tlc.integration.super_gradients.callbacks.detection_callback

Callback for collecting predictions from SuperGradients detection models.

Module Contents

Classes

Class	Description
DetectionMetricsCollectionCallback

API

class DetectionMetricsCollectionCallback(

project_name: str | None = None,

run_name: str | None = None,

run_description: str | None = None,

image_column_name: str = 'image',

label_column_name: str | None = None,

metrics_collection_epochs: list[int] | None = None,

collect_metrics_on_train_end: bool = True,

collect_val_only: bool = False,

batch_size: int | None = 32,

pipeline_params: PipelineParams | dict[str, Any] | None = None,

collect_predictions: bool | None = None,

collect_embeddings: bool = False,

embeddings_dim: int = 2,

embeddings_method: Literal[pacmap, umap] = 'pacmap',

inference_chunk_size: int = 5000,

)

Bases: tlc.integration.super_gradients.callbacks.base_callback.MetricsCollectionCallback

property label_column_name: str

compute_metrics(

images: list[str],

predictions: super_gradients.training.utils.predict.prediction_results.ImagesDetectionPrediction | super_gradients.training.utils.predict.prediction_results.ImageDetectionPrediction,

table: Table,

) → dict[str, Any]

Compute metrics from a batch of data and corresponding predictions.

metrics_column_schemas(

table: Table,

) → dict[str, Schema]

Return the column schemas for the metrics of this callback.