Comments (3)
yinboc
commented on May 30, 2024
Those pickle-style datasets are obtained from the reference repos, I didn't generate them by meself. Using pickle package to check their format and store your own dataset with the same format should work.
For using your own dataset, it is not necessary to follow the pickle format (e.g. ImageNet-800 uses image folders), you can write your own pytorch data loader. This may help: #5
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xqyd
commented on May 30, 2024
After writing my own code to split and load the corresponding data into base and novel set respectively, I was able to train and test the code successfully. Thanks for your wonderful work!!!
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yinboc
commented on May 30, 2024
You're welcome.
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Related Issues (20)
- cite
- Question about the meta-test. HOT 2
- Thank you for your attention HOT 5
- The expected results are not achieved on the tiered-imagenet HOT 9
- 训练自己的数据集 HOT 2
- How did you get the encoder that you shared in the git hub project? HOT 1
- An error occurred during operation
- classifier related to baseline in Closer look at few-shot leawrning
- some training problems using "max_epoch=100"
- 您好，meta-learning会导致新类别泛化能力下降，那么为什么还会提升classifier-baseline的性能呢？ HOT 2
- partition of dataset
- The question of distance selection
- how to run on CPU?
- 关于encoder训练的问题
- How do I know what the real category of tieredImagenet is?
- EOFError: Ran out of input HOT 1
- tval_dataset uses the test dataset?
- Hello, could you please upload these three data sets? I think they are pickle files, thank you very much。
- I think the URL of miniImagenet is outdated, could you please upload it again?
- I think the URL of miniImagenet is outdated, could you please upload it again? Thank you very much.
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