9a8d91022cfde0a380d8700be76d6ddbd716a2af,robosat/tools/train.py,,validate,#Any#Any#Any#Any#Any#,156

Before Change

        for mask, output in zip(masks, outputs):
            mask = mask.data.cpu().numpy()
            prediction = output.data.max(0)[1].cpu().numpy()
            iou.add(mask.ravel(), prediction.ravel())

    assert num_samples > 0, "dataset contains validation images and labels"

    return {"loss": running_loss / num_samples, "iou": iou.get()}

After Change

        running_loss += loss.item()

        for mask, output in zip(masks, outputs):
            iou.add(mask.float(), output.max(0)[1].float())

    assert num_samples > 0, "dataset contains validation images and labels"

    return {"loss": running_loss / num_samples, "iou": iou.get()}

Instances