b8f55323541eae6bbdaf348932b4eaa67320c432,robosat/metrics.py,MeanIoU,add,#MeanIoU#,22

Before Change

        confusion = predicted / actual

        matrix = np.array(
            [
                [
                    torch.sum(torch.isnan(confusion)).item(),
                    torch.sum(confusion == float("inf")).item(),
                ],
                [torch.sum(confusion == 0).item(), torch.sum(confusion == 1).item()],
            ]
        )

        if self.confusion_matrix is None:
            self.confusion_matrix = matrix

After Change

        confusion = predicted / actual

        tn = torch.sum(torch.isnan(confusion)).item()
        fn = torch.sum(confusion == float("inf")).item()
        fp = torch.sum(confusion == 0).item()
        tp = torch.sum(confusion == 1).item()

        matrix = np.array([[tn, fn], [fp, tp]])

        if self.confusion_matrix is None:
            self.confusion_matrix = matrix

Instances