import torch

from .utils import *

import numpy as np

def IoU_loss(input, target, threshold=0.5):

    """

    2d dice loss

    :param input: predict tensor

    :param target: target tensor

    :return: scalar loss value

    """

    input = input > 0.5

    target = target == torch.max(target)

    input = to_float_and_cuda(input)

    target = to_float_and_cuda(target)

    num = input * target

    num = torch.sum(num, dim=2)

    num = torch.sum(num, dim=2)

    den1 = input * input

    den1 = torch.sum(den1, dim=2)

    den1 = torch.sum(den1, dim=2)

    den2 = target * target

    den2 = torch.sum(den2, dim=2)

    den2 = torch.sum(den2, dim=2)

    iou =  num / (den1 + den2 - num) + 1e-6

    iou_total = 1 - 1 * torch.sum(iou) / iou.size(0)  # divide by batchsize

    return iou_total