Box3D is a type of label with a 3D bounding box on point cloud, which is often used for 3D object detection.
Currently, Box3D labels applies to point data only.
Each point cloud can be assigned with multiple Box3D label.
The structure of one Box3D label is like:
{
"box3d": {
"translation": {
"x": <float>
"y": <float>
"z": <float>
},
"rotation": {
"w": <float>
"x": <float>
"y": <float>
"z": <float>
},
"size": {
"x": <float>
"y": <float>
"z": <float>
}
},
"category": <str>
"attributes": {
<key>: <value>
...
...
},
"instance": <str>
}To create a ~tensorbay.label.label_box.LabeledBox3D label:
>>> from tensorbay.label import LabeledBox3D >>> box3d_label = LabeledBox3D( ... size=[10, 20, 30], ... translation=[0, 0, 0], ... rotation=[1, 0, 0, 0], ... category="category", ... attributes={"attribute_name": "attribute_value"}, ... instance="instance_ID" ... ) >>> box3d_label LabeledBox3D( (size): Vector3D(10, 20, 30), (translation): Vector3D(0, 0, 0), (rotation): quaternion(1.0, 0.0, 0.0, 0.0), (category): 'category', (attributes): {...}, (instance): 'instance_ID' )
~tensorbay.label.label_box.LabeledBox3D extends ~tensorbay.geometry.box.Box3D.
To construct a ~tensorbay.label.label_box.LabeledBox3D instance with only the geometry information, use the transform matrix and the size of the 3D bounding box, or use translation and rotation to represent the transform of the 3D bounding box.
>>> LabeledBox3D( ... size=[10, 20, 30], ... transform_matrix=[[1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 1, 0]], ... ) LabeledBox3D( (size): Vector3D(10, 20, 30) (translation): Vector3D(0, 0, 0), (rotation): quaternion(1.0, -0.0, -0.0, -0.0), ) >>> LabeledBox3D( ... size=[10, 20, 30], ... translation=[0, 0, 0], ... rotation=[1, 0, 0, 0], ... ) LabeledBox3D( (size): Vector3D(10, 20, 30) (translation): Vector3D(0, 0, 0), (rotation): quaternion(1.0, 0.0, 0.0, 0.0), )
It contains the basic geometry information of the 3D bounding box.
>>> box3d_label.transform Transform3D( (translation): Vector3D(0, 0, 0), (rotation): quaternion(1.0, 0.0, 0.0, 0.0) ) >>> box3d_label.translation Vector3D(0, 0, 0) >>> box3d_label.rotation quaternion(1.0, 0.0, 0.0, 0.0) >>> box3d_label.size Vector3D(10, 20, 30) >>> box3d_label.volumn() 6000
The category of the object inside the 3D bounding box. See reference/label_format/CommonLabelProperties:category for details.
Attributes are the additional information about this object, which are stored in key-value pairs. See reference/label_format/CommonLabelProperties:attributes for details.
Instance is the unique id for the object inside of the 3D bounding box, which is mostly used for tracking tasks. See reference/label_format/CommonLabelProperties:instance for details.
Before adding the Box3D labels to data, ~tensorbay.label.label_box.Box3DSubcatalog should be defined.
~tensorbay.label.label_box.Box3DSubcatalog has categories, attributes and tracking information, see reference/label_format/CommonSubcatalogProperties:common category information, reference/label_format/CommonSubcatalogProperties:attributes information and reference/label_format/CommonSubcatalogProperties:tracking information for details.
The catalog with only Box3D subcatalog is typically stored in a json file as follows:
{
"BOX3D": { <object>*
"description": <string>! -- Subcatalog description, (default: "").
"isTracking": <boolean>! -- Whether this type of label in the dataset contains tracking
information, (default: false).
"categoryDelimiter": <string> -- The delimiter in category names indicating subcategories.
Recommended delimiter is ".". There is no "categoryDelimiter"
field by default which means the category is of one level.
"categories": [ <array> -- Category list, which contains all category information.
{
"name": <string>* -- Category name.
"description": <string>! -- Category description, (default: "").
},
...
...
],
"attributes": [ <array> -- Attribute list, which contains all attribute information.
{
"name": <string>* -- Attribute name.
"enum": [...], <array> -- All possible options for the attribute.
"type": <string or array> -- Type of the attribute including "boolean", "integer",
"number", "string", "array" and "null". And it is not
required when "enum" is provided.
"minimum": <number> -- Minimum value of the attribute when type is "number".
"maximum": <number> -- Maximum value of the attribute when type is "number".
"items": { <object> -- Used only if the attribute type is "array".
"enum": [...], <array> -- All possible options for elements in the attribute array.
"type": <string or array> -- Type of elements in the attribute array.
"minimum": <number> -- Minimum value of elements in the attribute array when type is
"number".
"maximum": <number> -- Maximum value of elements in the attribute array when type is
"number".
},
"parentCategories": [...], <array> -- Indicates the category to which the attribute belongs. Do not
add this field if it is a global attribute.
"description": <string>! -- Attribute description, (default: "").
},
...
...
]
}
}Note
* indicates that the field is required. ! indicates that the field has a default value.
To add a ~tensorbay.label.label_box.LabeledBox3D label to one data:
>>> from tensorbay.dataset import Data >>> data = Data("local_path") >>> data.label.box3d = [] >>> data.label.box3d.append(box3d_label)
Note
One data may contain multiple Box3D labels, so the Data.label.box3d<tensorbay.dataset.data.Data.label.box3d> must be a list.