def init_tasks(self, _tasks_dict, _odm_app):
# dict to store tasks objects
tasks = {}
# loop over tasks dict
for key, in _tasks_dict:
# instantiate and append ODMTask
task_name = _tasks_dict[key]
tasks[key] = ODMTask(key, task_name)
# setup tasks
if task_name == 'resize':
# setup this task
command = resize
inputs = {
'project_path': _odm_app.project_path,
'args': _odm_app.args,
'photos': _odm_app.photos
}
elif task_name == 'opensfm':
# setup this task
command = opensfm
inputs = {
'project_path': _odm_app.project_path,
'args': _odm_app.args,
'photos': _odm_app.photos
}
elif task_name in [
'cmvs', 'pmvs', 'odm_meshing', 'mvs_texturing',
'odm_georeferencing', 'odm_orthophoto', 'zip_results'
]:
# setup this task
command = None
inputs = {}
else:
log.ODM_ERROR('task_name %s is not valid' % task_name)
# setup task configuration
task = tasks[key]
task.command = command
task.inputs = inputs
return tasks
def run_tasks(self):
# curr_task = self.tasks['resize']
# self.tasks['resize']
for id in range(self.initial_task_id, self.final_task_id + 1):
# catch task with current id
task = self.tasks[str(id)]
# update task tracking
log.ODM_INFO('Running task %s: %s' % (task.id, task.name))
self.current_task_id = task.id
# run task
task.state = task.run()
if task.state == 2:
log.ODM_INFO('Succeeded task %s: %s - %s' % (task.id, task.name, system.now()))
else:
log.ODM_ERROR('Aborted task %s: %s' % (task.id, task.name))
def detect_multi_camera(self):
"""
Looks at the reconstruction photos and determines if this
is a single or multi-camera setup.
"""
band_photos = {}
band_indexes = {}
for p in self.photos:
if not p.band_name in band_photos:
band_photos[p.band_name] = []
if not p.band_name in band_indexes:
band_indexes[p.band_name] = p.band_index
band_photos[p.band_name].append(p)
bands_count = len(band_photos)
if bands_count >= 2 and bands_count <= 8:
# Validate that all bands have the same number of images,
# otherwise this is not a multi-camera setup
img_per_band = len(band_photos[p.band_name])
for band in band_photos:
if len(band_photos[band]) != img_per_band:
log.ODM_ERROR(
"Multi-camera setup detected, but band \"%s\" (identified from \"%s\") has only %s images (instead of %s), perhaps images are missing or are corrupted. Please include all necessary files to process all bands and try again."
% (band, band_photos[band][0].filename,
len(band_photos[band]), img_per_band))
raise RuntimeError("Invalid multi-camera images")
mc = []
for band_name in band_indexes:
mc.append({
'name': band_name,
'photos': band_photos[band_name]
})
# Sort by band index
mc.sort(key=lambda x: band_indexes[x['name']])
return mc
return None
def convert_to_las(self, _file, _file_out, json_file):
if not self.epsg:
log.ODM_ERROR('Empty EPSG: Could not convert to LAS')
return
kwargs = {
'bin': context.pdal_path,
'f_in': _file,
'f_out': _file_out,
'east': self.utm_east_offset,
'north': self.utm_north_offset,
'epsg': self.epsg,
'json': json_file
}
# create pipeline file transform.xml to enable transformation
pipeline = '{{' \
' "pipeline":[' \
' "untransformed.ply",' \
' {{' \
' "type":"filters.transformation",' \
' "matrix":"1 0 0 {east} 0 1 0 {north} 0 0 1 0 0 0 0 1"' \
' }},' \
' {{' \
' "a_srs":"EPSG:{epsg}",' \
' "offset_x":"{east}",' \
' "offset_y":"{north}",' \
' "offset_z":"0",' \
' "filename":"transformed.las"' \
' }}' \
' ]' \
'}}'.format(**kwargs)
with open(json_file, 'w') as f:
f.write(pipeline)
# call pdal
system.run(
'{bin}/pdal pipeline -i {json} --readers.ply.filename={f_in} '
'--writers.las.filename={f_out}'.format(**kwargs))
def convert_to_las(self, _file, _file_out, json_file):
if not self.projection.srs:
log.ODM_ERROR('Empty CRS: Could not convert to LAS')
return
kwargs = {
'bin': context.pdal_path,
'f_in': _file,
'f_out': _file_out,
'east': self.utm_east_offset,
'north': self.utm_north_offset,
'srs': self.projection.srs,
'json': json_file
}
# create pipeline file las.json to write odm_georeferenced_model.laz point cloud
pipeline = '{{' \
' "pipeline":[' \
' "untransformed.ply",' \
' {{' \
' "type":"writers.las",' \
' "a_srs":"{srs}",' \
' "offset_x":"{east}",' \
' "offset_y":"{north}",' \
' "offset_z":"0",' \
' "compression":"laszip",' \
' "filename":"{f_out}"' \
' }}' \
' ]' \
'}}'.format(**kwargs)
with open(json_file, 'w') as f:
f.write(pipeline)
# call pdal
system.run(
'{bin}/pdal pipeline -i {json} --readers.ply.filename={f_in}'.
format(**kwargs))
def utm_to_latlon(self, _file, _photo, idx):
gcp = self.gcps[idx]
kwargs = {
'epsg': self.epsg,
'file': _file,
'x': gcp.x + self.utm_east_offset,
'y': gcp.y + self.utm_north_offset,
'z': gcp.z
}
latlon = system.run_and_return(
'echo {x} {y} {z} '.format(**kwargs),
'gdaltransform -s_srs \"EPSG:{epsg}\" '
'-t_srs \"EPSG:4326\"'.format(**kwargs)).split()
# Example: 83d18'16.285"W
# Example: 41d2'11.789"N
# Example: 0.998
if len(latlon) == 3:
lon_str, lat_str, alt_str = latlon
elif len(latlon) == 2:
lon_str, lat_str = latlon
alt_str = ''
else:
log.ODM_ERROR('Something went wrong %s' % latlon)
lat_frac = self.coord_to_fractions(latlon[1], ['N', 'S'])
lon_frac = self.coord_to_fractions(latlon[0], ['E', 'W'])
# read image metadata
metadata = pyexiv2.ImageMetadata(_photo.path_file)
metadata.read()
# set values
# GPS latitude
key = 'Exif.GPSInfo.GPSLatitude'
value = lat_frac[0].split(' ')
log.ODM_DEBUG('lat_frac: %s %s %s' % (value[0], value[1], value[2]))
metadata[key] = pyexiv2.ExifTag(
key, [Fraction(value[0]),
Fraction(value[1]),
Fraction(value[2])])
key = 'Exif.GPSInfo.GPSLatitudeRef'
value = lat_frac[1]
metadata[key] = pyexiv2.ExifTag(key, value)
# GPS longitude
key = 'Exif.GPSInfo.GPSLongitude'
value = lon_frac[0].split(' ')
metadata[key] = pyexiv2.ExifTag(
key, [Fraction(value[0]),
Fraction(value[1]),
Fraction(value[2])])
key = 'Exif.GPSInfo.GPSLongitudeRef'
value = lon_frac[1]
metadata[key] = pyexiv2.ExifTag(key, value)
# GPS altitude
altitude = abs(int(float(latlon[2]) * 100))
key = 'Exif.GPSInfo.GPSAltitude'
value = Fraction(altitude, 1)
metadata[key] = pyexiv2.ExifTag(key, value)
if latlon[2] >= 0:
altref = '0'
else:
altref = '1'
key = 'Exif.GPSInfo.GPSAltitudeRef'
metadata[key] = pyexiv2.ExifTag(key, altref)
# write values
metadata.write()
