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mmcls.core.precision_recall_f1

mmcls.core.precision_recall_f1(pred, target, average_mode='macro', thrs=0.0)[source]

Calculate precision, recall and f1 score according to the prediction and target.

Parameters
  • pred (torch.Tensor | np.array) – The model prediction with shape (N, C).

  • target (torch.Tensor | np.array) – The target of each prediction with shape (N, 1) or (N,).

  • average_mode (str) – The type of averaging performed on the result. Options are ‘macro’ and ‘none’. If ‘none’, the scores for each class are returned. If ‘macro’, calculate metrics for each class, and find their unweighted mean. Defaults to ‘macro’.

  • thrs (Number | tuple[Number], optional) – Predictions with scores under the thresholds are considered negative. Default to 0.

Returns

tuple containing precision, recall, f1 score.

The type of precision, recall, f1 score is one of the following:

Args

thrs is number

thrs is tuple

average_mode = “macro”

float

list[float]

average_mode = “none”

np.array

list[np.array]

Return type

tuple

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