mmcls.core.precision

mmcls.core.precision(pred, target, average_mode='macro', thrs=0.0)

Calculate precision 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

Precision.

Return type

float | np.array | list[float | np.array]

Args	thrs is number	thrs is tuple
average_mode = “macro”	float	list[float]
average_mode = “none”	np.array	list[np.array]