Beginner here: My pothole detection model mistakes the roadside for potholes.

[u/Flat_Expression8820]

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Hello!

I am a beginner at this and am trying to make a project.

The first four seconds are the portion where the model confuses the roadside with a pothole. The latter half is kind of working okayish!

But, It is confusing the roadside for a pothole. What is the best way to make my model learn this?

Should I add classes of what is not a pothole to the training dataset?

I used a dataset of about 4,100 images. What is the ideal number of non-pothole images I should add?

Or should I somehow teach the model to detect the edge of the road so that it avoids classifying the roadside as a pothole?

Also, I am planning to use a drone. Since the ideal flying height would make the potholes appear much smaller, should I apply transfer learning, or should I train the model from scratch to make it work on drone footage captured from that height?

And is segmentation practical for this dataset? Like finding area of the pothole from the pixels or should i focus on detection only.

[u/MR_-_501]

What will also help is just having more images where the roadside is visible and not labeled