def __init__(self) -> None:
""" Initialize the Argoverse Map. """
self.city_name_to_city_id_dict = {
"PIT": PITTSBURGH_ID,
"MIA": MIAMI_ID
}
self.render_window_radius = 150
self.im_scale_factor = 50
self.city_lane_centerlines_dict = self.build_centerline_index()
self.city_halluc_bbox_table, self.city_halluc_tableidx_to_laneid_map = self.build_hallucinated_lane_bbox_index(
)
self.city_rasterized_da_roi_dict = self.build_city_driveable_area_roi_index(
)
self.city_rasterized_ground_height_dict = self.build_city_ground_height_index(
)
# get hallucinated lane extends and driveable area from binary img
self.city_to_lane_polygons_dict: Mapping[str, np.ndarray] = {}
self.city_to_driveable_areas_dict: Mapping[str, np.ndarray] = {}
self.city_to_lane_bboxes_dict: Mapping[str, np.ndarray] = {}
self.city_to_da_bboxes_dict: Mapping[str, np.ndarray] = {}
for city_name in self.city_name_to_city_id_dict.keys():
lane_polygons = np.array(
self.get_vector_map_lane_polygons(city_name))
driveable_areas = np.array(
self.get_vector_map_driveable_areas(city_name))
lane_bboxes = compute_polygon_bboxes(lane_polygons)
da_bboxes = compute_polygon_bboxes(driveable_areas)
self.city_to_lane_polygons_dict[city_name] = lane_polygons
self.city_to_driveable_areas_dict[city_name] = driveable_areas
self.city_to_lane_bboxes_dict[city_name] = lane_bboxes
self.city_to_da_bboxes_dict[city_name] = da_bboxes
def test_compute_polygon_bboxes(
polygons_and_gt_bboxes: Tuple[List[np.ndarray],
List[np.ndarray]]) -> None:
"""Test for correctness of compute_polygon_bboxes."""
polygon_bboxes = compute_polygon_bboxes(
np.array(polygons_and_gt_bboxes[0], dtype=object))
gt_polygon_bboxes = np.array(polygons_and_gt_bboxes[1])
assert np.allclose(polygon_bboxes, gt_polygon_bboxes)
def __init__(self, is_nuscenes=False) -> None:
""" Initialize the Argoverse Map. """
self.is_nuscenes = is_nuscenes
self.city_name_to_city_id_dict = {
"PIT": PITTSBURGH_ID,
"MIA": MIAMI_ID
} if not is_nuscenes else {
"BSP": BOSTON_SEAPORT_ID,
"SHV": SINGAPORE_HOLLANDVILLAGE_ID,
"SON": SINGAPORE_ONENORTH_ID,
"SQT": SINGAPORE_QUEENSTOWN_ID
}
self.render_window_radius = 150
self.im_scale_factor = 50
self.city_lane_centerlines_dict = self.build_centerline_index()
(
self.city_halluc_bbox_table,
self.city_halluc_tableidx_to_laneid_map,
) = self.build_hallucinated_lane_bbox_index()
#self.city_rasterized_da_roi_dict = self.build_city_driveable_area_roi_index()
#self.city_rasterized_ground_height_dict = self.build_city_ground_height_index()
# get hallucinated lane extends and driveable area from binary img
self.city_to_lane_polygons_dict: Mapping[str, np.ndarray] = {}
self.city_to_driveable_areas_dict: Mapping[str, np.ndarray] = {}
self.city_to_lane_bboxes_dict: Mapping[str, np.ndarray] = {}
self.city_to_da_bboxes_dict: Mapping[str, np.ndarray] = {}
for city_name in self.city_name_to_city_id_dict.keys():
lane_polygons = np.array(
self.get_vector_map_lane_polygons(city_name))
#driveable_areas = np.array(self.get_vector_map_driveable_areas(city_name))
lane_bboxes = compute_polygon_bboxes(lane_polygons)
#da_bboxes = compute_polygon_bboxes(driveable_areas)
self.city_to_lane_polygons_dict[city_name] = lane_polygons
#self.city_to_driveable_areas_dict[city_name] = driveable_areas
self.city_to_lane_bboxes_dict[city_name] = lane_bboxes
def test_compute_polygon_bboxes(polygons_and_gt_bboxes):
"""Test for correctness of compute_polygon_bboxes."""
polygon_bboxes = compute_polygon_bboxes(np.array(
polygons_and_gt_bboxes[0]))
gt_polygon_bboxes = np.array(polygons_and_gt_bboxes[1])
assert np.allclose(polygon_bboxes, gt_polygon_bboxes)
