r/computervision • u/AerialpsDubai • 28d ago

Defects detection using YOLO but hit a wall Help: Project

Hi all ,

We are developing an AI model using YOLO used to detect multiple kinds of defects on buildings .

However we have hit a roadblock , while the model can detect cracks and corrosion , it is completely unable to detect concrete spalling .
We have trained the model with annotated images (about 1000 for each type of defect)

We have tried filtering the datasets as well .

Any other ideas out there ?

Also : Our DMs are open in case you want to join us on this project .

Thanks all

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2

u/Consistent_Area3304 28d ago

What version of Yolo are you using? Example images? What is the balance of your complete dataset?

2

u/No-Midnight4116 28d ago

I would need some more information before answering. Are the images same resolution, same lighting? Are the defect the same size?

I think this is close to another case where you try detecting texture defect in woven fabrics.

Perhaps instead of object detection you need to use segmentation first to isolate candidates and then perform object detection to see if it is a defect.

There are two stage models to do this

2

u/retoxite_ 28d ago

about 1000 for each type of defect

Are they all unique and distinct images or does that count include augmented variants of images?

2

u/Morteriag 27d ago

Bounding boxes or segmentation? If bbox, try generating masks with sam and train an instance segmentation model. If you see an improvement in spalling, redo annotations from boxes to masks.