Source code for kornia.metrics.accuracy

from typing import List, Tuple

from kornia.core import Tensor

[docs]def accuracy(input: Tensor, target: Tensor, topk: Tuple[int, ...] = (1,)) -> List[Tensor]: """Computes the accuracy over the k top predictions for the specified values of k. Args: input: the input tensor with the logits to evaluate. target: the tensor containing the ground truth. topk: the expected topk ranking. Example: >>> logits = torch.tensor([[0, 1, 0]]) >>> target = torch.tensor([[1]]) >>> accuracy(logits, target) [tensor(100.)] """ maxk = min(max(topk), input.size()[1]) batch_size = target.size(0) _, pred = input.topk(maxk, 1, True, True) pred = pred.t() correct = pred.eq(target.reshape(1, -1).expand_as(pred)) return [correct[: min(k, maxk)].reshape(-1).float().sum(0) * 100.0 / batch_size for k in topk]