Hi! Sorry if this has been asked before, but I couldn’t find an answer.
I’m building an image dataset for applying lesson 1 learnings.
Already collected images quite easily thanks to Fastclass
- But how many images per class should I collect? What’s a general guideline?
- And what’s the suggested train/validation split? I planned on using
ImageDataBunch.from_folderand from what I see in the docs, my dataset should look like this:
path\ train\ clas1\ clas2\ ... valid\ clas1\ clas2\
But I couldn’t find how many images should be put in each category (train/valid)