Yeah the csv file has three columns separated into emotion, pixels, and usage. Emotion corresponds to the labels whereas usage corresponds to training/test/val, and the pixels column is made up of all of the pixel values used to make the image. It seems to produce much quicker training times than using the images, which is my main reason for wanting to use it. Training on .csv takes around 10 seconds per epoch whereas images take 10 minutes or so.

They both produce the same result, a trained model which can make predictions on facial expressions, however its felt weird throughout the entire process that the model trains so quick, you know? I've been led to believe that machine learning is an extremely time intensive process but for me it hasn't took long at all, so I was wondering if there's some fundamental error with using the .csv data instead of the images. Hopefully it should be fine though, I don't see the issue myself if it produces the same result.