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Box3D 

Box3D(center: List[float], size: List[float], orientation: Quaternion, label: int = np.nan, score: float = np.nan, velocity: Tuple = (np.nan, np.nan, np.nan), name: str = None, token: str = None)

An wrapper of NuScenes Box.

Construct instance.

Parameters:

  • center (List[float]) –

    Center of box given as (x, y, z).

  • size (List[float]) –

    Size of box given as (width, length, height).

  • orientation (Quaternion) –

    Box orientation.

  • label (int, default: nan ) –

    Integer label.

  • score (float, default: nan ) –

    Classification score.

  • velocity (Tuple, default: (nan, nan, nan) ) –

    Box velocity given as (vx, vy, vz).

  • name (str, default: None ) –

    Box category name.

  • token (str, default: None ) –

    Unique string identifier.

Box2D 

Box2D(roi: RoiType, label: int = -1, score: float = np.nan, name: str | None = None, token: str | None = None)

A class to represent 2D box.

Construct instance.

Parameters:

  • roi (RoiType) –

    Roi elements, which is the order of (xmin, ymin, xmax, ymax).

  • label (int, default: -1 ) –

    Box label.

  • score (float, default: nan ) –

    Box score.

  • name (str | None, default: None ) –

    Category name.

  • token (str | None, default: None ) –

    Unique identifier token corresponding to token of object_ann.

distance_color 

distance_color(distances: Number | ArrayLike, cmap: str | None = None, v_min: float = 3.0, v_max: float = 75.0) -> tuple[float, float, float] | NDArrayF64

Return color map depending on distance values.

Parameters:

  • distances (Number | ArrayLike) –

    Array of distances in the shape of (N,).

  • cmap (str | None, default: None ) –

    Color map name in matplotlib. If None, turbo_r will be used.

  • v_min (float, default: 3.0 ) –

    Min value to normalize.

  • v_max (float, default: 75.0 ) –

    Max value to normalize.

Returns:

  • tuple[float, float, float] | NDArrayF64 –

    Color map in the shape of (N,). If input type is any number, returns a color as tuple[float, float, float]. Otherwise, returns colors as NDArrayF64.

view_points 

view_points(points: NDArrayF64, intrinsic: NDArrayF64, distortion: NDArrayF64 | None = None, *, normalize: bool = True) -> NDArrayF64

Project 3d points on a 2d plane. It can be used to implement both perspective and orthographic projections.

It first applies the dot product between the points and the view.

Parameters:

  • points (NDArrayF64) –

    Matrix of points, which is the shape of (3, n) and (x, y, z) is along each column.

  • intrinsic (NDArrayF64) –

    nxn camera intrinsic matrix (n <= 4).

  • distortion (NDArrayF64 | None, default: None ) –

    Camera distortion coefficients, which is the shape of (n,) (n >= 5).

  • normalize (bool, default: True ) –

    Whether to normalize the remaining coordinate (along the 3rd axis).

Returns:

  • NDArrayF64 –

    Projected points in the shape of (3, n). If normalize=False, the 3rd coordinate is the height.

is_box_in_image 

is_box_in_image(box: Box3D, intrinsic: NDArrayF64, img_size: tuple[int, int], visibility: VisibilityLevel = VisibilityLevel.NONE) -> bool

Check if a box is visible inside of an image without considering its occlusions.

Parameters:

  • box (Box3D) –

    The box to be checked.

  • intrinsic (NDArrayF64) –

    3x3 camera intrinsic matrix.

  • img_size (tuple[int, int]) –

    Image size in the order of (width, height).

  • visibility (VisibilityLevel, default: NONE ) –

    Enum member of VisibilityLevel.

Returns:

  • bool –

    Return True if visibility condition is satisfied.

load_json 

load_json(filename: str) -> Any

Load json data from specified filepath.

Parameters:

  • filename (str) –

    File path to .json file.

Returns:

  • Any –

    Loaded data.

save_json 

save_json(data: Any, filename: str) -> None

Save data into json file.

Parameters:

  • data (Any) –

    Data to be saved.

  • filename (str) –

    File path to save as json.

us2sec 

us2sec(timestamp: Number) -> float

Convert timestamp from micro seconds [us] to seconds [s].

Parameters:

  • timestamp (Number) –

    Timestamp in [us].

Returns:

  • float –

    Timestamp in [s].

sec2us 

sec2us(timestamp: Number) -> float

Convert timestamp from seconds [s] to micro seconds [us].

Parameters:

  • timestamp (Number) –

    Timestamp in [s].

Returns:

  • float –

    Timestamp in [us].