def _read_ground_control_points_list_line(line, projection, reference_lla, exif):
words = line.split()
easting, northing, alt, pixel_x, pixel_y = map(float, words[:5])
shot_id = words[5]
# Convert 3D coordinates
if projection is not None:
lon, lat = projection(easting, northing, inverse=True)
else:
lon, lat = easting, northing
x, y, z = geo.topocentric_from_lla(
lat, lon, alt,
reference_lla['latitude'],
reference_lla['longitude'],
reference_lla['altitude'])
# Convert 2D coordinates
d = exif[shot_id]
coordinates = features.normalized_image_coordinates(
np.array([[pixel_x, pixel_y]]), d['width'], d['height'])[0]
o = types.GroundControlPointObservation()
o.lla = np.array([lat, lon, alt])
o.coordinates = np.array([x, y, z])
o.shot_id = shot_id
o.shot_coordinates = coordinates
return o
def read_ground_control_points(fileobj, reference):
"""Read ground control points from json file.
Returns list of types.GroundControlPoint.
"""
obj = json_load(fileobj)
points = []
for point_dict in obj['points']:
point = types.GroundControlPoint()
point.id = point_dict['id']
point.lla = point_dict.get('position')
if point.lla:
point.coordinates = reference.to_topocentric(
point.lla['latitude'], point.lla['longitude'],
point.lla.get('altitude', 0))
point.has_altitude = ('altitude' in point.lla)
point.observations = []
for o_dict in point_dict['observations']:
o = types.GroundControlPointObservation()
o.shot_id = o_dict['shot_id']
if 'projection' in o_dict:
o.projection = np.array(o_dict['projection'])
point.observations.append(o)
points.append(point)
return points
def _read_gcp_list_lines(lines, projection, reference, exif):
points = {}
for line in lines:
words = line.split(None, 5)
easting, northing, alt, pixel_x, pixel_y = map(float, words[:5])
shot_id = words[5].strip()
key = (easting, northing, alt)
if key in points:
point = points[key]
else:
# Convert 3D coordinates
if np.isnan(alt):
alt = 0
has_altitude = False
else:
has_altitude = True
if projection is not None:
lon, lat = projection(easting, northing, inverse=True)
else:
lon, lat = easting, northing
point = types.GroundControlPoint()
point.id = "unnamed-%d" % len(points)
point.lla = np.array([lat, lon, alt])
point.has_altitude = has_altitude
if reference:
x, y, z = reference.to_topocentric(lat, lon, alt)
point.coordinates = np.array([x, y, z])
else:
point.coordinates = None
points[key] = point
# Convert 2D coordinates
d = exif[shot_id]
coordinates = features.normalized_image_coordinates(
np.array([[pixel_x, pixel_y]]), d['width'], d['height'])[0]
o = types.GroundControlPointObservation()
o.shot_id = shot_id
o.projection = coordinates
point.observations.append(o)
return list(points.values())
def read_ground_control_points(fileobj, reference):
"""Read ground control points from json file.
Returns list of types.GroundControlPoint.
"""
obj = json_load(fileobj)
points = []
for point_dict in obj['points']:
point = types.GroundControlPoint()
point.id = point_dict['id']
point.lla = point_dict.get('position')
if point.lla:
point.has_altitude = ('altitude' in point.lla)
if reference:
point.coordinates = reference.to_topocentric(
point.lla['latitude'],
point.lla['longitude'],
point.lla.get('altitude', 0))
else:
point.coordinates = None
point.observations = []
observing_images = set()
for o_dict in point_dict['observations']:
o = types.GroundControlPointObservation()
o.shot_id = o_dict['shot_id']
if o.shot_id in observing_images:
logger.warning("GCP {} has multiple observations in image {}"
.format(point.id, o.shot_id))
observing_images.add(o.shot_id)
if 'projection' in o_dict:
o.projection = np.array(o_dict['projection'])
point.observations.append(o)
points.append(point)
return points
