Best Way to create a bounding box for object detection
I am not specialized in bounding box, but in general in deep learning, we try to obtain a network which will be robust against irrelevant variables, in your case, the background. Bounding should not be dependant of the background, so set your bounding box the way you want, it should be learned by the network how to replicate it. 
The most important thing is more the size of the database and having consistent bounding than precise bounding.
Also if you want your network to be robust against changes of backgrounds, you should have as many backgrounds as possible, uncorrelated with the bounding.
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,