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let me start with this image and then I will explain the concept by using only the bounding boxes in this image the green box around the dog is the ground truth label and the blue box is a potential prediction for it by your neural network clearly the ground truth box and this predicted box are not the same what if the network predicted the box to be here it is closer but we can say that it is still no match at all how about this there is some overlap now but you and I can easily conclude that it is not a good prediction maybe this is good enough its better but nowhere near perfect also please remember that in machine learning or any modeling exercise we are okay with imperfections as long as they are useful to us what is our threshold of accepting the imperfect prediction is something that depends on the use case that you have lets make the situation a bit more complex here is another scenario now tell me which one is better Im sounding like an eye doctor who changes the glasses an
