def process(self, args, outputs):
tree = outputs['tree']
reconstruction = outputs['reconstruction']
photos = reconstruction.photos
if not photos:
log.ODM_ERROR('Not enough photos in photos array to start OpenSfM')
exit(1)
octx = OSFMContext(tree.opensfm)
octx.setup(args,
tree.dataset_raw,
photos,
reconstruction=reconstruction,
rerun=self.rerun())
octx.extract_metadata(self.rerun())
self.update_progress(20)
octx.feature_matching(self.rerun())
self.update_progress(30)
octx.reconstruct(self.rerun())
octx.extract_cameras(tree.path("cameras.json"), self.rerun())
self.update_progress(70)
if args.optimize_disk_space:
for folder in ["features", "matches", "exif", "reports"]:
folder_path = octx.path(folder)
if os.path.islink(folder_path):
os.unlink(folder_path)
else:
shutil.rmtree(folder_path)
# If we find a special flag file for split/merge we stop right here
if os.path.exists(octx.path("split_merge_stop_at_reconstruction.txt")):
log.ODM_INFO("Stopping OpenSfM early because we found: %s" %
octx.path("split_merge_stop_at_reconstruction.txt"))
self.next_stage = None
return
if args.fast_orthophoto:
output_file = octx.path('reconstruction.ply')
elif args.use_opensfm_dense:
output_file = tree.opensfm_model
else:
output_file = tree.opensfm_reconstruction
updated_config_flag_file = octx.path('updated_config.txt')
# Make sure it's capped by the depthmap-resolution arg,
# since the undistorted images are used for MVS
outputs['undist_image_max_size'] = max(
gsd.image_max_size(photos,
args.orthophoto_resolution,
tree.opensfm_reconstruction,
ignore_gsd=args.ignore_gsd,
has_gcp=reconstruction.has_gcp()),
args.depthmap_resolution)
if not io.file_exists(updated_config_flag_file) or self.rerun():
octx.update_config({
'undistorted_image_max_size':
outputs['undist_image_max_size']
})
octx.touch(updated_config_flag_file)
# These will be used for texturing / MVS
if args.radiometric_calibration == "none":
octx.convert_and_undistort(self.rerun())
else:
def radiometric_calibrate(shot_id, image):
photo = reconstruction.get_photo(shot_id)
return multispectral.dn_to_reflectance(
photo,
image,
use_sun_sensor=args.radiometric_calibration ==
"camera+sun")
octx.convert_and_undistort(self.rerun(), radiometric_calibrate)
self.update_progress(80)
if reconstruction.multi_camera:
# Dump band image lists
log.ODM_INFO("Multiple bands found")
for band in reconstruction.multi_camera:
log.ODM_INFO("Exporting %s band" % band['name'])
image_list_file = octx.path("image_list_%s.txt" %
band['name'].lower())
if not io.file_exists(image_list_file) or self.rerun():
with open(image_list_file, "w") as f:
f.write("\n".join([p.filename
for p in band['photos']]))
log.ODM_INFO("Wrote %s" % image_list_file)
else:
log.ODM_WARNING(
"Found a valid image list in %s for %s band" %
(image_list_file, band['name']))
nvm_file = octx.path(
"undistorted",
"reconstruction_%s.nvm" % band['name'].lower())
if not io.file_exists(nvm_file) or self.rerun():
octx.run('export_visualsfm --points --image_list "%s"' %
image_list_file)
os.rename(tree.opensfm_reconstruction_nvm, nvm_file)
else:
log.ODM_WARNING(
"Found a valid NVM file in %s for %s band" %
(nvm_file, band['name']))
if not io.file_exists(tree.opensfm_reconstruction_nvm) or self.rerun():
octx.run('export_visualsfm --points')
else:
log.ODM_WARNING(
'Found a valid OpenSfM NVM reconstruction file in: %s' %
tree.opensfm_reconstruction_nvm)
self.update_progress(85)
# Skip dense reconstruction if necessary and export
# sparse reconstruction instead
if args.fast_orthophoto:
if not io.file_exists(output_file) or self.rerun():
octx.run('export_ply --no-cameras')
else:
log.ODM_WARNING("Found a valid PLY reconstruction in %s" %
output_file)
elif args.use_opensfm_dense:
if not io.file_exists(output_file) or self.rerun():
octx.run('compute_depthmaps')
else:
log.ODM_WARNING("Found a valid dense reconstruction in %s" %
output_file)
self.update_progress(90)
if reconstruction.is_georeferenced() and (not io.file_exists(
tree.opensfm_transformation) or self.rerun()):
octx.run('export_geocoords --transformation --proj \'%s\'' %
reconstruction.georef.proj4())
else:
log.ODM_WARNING("Will skip exporting %s" %
tree.opensfm_transformation)
if args.optimize_disk_space:
os.remove(octx.path("tracks.csv"))
os.remove(octx.path("undistorted", "tracks.csv"))
os.remove(octx.path("undistorted", "reconstruction.json"))
if io.dir_exists(octx.path("undistorted", "depthmaps")):
files = glob.glob(
octx.path("undistorted", "depthmaps", "*.npz"))
for f in files:
os.remove(f)
def process(self, args, outputs):
tree = outputs['tree']
reconstruction = outputs['reconstruction']
photos = reconstruction.photos
if not photos:
raise system.ExitException(
'Not enough photos in photos array to start OpenSfM')
octx = OSFMContext(tree.opensfm)
octx.setup(args,
tree.dataset_raw,
reconstruction=reconstruction,
rerun=self.rerun())
octx.photos_to_metadata(photos, self.rerun())
self.update_progress(20)
octx.feature_matching(self.rerun())
self.update_progress(30)
octx.reconstruct(self.rerun())
octx.extract_cameras(tree.path("cameras.json"), self.rerun())
self.update_progress(70)
def cleanup_disk_space():
if args.optimize_disk_space:
for folder in ["features", "matches", "reports"]:
folder_path = octx.path(folder)
if os.path.exists(folder_path):
if os.path.islink(folder_path):
os.unlink(folder_path)
else:
shutil.rmtree(folder_path)
# If we find a special flag file for split/merge we stop right here
if os.path.exists(octx.path("split_merge_stop_at_reconstruction.txt")):
log.ODM_INFO("Stopping OpenSfM early because we found: %s" %
octx.path("split_merge_stop_at_reconstruction.txt"))
self.next_stage = None
cleanup_disk_space()
return
# Stats are computed in the local CRS (before geoprojection)
if not args.skip_report:
# TODO: this will fail to compute proper statistics if
# the pipeline is run with --skip-report and is subsequently
# rerun without --skip-report a --rerun-* parameter (due to the reconstruction.json file)
# being replaced below. It's an isolated use case.
octx.export_stats(self.rerun())
self.update_progress(75)
# We now switch to a geographic CRS
if reconstruction.is_georeferenced() and (not io.file_exists(
tree.opensfm_topocentric_reconstruction) or self.rerun()):
octx.run(
'export_geocoords --reconstruction --proj "%s" --offset-x %s --offset-y %s'
% (reconstruction.georef.proj4(),
reconstruction.georef.utm_east_offset,
reconstruction.georef.utm_north_offset))
shutil.move(tree.opensfm_reconstruction,
tree.opensfm_topocentric_reconstruction)
shutil.move(tree.opensfm_geocoords_reconstruction,
tree.opensfm_reconstruction)
else:
log.ODM_WARNING("Will skip exporting %s" %
tree.opensfm_geocoords_reconstruction)
self.update_progress(80)
updated_config_flag_file = octx.path('updated_config.txt')
# Make sure it's capped by the depthmap-resolution arg,
# since the undistorted images are used for MVS
outputs['undist_image_max_size'] = max(
gsd.image_max_size(photos,
args.orthophoto_resolution,
tree.opensfm_reconstruction,
ignore_gsd=args.ignore_gsd,
has_gcp=reconstruction.has_gcp()),
get_depthmap_resolution(args, photos))
if not io.file_exists(updated_config_flag_file) or self.rerun():
octx.update_config({
'undistorted_image_max_size':
outputs['undist_image_max_size']
})
octx.touch(updated_config_flag_file)
# Undistorted images will be used for texturing / MVS
alignment_info = None
primary_band_name = None
largest_photo = None
undistort_pipeline = []
def undistort_callback(shot_id, image):
for func in undistort_pipeline:
image = func(shot_id, image)
return image
def resize_thermal_images(shot_id, image):
photo = reconstruction.get_photo(shot_id)
if photo.is_thermal():
return thermal.resize_to_match(image, largest_photo)
else:
return image
def radiometric_calibrate(shot_id, image):
photo = reconstruction.get_photo(shot_id)
if photo.is_thermal():
return thermal.dn_to_temperature(photo, image,
tree.dataset_raw)
else:
return multispectral.dn_to_reflectance(
photo,
image,
use_sun_sensor=args.radiometric_calibration ==
"camera+sun")
def align_to_primary_band(shot_id, image):
photo = reconstruction.get_photo(shot_id)
# No need to align if requested by user
if args.skip_band_alignment:
return image
# No need to align primary
if photo.band_name == primary_band_name:
return image
ainfo = alignment_info.get(photo.band_name)
if ainfo is not None:
return multispectral.align_image(image, ainfo['warp_matrix'],
ainfo['dimension'])
else:
log.ODM_WARNING(
"Cannot align %s, no alignment matrix could be computed. Band alignment quality might be affected."
% (shot_id))
return image
if reconstruction.multi_camera:
largest_photo = find_largest_photo(photos)
undistort_pipeline.append(resize_thermal_images)
if args.radiometric_calibration != "none":
undistort_pipeline.append(radiometric_calibrate)
image_list_override = None
if reconstruction.multi_camera:
# Undistort only secondary bands
image_list_override = [
os.path.join(tree.dataset_raw, p.filename) for p in photos
] # if p.band_name.lower() != primary_band_name.lower()
# We backup the original reconstruction.json, tracks.csv
# then we augment them by duplicating the primary band
# camera shots with each band, so that exports, undistortion,
# etc. include all bands
# We finally restore the original files later
added_shots_file = octx.path('added_shots_done.txt')
s2p, p2s = None, None
if not io.file_exists(added_shots_file) or self.rerun():
primary_band_name = multispectral.get_primary_band_name(
reconstruction.multi_camera, args.primary_band)
s2p, p2s = multispectral.compute_band_maps(
reconstruction.multi_camera, primary_band_name)
if not args.skip_band_alignment:
alignment_info = multispectral.compute_alignment_matrices(
reconstruction.multi_camera,
primary_band_name,
tree.dataset_raw,
s2p,
p2s,
max_concurrency=args.max_concurrency)
else:
log.ODM_WARNING("Skipping band alignment")
alignment_info = {}
log.ODM_INFO("Adding shots to reconstruction")
octx.backup_reconstruction()
octx.add_shots_to_reconstruction(p2s)
octx.touch(added_shots_file)
undistort_pipeline.append(align_to_primary_band)
octx.convert_and_undistort(self.rerun(), undistort_callback,
image_list_override)
self.update_progress(95)
if reconstruction.multi_camera:
octx.restore_reconstruction_backup()
# Undistort primary band and write undistorted
# reconstruction.json, tracks.csv
octx.convert_and_undistort(self.rerun(),
undistort_callback,
runId='primary')
if not io.file_exists(tree.opensfm_reconstruction_nvm) or self.rerun():
octx.run('export_visualsfm --points')
else:
log.ODM_WARNING(
'Found a valid OpenSfM NVM reconstruction file in: %s' %
tree.opensfm_reconstruction_nvm)
if reconstruction.multi_camera:
log.ODM_INFO("Multiple bands found")
# Write NVM files for the various bands
for band in reconstruction.multi_camera:
nvm_file = octx.path(
"undistorted",
"reconstruction_%s.nvm" % band['name'].lower())
if not io.file_exists(nvm_file) or self.rerun():
img_map = {}
if primary_band_name is None:
primary_band_name = multispectral.get_primary_band_name(
reconstruction.multi_camera, args.primary_band)
if p2s is None:
s2p, p2s = multispectral.compute_band_maps(
reconstruction.multi_camera, primary_band_name)
for fname in p2s:
# Primary band maps to itself
if band['name'] == primary_band_name:
img_map[add_image_format_extension(
fname, 'tif')] = add_image_format_extension(
fname, 'tif')
else:
band_filename = next(
(p.filename for p in p2s[fname]
if p.band_name == band['name']), None)
if band_filename is not None:
img_map[add_image_format_extension(
fname,
'tif')] = add_image_format_extension(
band_filename, 'tif')
else:
log.ODM_WARNING(
"Cannot find %s band equivalent for %s" %
(band, fname))
nvm.replace_nvm_images(tree.opensfm_reconstruction_nvm,
img_map, nvm_file)
else:
log.ODM_WARNING("Found existing NVM file %s" % nvm_file)
# Skip dense reconstruction if necessary and export
# sparse reconstruction instead
if args.fast_orthophoto:
output_file = octx.path('reconstruction.ply')
if not io.file_exists(output_file) or self.rerun():
octx.run('export_ply --no-cameras --point-num-views')
else:
log.ODM_WARNING("Found a valid PLY reconstruction in %s" %
output_file)
cleanup_disk_space()
if args.optimize_disk_space:
os.remove(octx.path("tracks.csv"))
if io.file_exists(octx.recon_backup_file()):
os.remove(octx.recon_backup_file())
if io.dir_exists(octx.path("undistorted", "depthmaps")):
files = glob.glob(
octx.path("undistorted", "depthmaps", "*.npz"))
for f in files:
os.remove(f)
# Keep these if using OpenMVS
if args.fast_orthophoto:
files = [
octx.path("undistorted", "tracks.csv"),
octx.path("undistorted", "reconstruction.json")
]
for f in files:
if os.path.exists(f):
os.remove(f)
def process(self, args, outputs):
tree = outputs['tree']
reconstruction = outputs['reconstruction']
photos = reconstruction.photos
if not photos:
log.ODM_ERROR('Not enough photos in photos array to start OpenSfM')
exit(1)
octx = OSFMContext(tree.opensfm)
octx.setup(args,
tree.dataset_raw,
photos,
gcp_path=reconstruction.gcp.gcp_path,
rerun=self.rerun())
octx.extract_metadata(self.rerun())
self.update_progress(20)
octx.feature_matching(self.rerun())
self.update_progress(30)
octx.reconstruct(self.rerun())
octx.extract_cameras(tree.path("cameras.json"), self.rerun())
self.update_progress(70)
# If we find a special flag file for split/merge we stop right here
if os.path.exists(octx.path("split_merge_stop_at_reconstruction.txt")):
log.ODM_INFO("Stopping OpenSfM early because we found: %s" %
octx.path("split_merge_stop_at_reconstruction.txt"))
self.next_stage = None
return
if args.fast_orthophoto:
output_file = octx.path('reconstruction.ply')
elif args.use_opensfm_dense:
output_file = tree.opensfm_model
else:
output_file = tree.opensfm_reconstruction
updated_config_flag_file = octx.path('updated_config.txt')
if not io.file_exists(updated_config_flag_file) or self.rerun():
octx.update_config({
'undistorted_image_max_size':
gsd.image_max_size(photos,
args.orthophoto_resolution,
tree.opensfm_reconstruction,
ignore_gsd=args.ignore_gsd)
})
octx.touch(updated_config_flag_file)
# These will be used for texturing
undistorted_images_path = octx.path("undistorted")
if not io.dir_exists(undistorted_images_path) or self.rerun():
octx.run('undistort')
else:
log.ODM_WARNING("Found an undistorted directory in %s" %
undistorted_images_path)
self.update_progress(80)
if not io.file_exists(tree.opensfm_reconstruction_nvm) or self.rerun():
octx.run('export_visualsfm --undistorted')
else:
log.ODM_WARNING(
'Found a valid OpenSfM NVM reconstruction file in: %s' %
tree.opensfm_reconstruction_nvm)
self.update_progress(85)
# Skip dense reconstruction if necessary and export
# sparse reconstruction instead
if args.fast_orthophoto:
if not io.file_exists(output_file) or self.rerun():
octx.run('export_ply --no-cameras')
else:
log.ODM_WARNING("Found a valid PLY reconstruction in %s" %
output_file)
elif args.use_opensfm_dense:
if not io.file_exists(output_file) or self.rerun():
octx.run('compute_depthmaps')
else:
log.ODM_WARNING("Found a valid dense reconstruction in %s" %
output_file)
# check if reconstruction was exported to bundler before
octx.export_bundler(tree.opensfm_bundle_list, self.rerun())
self.update_progress(90)
if reconstruction.is_georeferenced() and (not io.file_exists(
tree.opensfm_transformation) or self.rerun()):
octx.run('export_geocoords --transformation --proj \'%s\'' %
reconstruction.georef.proj4())
else:
log.ODM_WARNING("Will skip exporting %s" %
tree.opensfm_transformation)
