jiaxuan-li / mgu-net Goto Github PK

First of all, thanks Jiaxuan-Li for your work and how tidy the code base is. It worked for me almost straight off the shelf!

Regarding the public dataset - it is not in the format the code expects, but rather in Matlab objects. I guess you've been using a script to transform it. Is that the case? If so, would it be possible to share it?

Thanks!
Dan

In the Dice loss, there's a line:
input = torch.exp(input)
but shouldn't it be the sigmoid function? The input is the last conv layer output from the network and a sigmoid will convert it to probability within [0,1]
input = torch.sigmoid(input)

(MGU-Net-main) E:_BACKUP\lbc\MGU-Net-main>python main_ts.py --name tsmgunet -d ./data/dataset --batch-size 1 --epoch 50 --lr 0.001
torch version: 1.10.0
Total amount of train images is : 96
Total amount of eval images is : 96
Total amount of test images is : 96
data_dir : ./data/dataset
name : tsmgunet
workers : 2
step : 20
batch_size : 1
epochs : 50
lr : 0.001
lr_mode : step
momentum : 0.9
weight_decay : 0.0001
t : t1
model_path :
############### tsmgunet ###############
[2021-12-03 04:27:43,359 main_ts.py:278 train_seg] Epoch: [0]
Traceback (most recent call last):
File "main_ts.py", line 394, in
main()
File "main_ts.py", line 386, in main
train_seg(args,train_result_path,train_loader,eval_loader)
File "main_ts.py", line 280, in train_seg
loss,dice_train,dice_1,dice_2,dice_3,dice_4,dice_5,dice_6,dice_7,dice_8,dice_9,dice_10 = train(args,train_loader, model,criterion1, criterion2, optimizer,epoch)
File "main_ts.py", line 53, in train
output_seg1,_,output_seg = model(input_var1)
File "E:\anaconda\envs\MGU-Net-main\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "E:\anaconda\envs\MGU-Net-main\lib\site-packages\torch\nn\parallel\data_parallel.py", line 166, in forward
return self.module(*inputs[0], **kwargs[0])
File "E:\anaconda\envs\MGU-Net-main\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "E:_BACKUP\lbc\MGU-Net-main\models\nets\TSNet.py", line 16, in forward
out1 = self.stage1(inputs)
File "E:\anaconda\envs\MGU-Net-main\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "E:_BACKUP\lbc\MGU-Net-main\models\nets\MGUNet.py", line 106, in forward
up3 = self.up_concat3(center, conv3)
File "E:\anaconda\envs\MGU-Net-main\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "E:_BACKUP\lbc\MGU-Net-main\models\utils\utils.py", line 91, in forward
outputs0 = torch.cat([outputs0,input[i]], 1)
RuntimeError: Sizes of tensors must match except in dimension 1. Expected size 52 but got size 53 for tensor number 1 in the list.
I would like to ask what went wrong

test_dataset的参数phase是不是应该设置为predict更加的合理，因为设置test或eval实际上调用的是一个函数

First of all, thank you for your contribution, Jiaxuan Li. Since I have not been able to get a response after filling out the data collection form, I would like to ask if you can give me a way to get the dataset. My Google email is [email protected].

Thanks!
Tom