Hello community,
I am new to Dl, so plz excuse me if the questions are very nub. I went through several articles and tutorials, and before deciding I understood deep learning, I wanted to make my own project and this is what I came up with.
I tried implementing it in fastai using resnet50 after getting crowdsourcing the data( mostly me). I got a model predicting one category for everything.
This is the kaggle link:
https://www.kaggle.com/vikranthkanumuru/naruto-hand-sign-detection-usin-fastai-diff-method
Not sure if this is a problem, but earlier I had around 28 images per group so I made a video of myself doing the various signs and used opencv to save frame by frame. I later removed the ones that did not confine to any group and this increased the size of the dataset from 220mb to 2GB. Was this proper or is it the reason the model is bad?
This is the link to the dataset
https://www.kaggle.com/vikranthkanumuru/naruto-hand-sign-dataset
I am not sure how to proceed further and would appreciate any help. Thank you very much.