def _load_mask_list(self):
"""Load mask list from mask_list.txt or list masks/ folder."""
mask_list_file = os.path.join(self.data_path, 'mask_list.txt')
if os.path.isfile(mask_list_file):
with io.open_rt(mask_list_file) as fin:
lines = fin.read().splitlines()
self._set_mask_list(lines)
else:
self._set_mask_path(os.path.join(self.data_path, 'masks'))
def _load_image_list(self):
"""Load image list from image_list.txt or list image/ folder."""
image_list_file = os.path.join(self.data_path, 'image_list.txt')
if os.path.isfile(image_list_file):
with io.open_rt(image_list_file) as fin:
lines = fin.read().splitlines()
self._set_image_list(lines)
else:
self._set_image_path(os.path.join(self.data_path, 'images'))
def images_with_gps(self):
with io.open_rt(self._image_list_path()) as csvfile:
image_reader = csv.reader(
csvfile,
delimiter='\t',
quotechar='"',
quoting=csv.QUOTE_MINIMAL)
for image, lat, lon in image_reader:
yield image, float(lat), float(lon)
def load_ground_control_points(self):
"""Load ground control points.
It uses reference_lla to convert the coordinates
to topocentric reference frame.
"""
exif = {image: self.load_exif(image) for image in self.images()}
reference = self.load_reference()
with io.open_rt(self._ground_control_points_file()) as fin:
return io.read_ground_control_points_list(fin, reference, exif)
def load_exif(self, image):
"""
Return extracted exif information, as dictionary, usually with fields:
================ ===== ===================================
Field Type Description
================ ===== ===================================
width int Width of image, in pixels
height int Height of image, in pixels
focal_prior float Focal length (real) / sensor width
================ ===== ===================================
:param image: Image name, with extension (i.e. 123.jpg)
"""
with io.open_rt(self._exif_file(image)) as fin:
return json.load(fin)
def _transform_dense_point_cloud(self, data, transformation, output):
"""Apply a transformation to the merged point cloud."""
A, b = transformation[:3, :3], transformation[:3, 3]
input_path = os.path.join(data._depthmap_path(), 'merged.ply')
output_path = os.path.join(data.data_path, output)
with io.open_rt(input_path) as fin:
with io.open_wt(output_path) as fout:
for i, line in enumerate(fin):
if i < 13:
fout.write(line)
else:
x, y, z, nx, ny, nz, red, green, blue = line.split()
x, y, z = np.dot(A, map(float, [x, y, z])) + b
nx, ny, nz = np.dot(A, map(float, [nx, ny, nz]))
fout.write(
"{} {} {} {} {} {} {} {} {}\n".format(
x, y, z, nx, ny, nz, red, green, blue))
def load_tracks_graph(self, filename=None):
"""Return graph (networkx data structure) of tracks"""
with io.open_rt(self._tracks_graph_file(filename)) as fin:
return load_tracks_graph(fin)
def load_reconstruction(self, filename=None):
with io.open_rt(self._reconstruction_file(filename)) as fin:
reconstructions = io.reconstructions_from_json(io.json_load(fin))
return reconstructions
def load_undistorted_reconstruction(self):
filename = os.path.join(self.data_path, "reconstruction.json")
with io.open_rt(filename) as fin:
return io.reconstructions_from_json(io.json_load(fin))
def load_undistorted_shot_ids(self):
filename = os.path.join(self.data_path, "undistorted_shot_ids.json")
with io.open_rt(filename) as fin:
return io.json_load(fin)
def load_report(self, path):
"""Load a report file as a string."""
with io.open_rt(os.path.join(self._report_path(), path)) as fin:
return fin.read()
def images_with_gps(self):
with io.open_rt(self._image_list_path()) as csvfile:
for line in csvfile:
image, lat, lon = line.split(u"\t")
yield image, float(lat), float(lon)
def load_match_adjacency_list(self):
with io.open_rt(self._match_adjacency_list_file()) as fin:
obj = json.load(fin)
return obj
def load_camera_models_overrides(self):
"""Load camera models overrides data."""
with io.open_rt(self._camera_models_overrides_file()) as fin:
obj = json.load(fin)
return io.cameras_from_json(obj)
def load_camera_models(self):
"""Return camera models data"""
with io.open_rt(self._camera_models_file()) as fin:
obj = json.load(fin)
return io.cameras_from_json(obj)
def load_camera_models_overrides(self):
"""Load camera models overrides data."""
with io.open_rt(self._camera_models_overrides_file()) as fin:
obj = json.load(fin)
return io.cameras_from_json(obj)
def load_reference_lla(self):
with io.open_rt(self._reference_lla_path()) as fin:
return io.json_load(fin)
def load_reconstruction(self, filename=None):
with io.open_rt(self._reconstruction_file(filename)) as fin:
reconstructions = io.reconstructions_from_json(io.json_load(fin))
return reconstructions
def load_exif(self, image):
"""Load pre-extracted image exif metadata."""
with io.open_rt(self._exif_file(image)) as fin:
return json.load(fin)
def load_reference_lla(self):
with io.open_rt(self._reference_lla_path()) as fin:
return io.json_load(fin)
def load_rig_assignments(self):
"""Return rig assignments data"""
with io.open_rt(self._rig_assignments_file()) as fin:
return json.load(fin)
def load_camera_models(self):
"""Return camera models data"""
with io.open_rt(self._camera_models_file()) as fin:
obj = json.load(fin)
return io.cameras_from_json(obj)
def load_tracks_graph(self, filename=None):
"""Return graph (networkx data structure) of tracks"""
with io.open_rt(self._tracks_graph_file(filename)) as fin:
return tracking.load_tracks_graph(fin)
def load_exif_overrides(self):
"""Load EXIF overrides data."""
with io.open_rt(self._exif_overrides_file()) as fin:
return json.load(fin)
def images_with_gps(self):
with io.open_rt(self._image_list_path()) as csvfile:
for line in csvfile:
image, lat, lon = line.split(u'\t')
yield image, float(lat), float(lon)
def load_exif_overrides(self):
"""Load EXIF overrides data."""
with io.open_rt(self._exif_overrides_file()) as fin:
return json.load(fin)
def load_report(self, path):
"""Load a report file as a string."""
with io.open_rt(os.path.join(self._report_path(), path)) as fin:
return fin.read()
import json
from opensfm import context
from opensfm import io
with io.open_rt(context.SENSOR) as f:
sensor_data = io.json_load(f)
# Convert model types to lower cases for easier query
keys = [k.lower() for k in sensor_data.keys()]
values = sensor_data.values()
sensor_data = dict(zip(keys, values))
def load_rig_models(self):
"""Return rig models data"""
with io.open_rt(self._rig_models_file()) as fin:
return json.load(fin)
