We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
1,如果使用M1数据集,请问具体的预处理是如何进行的?utiles/utils.py 中的函数 'smooth_swc'似乎并没有实现对swc文件的处理及保存。以及部分的单M1神经元输入处理时会出现bug。如何进行简洁直接的预处理,还请详细解释一下。 2,请告知预训练的具体信息,应该用什么数据集预训练。 3,如果采用M1数据集,最终评估生成神经元指标的时候,morphvae和morphgrower都是和预处理之后的swc文件进行比较吗,还是和原始的数据集?
The text was updated successfully, but these errors were encountered:
No branches or pull requests
1,如果使用M1数据集,请问具体的预处理是如何进行的?utiles/utils.py 中的函数 'smooth_swc'似乎并没有实现对swc文件的处理及保存。以及部分的单M1神经元输入处理时会出现bug。如何进行简洁直接的预处理,还请详细解释一下。
2,请告知预训练的具体信息,应该用什么数据集预训练。
3,如果采用M1数据集,最终评估生成神经元指标的时候,morphvae和morphgrower都是和预处理之后的swc文件进行比较吗,还是和原始的数据集?
The text was updated successfully, but these errors were encountered: