tensorbay.label.label_mask#
The implementation of the TensorBay mask label.
- class tensorbay.label.label_mask.SemanticMaskSubcatalog(description='')[source]#
Bases:
tensorbay.label.basic.SubcatalogBase
,tensorbay.label.supports.MaskCategoriesMixin
,tensorbay.label.supports.AttributesMixin
This class defines the subcatalog for semantic mask type of labels.
- Parameters
description (str) –
- Return type
None
- description#
The description of the entire semantic mask subcatalog.
- Type
str
- categories#
All the possible categories in the corresponding dataset stored in a
NameList
with the category names as keys and theCategoryInfo
as values.
- 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 theAttributeInfo
as values.
- is_tracking#
Whether the Subcatalog contains tracking information.
Examples
Initialization Method 1: Init from
SemanticMaskSubcatalog.loads()
method.>>> catalog = { ... "SEMANTIC_MASK": { ... "categories": [ ... {'name': 'cat', "categoryId": 1}, ... {'name': 'dog', "categoryId": 2} ... ], ... "attributes": [{'name': 'occluded', 'type': 'boolean'}], ... } ... } >>> SemanticMaskSubcatalog.loads(catalog["SEMANTIC_MASK"]) SemanticMaskSubcatalog( (categories): NameList [...], (attributes): NameList [...] )
Initialization Method 2: Init an empty SemanticMaskSubcatalog and then add the attributes.
>>> semantic_mask_subcatalog = SemanticMaskSubcatalog() >>> semantic_mask_subcatalog.add_category("cat", 1) >>> semantic_mask_subcatalog.add_category("dog", 2) >>> semantic_mask_subcatalog.add_attribute("occluded", type_="boolean") >>> semantic_mask_subcatalog SemanticMaskSubcatalog( (categories): NameList [...], (attributes): NameList [...] )
- class tensorbay.label.label_mask.InstanceMaskSubcatalog(description='')[source]#
Bases:
tensorbay.label.basic.SubcatalogBase
,tensorbay.label.supports.MaskCategoriesMixin
,tensorbay.label.supports.IsTrackingMixin
,tensorbay.label.supports.AttributesMixin
This class defines the subcatalog for instance mask type of labels.
- Parameters
description (str) –
- Return type
None
- description#
The description of the entire instance mask subcatalog.
- Type
str
- categories#
All the possible categories in the corresponding dataset stored in a
NameList
with the category names as keys and theCategoryInfo
as values.
- 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 theAttributeInfo
as values.
- is_tracking#
Whether the Subcatalog contains tracking information.
- Type
bool
Examples
Initialization Method 1: Init from
InstanceMaskSubcatalog.loads()
method.>>> catalog = { ... "INSTANCE_MASK": { ... "categories": [ ... {'name': 'background', "categoryId": 0} ... ], ... "attributes": [{'name': 'occluded', 'type': 'boolean'}], ... } ... } >>> InstanceMaskSubcatalog.loads(catalog["INSTANCE_MASK"]) InstanceMaskSubcatalog( (is_tracking): False, (categories): NameList [...], (attributes): NameList [...] )
Initialization Method 2: Init an empty InstanceMaskSubcatalog and then add the attributes.
>>> instance_mask_subcatalog = InstanceMaskSubcatalog() >>> instance_mask_subcatalog.add_category("background", 0) >>> instance_mask_subcatalog.add_attribute("occluded", type_="boolean") >>> instance_mask_subcatalog InstanceMaskSubcatalog( (categories): NameList [...], (attributes): NameList [...] )
- class tensorbay.label.label_mask.PanopticMaskSubcatalog(description='')[source]#
Bases:
tensorbay.label.basic.SubcatalogBase
,tensorbay.label.supports.MaskCategoriesMixin
,tensorbay.label.supports.AttributesMixin
This class defines the subcatalog for panoptic mask type of labels.
- Parameters
description (str) –
- Return type
None
- description#
The description of the entire panoptic mask subcatalog.
- Type
str
- categories#
All the possible categories in the corresponding dataset stored in a
NameList
with the category names as keys and theCategoryInfo
as values.
- 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 theAttributeInfo
as values.
- is_tracking#
Whether the Subcatalog contains tracking information.
Examples
Initialization Method 1: Init from
PanopticMaskSubcatalog.loads()
method.>>> catalog = { ... "PANOPTIC_MASK": { ... "categories": [ ... {'name': 'cat', "categoryId": 1}, ... {'name': 'dog', "categoryId": 2} ... ], ... "attributes": [{'name': 'occluded', 'type': 'boolean'}], ... } ... } >>> PanopticMaskSubcatalog.loads(catalog["PANOPTIC_MASK"]) PanopticMaskSubcatalog( (categories): NameList [...], (attributes): NameList [...] )
Initialization Method 2: Init an empty PanopticMaskSubcatalog and then add the attributes.
>>> panoptic_mask_subcatalog = PanopticMaskSubcatalog() >>> panoptic_mask_subcatalog.add_category("cat", 1) >>> panoptic_mask_subcatalog.add_category("dog", 2) >>> panoptic_mask_subcatalog.add_attribute("occluded", type_="boolean") >>> panoptic_mask_subcatalog PanopticMaskSubcatalog( (categories): NameList [...], (attributes): NameList [...] )
- class tensorbay.label.label_mask.SemanticMaskBase[source]#
Bases:
tensorbay.utility.repr.ReprMixin
SemanticMaskBase is a base class for the semantic mask label.
- all_attributes#
The dict of the attributes in this mask, which key is the category id, and the value is the corresponding attributes.
- Type
Dict[int, Dict[str, Union[str, int, float, bool, List[Union[str, int, float, bool]]]]]
- class tensorbay.label.label_mask.InstanceMaskBase[source]#
Bases:
tensorbay.utility.repr.ReprMixin
InstanceMaskBase is a base class for the instance mask label.
- all_attributes#
The dict of the attributes in this mask, which key is the instance id, and the value is the corresponding attributes.
- Type
Dict[int, Dict[str, Union[str, int, float, bool, List[Union[str, int, float, bool]]]]]
- class tensorbay.label.label_mask.PanopticMaskBase[source]#
Bases:
tensorbay.utility.repr.ReprMixin
PanopticMaskBase is a base class for the panoptic mask label.
- Return type
None
- all_attributes#
The dict of the attributes in this mask, which key is the instance id, and the value is the corresponding attributes.
- Type
Dict[int, Dict[str, Union[str, int, float, bool, List[Union[str, int, float, bool]]]]]
- all_category_ids#
The dict of the category id in this mask, which key is the instance id, and the value is the corresponding category id.
- class tensorbay.label.label_mask.SemanticMask(local_path)[source]#
Bases:
tensorbay.label.label_mask.SemanticMaskBase
,tensorbay.utility.file.FileMixin
SemanticMask is a class for the local semantic mask label.
- Parameters
local_path (str) –
- Return type
None
- all_attributes#
The dict of the attributes in this mask, which key is the category id, and the value is the corresponding attributes.
- Type
Dict[int, Dict[str, Union[str, int, float, bool, List[Union[str, int, float, bool]]]]]
- get_callback_body()[source]#
Get the callback request body for uploading.
- Returns
The callback request body, which looks like:
{ "checksum": <str>, "fileSize": <int>, "info": [ { "categoryId": 0, "attributes": { "occluded": True } }, { "categoryId": 1, "attributes": { "occluded": False } } ] }
- Return type
Dict[str, Any]
- class tensorbay.label.label_mask.InstanceMask(local_path)[source]#
Bases:
tensorbay.label.label_mask.InstanceMaskBase
,tensorbay.utility.file.FileMixin
InstanceMask is a class for the local instance mask label.
- Parameters
local_path (str) –
- Return type
None
- all_attributes#
The dict of the attributes in this mask, which key is the instance id, and the value is the corresponding attributes.
- Type
Dict[int, Dict[str, Union[str, int, float, bool, List[Union[str, int, float, bool]]]]]
- get_callback_body()[source]#
Get the callback request body for uploading.
- Returns
The callback request body, which looks like:
{ "checksum": <str>, "fileSize": <int>, "info": [ { "instanceId": 0, "attributes": { "occluded": True } }, { "instanceId": 1, "attributes": { "occluded": False } } ] }
- Return type
Dict[str, Any]
- class tensorbay.label.label_mask.PanopticMask(local_path)[source]#
Bases:
tensorbay.label.label_mask.PanopticMaskBase
,tensorbay.utility.file.FileMixin
PanopticMask is a class for the local panoptic mask label.
- Parameters
local_path (str) –
- Return type
None
- all_attributes#
The dict of the attributes in this mask, which key is the instance id, and the value is the corresponding attributes.
- Type
Dict[int, Dict[str, Union[str, int, float, bool, List[Union[str, int, float, bool]]]]]
- all_category_ids#
The dict of the category id in this mask, which key is the instance id, and the value is the corresponding category id.
- get_callback_body()[source]#
Get the callback request body for uploading.
- Returns
The callback request body, which looks like:
{ "checksum": <str>, "fileSize": <int>, "info": [ { "instanceId": 0, "categoryId": 100, "attributes": { "occluded": True } }, { "instanceId": 1, "categoryId": 101, "attributes": { "occluded": False } } ] }
- Return type
Dict[str, Any]
- class tensorbay.label.label_mask.RemoteSemanticMask(remote_path, *, url=None, cache_path='')[source]#
Bases:
tensorbay.label.label_mask.SemanticMaskBase
,tensorbay.utility.file.RemoteFileMixin
RemoteSemanticMask is a class for the remote semantic mask label.
- Parameters
remote_path (str) –
url (Optional[tensorbay.utility.file.URL]) –
cache_path (str) –
- Return type
None
- all_attributes#
The dict of the attributes in this mask, which key is the category id, and the value is the corresponding attributes.
- Type
Dict[int, Dict[str, Union[str, int, float, bool, List[Union[str, int, float, bool]]]]]
- classmethod from_response_body(body)[source]#
Loads a
RemoteSemanticMask
object from a response body.- Parameters
body (Dict[str, Any]) –
The response body which contains the information of a remote semantic mask, whose format should be like:
{ "remotePath": <str>, "info": [ { "categoryId": 0, "attributes": { "occluded": True } }, { "categoryId": 1, "attributes": { "occluded": False } } ] }
- Returns
The loaded
RemoteSemanticMask
object.- Return type
tensorbay.label.label_mask._T
- class tensorbay.label.label_mask.RemoteInstanceMask(remote_path, *, url=None, cache_path='')[source]#
Bases:
tensorbay.label.label_mask.InstanceMaskBase
,tensorbay.utility.file.RemoteFileMixin
RemoteInstanceMask is a class for the remote instance mask label.
- Parameters
remote_path (str) –
url (Optional[tensorbay.utility.file.URL]) –
cache_path (str) –
- Return type
None
- all_attributes#
The dict of the attributes in this mask, which key is the instance id, and the value is the corresponding attributes.
- Type
Dict[int, Dict[str, Union[str, int, float, bool, List[Union[str, int, float, bool]]]]]
- classmethod from_response_body(body)[source]#
Loads a
RemoteInstanceMask
object from a response body.- Parameters
body (Dict[str, Any]) –
The response body which contains the information of a remote instance mask, whose format should be like:
{ "remotePath": <str>, "info": [ { "instanceId": 0, "attributes": { "occluded": True } }, { "instanceId": 1, "attributes": { "occluded": False } } ] }
- Returns
The loaded
RemoteInstanceMask
object.- Return type
tensorbay.label.label_mask._T
- class tensorbay.label.label_mask.RemotePanopticMask(remote_path, *, url=None)[source]#
Bases:
tensorbay.label.label_mask.PanopticMaskBase
,tensorbay.utility.file.RemoteFileMixin
RemotePanoticMask is a class for the remote panotic mask label.
- Parameters
remote_path (str) –
url (Optional[tensorbay.utility.file.URL]) –
- Return type
None
- all_attributes#
The dict of the attributes in this mask, which key is the instance id, and the value is the corresponding attributes.
- Type
Dict[int, Dict[str, Union[str, int, float, bool, List[Union[str, int, float, bool]]]]]
- classmethod from_response_body(body)[source]#
Loads a
RemotePanopticMask
object from a response body.- Parameters
body (Dict[str, Any]) –
The response body which contains the information of a remote panoptic mask, whose format should be like:
{ "remotePath": <str>, "info": [ { "instanceId": 0, "categoryId": 100, "attributes": { "occluded": True } }, { "instanceId": 1, "categoryId": 101, "attributes": { "occluded": False } } ] }
- Returns
The loaded
RemotePanopticMask
object.- Return type
tensorbay.label.label_mask._T