open3d.ml.torch.vis.BoundingBox3D#

class open3d.ml.torch.vis.BoundingBox3D(center, front, up, left, size, label_class, confidence, meta=None, show_class=False, show_confidence=False, show_meta=None, identifier=None, arrow_length=1.0)#

Class that defines an axially-oriented bounding box.

__init__(center, front, up, left, size, label_class, confidence, meta=None, show_class=False, show_confidence=False, show_meta=None, identifier=None, arrow_length=1.0)#

Creates a bounding box.

Front, up, left define the axis of the box and must be normalized and mutually orthogonal.

Parameters:

  • center – (x, y, z) that defines the center of the box.

  • front – normalized (i, j, k) that defines the front direction of the box.

  • up – normalized (i, j, k) that defines the up direction of the box.

  • left – normalized (i, j, k) that defines the left direction of the box.

  • size – (width, height, depth) that defines the size of the box, as measured from edge to edge.

  • label_class – integer specifying the classification label. If an LUT is specified in create_lines() this will be used to determine the color of the box.

  • confidence – confidence level of the box.

  • meta – a user-defined string (optional).

  • show_class – displays the class label in text near the box (optional).

  • show_confidence – displays the confidence value in text near the box (optional).

  • show_meta – displays the meta string in text near the box (optional).

  • identifier – a unique integer that defines the id for the box (optional, will be generated if not provided).

  • arrow_length – the length of the arrow in the front_direct. Set to zero to disable the arrow (optional).

static create_lines(boxes, lut=None, out_format='lineset')#

Creates a LineSet that can be used to render the boxes.

Parameters:

  • boxes – the list of bounding boxes

  • lut – a ml3d.vis.LabelLUT that is used to look up the color based on the label_class argument of the BoundingBox3D constructor. If not provided, a color of 50% grey will be used. (optional)

  • out_format (str) – Output format. Can be “lineset” (default) for the Open3D lineset or “dict” for a dictionary of lineset properties.

Returns:

open3d.geometry.LineSet For out_format == “dict”: Dictionary of lineset properties

(“vertex_positions”, “line_indices”, “line_colors”, “bbox_labels”, “bbox_confidences”).

Return type:

For out_format == “lineset”

static plot_rect3d_on_img(img, num_rects, rect_corners, line_indices, color=None, thickness=1)#

Plot the boundary lines of 3D rectangular on 2D images.

Parameters:

  • img (numpy.array) – The numpy array of image.

  • num_rects (int) – Number of 3D rectangulars.

  • rect_corners (numpy.array) – Coordinates of the corners of 3D rectangulars. Should be in the shape of [num_rect, 8, 2] or [num_rect, 14, 2] if counting arrows.

  • line_indices (numpy.array) – indicates connectivity of lines between rect_corners. Should be in the shape of [num_rect, 12, 2] or [num_rect, 17, 2] if counting arrows.

  • color (tuple[int]) – The color to draw bboxes. Default: (1.0, 1.0, 1.0), i.e. white.

  • thickness (int, optional) – The thickness of bboxes. Default: 1.

static project_to_img(boxes, img, lidar2img_rt=array([1., 1., 1., 1.]), lut=None)#

Returns image with projected 3D bboxes

Parameters:

  • boxes – the list of bounding boxes

  • img – an RGB image

  • lidar2img_rt – 4x4 transformation from lidar frame to image plane

  • lut – a ml3d.vis.LabelLUT that is used to look up the color based on the label_class argument of the BoundingBox3D constructor. If not provided, a color of 50% grey will be used. (optional)

next_id = 1#