otx.core.model.keypoint_detection#

Class definition for keypoint detection model entity used in OTX.

Classes

`OTXKeypointDetectionModel`(label_info, ...)	Base class for the keypoint detection models used in OTX.
`OVKeypointDetectionModel`(model_name, ...)	Keypoint detection model compatible for OpenVINO IR inference.

class otx.core.model.keypoint_detection.OTXKeypointDetectionModel(label_info: LabelInfoTypes, input_size: tuple[int, int], optimizer: OptimizerCallable = <function _default_optimizer_callable>, scheduler: LRSchedulerCallable | LRSchedulerListCallable = <function _default_scheduler_callable>, metric: MetricCallable = <function _pck_measure_callable>, torch_compile: bool = False)[source]#

Bases: OTXModel[KeypointDetBatchDataEntity, KeypointDetBatchPredEntity]

Base class for the keypoint detection models used in OTX.

configure_metric() → None[source]#: Configure the metric.

forward_for_tracing(image: Tensor) → Tensor | tuple[Tensor][source]#: Model forward function used for the model tracing during model exportation.

get_classification_layers(prefix: str = 'model.') → dict[str, dict[str, int]][source]#: Get final classification layer information for incremental learning case.

get_dummy_input(batch_size: int = 1) → KeypointDetBatchDataEntity[source]#

Generates a dummy input, suitable for launching forward() on it.

Parameters:: batch_size (int, optional) – number of elements in a dummy input sequence. Defaults to 1.
Returns:: An entity containing randomly generated inference data.
Return type:: KeypointDetBatchDataEntity

class otx.core.model.keypoint_detection.OVKeypointDetectionModel(model_name: str, model_type: str = 'keypoint_detection', async_inference: bool = True, max_num_requests: int | None = None, use_throughput_mode: bool = True, model_api_configuration: dict[str, ~typing.Any] | None = None, metric: ~typing.Callable[[~otx.core.types.label.LabelInfo], ~torchmetrics.metric.Metric | ~torchmetrics.collections.MetricCollection] = <function _pck_measure_callable>, **kwargs)[source]#

Bases: OVModel[KeypointDetBatchDataEntity, KeypointDetBatchPredEntity]

Keypoint detection model compatible for OpenVINO IR inference.

It can consume OpenVINO IR model path or model name from Intel OMZ repository and create the OTX keypoint detection model compatible for OTX testing pipeline.

configure_metric() → None[source]#: Configure the metric.