kopia lustrzana https://github.com/OpenDroneMap/ODM
103 wiersze
3.3 KiB
Python
103 wiersze
3.3 KiB
Python
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import os, shutil, sys, struct
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from gippy import GeoImage
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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 scipy import signal
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def create_25dmesh(inPointCloud, outMesh, dsm_resolution=0.05, depth=8, samples=1, verbose=False):
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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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# Always use just two steps
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radius_steps = [dsm_resolution, dsm_resolution * 3, dsm_resolution * 9]
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log.ODM_INFO('Creating DSM for 2.5D mesh')
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commands.create_dems(
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[inPointCloud],
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'mesh_dsm',
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radius=map(str, 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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verbose=verbose
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)
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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, samples=samples, verbose=verbose)
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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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image = GeoImage.open([inGeotiff], bandnames=['z'], nodata=-9999)
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arr = image['z'].read_raw()
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# Median filter
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log.ODM_INFO('Applying median filter...')
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arr = signal.medfilt(arr, 1)
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log.ODM_INFO('Writing points...')
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with open(outPointCloud, "wb") as f:
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f.write("ply\n")
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f.write("format binary_%s_endian 1.0\n" % sys.byteorder)
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f.write("element vertex %s\n" % arr.size)
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f.write("property float x\n")
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f.write("property float y\n")
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f.write("property float z\n")
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f.write("property float nx\n")
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f.write("property float ny\n")
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f.write("property float nz\n")
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f.write("end_header\n")
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xmin, xmax, ymin, ymax = image.extent().x0(), image.extent().x1(), image.extent().y0(), image.extent().y1()
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ext_width, ext_height = xmax - xmin, ymax - ymin
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arr_height, arr_width = arr.shape
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for x in range(arr_width):
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for y in range(arr_height):
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tx = xmin + (float(x) / float(arr_width)) * ext_width
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ty = ymax - (float(y) / float(arr_height)) * ext_height
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f.write(struct.pack('ffffff', tx, ty, arr[y][x], 0, 0, 1))
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#f.write('%s %s %s\n' % (tx, ty, z))
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log.ODM_INFO('Wrote points to: %s' % outPointCloud)
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return outPointCloud
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def screened_poisson_reconstruction(inPointCloud, outMesh, depth = 8, samples = 1, verbose=False):
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#TODO: @dakotabenjamin adjust path to PoissonRecon program
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kwargs = {
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'bin': '/PoissonRecon/Bin/Linux/PoissonRecon',
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'outfile': outMesh,
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'infile': inPointCloud,
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'depth': depth,
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'samples': samples,
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'verbose': '--verbose' if verbose else ''
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}
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# Run PoissonRecon
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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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'--normals --linearFit '
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'{verbose}'.format(**kwargs))
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return outMesh
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