def test_loading_image_lidar(data_loader: ArgoverseTrackingLoader) -> None:
camera = CAMERA_LIST[0]
log = "1"
image_1 = data_loader.get_image_at_timestamp(0, camera, log)
image_2 = data_loader.get_image_list_sync(camera, log, load=True)[0]
image_3 = data_loader.get_image(0, camera, log)
image_4 = data_loader.get_image_sync(0, camera, log)
assert np.array_equal(image_1, image_2) and np.array_equal(
image_1, image_3) and np.array_equal(image_1, image_4)
lidar_0 = data_loader.get_lidar(0, log)
lidar_gt = np.array([
[0.0, 0.0, 5.0],
[1.0, 0.0, 5.0],
[2.0, 0.0, 5.0],
[3.0, 0.0, 5.0],
[4.0, 0.0, 5.0],
[5.0, 0.0, 5.0],
[6.0, 0.0, 5.0],
[7.0, 0.0, 5.0],
[8.0, 0.0, 5.0],
[9.0, 0.0, 5.0],
])
assert np.array_equal(lidar_0, lidar_gt)
def shuffle_log(subset, log: ArgoverseTrackingLoader):
index = np.arange(log.num_lidar_frame)
random.shuffle(index)
for idx in index:
lidar = log.get_lidar(idx)
label = log.get_label_object(idx)
yield idx, subset, lidar, label, log
def test_calib(data_loader: ArgoverseTrackingLoader) -> None:
assert data_loader.calib
camera = "ring_front_center"
calib = data_loader.get_calibration(camera)
pc = data_loader.get_lidar(0)
uv = calib.project_ego_to_image(pc)
uv_cam = calib.project_ego_to_cam(pc)
assert (uv == calib.project_cam_to_image(uv_cam)).all
assert (uv_cam == calib.project_image_to_cam(uv)).all
assert (pc == calib.project_image_to_ego(uv)).all
def draw_point_cloud(
ax: plt.Axes,
title: str,
argoverse_data: ArgoverseTrackingLoader,
idx: int,
axes: Optional[Any] = None,
xlim3d: Any = None,
ylim3d: Any = None,
zlim3d: Any = None,
) -> None:
axes = _get_axes_or_default(axes)
pc = argoverse_data.get_lidar(idx)
assert isinstance(pc, np.ndarray)
objects = argoverse_data.get_label_object(idx)
ax.scatter(*np.transpose(pc[:, axes]),
s=point_size,
c=pc[:, 2],
cmap="gray")
ax.set_title(title)
ax.set_xlabel("{} axis".format(axes_str[axes[0]]))
ax.set_ylabel("{} axis".format(axes_str[axes[1]]))
if len(axes) > 2:
ax.set_xlim3d(*axes_limits[axes[0]])
ax.set_ylim3d(*axes_limits[axes[1]])
ax.set_zlim3d(*axes_limits[axes[2]])
ax.set_zlabel("{} axis".format(axes_str[axes[2]]))
else:
ax.set_xlim(*axes_limits[axes[0]])
ax.set_ylim(*axes_limits[axes[1]])
# User specified limits
if xlim3d != None:
ax.set_xlim3d(xlim3d)
if ylim3d != None:
ax.set_ylim3d(ylim3d)
if zlim3d != None:
ax.set_zlim3d(zlim3d)
for obj in objects:
if obj.occlusion == 100:
continue
if obj.label_class is None:
logger.warning("No label class, just picking the default color.")
color = _COLOR_MAP[-1]
else:
color = _COLOR_MAP[OBJ_CLASS_MAPPING_DICT[obj.label_class]]
draw_box(ax, obj.as_3d_bbox().T, axes=axes, color=color)
def draw_point_cloud_trajectory(
ax: plt.Axes,
title: str,
argoverse_data: ArgoverseTrackingLoader,
idx: int,
axes: Optional[Any] = None,
xlim3d: Any = None,
ylim3d: Any = None,
zlim3d: Any = None,
) -> None:
axes = _get_axes_or_default(axes)
unique_id_list = set()
for i in range(len(argoverse_data.lidar_list)):
for label in argoverse_data.get_label_object(i):
unique_id_list.add(label.track_id)
color_map = {
track_id: (
float(np.random.rand()),
float(np.random.rand()),
float(np.random.rand()),
)
for track_id in unique_id_list
}
pc = argoverse_data.get_lidar(idx)
assert isinstance(pc, np.ndarray)
objects = argoverse_data.get_label_object(idx)
ax.scatter(*np.transpose(pc[:, axes]),
s=point_size,
c=pc[:, 2],
cmap="gray")
ax.set_title(title)
ax.set_xlabel("{} axis".format(axes_str[axes[0]]))
ax.set_ylabel("{} axis".format(axes_str[axes[1]]))
if len(axes) > 2:
ax.set_xlim3d(*axes_limits[axes[0]])
ax.set_ylim3d(*axes_limits[axes[1]])
ax.set_zlim3d(*axes_limits[axes[2]])
ax.set_zlabel("{} axis".format(axes_str[axes[2]]))
else:
ax.set_xlim(*axes_limits[axes[0]])
ax.set_ylim(*axes_limits[axes[1]])
# User specified limits
if xlim3d != None:
ax.set_xlim3d(xlim3d)
if ylim3d != None:
ax.set_ylim3d(ylim3d)
if zlim3d != None:
ax.set_zlim3d(zlim3d)
visible_track_id = set()
for obj in objects:
if obj.occlusion == 100:
continue
draw_box(ax,
obj.as_3d_bbox().T,
axes=axes,
color=color_map[obj.track_id])
visible_track_id.add(obj.track_id)
current_pose = argoverse_data.get_pose(idx)
traj_by_id: Dict[Optional[str], List[Any]] = defaultdict(list)
for i in range(0, idx, 1):
if current_pose is None:
logger.warning("`current_pose` is missing at index %d", idx)
break
pose = argoverse_data.get_pose(i)
if pose is None:
logger.warning("`pose` is missing at index %d", i)
continue
objects = argoverse_data.get_label_object(i)
for obj in objects:
if obj.occlusion == 100:
continue
if obj.track_id is None or obj.track_id not in visible_track_id:
continue
x, y, z = pose.transform_point_cloud(
np.array([np.array(obj.translation)]))[0]
x, y, _ = current_pose.inverse_transform_point_cloud(
np.array([np.array([x, y, z])]))[0]
# ax.scatter(x,y, s=point_size, c=color_map[obj.track_id])
if obj.track_id is None:
logger.warning(
"Label has no track_id. Collisions with other tracks that are missing IDs could happen"
)
traj_by_id[obj.track_id].append([x, y])
for track_id in traj_by_id.keys():
traj = np.array(traj_by_id[track_id])
ax.plot(
traj[:, 0],
traj[:, 1],
color=color_map[track_id],
linestyle="--",
linewidth=1,
)
