Comments (12)
all1-know
commented on July 19, 2024
1
Thank you very much for your reply, I ran the code again this afternoon with your dataset, and it was not much different from the results in the paper table.
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JCruan519
commented on July 19, 2024
2022-04-23 04:21:43 - val epoch: 299, loss: 0.3479
2022-04-23 04:21:43 - train: epoch 300, iter:0, loss: 0.1446, lr: 0.000999023230571994
2022-04-23 04:21:49 - train: epoch 300, iter:20, loss: 0.1743, lr: 0.000999023230571994
2022-04-23 04:21:55 - train: epoch 300, iter:40, loss: 0.1683, lr: 0.000999023230571994
2022-04-23 04:22:00 - train: epoch 300, iter:60, loss: 0.1629, lr: 0.000999023230571994
2022-04-23 04:22:06 - train: epoch 300, iter:80, loss: 0.1638, lr: 0.000999023230571994
2022-04-23 04:22:12 - train: epoch 300, iter:100, loss: 0.1653, lr: 0.000999023230571994
2022-04-23 04:22:17 - train: epoch 300, iter:120, loss: 0.1645, lr: 0.000999023230571994
2022-04-23 04:22:23 - train: epoch 300, iter:140, loss: 0.1616, lr: 0.000999023230571994
2022-04-23 04:22:29 - train: epoch 300, iter:160, loss: 0.1630, lr: 0.000999023230571994
2022-04-23 04:22:36 - train: epoch 300, iter:180, loss: 0.1610, lr: 0.000999023230571994
2022-04-23 04:22:42 - train: epoch 300, iter:200, loss: 0.1623, lr: 0.000999023230571994
2022-04-23 04:22:48 - train: epoch 300, iter:220, loss: 0.1662, lr: 0.000999023230571994
2022-04-23 04:23:55 - val epoch: 300, loss: 0.3976, miou: 0.7376317996433632, f1_or_dsc: 0.8490081728416308, accuracy: 0.9178844489673577, specificity: 0.9080565533258367, sensitivity: 0.94843156776658, confusion_matrix: [[36379921 3683576]
[ 664696 12224895]]
2022-04-23 04:25:04 - test of best model, loss: 0.2816,miou: 0.8071077684988276, f1_or_dsc: 0.8932591432212099, accuracy: 0.9481092018656211, specificity: 0.9661648357855531, sensitivity: 0.8919885821047386, confusion_matrix: [[38707942 1355555]
[ 1392223 11497368]]
Hi, thanks for following our work. The above result is the best one when training and testing our model on the ISIC2018 dataset. And the datasets of two datasets and the all weights will be update in the readme.md file later in the form of a link.
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all1-know
commented on July 19, 2024
First of all, thanks for your reply. I have another question, the following is my log, but the result is very different with yours (my environment is ubuntu server and RTX3090). The code has not been changed, and the dataset uses isic2018_256.
2023-05-05 18:05:59 - train: epoch 300, iter:0, loss: 0.5077, lr: 0.000999023230571994
2023-05-05 18:06:00 - train: epoch 300, iter:20, loss: 0.6688, lr: 0.000999023230571994
2023-05-05 18:06:01 - train: epoch 300, iter:40, loss: 0.6885, lr: 0.000999023230571994
2023-05-05 18:06:02 - train: epoch 300, iter:60, loss: 0.6861, lr: 0.000999023230571994
2023-05-05 18:06:02 - train: epoch 300, iter:80, loss: 0.6950, lr: 0.000999023230571994
2023-05-05 18:06:03 - train: epoch 300, iter:100, loss: 0.6876, lr: 0.000999023230571994
2023-05-05 18:06:04 - train: epoch 300, iter:120, loss: 0.6910, lr: 0.000999023230571994
2023-05-05 18:06:05 - train: epoch 300, iter:140, loss: 0.6931, lr: 0.000999023230571994
2023-05-05 18:06:06 - train: epoch 300, iter:160, loss: 0.6945, lr: 0.000999023230571994
2023-05-05 18:06:07 - train: epoch 300, iter:180, loss: 0.6977, lr: 0.000999023230571994
2023-05-05 18:06:08 - train: epoch 300, iter:200, loss: 0.6980, lr: 0.000999023230571994
2023-05-05 18:06:09 - train: epoch 300, iter:220, loss: 0.6949, lr: 0.000999023230571994
2023-05-05 18:06:27 - val epoch: 300, loss: 1.2017, miou: 0.3388203635288079, f1_or_dsc: 0.5061476098791312, accuracy: 0.7951686633583206, specificity: 0.8953288610390496, sensitivity: 0.45815140322845055, confusion_matrix: [[35191396 4114157]
[ 6329580 5351875]]
2023-05-05 18:06:47 - test of best model, loss: 0.9647,miou: 0.38495204677204725, f1_or_dsc: 0.5559066794684588, accuracy: 0.8147856606922297, specificity: 0.9065609635361191, sensitivity: 0.5059817462807501, confusion_matrix: [[35632880 3672673]
[ 5770852 5910603]]
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JCruan519
commented on July 19, 2024
Hello, this result is indeed somewhat strange. The code I uploaded on GitHub is only a part of my complete project files, and I will check it when I have time later. You can try using the updated dataset link in the readme file for retraining and testing, and the results should not be biased so much. In addition, because the model parameters in this article are very small, it is certain that there is some bias in the training results.
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all1-know
commented on July 19, 2024
Thank you for your answer.
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all1-know
commented on July 19, 2024
The ISIC2018 of the official dataset is 2594, is it convenient to ask how the remaining 100 sheets came about?
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JCruan519
commented on July 19, 2024
2694 is composed of 2594 for training and 100 for validation from the offical site.
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guyuehhhhh
commented on July 19, 2024
Thank you very much for your reply, I ran the code again this afternoon with your dataset, and it was not much different from the results in the paper table.
你好，看到你使用了这个代码，想请问一下你每个epoch会花费多少时间呢
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all1-know
commented on July 19, 2024
您好，刚注意到邮箱的邮件，我按照作者的设定，在RTX3090上整套代码大约跑了3个半小时左右，具体每个epoch跑多长时间没有计算
…---Original---
From: ***@***.***>
Date: Thu, Aug 3, 2023 21:37 PM
To: ***@***.***>;
Cc: ***@***.******@***.***>;
Subject: Re: [JCruan519/MALUNet] a question and a request (Issue #5)
Thank you very much for your reply, I ran the code again this afternoon with your dataset, and it was not much different from the results in the paper table.
你好，看到你使用了这个代码，想请问一下你每个epoch会花费多少时间呢
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Reply to this email directly, view it on GitHub, or unsubscribe.
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guyuehhhhh
commented on July 19, 2024
你好，感谢你的回答。请问你用整个代码训练的时候，isic数据集的图片是先处理为合适大小再放入代码中用来训练的，还是直接把网上下载的高像素的图片直接用来训练的。
1169389787
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…------------------ 原始邮件 ------------------
发件人: ***@***.***>;
发送时间: 2023年8月9日(星期三) 晚上11:04
收件人: ***@***.***>;
抄送: ***@***.***>; ***@***.***>;
主题: Re: [JCruan519/MALUNet] a question and a request (Issue #5)
您好，刚注意到邮箱的邮件，我按照作者的设定，在RTX3090上整套代码大约跑了3个半小时左右，具体每个epoch跑多长时间没有计算
---Original---
From: ***@***.***>
Date: Thu, Aug 3, 2023 21:37 PM
To: ***@***.***>;
Cc: ***@***.******@***.***>;
Subject: Re: [JCruan519/MALUNet] a question and a request (Issue #5)
Thank you very much for your reply, I ran the code again this afternoon with your dataset, and it was not much different from the results in the paper table.
你好，看到你使用了这个代码，想请问一下你每个epoch会花费多少时间呢
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You are receiving this because you authored the thread.Message ID: ***@***.***>
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all1-know
commented on July 19, 2024
第一种，作者在github上现在也已经更新了，可以查看一下作者的readme
…---Original---
From: ***@***.***>
Date: Wed, Aug 9, 2023 23:48 PM
To: ***@***.***>;
Cc: ***@***.******@***.***>;
Subject: Re: [JCruan519/MALUNet] a question and a request (Issue #5)
你好，感谢你的回答。请问你用整个代码训练的时候，isic数据集的图片是先处理为合适大小再放入代码中用来训练的，还是直接把网上下载的高像素的图片直接用来训练的。
 
1169389787
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------------------ 原始邮件 ------------------
发件人: ***@***.***>;
发送时间: 2023年8月9日(星期三) 晚上11:04
收件人: ***@***.***>;
抄送: ***@***.***>; ***@***.***>;
主题: Re: [JCruan519/MALUNet] a question and a request (Issue #5)
您好，刚注意到邮箱的邮件，我按照作者的设定，在RTX3090上整套代码大约跑了3个半小时左右，具体每个epoch跑多长时间没有计算
---Original---
From: ***@***.***>
Date: Thu, Aug 3, 2023 21:37 PM
To: ***@***.***>;
Cc: ***@***.******@***.***>;
Subject: Re: [JCruan519/MALUNet] a question and a request (Issue #5)
Thank you very much for your reply, I ran the code again this afternoon with your dataset, and it was not much different from the results in the paper table.
你好，看到你使用了这个代码，想请问一下你每个epoch会花费多少时间呢
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You are receiving this because you authored the thread.Message ID: ***@***.***>
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guyuehhhhh
commented on July 19, 2024
好的，，谢谢谢谢
1169389787
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…------------------ 原始邮件 ------------------
发件人: ***@***.***>;
发送时间: 2023年8月9日(星期三) 晚上11:51
收件人: ***@***.***>;
抄送: ***@***.***>; ***@***.***>;
主题: Re: [JCruan519/MALUNet] a question and a request (Issue #5)
第一种，作者在github上现在也已经更新了，可以查看一下作者的readme
---Original---
From: ***@***.***>
Date: Wed, Aug 9, 2023 23:48 PM
To: ***@***.***>;
Cc: ***@***.******@***.***>;
Subject: Re: [JCruan519/MALUNet] a question and a request (Issue #5)
你好，感谢你的回答。请问你用整个代码训练的时候，isic数据集的图片是先处理为合适大小再放入代码中用来训练的，还是直接把网上下载的高像素的图片直接用来训练的。
 
1169389787
***@***.***
 
------------------ 原始邮件 ------------------
发件人: ***@***.***>;
发送时间: 2023年8月9日(星期三) 晚上11:04
收件人: ***@***.***>;
抄送: ***@***.***>; ***@***.***>;
主题: Re: [JCruan519/MALUNet] a question and a request (Issue #5)
您好，刚注意到邮箱的邮件，我按照作者的设定，在RTX3090上整套代码大约跑了3个半小时左右，具体每个epoch跑多长时间没有计算
---Original---
From: ***@***.***>
Date: Thu, Aug 3, 2023 21:37 PM
To: ***@***.***>;
Cc: ***@***.******@***.***>;
Subject: Re: [JCruan519/MALUNet] a question and a request (Issue #5)
Thank you very much for your reply, I ran the code again this afternoon with your dataset, and it was not much different from the results in the paper table.
你好，看到你使用了这个代码，想请问一下你每个epoch会花费多少时间呢
—
Reply to this email directly, view it on GitHub, or unsubscribe.
You are receiving this because you authored the thread.Message ID: ***@***.***>
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Related Issues (11)
- There is no way to use the "GPU" when training HOT 18
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