You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Hello,
First of all thank you for this package, it is a game changer! I was wondering if there is a preferred way of using grayscale image datasets, like MNIST, with FFCV. Since torchvision dataset yields PIL images, I don't think it is suitable to use BytesField or NDArrayField in the DatasetWriter. I was able to use ffcv with MNIST by manually adding a num_channels parameter to image decoders and commenting out this line in the RGBImageField but I was wondering if there was a built-in way that I am missing.
Thanks
The text was updated successfully, but these errors were encountered:
Hi @gsaltintas ! We are still working on merging this in but there is a grayscale fork pending a PR Review here: #176. I think that should suit your needs!
Hello,
First of all thank you for this package, it is a game changer! I was wondering if there is a preferred way of using grayscale image datasets, like MNIST, with FFCV. Since torchvision dataset yields PIL images, I don't think it is suitable to use
BytesField
orNDArrayField
in theDatasetWriter
. I was able to use ffcv with MNIST by manually adding anum_channels
parameter to image decoders and commenting out this line in theRGBImageField
but I was wondering if there was a built-in way that I am missing.Thanks
The text was updated successfully, but these errors were encountered: