How to detect defect on Umbrella with bounding box, polygon, mask?

[jasonrichdarmawan]

My goal is to create a model to detect defect from an Umbrella: good, perforated, fading, scratch.

The problem is that the scratch is long. So I am not sure if bounding box is the right choice.

I believe mask is the right choice to train YOLO to detect defect.

Is my decision correct?

[isLinXu]

If the scratch is long and extends over a significant portion of the umbrella, a bounding box might not be the best choice. There might be situations where it would be difficult to determine where the scratch starts or ends, making it challenging to get an accurate label for the defect. In this case, a mask or segmentation approach might be more appropriate.

A mask-based approach can provide more precise information about the location and extent of the defect. This can, in turn, help to minimize both false positives and false negatives, making the model more accurate.

Take into consideration the size and complexity of your dataset, as well as the required level of accuracy. Depending on these factors, you may need to choose a different approach.

In summary, depending on the characteristics of the scratch and the specifics of your task, a mask-based approach could be a viable option. However, it's essential to evaluate all the options and consider the benefits and drawbacks of each to make an informed decision.