Advice for labeling my dataset for image classification

My project is heavily inspired by [auto-tinder](https://github.com/joelbarmettlerUZH/auto-tinder), I am doing transfer learning using inception-v3.

I have however rewritten most of it and upgraded it to use TensorFlow 2 as I am using a MBP M1 and the performance isn’t really great with TensorFlow 1.x

So I have a dataset of about 5000 images scraped from Tinder, and what I am currently doing is labeling images from yes,likely,maybe,unlikely,no.

The dataset is first balanced to make sure every class has the same …

advice classification dataset deeplearning detection image images inference labeling performance person profile tensorflow tinder