Best Way to create a bounding box for object detection
There is not any rule as such but yes the best practice of proper annotation is to keep certain pixel width while creating bounding boxes.
See, the background changes are the variations in the object which will make it robust but keep in mind to have enough samples to properly recognizing the patterns in object(edges, shapes, textures, etc.)
Hope i addressed your query!
Currently, I am working to create a deep neural network for object detection, and i am also create my own dataset, and I use the bounding box to annotate my images, and my question is what are the rules to have the best bounding box for my images training. I mean if I wrap my object is it good to limit the background of my object or do I need t find a way to bound only my object.
Thanks,