I’ve build a few image detection models using SSD on amazon sagemaker and building on pre-trained models. I’ve learned a lot, but I’m still just guessing when it comes to image size and resolutions, as well as bounding box placement.
For example say I wanted to detect solar panels in an image show from a drone, what would be the best approach? Lots of shots all from a similar heights, lots of varying heights, direct over the top, many various angles etc?
Then once I have the shots what about bounding box placement? Should the boxes be run as close to the sides of the panels as possible or should there be a slight border? Is it better to avoid overlapping boxes, or doesn’t that matter etc?
Is anyone aware of some resources that cover these topics in any details? I’d love to get a better understanding of the recommended best practices rather than continue down as path that may be generating sub optimal results.