def produce_lidarviewer(s2poutdir, output):
"""
Produce a single multiscale point cloud for the whole processed region.
Args:
tiles: list of tiles dictionaries
"""
tiles_file = os.path.join(s2poutdir, 'tiles.txt')
# Read the tiles file
tiles = s2p.read_tiles(tiles_file)
print(str(len(tiles)) + ' tiles found')
# collect all plys
plys = [
os.path.join(os.path.abspath(os.path.dirname(t)), 'cloud.ply')
for t in tiles
]
nthreads = 4
plys = ' '.join(plys)
common.run(
"LidarPreprocessor -to %s.LidarO -tp %s.LidarP -nt %d %s -o %s" %
(output, output, nthreads, plys, output))
def main(tiles_file, outfile, sub_img):
outfile_basename = os.path.basename(outfile)
outfile_dirname = os.path.dirname(outfile)
output_format = outfile_basename[-3:]
print('Output format is ' + output_format)
# If output format is tif, we need to generate a temporary vrt
# with the same name
vrt_basename = outfile_basename
if output_format == 'tif':
vrt_basename = vrt_basename[:-3] + 'vrt'
elif output_format != 'vrt':
print('Error: only vrt or tif extension is allowed for output image.')
return
vrt_name = os.path.join(outfile_dirname, vrt_basename)
# Read the tiles file
tiles = s2p.read_tiles(tiles_file)
print(str(len(tiles)) + ' tiles found')
# Compute the global extent of the output image
(min_x, max_x, min_y, max_y) = global_extent(tiles)
print('Global extent: [%i,%i]x[%i,%i]' % (min_x, max_x, min_y, max_y))
# Now, write all row vrts
print("Writing row vrt files " + vrt_basename)
vrt_row = write_row_vrts(tiles, sub_img, vrt_basename, min_x, max_x)
# Finally, write main vrt
print('Writing ' + vrt_name)
write_main_vrt(vrt_row, vrt_name, min_x, max_x, min_y, max_y)
# If Output format is tif, convert vrt file to tif
if output_format == 'tif':
print('Converting vrt to tif ...')
common.run(('gdal_translate -ot Float32 -co TILED=YES -co'
' BIGTIFF=IF_NEEDED %s %s' %
(common.shellquote(vrt_name), common.shellquote(outfile))))
print('Removing temporary vrt files')
# Do not use items()/iteritems() here because of python 2 and 3 compat
for y in vrt_row:
vrt_data = vrt_row[y]
row_vrt_filename = os.path.join(vrt_data['vrt_dir'], vrt_basename)
try:
os.remove(row_vrt_filename)
except OSError:
pass
try:
os.remove(vrt_name)
except OSError:
pass
def end2end_cluster(config):
print('Configuration file: ',config)
print('Running end2end in sequential mode to get reference DSM ...')
test_cfg = s2p.read_config_file(config)
test_cfg['skip_existing'] = True
s2p.main(test_cfg)
outdir = test_cfg['out_dir']
expected = s2plib.common.gdal_read_as_array_with_nans(os.path.join(outdir,'dsm.tif'))
print('Running end2end in cluster mode ...')
test_cfg_cluster = dict()
test_cfg_cluster.update(test_cfg)
test_cfg_cluster['out_dir'] = test_cfg_cluster['out_dir'] + "_cluster"
test_cfg_cluster['skip_existing'] = True
print("Running initialisation step ...")
s2p.main(test_cfg_cluster,["initialisation"])
# Retrieve tiles list
outdir = test_cfg_cluster['out_dir']
tiles_file = os.path.join(outdir,'tiles.txt')
tiles = s2p.read_tiles(tiles_file)
print('Found '+str(len(tiles))+' tiles to process')
for step in s2p.ALL_STEPS:
if s2p.ALL_STEPS[step] is True:
print('Running %s on each tile...' % step)
for tile in tiles:
print('tile : %s' % tile)
tile_cfg_cluster = s2p.read_config_file(tile)
s2p.main(tile_cfg_cluster, [step])
else:
print('Running %s...' % step)
print('test_cfg_cluster : %s' % test_cfg_cluster)
s2p.main(test_cfg_cluster, [step])
computed = s2plib.common.gdal_read_as_array_with_nans(os.path.join(outdir,'dsm.tif'))
end2end_compare_dsm(computed,expected,0,0)
def end2end_cluster(config):
print('Configuration file: ',config)
print('Running end2end in sequential mode to get reference DSM ...')
test_cfg = s2p.read_config_file(config)
test_cfg['skip_existing'] = True
s2p.main(test_cfg)
outdir = test_cfg['out_dir']
expected = s2plib.common.gdal_read_as_array_with_nans(os.path.join(outdir,'dsm.tif'))
print('Running end2end in cluster mode ...')
test_cfg_cluster = dict()
test_cfg_cluster.update(test_cfg)
test_cfg_cluster['out_dir'] = test_cfg_cluster['out_dir'] + "_cluster"
test_cfg_cluster['skip_existing'] = True
print("Running initialisation step ...")
s2p.main(test_cfg_cluster,["initialisation"])
# Retrieve tiles list
outdir = test_cfg_cluster['out_dir']
tiles_file = os.path.join(outdir,'tiles.txt')
tiles = s2p.read_tiles(tiles_file)
print('Found '+str(len(tiles))+' tiles to process')
for step in s2p.ALL_STEPS:
if s2p.ALL_STEPS[step] is True:
print('Running %s on each tile...' % step)
for tile in tiles:
print('tile : %s' % tile)
tile_cfg_cluster = s2p.read_config_file(tile)
s2p.main(tile_cfg_cluster, [step])
else:
print('Running %s...' % step)
print('test_cfg_cluster : %s' % test_cfg_cluster)
s2p.main(test_cfg_cluster, [step])
computed = s2plib.common.gdal_read_as_array_with_nans(os.path.join(outdir,'dsm.tif'))
end2end_compare_dsm(computed,expected,0,0)
def produce_potree(s2poutdir, potreeoutdir):
"""
Produce a single multiscale point cloud for the whole processed region.
Args:
tiles: list of tiles dictionaries
"""
basedir = os.path.dirname(os.path.abspath(__file__))
test_for_potree(os.path.join(basedir,'PotreeConverter_PLY_toolchain/'))
tiles_file = os.path.join(s2poutdir, 'tiles.txt')
# Read the tiles file
tiles = s2p.read_tiles(tiles_file)
print(str(len(tiles))+' tiles found')
def plyvertex(fname):
with open(fname, 'r', 'utf-8') as f:
for x in f:
if x.split()[0] == 'element' and x.split()[1] == 'vertex':
return int(x.split()[2])
# collect all plys
plys = []
for t in tiles:
clo = os.path.join(os.path.abspath(os.path.dirname(t)), 'cloud.ply')
if os.path.isfile(clo):
if plyvertex(clo) > 0 :
plys.append(clo)
# plys = [os.path.join(os.path.abspath(os.path.dirname(t)), 'cloud.ply') for t in tiles if os.path.isfile(os.path.join(os.path.abspath(os.path.dirname(t)), 'cloud.ply'))]
# produce the potree point cloud
plys_to_potree(plys, os.path.join(potreeoutdir, 'cloud.potree'),
os.path.join(basedir, 'PotreeConverter_PLY_toolchain/'))
def produce_potree(s2p_outdirs_list, potreeoutdir):
"""
Produce a single multiscale point cloud for the whole processed region.
Args:
s2poutdirs_list: list of s2p output directories
"""
basedir = os.path.dirname(os.path.abspath(__file__))
test_for_potree(os.path.join(basedir, 'PotreeConverter_PLY_toolchain/'))
def plyvertex(fname):
with open(fname, 'r', 'utf-8') as f:
for x in f:
if x.split()[0] == 'element' and x.split()[1] == 'vertex':
return int(x.split()[2])
js_scripts = []
regex = re.compile("Potree\.loadPointCloud\(.*\);", re.DOTALL)
cloudoutdir = os.path.join(potreeoutdir, "cloud.potree")
# Produce a "cloud_?.html" file for all given s2p outdirs
for i, s2p_outdir in enumerate(s2p_outdirs_list):
tiles = s2p.read_tiles(os.path.join(s2p_outdir, 'tiles.txt'))
print(str(len(tiles)) + ' tiles found')
# collect all plys
plys = []
for t in tiles:
clo = os.path.join(os.path.abspath(os.path.dirname(t)),
'cloud.ply')
if os.path.isfile(clo):
if plyvertex(clo) > 0:
plys.append(clo)
# produce the potree point cloud
cloud_name = "cloud_{}".format(i)
plys_to_potree(
plys,
cloudoutdir,
os.path.join(basedir, 'PotreeConverter_PLY_toolchain/'),
cloud_name,
)
# Gather the js script inside the HTML file that is relevant
# to the point cloud
cloud_html = os.path.join(cloudoutdir, "{}.html".format(cloud_name))
with open(cloud_html) as f:
soup = BeautifulSoup(f, features="lxml")
script = soup.find_all("script")[-1]
js_script = re.search(regex, script.text).group(0)
js_scripts.append(js_script)
os.remove(cloud_html)
# The "main.html" file will contain a concatenation of all the js
# scripts that were gathered in the loop above.
# Use the last HTML file as a basis for the "main.html", and replace
# its js script by all the js scripts
main_html = os.path.join(cloudoutdir, "main.html")
script.string = re.sub(regex, "\n".join(js_scripts), script.text)
with open(main_html, "w") as f:
f.write(soup.prettify())