kopia lustrzana https://github.com/OpenDroneMap/ODM
458 wiersze
19 KiB
Python
458 wiersze
19 KiB
Python
"""
|
|
OpenSfM related utils
|
|
"""
|
|
|
|
import os, shutil, sys, json, argparse
|
|
import yaml
|
|
from opendm import io
|
|
from opendm import log
|
|
from opendm import system
|
|
from opendm import context
|
|
from opendm import camera
|
|
from opensfm.large import metadataset
|
|
from opensfm.large import tools
|
|
from opensfm.commands import undistort
|
|
|
|
class OSFMContext:
|
|
def __init__(self, opensfm_project_path):
|
|
self.opensfm_project_path = opensfm_project_path
|
|
|
|
def run(self, command):
|
|
system.run('/usr/bin/env python3 %s/bin/opensfm %s "%s"' %
|
|
(context.opensfm_path, command, self.opensfm_project_path))
|
|
|
|
def is_reconstruction_done(self):
|
|
tracks_file = os.path.join(self.opensfm_project_path, 'tracks.csv')
|
|
reconstruction_file = os.path.join(self.opensfm_project_path, 'reconstruction.json')
|
|
|
|
return io.file_exists(tracks_file) and io.file_exists(reconstruction_file)
|
|
|
|
def reconstruct(self, rerun=False):
|
|
tracks_file = os.path.join(self.opensfm_project_path, 'tracks.csv')
|
|
reconstruction_file = os.path.join(self.opensfm_project_path, 'reconstruction.json')
|
|
|
|
if not io.file_exists(tracks_file) or rerun:
|
|
self.run('create_tracks')
|
|
else:
|
|
log.ODM_WARNING('Found a valid OpenSfM tracks file in: %s' % tracks_file)
|
|
|
|
if not io.file_exists(reconstruction_file) or rerun:
|
|
self.run('reconstruct')
|
|
else:
|
|
log.ODM_WARNING('Found a valid OpenSfM reconstruction file in: %s' % reconstruction_file)
|
|
|
|
# Check that a reconstruction file has been created
|
|
if not self.reconstructed():
|
|
log.ODM_ERROR("The program could not process this dataset using the current settings. "
|
|
"Check that the images have enough overlap, "
|
|
"that there are enough recognizable features "
|
|
"and that the images are in focus. "
|
|
"You could also try to increase the --min-num-features parameter."
|
|
"The program will now exit.")
|
|
exit(1)
|
|
|
|
|
|
def setup(self, args, images_path, photos, reconstruction, append_config = [], rerun=False):
|
|
"""
|
|
Setup a OpenSfM project
|
|
"""
|
|
if rerun and io.dir_exists(self.opensfm_project_path):
|
|
shutil.rmtree(self.opensfm_project_path)
|
|
|
|
if not io.dir_exists(self.opensfm_project_path):
|
|
system.mkdir_p(self.opensfm_project_path)
|
|
|
|
list_path = io.join_paths(self.opensfm_project_path, 'image_list.txt')
|
|
if not io.file_exists(list_path) or rerun:
|
|
|
|
# create file list
|
|
has_alt = True
|
|
has_gps = False
|
|
with open(list_path, 'w') as fout:
|
|
for photo in photos:
|
|
if not photo.altitude:
|
|
has_alt = False
|
|
if photo.latitude is not None and photo.longitude is not None:
|
|
has_gps = True
|
|
fout.write('%s\n' % io.join_paths(images_path, photo.filename))
|
|
|
|
# check for image_groups.txt (split-merge)
|
|
image_groups_file = os.path.join(args.project_path, "image_groups.txt")
|
|
if io.file_exists(image_groups_file):
|
|
log.ODM_INFO("Copied image_groups.txt to OpenSfM directory")
|
|
io.copy(image_groups_file, os.path.join(self.opensfm_project_path, "image_groups.txt"))
|
|
|
|
# check for cameras
|
|
if args.cameras:
|
|
try:
|
|
camera_overrides = camera.get_opensfm_camera_models(args.cameras)
|
|
with open(os.path.join(self.opensfm_project_path, "camera_models_overrides.json"), 'w') as f:
|
|
f.write(json.dumps(camera_overrides))
|
|
log.ODM_INFO("Wrote camera_models_overrides.json to OpenSfM directory")
|
|
except Exception as e:
|
|
log.ODM_WARNING("Cannot set camera_models_overrides.json: %s" % str(e))
|
|
|
|
use_bow = False
|
|
feature_type = "SIFT"
|
|
|
|
matcher_neighbors = args.matcher_neighbors
|
|
if matcher_neighbors != 0 and reconstruction.multi_camera is not None:
|
|
matcher_neighbors *= len(reconstruction.multi_camera)
|
|
log.ODM_INFO("Increasing matcher neighbors to %s to accomodate multi-camera setup" % matcher_neighbors)
|
|
log.ODM_INFO("Multi-camera setup, using BOW matching")
|
|
use_bow = True
|
|
|
|
# GPSDOP override if we have GPS accuracy information (such as RTK)
|
|
override_gps_dop = 'gps_accuracy_is_set' in args
|
|
for p in photos:
|
|
if p.get_gps_dop() is not None:
|
|
override_gps_dop = True
|
|
break
|
|
|
|
if override_gps_dop:
|
|
if 'gps_accuracy_is_set' in args:
|
|
log.ODM_INFO("Forcing GPS DOP to %s for all images" % args.gps_accuracy)
|
|
else:
|
|
log.ODM_INFO("Looks like we have RTK accuracy info for some photos. Good! We'll use it.")
|
|
|
|
exif_overrides = {}
|
|
for p in photos:
|
|
dop = args.gps_accuracy if 'gps_accuracy_is_set' in args else p.get_gps_dop()
|
|
if dop is not None and p.latitude is not None and p.longitude is not None:
|
|
exif_overrides[p.filename] = {
|
|
'gps': {
|
|
'latitude': p.latitude,
|
|
'longitude': p.longitude,
|
|
'altitude': p.altitude if p.altitude is not None else 0,
|
|
'dop': dop,
|
|
}
|
|
}
|
|
|
|
with open(os.path.join(self.opensfm_project_path, "exif_overrides.json"), 'w') as f:
|
|
f.write(json.dumps(exif_overrides))
|
|
|
|
# create config file for OpenSfM
|
|
config = [
|
|
"use_exif_size: no",
|
|
"flann_algorithm: KDTREE", # more stable, faster than KMEANS
|
|
"feature_process_size: %s" % args.resize_to,
|
|
"feature_min_frames: %s" % args.min_num_features,
|
|
"processes: %s" % args.max_concurrency,
|
|
"matching_gps_neighbors: %s" % matcher_neighbors,
|
|
"matching_gps_distance: %s" % args.matcher_distance,
|
|
"depthmap_method: %s" % args.opensfm_depthmap_method,
|
|
"depthmap_resolution: %s" % args.depthmap_resolution,
|
|
"depthmap_min_patch_sd: %s" % args.opensfm_depthmap_min_patch_sd,
|
|
"depthmap_min_consistent_views: %s" % args.opensfm_depthmap_min_consistent_views,
|
|
"optimize_camera_parameters: %s" % ('no' if args.use_fixed_camera_params or args.cameras else 'yes'),
|
|
"undistorted_image_format: tif",
|
|
"bundle_outlier_filtering_type: AUTO",
|
|
"align_orientation_prior: vertical",
|
|
"triangulation_type: ROBUST",
|
|
"bundle_common_position_constraints: %s" % ('no' if reconstruction.multi_camera is None else 'yes'),
|
|
]
|
|
|
|
if args.camera_lens != 'auto':
|
|
config.append("camera_projection_type: %s" % args.camera_lens.upper())
|
|
|
|
if not has_gps:
|
|
log.ODM_INFO("No GPS information, using BOW matching")
|
|
use_bow = True
|
|
|
|
feature_type = args.feature_type.upper()
|
|
|
|
if use_bow:
|
|
config.append("matcher_type: WORDS")
|
|
|
|
# Cannot use SIFT with BOW
|
|
if feature_type == "SIFT":
|
|
log.ODM_WARNING("Using BOW matching, will use HAHOG feature type, not SIFT")
|
|
feature_type = "HAHOG"
|
|
|
|
config.append("feature_type: %s" % feature_type)
|
|
|
|
if has_alt:
|
|
log.ODM_INFO("Altitude data detected, enabling it for GPS alignment")
|
|
config.append("use_altitude_tag: yes")
|
|
|
|
gcp_path = reconstruction.gcp.gcp_path
|
|
if has_alt or gcp_path:
|
|
config.append("align_method: auto")
|
|
else:
|
|
config.append("align_method: orientation_prior")
|
|
|
|
if args.use_hybrid_bundle_adjustment:
|
|
log.ODM_INFO("Enabling hybrid bundle adjustment")
|
|
config.append("bundle_interval: 100") # Bundle after adding 'bundle_interval' cameras
|
|
config.append("bundle_new_points_ratio: 1.2") # Bundle when (new points) / (bundled points) > bundle_new_points_ratio
|
|
config.append("local_bundle_radius: 1") # Max image graph distance for images to be included in local bundle adjustment
|
|
else:
|
|
config.append("local_bundle_radius: 0")
|
|
|
|
if gcp_path:
|
|
config.append("bundle_use_gcp: yes")
|
|
if not args.force_gps:
|
|
config.append("bundle_use_gps: no")
|
|
io.copy(gcp_path, self.path("gcp_list.txt"))
|
|
|
|
config = config + append_config
|
|
|
|
# write config file
|
|
log.ODM_INFO(config)
|
|
config_filename = self.get_config_file_path()
|
|
with open(config_filename, 'w') as fout:
|
|
fout.write("\n".join(config))
|
|
else:
|
|
log.ODM_WARNING("%s already exists, not rerunning OpenSfM setup" % list_path)
|
|
|
|
def get_config_file_path(self):
|
|
return io.join_paths(self.opensfm_project_path, 'config.yaml')
|
|
|
|
def reconstructed(self):
|
|
if not io.file_exists(self.path("reconstruction.json")):
|
|
return False
|
|
|
|
with open(self.path("reconstruction.json"), 'r') as f:
|
|
return f.readline().strip() != "[]"
|
|
|
|
def extract_metadata(self, rerun=False):
|
|
metadata_dir = self.path("exif")
|
|
if not io.dir_exists(metadata_dir) or rerun:
|
|
self.run('extract_metadata')
|
|
|
|
def is_feature_matching_done(self):
|
|
features_dir = self.path("features")
|
|
matches_dir = self.path("matches")
|
|
|
|
return io.dir_exists(features_dir) and io.dir_exists(matches_dir)
|
|
|
|
def feature_matching(self, rerun=False):
|
|
features_dir = self.path("features")
|
|
matches_dir = self.path("matches")
|
|
|
|
if not io.dir_exists(features_dir) or rerun:
|
|
self.run('detect_features')
|
|
else:
|
|
log.ODM_WARNING('Detect features already done: %s exists' % features_dir)
|
|
|
|
if not io.dir_exists(matches_dir) or rerun:
|
|
self.run('match_features')
|
|
else:
|
|
log.ODM_WARNING('Match features already done: %s exists' % matches_dir)
|
|
|
|
def align_reconstructions(self, rerun):
|
|
alignment_file = self.path('alignment_done.txt')
|
|
if not io.file_exists(alignment_file) or rerun:
|
|
log.ODM_INFO("Aligning submodels...")
|
|
meta_data = metadataset.MetaDataSet(self.opensfm_project_path)
|
|
reconstruction_shots = tools.load_reconstruction_shots(meta_data)
|
|
transformations = tools.align_reconstructions(reconstruction_shots,
|
|
tools.partial_reconstruction_name,
|
|
True)
|
|
tools.apply_transformations(transformations)
|
|
|
|
self.touch(alignment_file)
|
|
else:
|
|
log.ODM_WARNING('Found a alignment done progress file in: %s' % alignment_file)
|
|
|
|
def touch(self, file):
|
|
with open(file, 'w') as fout:
|
|
fout.write("Done!\n")
|
|
|
|
def path(self, *paths):
|
|
return os.path.join(self.opensfm_project_path, *paths)
|
|
|
|
def extract_cameras(self, output, rerun=False):
|
|
if not os.path.exists(output) or rerun:
|
|
try:
|
|
reconstruction_file = self.path("reconstruction.json")
|
|
with open(output, 'w') as fout:
|
|
fout.write(json.dumps(camera.get_cameras_from_opensfm(reconstruction_file), indent=4))
|
|
except Exception as e:
|
|
log.ODM_WARNING("Cannot export cameras to %s. %s." % (output, str(e)))
|
|
else:
|
|
log.ODM_INFO("Already extracted cameras")
|
|
|
|
def convert_and_undistort(self, rerun=False, imageFilter=None):
|
|
log.ODM_INFO("Undistorting %s ..." % self.opensfm_project_path)
|
|
undistorted_images_path = self.path("undistorted", "images")
|
|
|
|
if not io.dir_exists(undistorted_images_path) or rerun:
|
|
cmd = undistort.Command(imageFilter)
|
|
parser = argparse.ArgumentParser()
|
|
cmd.add_arguments(parser)
|
|
cmd.run(parser.parse_args([self.opensfm_project_path]))
|
|
else:
|
|
log.ODM_WARNING("Found an undistorted directory in %s" % undistorted_images_path)
|
|
|
|
|
|
def update_config(self, cfg_dict):
|
|
cfg_file = self.get_config_file_path()
|
|
log.ODM_INFO("Updating %s" % cfg_file)
|
|
if os.path.exists(cfg_file):
|
|
try:
|
|
with open(cfg_file) as fin:
|
|
cfg = yaml.safe_load(fin)
|
|
for k, v in cfg_dict.items():
|
|
cfg[k] = v
|
|
log.ODM_INFO("%s: %s" % (k, v))
|
|
with open(cfg_file, 'w') as fout:
|
|
fout.write(yaml.dump(cfg, default_flow_style=False))
|
|
except Exception as e:
|
|
log.ODM_WARNING("Cannot update configuration file %s: %s" % (cfg_file, str(e)))
|
|
else:
|
|
log.ODM_WARNING("Tried to update configuration, but %s does not exist." % cfg_file)
|
|
|
|
def name(self):
|
|
return os.path.basename(os.path.abspath(self.path("..")))
|
|
|
|
def get_submodel_argv(args, submodels_path = None, submodel_name = None):
|
|
"""
|
|
Gets argv for a submodel starting from the args passed to the application startup.
|
|
Additionally, if project_name, submodels_path and submodel_name are passed, the function
|
|
handles the <project name> value and --project-path detection / override.
|
|
When all arguments are set to None, --project-path and project name are always removed.
|
|
|
|
:return the same as argv, but removing references to --split,
|
|
setting/replacing --project-path and name
|
|
removing --rerun-from, --rerun, --rerun-all, --sm-cluster
|
|
removing --pc-las, --pc-csv, --pc-ept flags (processing these is wasteful)
|
|
adding --orthophoto-cutline
|
|
adding --dem-euclidean-map
|
|
adding --skip-3dmodel (split-merge does not support 3D model merging)
|
|
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.)
|
|
removing --gcp (the GCP path if specified is always "gcp_list.txt")
|
|
reading the contents of --cameras
|
|
"""
|
|
assure_always = ['orthophoto_cutline', 'dem_euclidean_map', 'skip_3dmodel']
|
|
remove_always = ['split', 'split_overlap', 'rerun_from', 'rerun', 'gcp', 'end_with', 'sm_cluster', 'rerun_all', 'pc_csv', 'pc_las', 'pc_ept']
|
|
read_json_always = ['cameras']
|
|
|
|
argv = sys.argv
|
|
result = [argv[0]] # Startup script (/path/to/run.py)
|
|
|
|
args_dict = vars(args).copy()
|
|
set_keys = [k[:-len("_is_set")] for k in args_dict.keys() if k.endswith("_is_set")]
|
|
|
|
# Handle project name and project path (special case)
|
|
if "name" in set_keys:
|
|
del args_dict["name"]
|
|
set_keys.remove("name")
|
|
|
|
if "project_path" in set_keys:
|
|
del args_dict["project_path"]
|
|
set_keys.remove("project_path")
|
|
|
|
# Remove parameters
|
|
set_keys = [k for k in set_keys if k not in remove_always]
|
|
|
|
# Assure parameters
|
|
for k in assure_always:
|
|
if not k in set_keys:
|
|
set_keys.append(k)
|
|
args_dict[k] = True
|
|
|
|
# Read JSON always
|
|
for k in read_json_always:
|
|
if k in set_keys:
|
|
try:
|
|
if isinstance(args_dict[k], str):
|
|
args_dict[k] = io.path_or_json_string_to_dict(args_dict[k])
|
|
if isinstance(args_dict[k], dict):
|
|
args_dict[k] = json.dumps(args_dict[k])
|
|
except ValueError as e:
|
|
log.ODM_WARNING("Cannot parse/read JSON: {}".format(str(e)))
|
|
|
|
# Handle crop (cannot be zero for split/merge)
|
|
if "crop" in set_keys:
|
|
crop_value = float(args_dict["crop"])
|
|
if crop_value == 0:
|
|
crop_value = 0.015625
|
|
args_dict["crop"] = crop_value
|
|
|
|
# Populate result
|
|
for k in set_keys:
|
|
result.append("--%s" % k.replace("_", "-"))
|
|
|
|
# No second value for booleans
|
|
if isinstance(args_dict[k], bool) and args_dict[k] == True:
|
|
continue
|
|
|
|
result.append(str(args_dict[k]))
|
|
|
|
if submodels_path:
|
|
result.append("--project-path")
|
|
result.append(submodels_path)
|
|
|
|
if submodel_name:
|
|
result.append(submodel_name)
|
|
|
|
return result
|
|
|
|
def get_submodel_args_dict(args):
|
|
submodel_argv = get_submodel_argv(args)
|
|
result = {}
|
|
|
|
i = 0
|
|
while i < len(submodel_argv):
|
|
arg = submodel_argv[i]
|
|
next_arg = None if i == len(submodel_argv) - 1 else submodel_argv[i + 1]
|
|
|
|
if next_arg and arg.startswith("--"):
|
|
if next_arg.startswith("--"):
|
|
result[arg[2:]] = True
|
|
else:
|
|
result[arg[2:]] = next_arg
|
|
i += 1
|
|
elif arg.startswith("--"):
|
|
result[arg[2:]] = True
|
|
i += 1
|
|
|
|
return result
|
|
|
|
|
|
def get_submodel_paths(submodels_path, *paths):
|
|
"""
|
|
:return Existing paths for all submodels
|
|
"""
|
|
result = []
|
|
if not os.path.exists(submodels_path):
|
|
return result
|
|
|
|
for f in os.listdir(submodels_path):
|
|
if f.startswith('submodel'):
|
|
p = os.path.join(submodels_path, f, *paths)
|
|
if os.path.exists(p):
|
|
result.append(p)
|
|
else:
|
|
log.ODM_WARNING("Missing %s from submodel %s" % (p, f))
|
|
|
|
return result
|
|
|
|
def get_all_submodel_paths(submodels_path, *all_paths):
|
|
"""
|
|
:return Existing, multiple paths for all submodels as a nested list (all or nothing for each submodel)
|
|
if a single file is missing from the submodule, no files are returned for that submodel.
|
|
|
|
(i.e. get_multi_submodel_paths("path/", "odm_orthophoto.tif", "dem.tif")) -->
|
|
[["path/submodel_0000/odm_orthophoto.tif", "path/submodel_0000/dem.tif"],
|
|
["path/submodel_0001/odm_orthophoto.tif", "path/submodel_0001/dem.tif"]]
|
|
"""
|
|
result = []
|
|
if not os.path.exists(submodels_path):
|
|
return result
|
|
|
|
for f in os.listdir(submodels_path):
|
|
if f.startswith('submodel'):
|
|
all_found = True
|
|
|
|
for ap in all_paths:
|
|
p = os.path.join(submodels_path, f, ap)
|
|
if not os.path.exists(p):
|
|
log.ODM_WARNING("Missing %s from submodel %s" % (p, f))
|
|
all_found = False
|
|
|
|
if all_found:
|
|
result.append([os.path.join(submodels_path, f, ap) for ap in all_paths])
|
|
|
|
return result |