def georeference_with_gps(self,
images_path,
output_coords_file,
output_model_txt_geo,
rerun=False):
try:
if not io.file_exists(output_coords_file) or rerun:
location.extract_utm_coords(self.photos, images_path,
output_coords_file)
else:
log.ODM_INFO("Coordinates file already exist: %s" %
output_coords_file)
# Deprecated: This is mostly for backward compatibility and should be
# be removed at some point
if not io.file_exists(output_model_txt_geo) or rerun:
with open(output_coords_file, 'r') as f:
with open(output_model_txt_geo, 'w+') as w:
w.write(f.readline()) # CRS
w.write(f.readline()) # Offset
else:
log.ODM_INFO("Model geo file already exist: %s" %
output_model_txt_geo)
self.georef = ODM_GeoRef.FromCoordsFile(output_coords_file)
except:
log.ODM_WARNING(
'Could not generate coordinates file. The orthophoto will not be georeferenced.'
)
self.gcp = GCPFile(None)
return self.georef
def georeference_with_gps(self, images_path, output_coords_file, rerun=False):
try:
if not io.file_exists(output_coords_file) or rerun:
location.extract_utm_coords(self.photos, images_path, output_coords_file)
else:
log.ODM_INFO("Coordinates file already exist: %s" % output_coords_file)
self.georef = ODM_GeoRef.FromCoordsFile(output_coords_file)
except:
log.ODM_WARNING('Could not generate coordinates file. The orthophoto will not be georeferenced.')
self.gcp = GCPFile(None)
return self.georef
def process(self, args, outputs):
# Load tree
tree = types.ODM_Tree(args.project_path, args.images, args.gcp)
outputs['tree'] = tree
if args.time and io.file_exists(tree.benchmarking):
# Delete the previously made file
os.remove(tree.benchmarking)
with open(tree.benchmarking, 'a') as b:
b.write(
'ODM Benchmarking file created %s\nNumber of Cores: %s\n\n'
% (system.now(), context.num_cores))
# check if the extension is supported
def supported_extension(file_name):
(pathfn, ext) = os.path.splitext(file_name)
return ext.lower() in context.supported_extensions
# Get supported images from dir
def get_images(in_dir):
# filter images for its extension type
log.ODM_DEBUG(in_dir)
return [
f for f in io.get_files_list(in_dir) if supported_extension(f)
]
# get images directory
input_dir = tree.input_images
images_dir = tree.dataset_raw
if not io.dir_exists(images_dir):
log.ODM_INFO(
"Project directory %s doesn't exist. Creating it now. " %
images_dir)
system.mkdir_p(images_dir)
copied = [
copyfile(io.join_paths(input_dir, f),
io.join_paths(images_dir, f))
for f in get_images(input_dir)
]
# define paths and create working directories
system.mkdir_p(tree.odm_georeferencing)
if not args.use_3dmesh: system.mkdir_p(tree.odm_25dgeoreferencing)
log.ODM_DEBUG('Loading dataset from: %s' % images_dir)
# check if we rerun cell or not
images_database_file = io.join_paths(tree.root_path, 'images.json')
if not io.file_exists(images_database_file) or self.rerun():
files = get_images(images_dir)
if files:
# create ODMPhoto list
path_files = [io.join_paths(images_dir, f) for f in files]
photos = []
with open(tree.dataset_list, 'w') as dataset_list:
for f in path_files:
photos += [types.ODM_Photo(f)]
dataset_list.write(photos[-1].filename + '\n')
# Save image database for faster restart
save_images_database(photos, images_database_file)
else:
log.ODM_ERROR('Not enough supported images in %s' % images_dir)
exit(1)
else:
# We have an images database, just load it
photos = load_images_database(images_database_file)
log.ODM_INFO('Found %s usable images' % len(photos))
# append photos to cell output
if not self.params.get('proj'):
if tree.odm_georeferencing_gcp:
outputs['reconstruction'] = types.ODM_Reconstruction(
photos, coords_file=tree.odm_georeferencing_gcp)
else:
# Generate UTM from images
try:
if not io.file_exists(
tree.odm_georeferencing_coords) or self.rerun():
location.extract_utm_coords(
photos, tree.dataset_raw,
tree.odm_georeferencing_coords)
else:
log.ODM_INFO("Coordinates file already exist: %s" %
tree.odm_georeferencing_coords)
except:
log.ODM_WARNING('Could not generate coordinates file. '
'Ignore if there is a GCP file')
outputs['reconstruction'] = types.ODM_Reconstruction(
photos, coords_file=tree.odm_georeferencing_coords)
else:
outputs['reconstruction'] = types.ODM_Reconstruction(
photos, projstring=self.params.get('proj'))
# Save proj to file for future use (unless this
# dataset is not georeferenced)
if outputs['reconstruction'].projection:
with open(
io.join_paths(tree.odm_georeferencing,
tree.odm_georeferencing_proj), 'w') as f:
f.write(outputs['reconstruction'].projection.srs)
def process(self, args, outputs):
log.ODM_INFO("Project path: %s" % args.project_path)
outputs["project_path"] = args.project_path
outputs["images_dir"] = os.path.join(args.project_path, 'images')
outputs["image_list_file"] = os.path.join(outputs["project_path"],
"image_list.txt")
outputs["cm"] = ColmapContext(args.project_path)
log.ODM_INFO("Images dir: %s" % outputs["images_dir"])
if not os.path.exists(outputs["images_dir"]):
log.ODM_ERROR("No images found in %s, exiting..." %
outputs["images_dir"])
exit(1)
# create output directories (match ODM conventions for compatibility)
odm_dirs = [
'odm_orthophoto', 'odm_meshing', 'odm_texturing', 'odm_dem',
'odm_georeferencing'
]
for odm_dir in odm_dirs:
system.mkdir_p(os.path.join(args.project_path, odm_dir))
images_database_file = io.join_paths(args.project_path, 'images.json')
if not io.file_exists(images_database_file) or self.rerun():
files = []
for ext in [
"JPG", "JPEG", "TIF", "TIFF", "jpg", "jpeg", "tif", "tiff"
]:
image_wildcard = '*.{}'.format(ext)
files += glob.glob(
os.path.join(outputs["images_dir"], image_wildcard))
if files:
photos = []
with open(outputs["image_list_file"], 'w') as image_list:
log.ODM_INFO("Loading %s images" % len(files))
for f in files:
photos += [ODM_Photo(f)]
image_list.write(photos[-1].filename + '\n')
# Save image database for faster restart
save_images_database(photos, images_database_file)
else:
log.ODM_ERROR('Not enough supported images in %s' % images_dir)
exit(1)
else:
# We have an images database, just load it
photos = load_images_database(images_database_file)
log.ODM_INFO('Found %s usable images' % len(photos))
if len(photos) == 0:
log.ODM_ERROR(
"No images found (JPG or TIFF). Check that you placed some images in the images/ directory."
)
exit(1)
utm_coords_file = os.path.join(args.project_path, "utm_coords.txt")
if not os.path.exists(utm_coords_file) or self.rerun():
extract_utm_coords(photos, outputs["images_dir"], utm_coords_file)
else:
log.ODM_WARNING("Found existing %s" % utm_coords_file)
outputs["photos"] = photos
outputs["utm_coords_file"] = utm_coords_file
def process(self, inputs, outputs):
# check if the extension is supported
def supported_extension(file_name):
(pathfn, ext) = os.path.splitext(file_name)
return ext.lower() in context.supported_extensions
# Get supported images from dir
def get_images(in_dir):
# filter images for its extension type
log.ODM_DEBUG(in_dir)
return [
f for f in io.get_files_list(in_dir) if supported_extension(f)
]
log.ODM_INFO('Running ODM Load Dataset Cell')
# get inputs
tree = self.inputs.tree
args = self.inputs.args
# get images directory
input_dir = tree.input_images
images_dir = tree.dataset_raw
if not io.dir_exists(images_dir):
log.ODM_INFO(
"Project directory %s doesn't exist. Creating it now. " %
images_dir)
system.mkdir_p(images_dir)
copied = [
copyfile(io.join_paths(input_dir, f),
io.join_paths(images_dir, f))
for f in get_images(input_dir)
]
# define paths and create working directories
system.mkdir_p(tree.odm_georeferencing)
if not args.use_3dmesh: system.mkdir_p(tree.odm_25dgeoreferencing)
log.ODM_DEBUG('Loading dataset from: %s' % images_dir)
# check if we rerun cell or not
rerun_cell = (args.rerun is not None and
args.rerun == 'dataset') or \
(args.rerun_all) or \
(args.rerun_from is not None and
'dataset' in args.rerun_from)
images_database_file = io.join_paths(tree.root_path, 'images.json')
if not io.file_exists(images_database_file) or rerun_cell:
files = get_images(images_dir)
if files:
# create ODMPhoto list
path_files = [io.join_paths(images_dir, f) for f in files]
photos = []
with open(tree.dataset_list, 'w') as dataset_list:
for f in path_files:
photos += [types.ODM_Photo(f)]
dataset_list.write(photos[-1].filename + '\n')
# Save image database for faster restart
save_images_database(photos, images_database_file)
else:
log.ODM_ERROR('Not enough supported images in %s' % images_dir)
return ecto.QUIT
else:
# We have an images database, just load it
photos = load_images_database(images_database_file)
log.ODM_INFO('Found %s usable images' % len(photos))
# append photos to cell output
if not self.params.proj:
if tree.odm_georeferencing_gcp:
outputs.reconstruction = types.ODM_Reconstruction(
photos, coords_file=tree.odm_georeferencing_gcp)
else:
# Generate UTM from images
try:
if not io.file_exists(
tree.odm_georeferencing_coords) or rerun_cell:
location.extract_utm_coords(
photos, tree.dataset_raw,
tree.odm_georeferencing_coords)
else:
log.ODM_INFO("Coordinates file already exist: %s" %
tree.odm_georeferencing_coords)
except:
log.ODM_WARNING('Could not generate coordinates file. '
'Ignore if there is a GCP file')
outputs.reconstruction = types.ODM_Reconstruction(
photos, coords_file=tree.odm_georeferencing_coords)
else:
outputs.reconstruction = types.ODM_Reconstruction(
photos, projstring=self.params.proj)
# Save proj to file for future use (unless this
# dataset is not georeferenced)
if outputs.reconstruction.projection:
with open(
io.join_paths(tree.odm_georeferencing,
tree.odm_georeferencing_proj), 'w') as f:
f.write(outputs.reconstruction.projection.srs)
log.ODM_INFO('Running ODM Load Dataset Cell - Finished')
return ecto.OK if args.end_with != 'dataset' else ecto.QUIT