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40 Open 5 Closed
40 Open 5 Closed
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Issues list

为什么我使用这个网络进行推理，fps这么低，跟论文里的完全不一样，我看到一篇综述他们实现的结果也是这样，可能就是根据这个代码仓库实现的。
#45 opened Apr 11, 2023 by caixiongjiang
求backbone.pth文件
#44 opened Nov 22, 2022 by 18776650143
1
hello
#43 opened Oct 15, 2022 by 1787648106
DataAugment_random crop size
#41 opened Nov 9, 2021 by ethan5722
problem about weight files!!!
#39 opened Aug 26, 2021 by zhangjiawei1998
System can not find the route
#38 opened Apr 29, 2021 by breazyG
FLOPs
#37 opened Feb 6, 2021 by InvictusRichard
The mIOU haven't improved
#36 opened Nov 20, 2020 by gaowq2017
1
请问您有尝试过从0开始训练模型吗？有的话大概训练了多少个epoch模型能比较好的收敛的？感谢回复！
#35 opened Oct 14, 2020 by Cinderstones
2
请问模型定义时，DFANet的decoder_channel=64是根据原论文设置的嘛？感谢答复！
#34 opened Oct 8, 2020 by Cinderstones
1
computer loss
#33 opened Apr 26, 2020 by wshj2020
1
new problem
#32 opened Apr 22, 2020 by electronicYH
1
No such file or directory: 'backbone.pth'
#31 opened Apr 6, 2020 by deeplearning666
8
I am executing main.py times error as follows: how to solve?
#30 opened Apr 3, 2020 by liangcheng123
1
训练数据
#29 opened Mar 31, 2020 by lyc1995452-star
6
模型不收敛
#28 opened Mar 26, 2020 by sharpening
3
Loss NaN, incorrect value Nan or Inf in input Tensor
#27 opened Mar 18, 2020 by wangq95
6
How to Solve My Problem?
#26 opened Mar 5, 2020 by CoolLoveBoy
3
Hello! Thank you very much for your open source code, which is very exciting. I encountered the following problems in the process of training the model. I wonder if you have encountered any before?
#25 opened Feb 5, 2020 by tensorflowt
2
Hello! May I ask you, what is the latest test accuracy miou of DFANet network model in your project?
#24 opened Feb 2, 2020 by tensorflowt
1
NaN or Inf found in input tensor.
#23 opened Jan 8, 2020 by mx1mx2
Final mIoU
#21 opened Nov 30, 2019 by lxtGH
有关网络中深度可分离卷积计算量的问题
#20 opened Nov 8, 2019 by guoguotingzhu
(train.py)In class trainer, func evaluate, what does the variable P, R, F1, Mr, Acc exactly mean?
#19 opened Nov 1, 2019 by BunnySF
2
Help! How to solve the problem?
#18 opened Oct 10, 2019 by Hekeshi
29
ProTip! Exclude everything labeled bug with -label:bug.