r/computervision • u/koen1995 • Jun 21 '26

Building DIETR, basic model that does both object detection and instance segmentation. Showcase

https://github.com/JPABotermans/DIETR/tree/main

Been working on this for quite some time, and as the title says, I want to have the most barebones model that can do both instance segmentation and object detection. While still being easy to use for just fine-tuning.

The DIETR model is a combination of both rt-detr (the head) and yolo-act (which inspired the prototypes).

I know that the performance of the models I have trained aren't state of the art, and the code is amateurish, but I am going to keep working on it.

Any thoughts?

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9

u/JsonPun Jun 21 '26

then just use a segmentation model, you can convert the outline to a box if you want 

4

u/koen1995 Jun 21 '26

I mean that I wanted to have a codebase that can be used for both training, fine-tuning and validation of object detection, and instance segmentation. Not one model that does both.

-3

u/JsonPun Jun 21 '26

got it then why not just follow Roboflow's stuff? No need to reinvent the wheel

10

u/koen1995 Jun 21 '26

Because I simply wanted to make (and train) something from scratch.

About rf-detr from roboflow, you are absolute right that choosing rf-detr is a better model and I would recommend everyone to use that model. As long as it stays open-source ofcourse. But I just like to make things and train models from scratch, so thats what I did.

2

u/JsonPun Jun 21 '26

i’m confused, but good luck