CustomBoxObjectData Class Reference

Class that store externally detected objects. More...

Functions
str	unique_object_id (self)
	Unique id to help identify and track AI detections. More...
np.array[int][int]	bounding_box_2d (self)
	2D bounding box of the object represented as four 2D points starting at the top left corner and rotation clockwise. More...
int	label (self)
	Object label. More...
float	probability (self)
	Detection confidence value of the object. More...
bool	is_grounded (self)
	Provide hypothesis about the object movements (degrees of freedom or DoF) to improve the object tracking. More...
bool	is_static (self)
	Provide hypothesis about the object staticity to improve the object tracking. More...
float	tracking_timeout (self)
	Maximum tracking time threshold (in seconds) before dropping the tracked object when unseen for this amount of time. More...
float	tracking_max_dist (self)
	Maximum tracking distance threshold (in meters) before dropping the tracked object when unseen for this amount of meters. More...

Detailed Description

Class that store externally detected objects.

The objects can be ingested with sl.Camera.ingest_custom_box_objects() to extract 3D and tracking information over time.

Functions

unique_object_id()

str unique_object_id

(

self

)

Unique id to help identify and track AI detections.

It can be either generated externally, or by using generate_unique_id() or left empty.

bounding_box_2d()

np.array[int][int] bounding_box_2d

(

self

)

2D bounding box of the object represented as four 2D points starting at the top left corner and rotation clockwise.

Note

Expressed in pixels on the original image resolution, [0, 0] is the top left corner.

A ------ B
| Object |
D ------ C

label()

int label

(

self

)

Object label.

This information is passed-through and can be used to improve object tracking.

Note

It should define an object class. This means that any similar object (in classification) should share the same label number.

probability()

float probability

(

self

)

Detection confidence value of the object.

Note

The value should be in [0-1].

It can be used to improve the object tracking.

is_grounded()

bool is_grounded

(

self

)

Provide hypothesis about the object movements (degrees of freedom or DoF) to improve the object tracking.

• true: 2 DoF projected alongside the floor plane. Case for object standing on the ground such as person, vehicle, etc.
  The projection implies that the objects cannot be superposed on multiple horizontal levels.
• false: 6 DoF (full 3D movements are allowed).

Note

This parameter cannot be changed for a given object tracking id.

It is advised to set it by labels to avoid issues.

is_static()

bool is_static

(

self

)

Provide hypothesis about the object staticity to improve the object tracking.

• true: the object will be assumed to never move nor being moved.
• false: the object will be assumed to be able to move or being moved.

tracking_timeout()

float tracking_timeout

(

self

)

Maximum tracking time threshold (in seconds) before dropping the tracked object when unseen for this amount of time.

By default, let the tracker decide internally based on the internal sub class of the tracked object. Only valid for static object.

tracking_max_dist()

float tracking_max_dist

(

self

)

Maximum tracking distance threshold (in meters) before dropping the tracked object when unseen for this amount of meters.

By default, do not discard tracked object based on distance. Only valid for static object.