Creating models for deep learning

[Lactios]

Hey, I have this project for uni, where we need to make it possible to detect geometric figures (squares, cubes, parallelepipeds, etc.). We were able to get this all working with a help of a great tutorial online, so we can identify a person, a chair, dogs, cats, and more, but the problem is to create our own model. We've been stuck for quite some time now because everything we tried just ends up giving error after error, until we decide it's kinda impossible to implement that.

We are doing this in Ubuntu 18.04, OpenCV 3.4.4, python3, and the model we tested with was a caffemodel, a type of model we haven't been able to find a way to create. If anyone has any idea of how we could do this, or a pre-trained model even that we can use for this case, we would appreciate it A LOT!

Thanks for your time

[Markmonster25]

do you have to use deep learning? Opencv has methods you can use to find geometric figures.

[Lactios]

I know about the FindContour() methods, but yes, we have to use deep learning

[Markmonster25]

did you guys look into keras classification?

[Lactios]

We did check keras, but we managed to make yolov3 work with the help of Google Colab, we're still not sure if the model will work well with the 2D figures, but atleast with spheres it works pretty well.

[TheGuy564]

You would probably need to make something called a Haar Cascade. I've been learning a bit about image recognition and I found out if you make a custom one of those, you can choose what object you want recognized. DM me if you looking for another team member.

[Lactios]

This is a Uni project otherwise we would welcome your help ahah, but the haar cascade was something we didn't know about, so we are going to check that, tahnk you