OpenDroneMap-ODM/stages/dataset.py

152 wiersze
5.8 KiB
Python

import os
import json
from opendm import context
from opendm import io
from opendm import types
from opendm import log
from opendm import system
from opendm.geo import GeoFile
from shutil import copyfile
from opendm import progress
def save_images_database(photos, database_file):
with open(database_file, 'w') as f:
f.write(json.dumps([p.__dict__ for p in photos]))
log.ODM_INFO("Wrote images database: %s" % database_file)
def load_images_database(database_file):
# Empty is used to create types.ODM_Photo class
# instances without calling __init__
class Empty:
pass
result = []
log.ODM_INFO("Loading images database: %s" % database_file)
with open(database_file, 'r') as f:
photos_json = json.load(f)
for photo_json in photos_json:
p = Empty()
for k in photo_json:
setattr(p, k, photo_json[k])
p.__class__ = types.ODM_Photo
result.append(p)
return result
class ODMLoadDatasetStage(types.ODM_Stage):
def process(self, args, outputs):
tree = types.ODM_Tree(args.project_path, args.gcp, args.geo)
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 image filename is supported
def valid_image_filename(filename):
(pathfn, ext) = os.path.splitext(filename)
return ext.lower() in context.supported_extensions and pathfn[-5:] != "_mask"
# Get supported images from dir
def get_images(in_dir):
log.ODM_DEBUG(in_dir)
entries = os.listdir(in_dir)
valid, rejects = [], []
for f in entries:
if valid_image_filename(f):
valid.append(f)
else:
rejects.append(f)
return valid, rejects
def find_mask(photo_path, masks):
(pathfn, ext) = os.path.splitext(os.path.basename(photo_path))
k = "{}_mask".format(pathfn)
mask = masks.get(k)
if mask:
# Spaces are not supported due to OpenSfM's mask_list.txt format reqs
if not " " in mask:
return mask
else:
log.ODM_WARNING("Image mask {} has a space. Spaces are currently not supported for image masks.".format(mask))
# get images directory
images_dir = tree.dataset_raw
# 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_INFO('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, rejects = get_images(images_dir)
if files:
# create ODMPhoto list
path_files = [io.join_paths(images_dir, f) for f in files]
# Lookup table for masks
masks = {}
for r in rejects:
(p, ext) = os.path.splitext(r)
if p[-5:] == "_mask" and ext.lower() in context.supported_extensions:
masks[p] = r
photos = []
with open(tree.dataset_list, 'w') as dataset_list:
log.ODM_INFO("Loading %s images" % len(path_files))
for f in path_files:
p = types.ODM_Photo(f)
p.set_mask(find_mask(f, masks))
photos += [p]
dataset_list.write(photos[-1].filename + '\n')
# Check if a geo file is available
if tree.odm_geo_file is not None and os.path.exists(tree.odm_geo_file):
log.ODM_INFO("Found image geolocation file")
gf = GeoFile(tree.odm_geo_file)
updated = 0
for p in photos:
entry = gf.get_entry(p.filename)
if entry:
p.update_with_geo_entry(entry)
updated += 1
log.ODM_INFO("Updated %s image positions" % updated)
# 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))
# Create reconstruction object
reconstruction = types.ODM_Reconstruction(photos)
if tree.odm_georeferencing_gcp and not args.use_exif:
reconstruction.georeference_with_gcp(tree.odm_georeferencing_gcp,
tree.odm_georeferencing_coords,
tree.odm_georeferencing_gcp_utm,
rerun=self.rerun())
else:
reconstruction.georeference_with_gps(tree.dataset_raw,
tree.odm_georeferencing_coords,
rerun=self.rerun())
reconstruction.save_proj_srs(io.join_paths(tree.odm_georeferencing, tree.odm_georeferencing_proj))
outputs['reconstruction'] = reconstruction