Skip to content

Instantly share code, notes, and snippets.

Embed
What would you like to do?
dice loss
class DICELossMultiClass(nn.Module):
def __init__(self):
super(DICELossMultiClass, self).__init__()
def forward(self, output, mask):
probs = output[:, 1, :, :]
mask = torch.squeeze(mask, 1)
num = probs * mask
num = torch.sum(num, 2)
num = torch.sum(num, 1)
# print('num : ', num )
den1 = probs * probs
# print('den1 : ', den1.size())
den1 = torch.sum(den1, 2)
den1 = torch.sum(den1, 1)
# print('den1 2 : ', den1.size())
den2 = mask * mask
# print('den2 : ', den2.size())
den2 = torch.sum(den2, 2)
den2 = torch.sum(den2, 1)
# print('den2 2 : ', den2.size())
eps = 0.0000001
dice = 2 * ((num + eps) / (den1 + den2 + eps))
# dice_eso = dice[:, 1:]
dice_eso = dice
loss = 1 - torch.sum(dice_eso) / dice_eso.size(0)
return loss
class DICELoss(nn.Module):
def __init__(self):
super(DICELoss, self).__init__()
def forward(self, output, mask):
probs = torch.squeeze(output, 1)
mask = torch.squeeze(mask, 1)
intersection = probs * mask
intersection = torch.sum(intersection, 2)
intersection = torch.sum(intersection, 1)
# print( num )
den1 = probs * probs
# print(den1.size())
den1 = torch.sum(den1, 2)
den1 = torch.sum(den1, 1)
# print(den1.size())
den2 = mask * mask
# print(den2.size())
den2 = torch.sum(den2, 2)
den2 = torch.sum(den2, 1)
# print(den2.size())
eps = 0.0000001
dice = 2 * ((intersection + eps) / (den1 + den2 + eps))
# dice_eso = dice[:, 1:]
dice_eso = dice
loss = 1 - torch.sum(dice_eso) / dice_eso.size(0)
return loss
class DICELoss3D(nn.Module):
def __init__(self):
super(DICELoss3D, self).__init__()
def forward(self, output, mask):
batch_size, channel, x, y, z = output.size()
total_loss = 0
for i in range(batch_size):
for j in range(z):
loss = 0
output_z = output[i:i + 1, :, :, :, j]
label_z = mask[i, :, :, :, j]
softmax_output_z = nn.Softmax2d()(output_z)
logsoftmax_output_z = torch.log(softmax_output_z)
loss = nn.NLLLoss2d()(logsoftmax_output_z, label_z)
total_loss += loss
return total_loss
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment