tensorbay.label.label_polygon¶

LabeledPolygon, PolygonSubcatalog.

PolygonSubcatalog defines the subcatalog for polygon type of labels.

LabeledPolygon is the polygon type of label, which is often used for CV tasks such as semantic segmentation.

class tensorbay.label.label_polygon.PolygonSubcatalog(is_tracking: bool = False)[source]¶

Bases: tensorbay.utility.type.TypeMixin[tensorbay.label.basic.LabelType], tensorbay.utility.repr.ReprMixin, tensorbay.utility.attr.AttrsMixin

This class defines the subcatalog for polygon type of labels.

Parameters: is_tracking – A boolean value indicates whether the corresponding subcatalog contains tracking information.

description¶

The description of the entire polygon subcatalog.

Type: str

categories¶

All the possible categories in the corresponding dataset stored in a NameList with the category names as keys and the CategoryInfo as values.

Type: tensorbay.utility.name.NameList[tensorbay.label.supports.CategoryInfo]

category_delimiter¶

The delimiter in category values indicating parent-child relationship.

Type: str

attributes¶

All the possible attributes in the corresponding dataset stored in a NameList with the attribute names as keys and the AttributeInfo as values.

Type: tensorbay.utility.name.NameList[tensorbay.label.attributes.AttributeInfo]

is_tracking¶

Whether the Subcatalog contains tracking information.

Type: bool

Examples

Initialization Method 1: Init from PolygonSubcatalog.loads() method.

>>> catalog = {
...     "POLYGON": {
...         "isTracking": True,
...         "categories": [{"name": "0"}, {"name": "1"}],
...         "attributes": [{"name": "gender", "enum": ["male", "female"]}],
...     }
... }
>>> PolygonSubcatalog.loads(catalog["POLYGON"])
PolygonSubcatalog(
  (is_tracking): True,
  (categories): NameList [...],
  (attributes): NameList [...]
)

Initialization Method 2: Init an empty PolygonSubcatalog and then add the attributes.

>>> from tensorbay.utility import NameList
>>> from tensorbay.label import CategoryInfo, AttributeInfo
>>> categories = NameList()
>>> categories.append(CategoryInfo("a"))
>>> attributes = NameList()
>>> attributes.append(AttributeInfo("gender", enum=["female", "male"]))
>>> polygon_subcatalog = PolygonSubcatalog()
>>> polygon_subcatalog.is_tracking = True
>>> polygon_subcatalog.categories = categories
>>> polygon_subcatalog.attributes = attributes
>>> polygon_subcatalog
PolygonSubcatalog(
  (is_tracking): True,
  (categories): NameList [...],
  (attributes): NameList [...]
)

class tensorbay.label.label_polygon.LabeledPolygon(points: Optional[Iterable[Iterable[float]]] = None, *, category: Optional[str] = None, attributes: Optional[Dict[str, Any]] = None, instance: Optional[str] = None)[source]¶

Bases: tensorbay.utility.attr.AttrsMixin, tensorbay.utility.type.TypeMixin[tensorbay.label.basic.LabelType], tensorbay.utility.repr.ReprMixin

This class defines the concept of polygon label.

LabeledPolygon is the polygon type of label, which is often used for CV tasks such as semantic segmentation.

Parameters

points – A list of 2D points representing the vertexes of the polygon.
category – The category of the label.
attributes – The attributs of the label.
instance – The instance id of the label.

category¶

The category of the label.

Type: str

attributes¶

The attributes of the label.

Type: Dict[str, Union[str, int, float, bool, List[Union[str, int, float, bool]]]]

instance¶

The instance id of the label.

Type: str

Examples

>>> LabeledPolygon(
...     [(1, 2), (2, 3), (1, 3)],
...     category = "example",
...     attributes = {"key": "value"},
...     instance = "123",
... )
LabeledPolygon [
  Vector2D(1, 2),
  Vector2D(2, 3),
  Vector2D(1, 3)
](
  (category): 'example',
  (attributes): {...},
  (instance): '123'
)

classmethod loads(contents: Dict[str, Any]) → tensorbay.label.label_polygon._T[source]¶

Loads a LabeledPolygon from a dict containing the information of the label.

Parameters: contents – A dict containing the information of the polygon label.
Returns: The loaded LabeledPolygon object.

Examples

>>> contents = {
...     "polygon": [
...         {"x": 1, "y": 2},
...         {"x": 2, "y": 3},
...         {"x": 1, "y": 3},
...     ],
...     "category": "example",
...     "attributes": {"key": "value"},
...     "instance": "12345",
... }
>>> LabeledPolygon.loads(contents)
LabeledPolygon [
  Vector2D(1, 2),
  Vector2D(2, 3),
  Vector2D(1, 3)
](
  (category): 'example',
  (attributes): {...},
  (instance): '12345'
)

dumps() → Dict[str, Any][source]¶

Dumps the current polygon label into a dict.

Returns: A dict containing all the information of the polygon label.

Examples

>>> labeledpolygon = LabeledPolygon(
...     [(1, 2), (2, 3), (1, 3)],
...     category = "example",
...     attributes = {"key": "value"},
...     instance = "123",
... )
>>> labeledpolygon.dumps()
{
    'category': 'example',
    'attributes': {'key': 'value'},
    'instance': '123',
    'polygon': [{'x': 1, 'y': 2}, {'x': 2, 'y': 3}, {'x': 1, 'y': 3}],
}