.path.join(tree.odm_texturing, tree.odm_textured_model_obj)
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# run odm_orthophoto
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system.run('{bin}/odm_orthophoto -inputFile {model_geo} '
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'-logFile {log} -outputFile {ortho} -resolution {res} {verbose} '
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'-outputCornerFile {corners}'.format(**kwargs))
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if not io.file_exists(tree.odm_georeferencing_coords):
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log.ODM_WARNING('No coordinates file. A georeferenced raster '
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'will not be created')
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else:
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# Create georeferenced GeoTiff
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geotiffcreated = False
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georef = types.ODM_GeoRef()
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# creates the coord refs # TODO I don't want to have to do this twice- after odm_georef
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georef.parse_coordinate_system(tree.odm_georeferencing_coords)
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if georef.epsg and georef.utm_east_offset and georef.utm_north_offset:
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ulx = uly = lrx = lry = 0.0
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with open(tree.odm_orthophoto_corners) as f:
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for lineNumber, line in enumerate(f):
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if lineNumber == 0:
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tokens = line.split(' ')
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if len(tokens) == 4:
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ulx = float(tokens[0]) + \
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float(georef.utm_east_offset)
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lry = float(tokens[1]) + \
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float(georef.utm_north_offset)
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lrx = float(tokens[2]) + \
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float(georef.utm_east_offset)
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uly = float(tokens[3]) + \
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float(georef.utm_north_offset)
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log.ODM_INFO('Creating GeoTIFF')
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kwargs = {
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'ulx': ulx,
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'uly': uly,
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'lrx': lrx,
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'lry': lry,
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'tiled': '' if self.params.no_tiled else '-co TILED=yes ',
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'compress': self.params.compress,
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'predictor': '-co PREDICTOR=2 ' if self.params.compress in
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['LZW', 'DEFLATE'] else '',
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'epsg': georef.epsg,
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't_srs': self.params.t_srs or "EPSG:{0}".format(georef.epsg),
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'bigtiff': self.params.bigtiff,
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'png': tree.odm_orthophoto_file,
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'tiff': tree.odm_orthophoto_tif,
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'log': tree.odm_orthophoto_tif_log
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}
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system.run('gdal_translate -a_ullr {ulx} {uly} {lrx} {lry} '
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'{tiled} '
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'-co BIGTIFF={bigtiff} '
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'-co COMPRESS={compress} '
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'{predictor} '
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'-co BLOCKXSIZE=512 '
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'-co BLOCKYSIZE=512 '
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'-co NUM_THREADS=ALL_CPUS '
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'-a_srs \"EPSG:{epsg}\" '
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'{png} {tiff} > {log}'.format(**kwargs))
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if self.params.build_overviews:
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log.ODM_DEBUG("Building Overviews")
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kwargs = {
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'orthophoto': tree.odm_orthophoto_tif,
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'log': tree.odm_orthophoto_gdaladdo_log
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}
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# Run gdaladdo
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system.run('gdaladdo -ro -r average '
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'--config BIGTIFF_OVERVIEW IF_SAFER '
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'--config COMPRESS_OVERVIEW JPEG '
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'{orthophoto} 2 4 8 16 > {log}'.format(**kwargs))
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geotiffcreated = True
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if not geotiffcreated:
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log.ODM_WARNING('No geo-referenced orthophoto created due '
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'to missing geo-referencing or corner coordinates.')
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else:
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log.ODM_WARNING('Found a valid orthophoto in: %s' % tree.odm_orthophoto_file)
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if args.time:
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system.benchmark(start_time, tree.benchmarking, 'Orthophoto')
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log.ODM_INFO('Running ODM OrthoPhoto Cell - Finished')
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return ecto.OK if args.end_with != 'odm_orthophoto' else ecto.QUIT
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