OpenDroneMap-ODM/opendm/mesh.py

from __future__ import absolute_import
import os, shutil, sys, struct, random, math
from gippy import GeoImage
from opendm.dem import commands
from opendm import system
from opendm import log
from opendm import context
from scipy import signal, ndimage
import numpy as np

def create_25dmesh(inPointCloud, outMesh, dsm_radius=0.07, dsm_resolution=0.05, depth=8, samples=1, maxVertexCount=100000, verbose=False, max_workers=None):
    # Create DSM from point cloud

    # Create temporary directory
    mesh_directory = os.path.dirname(outMesh)
    tmp_directory = os.path.join(mesh_directory, 'tmp')
    if os.path.exists(tmp_directory):
        shutil.rmtree(tmp_directory)
    os.mkdir(tmp_directory)
    log.ODM_INFO('Created temporary directory: %s' % tmp_directory)

    radius_steps = [dsm_radius]

    log.ODM_INFO('Creating DSM for 2.5D mesh')

    commands.create_dems(
            [inPointCloud],
            'mesh_dsm',
            radius=map(str, radius_steps),
            gapfill=True,
            outdir=tmp_directory,
            resolution=dsm_resolution,
            products=['max'],
            verbose=verbose,
            max_workers=max_workers
        )

    mesh = dem_to_mesh(os.path.join(tmp_directory, 'mesh_dsm.tif'), outMesh, maxVertexCount, verbose)

    # Cleanup tmp
    # if os.path.exists(tmp_directory):
    #     shutil.rmtree(tmp_directory)

    return mesh

def dem_to_mesh(inGeotiff, outPointCloud, maxVertexCount, verbose=False):
    log.ODM_INFO('Creating mesh from DSM: %s' % inGeotiff)

    kwargs = {
        'bin': context.odm_modules_path,
        'outfile': outPointCloud,
        'infile': inGeotiff,
        'maxVertexCount': maxVertexCount,
        'verbose': '-verbose' if verbose else ''
    }

    system.run('{bin}/odm_dem2mesh -inputFile {infile} '
         '-outputFile {outfile} '
         '-maxVertexCount {maxVertexCount} '
         ' {verbose} '.format(**kwargs))

    return outPointCloud


def screened_poisson_reconstruction(inPointCloud, outMesh, depth = 8, samples = 1, maxVertexCount=100000, pointWeight=4, threads=context.num_cores, verbose=False):

    mesh_path, mesh_filename = os.path.split(outMesh)
    # mesh_path = path/to
    # mesh_filename = odm_mesh.ply

    basename, ext = os.path.splitext(mesh_filename)
    # basename = odm_mesh
    # ext = .ply

    outMeshDirty = os.path.join(mesh_path, "{}.dirty{}".format(basename, ext))

    poissonReconArgs = {
      'bin': context.poisson_recon_path,
      'outfile': outMeshDirty,
      'infile': inPointCloud,
      'depth': depth,
      'samples': samples,
      'pointWeight': pointWeight,
      'threads': threads,
      'verbose': '--verbose' if verbose else ''
    }

    # Run PoissonRecon
    system.run('{bin} --in {infile} '
             '--out {outfile} '
             '--depth {depth} '
             '--pointWeight {pointWeight} '
             '--samplesPerNode {samples} '
             '--threads {threads} '
             '--linearFit '
             '{verbose}'.format(**poissonReconArgs))

    # Cleanup and reduce vertex count if necessary
    cleanupArgs = {
        'bin': context.odm_modules_path,
        'outfile': outMesh,
        'infile': outMeshDirty,
        'max_vertex': maxVertexCount,
        'verbose': '-verbose' if verbose else ''
    }

    system.run('{bin}/odm_cleanmesh -inputFile {infile} '
         '-outputFile {outfile} '
         '-removeIslands '
         '-decimateMesh {max_vertex} {verbose} '.format(**cleanupArgs))

    # Delete intermediate results
    os.remove(outMeshDirty)

    return outMesh