Skirts, parameter tweaking

Former-commit-id: b54c4808e1
pull/1161/head
Piero Toffanin 2018-06-12 17:36:24 -04:00
rodzic e24b51e05f
commit 80e4e6f0fd
1 zmienionych plików z 42 dodań i 17 usunięć

Wyświetl plik

@ -1,4 +1,6 @@
from __future__ import absolute_import
import os, shutil, sys, struct
from io import BytesIO
from gippy import GeoImage
from opendm.dem import commands
from opendm import system
@ -17,12 +19,12 @@ def create_25dmesh(inPointCloud, outMesh, dsm_resolution=0.05, depth=8, samples=
log.ODM_INFO('Created temporary directory: %s' % tmp_directory)
# Always use just two steps
radius_steps = [dsm_resolution, dsm_resolution * 3, dsm_resolution * 9]
radius_steps = [dsm_resolution / 8.0, dsm_resolution / 4.0, dsm_resolution / 2.0, dsm_resolution]
log.ODM_INFO('Creating DSM for 2.5D mesh')
commands.create_dems(
[inPointCloud],
[inPointCloud],
'mesh_dsm',
radius=map(str, radius_steps),
gapfill=True,
@ -35,8 +37,8 @@ def create_25dmesh(inPointCloud, outMesh, dsm_resolution=0.05, depth=8, samples=
mesh = screened_poisson_reconstruction(dsm_points, outMesh, depth=depth, samples=samples, verbose=verbose)
# Cleanup tmp
if os.path.exists(tmp_directory):
shutil.rmtree(tmp_directory)
#if os.path.exists(tmp_directory):
# shutil.rmtree(tmp_directory)
return mesh
@ -45,18 +47,48 @@ def dem_to_points(inGeotiff, outPointCloud):
image = GeoImage.open([inGeotiff], bandnames=['z'], nodata=-9999)
arr = image['z'].read_raw()
resolution = max(abs(image.resolution().x()), abs(image.resolution().y()))
# Median filter
log.ODM_INFO('Applying median filter...')
arr = signal.medfilt(arr, 1)
arr = signal.medfilt2d(arr, 5)
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 = resolution
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 ((y + 1, x), (y - 1, x), (y, x + 1), (y, x - 1)):
current_z = z
neighbor_z = arr[nx][ny]
if current_z - neighbor_z > skirt_height_threshold:
stop_at_z = neighbor_z + skirt_increments
while current_z > stop_at_z:
current_z -= skirt_increments
mem_file.write(struct.pack('ffffff', tx, ty, current_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" % arr.size)
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")
@ -64,18 +96,11 @@ def dem_to_points(inGeotiff, outPointCloud):
f.write("property float ny\n")
f.write("property float nz\n")
f.write("end_header\n")
f.write(mem_file.getvalue())
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
for x in range(arr_width):
for y in range(arr_height):
tx = xmin + (float(x) / float(arr_width)) * ext_width
ty = ymax - (float(y) / float(arr_height)) * ext_height
f.write(struct.pack('ffffff', tx, ty, arr[y][x], 0, 0, 1))
#f.write('%s %s %s\n' % (tx, ty, z))
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
@ -96,7 +121,7 @@ def screened_poisson_reconstruction(inPointCloud, outMesh, depth = 8, samples =
system.run('{bin} --in {infile} '
'--out {outfile} '
'--depth {depth} '
'--normals --linearFit '
'--linearFit '
'{verbose}'.format(**kwargs))
return outMesh