I would like to create a classification model with the following characteristics:
- 4 different classification classes
- Each class directory contains several thousand measurement point directories
- Each measuring point directory contains 10 png files of the same size (images that follow each other
like a movie).
I have all the data on my disk
How do I load the data into a dataset ?
Should I use a 3D CNN? LSTM?
How do I do it ?
Thanks for your help!
Hi @Ecostate, Please try to arrange the images in a way that each sub directory contains images corresponding to one class like
so that you can load the images easily through
You can try with different models containing different layers like conv2d, lstm, conv3d and select the model which gives best results. Thank You.