def _sk_iou_multidim_multiclass(preds, target, average=None):
sk_preds = preds.view(-1).numpy()
sk_target = target.view(-1).numpy()
return sk_jaccard_score(y_true=sk_target, y_pred=sk_preds, average=average)
def _sk_iou_multilabel_prob(preds, target, average=None):
sk_preds = (preds.view(-1).numpy() >= THRESHOLD).astype(np.uint8)
sk_target = target.view(-1).numpy()
return sk_jaccard_score(y_true=sk_target, y_pred=sk_preds, average=average)
def _sk_iou_multidim_multiclass_prob(preds, target, average=None):
sk_preds = torch.argmax(preds, dim=len(preds.shape) - 2).view(-1).numpy()
sk_target = target.view(-1).numpy()
return sk_jaccard_score(y_true=sk_target, y_pred=sk_preds, average=average)
def _sk_jaccard_binary(preds, target, average=None):
sk_preds = preds.view(-1).numpy()
sk_target = target.view(-1).numpy()
return sk_jaccard_score(y_true=sk_target, y_pred=sk_preds, average=average)
