Comments (5)
wangyanchao123
commented on August 24, 2024
解决了吗兄弟，可否发我一份[email protected]感激不尽
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learning1314never
commented on August 24, 2024
May I ask if you have solved this problem? I would also like to know how to solve it. If you can could you please send the code to [email protected]. thanks. @wangyanchao123 @NJNUCS
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winderLan
commented on August 24, 2024
If you have solved this problem, may I ask for your advice? Thank you very much
[email protected]
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cuandzn
commented on August 24, 2024
我也想要一份，万分感谢！[email protected]
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CHENZhewei928
commented on August 24, 2024
Could you please let me know if you've managed to resolve this issue? I'm also interested in understanding how to address it. If possible, could you kindly share the solution or any relevant code to [email protected]? Thank you. @NJNUCS
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Related Issues (20)
- Different input size (width x height)
- Reason for [-125, 275] input clipping
- "ZeroDivisionError: integer division or modulo by zero" when vit_patches_size=8 HOT 3
- Need R50+ViT-B_16 rather than R50-ViT-B_16! HOT 1
- 当我在运行TransUNet-main的train.py时出现错误：KeyError: 'Transformer/encoderblock_0/Multi5HeadDotProductAttention_1/query/kernel is not a file in the archive' 这是在我进行KeyError: 'Transformer/encoderblock_0/MultiHeadDotProductAttention_1/query\\kernel is not a file in the archive'后的更改出现的错误，csdn说这是os.path.join 合并路径的时候出现的问题，更改后仍然出现以上错误 HOT 4
- Even if we fix the seed, the results change for each training. HOT 3
- asking for you help
- ACDC dataset 100 cases of data HOT 1
- Training for three-channel dataset
- Need R50+ViT-L_16 pretrained model rather than R50+ViT-L_32 HOT 1
- 导入包报错，文件夹重名导致的坑 HOT 2
- Data preprocessing HOT 2
- Training with different image size HOT 1
- Is the Synapse multi-organ segmentation dataset experimental result obtained from is the 20 samples official test set?
- change patch_size during test
- PreActBottleneck
- Training performance issues on small-sized targets
- The issue arises from the absence of the "lists_Synapse" folder.
- ACDC dataset HOT 1
- About the solution of problems like "have 3 channels, but got 1000 channels instead"
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