kopia lustrzana https://github.com/OpenDroneMap/ODM
Piero Toffanin
GitHub
commit
bd3069ee2b
2
VERSION
2
VERSION
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@ -1 +1 @@
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2.6.4
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2.6.5
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@ -0,0 +1,118 @@
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import fiona
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import fiona.crs
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import os
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import io
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import json
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from opendm import system
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from pyproj import CRS
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from opendm.location import transformer
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from opendm.utils import double_quote
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from osgeo import ogr
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from opendm.shots import get_origin
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def compute_boundary_from_shots(reconstruction_json, buffer=0, reconstruction_offset=(0, 0)):
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if not os.path.isfile(reconstruction_json):
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raise IOError(reconstruction_json + " does not exist.")
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with open(reconstruction_json) as f:
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data = json.load(f)
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reconstruction = data[0]
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mp = ogr.Geometry(ogr.wkbMultiPoint)
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for shot_image in reconstruction['shots']:
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shot = reconstruction['shots'][shot_image]
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if shot['gps_dop'] < 999999:
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camera = reconstruction['cameras'][shot['camera']]
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p = ogr.Geometry(ogr.wkbPoint)
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origin = get_origin(shot)
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p.AddPoint_2D(origin[0] + reconstruction_offset[0], origin[1] + reconstruction_offset[1])
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mp.AddGeometry(p)
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if mp.GetGeometryCount() < 3:
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return None
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convexhull = mp.ConvexHull()
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boundary = convexhull.Buffer(buffer)
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return load_boundary(boundary.ExportToJson())
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def load_boundary(boundary_json, reproject_to_proj4=None):
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if not isinstance(boundary_json, str):
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boundary_json = json.dumps(boundary_json)
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with fiona.open(io.BytesIO(boundary_json.encode('utf-8')), 'r') as src:
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if len(src) != 1:
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raise IOError("Boundary must have a single polygon (found: %s)" % len(src))
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geom = src[0]['geometry']
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if geom['type'] != 'Polygon':
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raise IOError("Boundary must have a polygon feature (found: %s)" % geom['type'])
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rings = geom['coordinates']
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if len(rings) == 0:
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raise IOError("Boundary geometry has no rings")
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coords = rings[0]
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if len(coords) == 0:
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raise IOError("Boundary geometry has no coordinates")
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dimensions = len(coords[0])
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if reproject_to_proj4 is not None:
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t = transformer(CRS.from_proj4(fiona.crs.to_string(src.crs)),
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CRS.from_proj4(reproject_to_proj4))
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coords = [t.TransformPoint(*c)[:dimensions] for c in coords]
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return coords
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def boundary_offset(boundary, reconstruction_offset):
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if boundary is None or reconstruction_offset is None:
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return boundary
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res = []
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dims = len(boundary[0])
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for c in boundary:
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if dims == 2:
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res.append((c[0] - reconstruction_offset[0], c[1] - reconstruction_offset[1]))
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else:
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res.append((c[0] - reconstruction_offset[0], c[1] - reconstruction_offset[1], c[2]))
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return res
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def as_polygon(boundary):
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if boundary is None:
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return None
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return "POLYGON((" + ", ".join([" ".join(map(str, c)) for c in boundary]) + "))"
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def export_to_bounds_files(boundary, proj4, bounds_json_file, bounds_gpkg_file):
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with open(bounds_json_file, "w") as f:
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f.write(json.dumps({
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"type": "FeatureCollection",
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"name": "bounds",
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"features": [{
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"type": "Feature",
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"properties": {},
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"geometry": {
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"type": "Polygon",
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"coordinates": [boundary]
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}
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}]
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}))
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if os.path.isfile(bounds_gpkg_file):
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os.remove(bounds_gpkg_file)
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kwargs = {
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'proj4': proj4,
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'input': double_quote(bounds_json_file),
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'output': double_quote(bounds_gpkg_file)
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}
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system.run('ogr2ogr -overwrite -f GPKG -a_srs "{proj4}" {output} {input}'.format(**kwargs))
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@ -303,6 +303,24 @@ def config(argv=None, parser=None):
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'Use 0 to disable cropping. '
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'Default: %(default)s'))
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parser.add_argument('--boundary',
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default='',
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metavar='<json>',
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action=StoreValue,
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type=path_or_json_string,
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help='GeoJSON polygon limiting the area of the reconstruction. '
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'Can be specified either as path to a GeoJSON file or as a '
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'JSON string representing the contents of a '
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'GeoJSON file. Default: %(default)s')
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parser.add_argument('--auto-boundary',
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action=StoreTrue,
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nargs=0,
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default=False,
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help='Automatically set a boundary using camera shot locations to limit the area of the reconstruction. '
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'This can help remove far away background artifacts (sky, background landscapes, etc.). See also --boundary. '
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'Default: %(default)s')
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parser.add_argument('--pc-quality',
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metavar='<string>',
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action=StoreValue,
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@ -5,6 +5,7 @@ from opendm.point_cloud import export_summary_json
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from osgeo import ogr
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import json, os
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from opendm.concurrency import get_max_memory
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from opendm.utils import double_quote
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class Cropper:
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def __init__(self, storage_dir, files_prefix = "crop"):
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@ -41,9 +42,9 @@ class Cropper:
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try:
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kwargs = {
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'gpkg_path': gpkg_path,
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'geotiffInput': original_geotiff,
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'geotiffOutput': geotiff_path,
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'gpkg_path': double_quote(gpkg_path),
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'geotiffInput': double_quote(original_geotiff),
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'geotiffOutput': double_quote(geotiff_path),
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'options': ' '.join(map(lambda k: '-co {}={}'.format(k, gdal_options[k]), gdal_options)),
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'warpOptions': ' '.join(warp_options),
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'max_memory': get_max_memory()
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@ -252,10 +253,13 @@ class Cropper:
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bounds_gpkg_path = os.path.join(self.storage_dir, '{}.bounds.gpkg'.format(self.files_prefix))
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if os.path.isfile(bounds_gpkg_path):
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os.remove(bounds_gpkg_path)
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# Convert bounds to GPKG
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kwargs = {
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'input': bounds_geojson_path,
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'output': bounds_gpkg_path,
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'input': double_quote(bounds_geojson_path),
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'output': double_quote(bounds_gpkg_path),
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'proj4': pc_proj4
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}
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@ -155,7 +155,7 @@ def run_pipeline(json, verbose=False):
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cmd = [
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'pdal',
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'pipeline',
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'-i %s' % jsonfile
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'-i %s' % double_quote(jsonfile)
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]
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if verbose or sys.platform == 'win32':
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system.run(' '.join(cmd))
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@ -126,7 +126,7 @@ def dem_to_mesh_gridded(inGeotiff, outMesh, maxVertexCount, verbose=False, maxCo
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system.run('"{reconstructmesh}" -i "{infile}" '
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'-o "{outfile}" '
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'--remove-spikes 0 --remove-spurious 20 --smooth 0 '
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'--remove-spikes 0 --remove-spurious 0 --smooth 0 '
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'--target-face-num {max_faces} '.format(**cleanupArgs))
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# Delete intermediate results
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@ -70,7 +70,7 @@ def generate_kmz(orthophoto_file, output_file=None, outsize=None):
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'--config GDAL_CACHEMAX %s%% ' % (orthophoto_file, output_file, bandparam, get_max_memory()))
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def post_orthophoto_steps(args, bounds_file_path, orthophoto_file, orthophoto_tiles_dir):
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if args.crop > 0:
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if args.crop > 0 or args.boundary:
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Cropper.crop(bounds_file_path, orthophoto_file, get_orthophoto_vars(args), keep_original=not args.optimize_disk_space, warp_options=['-dstalpha'])
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if args.build_overviews and not args.cog:
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@ -510,10 +510,11 @@ def get_submodel_argv(args, submodels_path = None, submodel_name = None):
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tweaking --crop if necessary (DEM merging makes assumption about the area of DEMs and their euclidean maps that require cropping. If cropping is skipped, this leads to errors.)
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removing --gcp (the GCP path if specified is always "gcp_list.txt")
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reading the contents of --cameras
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reading the contents of --boundary
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"""
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assure_always = ['orthophoto_cutline', 'dem_euclidean_map', 'skip_3dmodel', 'skip_report']
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remove_always = ['split', 'split_overlap', 'rerun_from', 'rerun', 'gcp', 'end_with', 'sm_cluster', 'rerun_all', 'pc_csv', 'pc_las', 'pc_ept', 'tiles', 'copy-to', 'cog']
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read_json_always = ['cameras']
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read_json_always = ['cameras', 'boundary']
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argv = sys.argv
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@ -1,4 +1,4 @@
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import os, sys, shutil, tempfile, json, math
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import os, sys, shutil, tempfile, math, json
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from opendm import system
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from opendm import log
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from opendm import context
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@ -7,6 +7,8 @@ from opendm import entwine
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from opendm import io
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from opendm.concurrency import parallel_map
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from opendm.utils import double_quote
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from opendm.boundary import as_polygon
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from opendm.dem.pdal import run_pipeline
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def ply_info(input_ply):
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if not os.path.exists(input_ply):
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@ -38,7 +40,8 @@ def ply_info(input_ply):
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return {
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'has_normals': has_normals,
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'vertex_count': vertex_count,
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'has_views': has_views
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'has_views': has_views,
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'header_lines': i + 1
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}
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@ -68,7 +71,7 @@ def split(input_point_cloud, outdir, filename_template, capacity, dims=None):
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return [os.path.join(outdir, f) for f in os.listdir(outdir)]
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def filter(input_point_cloud, output_point_cloud, standard_deviation=2.5, meank=16, sample_radius=0, verbose=False, max_concurrency=1):
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def filter(input_point_cloud, output_point_cloud, standard_deviation=2.5, meank=16, sample_radius=0, boundary=None, verbose=False, max_concurrency=1):
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"""
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Filters a point cloud
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"""
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@ -86,6 +89,10 @@ def filter(input_point_cloud, output_point_cloud, standard_deviation=2.5, meank=
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log.ODM_INFO("Filtering {} (statistical, meanK {}, standard deviation {})".format(input_point_cloud, meank, standard_deviation))
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filters.append('outlier')
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filters.append('range')
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if boundary is not None:
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log.ODM_INFO("Boundary {}".format(boundary))
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filters.append('crop')
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info = ply_info(input_point_cloud)
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dims = "x=float,y=float,z=float,"
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@ -116,7 +123,8 @@ def filter(input_point_cloud, output_point_cloud, standard_deviation=2.5, meank=
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filter(pcs['path'], io.related_file_path(pcs['path'], postfix="_filtered"),
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standard_deviation=standard_deviation,
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meank=meank,
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sample_radius=sample_radius,
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sample_radius=sample_radius,
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boundary=boundary,
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verbose=verbose,
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max_concurrency=1)
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# Filter
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@ -132,34 +140,40 @@ def filter(input_point_cloud, output_point_cloud, standard_deviation=2.5, meank=
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shutil.rmtree(partsdir)
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else:
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# Process point cloud (or a point cloud submodel) in a single step
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filterArgs = {
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'inputFile': input_point_cloud,
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'outputFile': output_point_cloud,
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'stages': " ".join(filters),
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'dims': dims
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}
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pipeline = []
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cmd = ("pdal translate -i \"{inputFile}\" "
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"-o \"{outputFile}\" "
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"{stages} "
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"--writers.ply.sized_types=false "
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"--writers.ply.storage_mode=\"little endian\" "
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"--writers.ply.dims=\"{dims}\" "
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"").format(**filterArgs)
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# Input
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pipeline.append(input_point_cloud)
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if 'sample' in filters:
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cmd += "--filters.sample.radius={} ".format(sample_radius)
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if 'outlier' in filters:
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cmd += ("--filters.outlier.method=\"statistical\" "
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"--filters.outlier.mean_k={} "
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"--filters.outlier.multiplier={} ").format(meank, standard_deviation)
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if 'range' in filters:
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# Remove outliers
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cmd += "--filters.range.limits=\"Classification![7:7]\" "
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# Filters
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for f in filters:
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params = {}
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if f == 'sample':
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params = {'radius': sample_radius}
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elif f == 'outlier':
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params = {'method': 'statistical', 'mean_k': meank, 'multiplier': standard_deviation}
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elif f == 'range':
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params = {'limits': 'Classification![7:7]'}
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elif f == 'crop':
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params = {'polygon': as_polygon(boundary)}
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else:
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raise RuntimeError("Invalid filter in PDAL pipeline (this should not have happened, please report it: https://github.com/OpenDroneMap/ODM/issues")
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pipeline.append(dict({
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'type': "filters.%s" % f,
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}, **params))
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system.run(cmd)
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# Output
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pipeline.append({
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'type': 'writers.ply',
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'sized_types': False,
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'storage_mode': 'little endian',
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'dims': dims,
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'filename': output_point_cloud
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})
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run_pipeline(pipeline, verbose=verbose)
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if not os.path.exists(output_point_cloud):
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log.ODM_WARNING("{} not found, filtering has failed.".format(output_point_cloud))
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@ -69,7 +69,7 @@ class ODM_Reconstruction(object):
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return self.georef is not None
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def has_gcp(self):
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return self.is_georeferenced() and self.gcp is not None
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return self.is_georeferenced() and self.gcp is not None and self.gcp.exists()
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def georeference_with_gcp(self, gcp_file, output_coords_file, output_gcp_file, output_model_txt_geo, rerun=False):
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if not io.file_exists(output_coords_file) or not io.file_exists(output_gcp_file) or rerun:
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@ -158,6 +158,12 @@ class ODM_Reconstruction(object):
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def get_proj_srs(self):
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if self.is_georeferenced():
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return self.georef.proj4()
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def get_proj_offset(self):
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if self.is_georeferenced():
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return (self.georef.utm_east_offset, self.georef.utm_north_offset)
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else:
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return (None, None)
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def get_photo(self, filename):
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for p in self.photos:
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@ -9,7 +9,7 @@ from opendm import system
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from opendm.geo import GeoFile
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from shutil import copyfile
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from opendm import progress
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from opendm import boundary
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def save_images_database(photos, database_file):
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with open(database_file, 'w') as f:
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@ -154,3 +154,11 @@ class ODMLoadDatasetStage(types.ODM_Stage):
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reconstruction.save_proj_srs(os.path.join(tree.odm_georeferencing, tree.odm_georeferencing_proj))
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outputs['reconstruction'] = reconstruction
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# Try to load boundaries
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if args.boundary:
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if reconstruction.is_georeferenced():
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outputs['boundary'] = boundary.load_boundary(args.boundary, reconstruction.get_proj_srs())
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else:
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args.boundary = None
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log.ODM_WARNING("Reconstruction is not georeferenced, but boundary file provided (will ignore boundary file)")
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@ -111,14 +111,14 @@ class ODMDEMStage(types.ODM_Stage):
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dem_geotiff_path = os.path.join(odm_dem_root, "{}.tif".format(product))
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bounds_file_path = os.path.join(tree.odm_georeferencing, 'odm_georeferenced_model.bounds.gpkg')
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if args.crop > 0:
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if args.crop > 0 or args.boundary:
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# Crop DEM
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Cropper.crop(bounds_file_path, dem_geotiff_path, utils.get_dem_vars(args), keep_original=not args.optimize_disk_space)
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if args.dem_euclidean_map:
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unfilled_dem_path = io.related_file_path(dem_geotiff_path, postfix=".unfilled")
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if args.crop > 0:
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if args.crop > 0 or args.boundary:
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# Crop unfilled DEM
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Cropper.crop(bounds_file_path, unfilled_dem_path, utils.get_dem_vars(args), keep_original=not args.optimize_disk_space)
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@ -6,6 +6,8 @@ from opendm import system
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from opendm import context
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from opendm import point_cloud
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from opendm import types
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from opendm import gsd
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from opendm.boundary import boundary_offset, compute_boundary_from_shots
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class ODMFilterPoints(types.ODM_Stage):
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def process(self, args, outputs):
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@ -21,12 +23,33 @@ class ODMFilterPoints(types.ODM_Stage):
|
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else:
|
||||
inputPointCloud = tree.openmvs_model
|
||||
|
||||
# Check if we need to compute boundary
|
||||
if args.auto_boundary:
|
||||
if reconstruction.is_georeferenced():
|
||||
if not 'boundary' in outputs:
|
||||
avg_gsd = gsd.opensfm_reconstruction_average_gsd(tree.opensfm_reconstruction)
|
||||
outputs['boundary'] = compute_boundary_from_shots(tree.opensfm_reconstruction, avg_gsd * 20, reconstruction.get_proj_offset()) # 20 is arbitrary
|
||||
if outputs['boundary'] is None:
|
||||
log.ODM_WARNING("Cannot compute boundary from camera shots")
|
||||
else:
|
||||
log.ODM_WARNING("--auto-boundary set but so is --boundary, will use --boundary")
|
||||
else:
|
||||
log.ODM_WARNING("Not a georeferenced reconstruction, will ignore --auto-boundary")
|
||||
|
||||
point_cloud.filter(inputPointCloud, tree.filtered_point_cloud,
|
||||
standard_deviation=args.pc_filter,
|
||||
sample_radius=args.pc_sample,
|
||||
boundary=boundary_offset(outputs.get('boundary'), reconstruction.get_proj_offset()),
|
||||
verbose=args.verbose,
|
||||
max_concurrency=args.max_concurrency)
|
||||
|
||||
# Quick check
|
||||
info = point_cloud.ply_info(tree.filtered_point_cloud)
|
||||
if info["vertex_count"] == 0:
|
||||
extra_msg = ''
|
||||
if 'boundary' in outputs:
|
||||
extra_msg = '. Also, since you used a boundary setting, make sure that the boundary polygon you specified covers the reconstruction area correctly.'
|
||||
raise system.ExitException("Uh oh! We ended up with an empty point cloud. This means that the reconstruction did not succeed. Have you followed best practices for data acquisition? See https://docs.opendronemap.org/flying/%s" % extra_msg)
|
||||
else:
|
||||
log.ODM_WARNING('Found a valid point cloud file in: %s' %
|
||||
tree.filtered_point_cloud)
|
||||
|
|
|
|||
|
|
@ -17,7 +17,7 @@ from opendm.cropper import Cropper
|
|||
from opendm import point_cloud
|
||||
from opendm.multispectral import get_primary_band_name
|
||||
from opendm.osfm import OSFMContext
|
||||
|
||||
from opendm.boundary import as_polygon, export_to_bounds_files
|
||||
|
||||
class ODMGeoreferencingStage(types.ODM_Stage):
|
||||
def process(self, args, outputs):
|
||||
|
|
@ -152,6 +152,14 @@ class ODMGeoreferencingStage(types.ODM_Stage):
|
|||
except:
|
||||
log.ODM_WARNING("Cannot calculate crop bounds! We will skip cropping")
|
||||
args.crop = 0
|
||||
|
||||
if 'boundary' in outputs and args.crop == 0:
|
||||
log.ODM_INFO("Using boundary JSON as cropping area")
|
||||
|
||||
bounds_base, _ = os.path.splitext(tree.odm_georeferencing_model_laz)
|
||||
bounds_json = bounds_base + ".bounds.geojson"
|
||||
bounds_gpkg = bounds_base + ".bounds.gpkg"
|
||||
export_to_bounds_files(outputs['boundary'], reconstruction.get_proj_srs(), bounds_json, bounds_gpkg)
|
||||
else:
|
||||
log.ODM_INFO("Converting point cloud (non-georeferenced)")
|
||||
system.run(cmd + ' ' + ' '.join(stages) + ' ' + ' '.join(params))
|
||||
|
|
|
|||
|
|
@ -152,7 +152,7 @@ class ODMReport(types.ODM_Stage):
|
|||
overlap_color_map = os.path.join(report_assets, "overlap_color_map.txt")
|
||||
|
||||
bounds_file_path = os.path.join(tree.odm_georeferencing, 'odm_georeferenced_model.bounds.gpkg')
|
||||
if args.crop > 0 and os.path.isfile(bounds_file_path):
|
||||
if (args.crop > 0 or args.boundary) and os.path.isfile(bounds_file_path):
|
||||
Cropper.crop(bounds_file_path, diagram_tiff, get_orthophoto_vars(args), keep_original=False)
|
||||
|
||||
system.run("gdaldem color-relief \"{}\" \"{}\" \"{}\" -of PNG -alpha".format(diagram_tiff, overlap_color_map, diagram_png))
|
||||
|
|
|
|||
|
|
@ -105,71 +105,6 @@ class ODMSplitStage(types.ODM_Stage):
|
|||
|
||||
self.update_progress(50)
|
||||
|
||||
# TODO: this is currently not working and needs a champion to fix it
|
||||
# https://community.opendronemap.org/t/filenotfound-error-cameras-json/6047/2
|
||||
|
||||
# resplit_done_file = octx.path('resplit_done.txt')
|
||||
# if not io.file_exists(resplit_done_file) and bool(args.split_multitracks):
|
||||
# submodels = mds.get_submodel_paths()
|
||||
# i = 0
|
||||
# for s in submodels:
|
||||
# template = octx.path("../aligned_submodels/submodel_%04d")
|
||||
# with open(s+"/reconstruction.json", "r") as f:
|
||||
# j = json.load(f)
|
||||
# for k in range(0, len(j)):
|
||||
# v = j[k]
|
||||
# path = template % i
|
||||
|
||||
# #Create the submodel path up to opensfm
|
||||
# os.makedirs(path+"/opensfm")
|
||||
# os.makedirs(path+"/images")
|
||||
|
||||
# #symlinks for common data
|
||||
# images = os.listdir(octx.path("../images"))
|
||||
# for image in images:
|
||||
# os.symlink("../../../images/"+image, path+"/images/"+image)
|
||||
# os.symlink("../../../opensfm/exif", path+"/opensfm/exif")
|
||||
# os.symlink("../../../opensfm/features", path+"/opensfm/features")
|
||||
# os.symlink("../../../opensfm/matches", path+"/opensfm/matches")
|
||||
# os.symlink("../../../opensfm/reference_lla.json", path+"/opensfm/reference_lla.json")
|
||||
# os.symlink("../../../opensfm/camera_models.json", path+"/opensfm/camera_models.json")
|
||||
|
||||
# shutil.copy(s+"/../cameras.json", path+"/cameras.json")
|
||||
|
||||
# shutil.copy(s+"/../images.json", path+"/images.json")
|
||||
|
||||
|
||||
# with open(octx.path("config.yaml")) as f:
|
||||
# doc = yaml.safe_load(f)
|
||||
|
||||
# dmcv = "depthmap_min_consistent_views"
|
||||
# if dmcv in doc:
|
||||
# if len(v["shots"]) < doc[dmcv]:
|
||||
# doc[dmcv] = len(v["shots"])
|
||||
# print("WARNING: Reduced "+dmcv+" to accommodate short track")
|
||||
|
||||
# with open(path+"/opensfm/config.yaml", "w") as f:
|
||||
# yaml.dump(doc, f)
|
||||
|
||||
# #We need the original tracks file for the visualsfm export, since
|
||||
# #there may still be point matches between the tracks
|
||||
# shutil.copy(s+"/tracks.csv", path+"/opensfm/tracks.csv")
|
||||
|
||||
# #Create our new reconstruction file with only the relevant track
|
||||
# with open(path+"/opensfm/reconstruction.json", "w") as o:
|
||||
# json.dump([v], o)
|
||||
|
||||
# #Create image lists
|
||||
# with open(path+"/opensfm/image_list.txt", "w") as o:
|
||||
# o.writelines(list(map(lambda x: "../images/"+x+'\n', v["shots"].keys())))
|
||||
# with open(path+"/img_list.txt", "w") as o:
|
||||
# o.writelines(list(map(lambda x: x+'\n', v["shots"].keys())))
|
||||
|
||||
# i+=1
|
||||
# os.rename(octx.path("../submodels"), octx.path("../unaligned_submodels"))
|
||||
# os.rename(octx.path("../aligned_submodels"), octx.path("../submodels"))
|
||||
# octx.touch(resplit_done_file)
|
||||
|
||||
mds = metadataset.MetaDataSet(tree.opensfm)
|
||||
submodel_paths = [os.path.abspath(p) for p in mds.get_submodel_paths()]
|
||||
|
||||
|
|
@ -332,7 +267,7 @@ class ODMMergeStage(types.ODM_Stage):
|
|||
|
||||
if io.file_exists(dem_file):
|
||||
# Crop
|
||||
if args.crop > 0:
|
||||
if args.crop > 0 or args.boundary:
|
||||
Cropper.crop(merged_bounds_file, dem_file, dem_vars, keep_original=not args.optimize_disk_space)
|
||||
log.ODM_INFO("Created %s" % dem_file)
|
||||
|
||||
|
|
|
|||
Ładowanie…
Reference in New Issue