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Dear authors,
Thank you for your work. I am experiencing the same issue as mentioned in #7 . Could you please let us know when the details of the training data generation will be released? Addition…
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Fix the data generation and training logistics (currently no shuffling)
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Hi, thanks for sharing your work.
Currently, I noticed that you had released your original complete mesh data, but the GCN-Denoiser took local patches for training, and the local path generation pr…
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Hi,
I noticed the code for validation set generations but didn't find any code for training data augmentation. Should we follow the same procedure for generating training data? Could you provide mo…
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### Feature request / 功能建议
The current Dataloader implementation in this repository is underperforming due to a lack of efficient parallelization. This often results in the CPU handling data preproc…
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hi，great code. Thanks for sharing. 在训练过程中，发现了一个地方有些疑问。
在数据生成的代码中有一些疑问， 在gernerator.py 的 line 180，这里需要随机生成文字。但是看到这里的逻辑确实从所有font文件中加载所有字符，而不是使用Generaotr初始化时传入的字典（self.alpha)。这个可能会导致不能更换字符集的问题。
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Thank you for great your work!
I have a question about your datasets.
I want to know how your training data is generated. The corresponding code is "RandomSpatialTransformation" in transform.py?…
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Hello,
We noticed that you mentioned in the article that all training utilized L1 Loss. However, in the Burst Denoising section, you referred to the experimental setups of KPN and BPN, where KPN em…
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Hello,
Thank you for sharing your implementation of CNN_Qbe_STD. I have been trying to run this model, however I am stuck with create the input training data. I tried BUT speech Recognizer tool but…
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Automated Pipeline for Autoencoder Models on GitHub
1. Data Preprocessing Automation
What:
Implement a CI/CD workflow that automatically processes and augments datasets when new data is available. T…