tfma.metrics.SemanticSegmentationFalsePositive

Calculates the true postive for semantic segmentation.

Inherits From: Metric

tfma.metrics.SemanticSegmentationFalsePositive(
    class_ids: List[int],
    ground_truth_key: str,
    prediction_key: str,
    decode_ground_truth: bool = True,
    decode_prediction: bool = False,
    ignore_ground_truth_id: Optional[int] = None,
    name: Optional[str] = None
)

class_idsthe class ids for calculating metrics.
ground_truth_keythe key for storing the ground truth of encoded image with class ids.
prediction_keythe key for storing the predictions of encoded image with class ids.
decode_ground_truthIf true, the ground truth is assumed to be bytes of images and will be decoded. By default it is true assuming the label is the bytes of image.
decode_predictionIf true, the prediction is assumed to be bytes of images and will be decoded. By default it is false assuming the model outputs numpy arrays or tensors.
ignore_ground_truth_id(Optional) The id of ground truth to be ignored.
name(Optional) string name of the metric instance.

compute_confidence_intervalWhether to compute confidence intervals for this metric.

Note that this may not completely remove the computational overhead involved in computing a given metric. This is only respected by the jackknife confidence interval method.

Methods

computations

View source

computations(
    eval_config: Optional[tfma.EvalConfig] = None,
    schema: Optional[schema_pb2.Schema] = None,
    model_names: Optional[List[str]] = None,
    output_names: Optional[List[str]] = None,
    sub_keys: Optional[List[Optional[SubKey]]] = None,
    aggregation_type: Optional[AggregationType] = None,
    class_weights: Optional[Dict[int, float]] = None,
    example_weighted: bool = False,
    query_key: Optional[str] = None
) -> tfma.metrics.MetricComputations

Creates computations associated with metric.

from_config

View source

@classmethod
from_config(
    config: Dict[str, Any]
) -> 'Metric'

get_config

View source

get_config() -> Dict[str, Any]

Returns serializable config.