Comments (4)
JacksonHacker
commented on May 28, 2024
@CassieMai Have you disposed of this problem? I also want to utilize unlabeled data in the semi-supervised training process.
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LuShuaie
commented on May 28, 2024
Dear author,
I didn't find unlabeled settings in your code, could you tell me where you set up the unlabeled settings?
thanks
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shaohua0116
commented on May 28, 2024
Thank you for pointing this out. Now the numbers of images that are used for training the generator can be change here https://github.com/gitlimlab/SSGAN-Tensorflow/blob/1323a53f02503caa28b67e1ee52a4c30252a51dd/datasets/hdf5_loader.py#L65
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ronghuiju
commented on May 28, 2024
I also want to know if this program could process unlabeled data, thanks
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Related Issues (20)
- About Generator loss HOT 1
- Batch normalization should behave differently in training and testing phase. HOT 2
- How do you test the model accuracy? + Check points are not stored correctly HOT 2
- ValueError: num_outputs should be int or long, got 11. HOT 4
- Number of labelled samples per class HOT 2
- label of generative samples HOT 1
- why the _groundtruths in the evaler.py is different from the original test label? HOT 1
- predicted probabilities not summed to 1 HOT 2
- visualize_training.py is not working HOT 1
- Why the g_loss becomes negative? HOT 6
- Have you use unlabeled data๏ผ
- Adding a requirements.txt file
- Could you give an example for building and training own datasets?
- TypeError: argument of type 'NoneType' is not iterable
- ValueError: num_outputs should be int or long, got 400.
- How to generate samples? HOT 4
- Where is the generated image stored? HOT 6
- can't create generator HOT 9
- errors when I try two separate data.hy files HOT 1
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