OpenDroneMap-ODM/opendm/mesh.py

from __future__ import absolute_import
import os, shutil, sys, struct, random
from io import BytesIO
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_resolution=0.05, depth=8, samples=1, maxVertexCount=100000, verbose=False):
    # 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_resolution / 4.0, dsm_resolution / 2.0, dsm_resolution]

    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=['idw'],
            verbose=verbose
        )

    dsm_points = dem_to_points(os.path.join(tmp_directory, 'mesh_dsm.tif'), os.path.join(tmp_directory, 'dsm_points.ply'))
    mesh = screened_poisson_reconstruction(dsm_points, outMesh, depth=depth, samples=samples, maxVertexCount=maxVertexCount, verbose=verbose)
    
    # Cleanup tmp
    if os.path.exists(tmp_directory):
        shutil.rmtree(tmp_directory)

    return mesh

def dem_to_points(inGeotiff, outPointCloud):
    log.ODM_INFO('Sampling points from DSM: %s' % inGeotiff)

    image = GeoImage.open([inGeotiff], bandnames=['z'], nodata=-9999)
    arr = image['z'].read_raw()
    resolution = max(abs(image.resolution().x()), abs(image.resolution().y()))

    log.ODM_INFO('Writing points...')

    mem_file = BytesIO()

    xmin, xmax, ymin, ymax = image.extent().x0(), image.extent().x1(), image.extent().y0(), image.extent().y1()
    ext_width, ext_height = xmax - xmin, ymax - ymin
    arr_height, arr_width = arr.shape
    vertex_count = (arr_height - 4) * (arr_width - 4)
    skirt_points = 0

    skirt_height_threshold = 1 # meter
    skirt_increments = 0.1

    for x in range(2, arr_width - 2):
        for y in range(2, arr_height - 2):
            z = arr[y][x]
            tx = xmin + (float(x) / float(arr_width)) * ext_width
            ty = ymax - (float(y) / float(arr_height)) * ext_height
            mem_file.write(struct.pack('ffffff', tx, ty, z, 0, 0, 1))
            
            # Skirting
            for (nx, ny) in ((x, y + 1), (x, y - 1), (x + 1, y), (x - 1, y)):
                current_z = z
                neighbor_z = arr[ny][nx]

                if current_z - neighbor_z > skirt_height_threshold:
                    while current_z > neighbor_z:
                        current_z -= skirt_increments
                        mem_file.write(struct.pack('ffffff', tx, ty, current_z, 0, 0, 1))
                        skirt_points += 1

                    mem_file.write(struct.pack('ffffff', tx, ty, neighbor_z, 0, 0, 1))
                    skirt_points += 1
                    

    with open(outPointCloud, "wb") as f:
        f.write("ply\n")
        f.write("format binary_%s_endian 1.0\n" % sys.byteorder) 
        f.write("element vertex %s\n" % (vertex_count + skirt_points))
        f.write("property float x\n")
        f.write("property float y\n")
        f.write("property float z\n")
        f.write("property float nx\n")
        f.write("property float ny\n")
        f.write("property float nz\n")
        f.write("end_header\n")
        f.write(mem_file.getvalue())

    mem_file.close()

    log.ODM_INFO("Points count: %s (%s samples, %s skirts)", vertex_count + skirt_points, vertex_count, skirt_points)
    log.ODM_INFO('Wrote points to: %s' % outPointCloud)

    return outPointCloud


def screened_poisson_reconstruction(inPointCloud, outMesh, depth = 8, samples = 1, maxVertexCount=100000, 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 = {
      #TODO: @dakotabenjamin adjust path to PoissonRecon program
      # 'bin': '/PoissonRecon/Bin/Linux/PoissonRecon',
      'bin': context.odm_modules_path,
      'outfile': outMeshDirty,
      'infile': inPointCloud,
      'depth': depth,
      'samples': samples,
      'verbose': '--verbose' if verbose else ''
    }

    # Run PoissonRecon (new)
    # system.run('{bin} --in {infile} '
    #          '--out {outfile} '
    #          '--depth {depth} '
    #          '--linearFit '
    #          '{verbose}'.format(**kwargs))

    # TODO: remove odm_meshing in favor of above
    system.run('{bin}/odm_meshing -inputFile {infile} '
         '-outputFile {outfile} '
         '-octreeDepth {depth} -verbose '
         '-samplesPerNode {samples} -solverDivide 9'.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