I have a dataset that contains information of pets (Breed,color,age,some text descriptions) and images of that pet. One pet can have more images than others.
I want to combine these images somehow to generate a single 1x255 feature so that I can merge it with the non-image features and use for my model.
One way I can think of is to put each image of a pet through a pretrained model to get a 1x255 output, then averaging out all of the outputs to get a single feature of that pet. But I havenät seen any paper/people doing the same to backup my intuition...
I'm new to data science, so if you have any thoughts just let me know. Thanks in advance.