mmcls.core¶

This package includes some runtime components. These components are useful in classification tasks but not supported by MMCV yet.

Note

Some components may be moved to MMCV in the future.

mmcls.core

Evaluation ¶

Evaluation metrics calculation functions

`precision`	Calculate precision according to the prediction and target.
`recall`	Calculate recall according to the prediction and target.
`f1_score`	Calculate F1 score according to the prediction and target.
`precision_recall_f1`	Calculate precision, recall and f1 score according to the prediction and target.
`average_precision`	Calculate the average precision for a single class.
`mAP`	Calculate the mean average precision with respect of classes.
`support`	Calculate the total number of occurrences of each label according to the prediction and target.
`average_performance`	Calculate CP, CR, CF1, OP, OR, OF1, where C stands for per-class average, O stands for overall average, P stands for precision, R stands for recall and F1 stands for F1-score.
`calculate_confusion_matrix`	Calculate confusion matrix according to the prediction and target.

`ClassNumCheckHook`
`PreciseBNHook`	Precise BN hook.
`CosineAnnealingCooldownLrUpdaterHook`	Cosine annealing learning rate scheduler with cooldown.

A pure pytorch variant of FuseLAMB (NvLamb variant) optimizer.