kopia lustrzana https://github.com/OpenDroneMap/ODM
211 wiersze
7.1 KiB
Python
211 wiersze
7.1 KiB
Python
from __future__ import absolute_import
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import os, shutil, sys, struct, random, math, platform
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from opendm.dem import commands
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from opendm import system
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from opendm import log
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from opendm import context
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from opendm import concurrency
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from opendm import point_cloud
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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, radius_steps=["0.05"], dsm_resolution=0.05, depth=8, samples=1, maxVertexCount=100000, available_cores=None, method='gridded', smooth_dsm=True, max_tiles=None):
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# Create DSM from point cloud
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# Create temporary directory
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mesh_directory = os.path.dirname(outMesh)
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tmp_directory = os.path.join(mesh_directory, 'tmp')
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if os.path.exists(tmp_directory):
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shutil.rmtree(tmp_directory)
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os.mkdir(tmp_directory)
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log.ODM_INFO('Created temporary directory: %s' % tmp_directory)
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log.ODM_INFO('Creating DSM for 2.5D mesh')
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commands.create_dem(
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inPointCloud,
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'mesh_dsm',
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output_type='max',
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radiuses=radius_steps,
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gapfill=True,
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outdir=tmp_directory,
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resolution=dsm_resolution,
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max_workers=available_cores,
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apply_smoothing=smooth_dsm,
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max_tiles=max_tiles
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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, 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'))
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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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else:
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raise 'Not a valid method: ' + method
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# Cleanup tmp
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if os.path.exists(tmp_directory):
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shutil.rmtree(tmp_directory)
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return mesh
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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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}
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system.run('"{bin}" -inputFile "{infile}" '
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'-outputFile "{outfile}" '
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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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return outPointCloud
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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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# mesh_path = path/to
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# mesh_filename = odm_mesh.ply
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basename, ext = os.path.splitext(mesh_filename)
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# basename = odm_mesh
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# ext = .ply
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outMeshDirty = os.path.join(mesh_path, "{}.dirty{}".format(basename, ext))
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# This should work without issues most of the times,
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# but just in case we lower maxConcurrency if it fails.
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while True:
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try:
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kwargs = {
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'bin': context.dem2mesh_path,
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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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}
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system.run('"{bin}" -inputFile "{infile}" '
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'-outputFile "{outfile}" '
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'-maxTileLength 2000 '
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'-maxVertexCount {maxVertexCount} '
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'-maxConcurrency {maxConcurrency} '
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'-edgeSwapThreshold 0.15 '
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'-verbose '.format(**kwargs))
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break
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except Exception as e:
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maxConcurrency = math.floor(maxConcurrency / 2)
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if maxConcurrency >= 1:
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log.ODM_WARNING("dem2mesh failed, retrying with lower concurrency (%s) in case this is a memory issue" % maxConcurrency)
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else:
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raise e
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# Cleanup and reduce vertex count if necessary
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# (as dem2mesh cannot guarantee that we'll have the target vertex count)
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cleanupArgs = {
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'reconstructmesh': context.omvs_reconstructmesh_path,
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'outfile': outMesh,
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'infile': outMeshDirty,
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'max_faces': maxVertexCount * 2
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}
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system.run('"{reconstructmesh}" -i "{infile}" '
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'-o "{outfile}" '
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'--archive-type 3 '
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'--remove-spikes 0 --remove-spurious 0 --smooth 0 '
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'--target-face-num {max_faces} -v 0'.format(**cleanupArgs))
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# Delete intermediate results
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os.remove(outMeshDirty)
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return outMesh
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def screened_poisson_reconstruction(inPointCloud, outMesh, depth = 8, samples = 1, maxVertexCount=100000, pointWeight=4, threads=context.num_cores):
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mesh_path, mesh_filename = os.path.split(outMesh)
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# mesh_path = path/to
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# mesh_filename = odm_mesh.ply
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basename, ext = os.path.splitext(mesh_filename)
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# basename = odm_mesh
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# ext = .ply
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outMeshDirty = os.path.join(mesh_path, "{}.dirty{}".format(basename, ext))
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if os.path.isfile(outMeshDirty):
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os.remove(outMeshDirty)
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# Since PoissonRecon has some kind of a race condition on ppc64el, and this helps...
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if platform.machine() == 'ppc64le':
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log.ODM_WARNING("ppc64le platform detected, forcing single-threaded operation for PoissonRecon")
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threads = 1
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while True:
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poissonReconArgs = {
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'bin': context.poisson_recon_path,
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'outfile': outMeshDirty,
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'infile': inPointCloud,
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'depth': depth,
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'samples': samples,
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'pointWeight': pointWeight,
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'threads': int(threads)
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}
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# Run PoissonRecon
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try:
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system.run('"{bin}" --in "{infile}" '
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'--out "{outfile}" '
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'--depth {depth} '
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'--pointWeight {pointWeight} '
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'--samplesPerNode {samples} '
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'--threads {threads} '
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'--bType 2 '
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'--linearFit '.format(**poissonReconArgs))
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except Exception as e:
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log.ODM_WARNING(str(e))
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if os.path.isfile(outMeshDirty):
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break # Done!
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else:
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# PoissonRecon will sometimes fail due to race conditions
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# on certain machines, especially on Windows
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threads //= 2
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if threads < 1:
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break
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else:
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log.ODM_WARNING("PoissonRecon failed with %s threads, let's retry with %s..." % (threads * 2, threads))
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# Cleanup and reduce vertex count if necessary
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cleanupArgs = {
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'reconstructmesh': context.omvs_reconstructmesh_path,
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'outfile': outMesh,
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'infile':outMeshDirty,
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'max_faces': maxVertexCount * 2
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}
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system.run('"{reconstructmesh}" -i "{infile}" '
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'-o "{outfile}" '
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'--archive-type 3 '
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'--remove-spikes 0 --remove-spurious 20 --smooth 0 '
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'--target-face-num {max_faces} -v 0'.format(**cleanupArgs))
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# Delete intermediate results
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os.remove(outMeshDirty)
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return outMesh
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