def resect(
data: DataSetBase,
tracks_manager: pymap.TracksManager,
reconstruction: types.Reconstruction,
shot_id: str,
threshold: float,
min_inliers: int,
) -> Tuple[bool, Set[str], Dict[str, Any]]:
"""Try resecting and adding a shot to the reconstruction.
Return:
True on success.
"""
rig_assignments = data.load_rig_assignments_per_image()
camera = reconstruction.cameras[data.load_exif(shot_id)["camera"]]
bs, Xs, ids = [], [], []
for track, obs in tracks_manager.get_shot_observations(shot_id).items():
if track in reconstruction.points:
b = camera.pixel_bearing(obs.point)
bs.append(b)
Xs.append(reconstruction.points[track].coordinates)
ids.append(track)
bs = np.array(bs)
Xs = np.array(Xs)
if len(bs) < 5:
return False, set(), {"num_common_points": len(bs)}
T = multiview.absolute_pose_ransac(bs, Xs, threshold, 1000, 0.999)
R = T[:, :3]
t = T[:, 3]
reprojected_bs = R.T.dot((Xs - t).T).T
reprojected_bs /= np.linalg.norm(reprojected_bs, axis=1)[:, np.newaxis]
inliers = np.linalg.norm(reprojected_bs - bs, axis=1) < threshold
ninliers = int(sum(inliers))
logger.info("{} resection inliers: {} / {}".format(shot_id, ninliers,
len(bs)))
report = {
"num_common_points": len(bs),
"num_inliers": ninliers,
}
if ninliers >= min_inliers:
R = T[:, :3].T
t = -R.dot(T[:, 3])
assert shot_id not in reconstruction.shots
new_shots = add_shot(data, reconstruction, rig_assignments, shot_id,
pygeometry.Pose(R, t))
if shot_id in rig_assignments:
triangulate_shot_features(tracks_manager, reconstruction,
new_shots, data.config)
for i, succeed in enumerate(inliers):
if succeed:
add_observation_to_reconstruction(tracks_manager,
reconstruction, shot_id,
ids[i])
# pyre-fixme [6]: Expected `int` for 2nd positional
report["shots"] = list(new_shots)
return True, new_shots, report
else:
return False, set(), report
def bootstrap_reconstruction(
data: DataSetBase,
tracks_manager: pymap.TracksManager,
im1: str,
im2: str,
p1: np.ndarray,
p2: np.ndarray,
) -> Tuple[Optional[types.Reconstruction], Dict[str, Any]]:
"""Start a reconstruction using two shots."""
logger.info("Starting reconstruction with {} and {}".format(im1, im2))
report: Dict[str, Any] = {
"image_pair": (im1, im2),
"common_tracks": len(p1),
}
camera_priors = data.load_camera_models()
camera1 = camera_priors[data.load_exif(im1)["camera"]]
camera2 = camera_priors[data.load_exif(im2)["camera"]]
threshold = data.config["five_point_algo_threshold"]
min_inliers = data.config["five_point_algo_min_inliers"]
iterations = data.config["five_point_refine_rec_iterations"]
R, t, inliers, report[
"two_view_reconstruction"] = two_view_reconstruction_general(
p1, p2, camera1, camera2, threshold, iterations)
logger.info("Two-view reconstruction inliers: {} / {}".format(
len(inliers), len(p1)))
if len(inliers) <= 5:
report["decision"] = "Could not find initial motion"
logger.info(report["decision"])
return None, report
rig_camera_priors = data.load_rig_cameras()
rig_assignments = data.load_rig_assignments_per_image()
reconstruction = types.Reconstruction()
reconstruction.reference = data.load_reference()
reconstruction.cameras = camera_priors
reconstruction.rig_cameras = rig_camera_priors
new_shots = add_shot(data, reconstruction, rig_assignments, im1,
pygeometry.Pose())
if im2 not in new_shots:
new_shots |= add_shot(data, reconstruction, rig_assignments, im2,
pygeometry.Pose(R, t))
align_reconstruction(reconstruction, None, data.config)
triangulate_shot_features(tracks_manager, reconstruction, new_shots,
data.config)
logger.info("Triangulated: {}".format(len(reconstruction.points)))
report["triangulated_points"] = len(reconstruction.points)
if len(reconstruction.points) < min_inliers:
report["decision"] = "Initial motion did not generate enough points"
logger.info(report["decision"])
return None, report
to_adjust = {s for s in new_shots if s != im1}
bundle_shot_poses(reconstruction, to_adjust, camera_priors,
rig_camera_priors, data.config)
retriangulate(tracks_manager, reconstruction, data.config)
if len(reconstruction.points) < min_inliers:
report[
"decision"] = "Re-triangulation after initial motion did not generate enough points"
logger.info(report["decision"])
return None, report
bundle_shot_poses(reconstruction, to_adjust, camera_priors,
rig_camera_priors, data.config)
report["decision"] = "Success"
report["memory_usage"] = current_memory_usage()
return reconstruction, report
