def _transform(self, point, reference, projection):
"""Transform on point from local coords to a proj4 projection."""
lat, lon, altitude = geo.lla_from_topocentric(
point[0], point[1], point[2],
reference['latitude'], reference['longitude'], reference['altitude'])
easting, northing = projection(lon, lat)
return [easting, northing, altitude]
def register_reconstruction_with_gps(reconstruction, reference):
"""
register reconstrution with gps positions and compass angles
"""
shots = reconstruction['shots']
for shot_id, shot in shots.iteritems():
gps = {}
topo = optical_center(shot)
lat, lon, alt = geo.lla_from_topocentric(topo[0], topo[1], topo[2],
reference['latitude'],
reference['longitude'],
reference['altitude'])
# find direction
shot['translation'][2] -= 1
topo2 = optical_center(shot)
dz = topo2 - topo
angle = np.rad2deg(np.arctan2(dz[0], dz[1]))
angle = (angle + 360) % 360
reconstruction['shots'][shot_id]['gps'] = {
'lon': lon,
'lat': lat,
'altitude': alt,
'direction': angle
}
def test_ecef_lla_topocentric_consistency() -> None:
lla_ref = [46.5, 6.5, 400]
lla_before = [46.5274109, 6.5722075, 402.16]
enu = geo.topocentric_from_lla(lla_before[0], lla_before[1], lla_before[2],
lla_ref[0], lla_ref[1], lla_ref[2])
lla_after = geo.lla_from_topocentric(enu[0], enu[1], enu[2], lla_ref[0],
lla_ref[1], lla_ref[2])
assert np.allclose(lla_after, lla_before)
def _transform(self, point, reference, projection):
lat, lon, altitude = geo.lla_from_topocentric(point[0], point[1],
point[2],
reference['latitude'],
reference['longitude'],
reference['altitude'])
easting, northing = projection(lon, lat)
return [easting, northing, altitude]
def _transform(self, point, reference, projection):
"""Transform on point from local coords to a proj4 projection."""
lat, lon, altitude = geo.lla_from_topocentric(point[0], point[1],
point[2],
reference['latitude'],
reference['longitude'],
reference['altitude'])
easting, northing = projection(lon, lat)
return [easting, northing, altitude]
def shot_lla_and_compass(shot, reference):
"""Lat, lon, alt and compass of the reconstructed shot position."""
topo = shot.pose.get_origin()
lat, lon, alt = geo.lla_from_topocentric(
topo[0], topo[1], topo[2],
reference['latitude'], reference['longitude'], reference['altitude'])
dz = shot.viewing_direction()
angle = np.rad2deg(np.arctan2(dz[0], dz[1]))
angle = (angle + 360) % 360
return lat, lon, alt, angle
def shot_lla_and_compass(shot, reference):
"""Lat, lon, alt and compass of the reconstructed shot position."""
topo = shot.pose.get_origin()
lat, lon, alt = geo.lla_from_topocentric(
topo[0], topo[1], topo[2],
reference['latitude'], reference['longitude'], reference['altitude'])
dz = shot.viewing_direction()
angle = np.rad2deg(np.arctan2(dz[0], dz[1]))
angle = (angle + 360) % 360
return lat, lon, alt, angle
def test_ecef_lla_topocentric_consistency():
lla_ref = [46.5, 6.5, 400]
lla_before = [46.5274109, 6.5722075, 402.16]
enu = geo.topocentric_from_lla(lla_before[0],
lla_before[1],
lla_before[2],
lla_ref[0],
lla_ref[1],
lla_ref[2])
lla_after = geo.lla_from_topocentric(enu[0],
enu[1],
enu[2],
lla_ref[0],
lla_ref[1],
lla_ref[2])
assert np.allclose(lla_after, lla_before)
def generate_exifs(reconstruction, gps_noise, speed_ms=10):
"""
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)
"""
previous_pose = None
previous_time = 0
exifs = {}
for shot_name in sorted(reconstruction.shots.keys()):
shot = reconstruction.shots[shot_name]
exif = {}
exif['width'] = shot.camera.width
exif['height'] = shot.camera.height
exif['focal_prior'] = shot.camera.focal_prior
exif['camera'] = str(shot.camera.id)
pose = shot.pose.get_origin()
if previous_pose is not None:
previous_time += np.linalg.norm(pose-previous_pose)*speed_ms
previous_pose = pose
exif['capture_time'] = previous_time
perturb_points([pose], [gps_noise, gps_noise, gps_noise])
lat, lon, alt = geo.lla_from_topocentric(pose[0], pose[1], pose[2],
0, 0, 0)
exif['gps'] = {}
exif['gps']['latitude'] = lat
exif['gps']['longitude'] = lon
exif['gps']['altitude'] = alt
exif['gps']['dop'] = gps_noise
exifs[shot_name] = exif
return exifs
def register_reconstruction_with_gps(reconstruction, reference):
"""
register reconstrution with gps positions and compass angles
"""
shots = reconstruction["shots"]
for shot_id, shot in shots.iteritems():
gps = {}
topo = optical_center(shot)
lat, lon, alt = geo.lla_from_topocentric(
topo[0], topo[1], topo[2], reference["latitude"], reference["longitude"], reference["altitude"]
)
# find direction
shot["translation"][2] -= 1
topo2 = optical_center(shot)
dz = topo2 - topo
angle = np.rad2deg(np.arctan2(dz[0], dz[1]))
angle = (angle + 360) % 360
reconstruction["shots"][shot_id]["gps"] = {"lon": lon, "lat": lat, "altitude": alt, "direction": angle}
def register_reconstruction_with_gps(reconstruction, reference):
"""
register reconstrution with gps positions and compass angles
"""
shots = reconstruction['shots']
for shot_id, shot in shots.iteritems():
gps = {}
topo = optical_center(shot)
lat, lon, alt = geo.lla_from_topocentric(topo[0], topo[1], topo[2],
reference['latitude'], reference['longitude'], reference['altitude'])
# find direction
shot['translation'][2] -= 1
topo2 = optical_center(shot)
dz = topo2 - topo
angle = np.rad2deg(np.arctan2(dz[0], dz[1]))
angle = (angle+360) % 360
reconstruction['shots'][shot_id]['gps'] = {
'lon': lon,
'lat': lat,
'altitude': alt,
'direction': angle
}
default=3,
type=int,
help='number of points to generate')
args = parser.parse_args()
data = dataset.DataSet(args.dataset)
reference = data.load_reference_lla()
reconstruction = data.load_reconstruction()[0]
print 'WGS84'
for i in range(args.num_points):
point = np.random.choice(reconstruction.points.values())
for shot in reconstruction.shots.values():
pixel = shot.project(point.coordinates)
if np.fabs(pixel).max() < 0.5:
lla = geo.lla_from_topocentric(point.coordinates[0],
point.coordinates[1],
point.coordinates[2],
reference['latitude'],
reference['longitude'],
reference['altitude'])
x, y = features.denormalized_image_coordinates(
pixel.reshape(1, 2), shot.camera.width,
shot.camera.height)[0]
print "{} {} {} {} {} {}".format(lla[0], lla[1], lla[2], x, y,
shot.id)
