I am trying to train a FOMO model. I have gone through all my images and labelled them. They are a mix of images where the object is present and labeled - and images with no labeled objects in them, but have things that are being incorrectly detected as the object. Are the images without objects being used in training? I remember that some Model training scripts only pull in images with objects.
I am trying to train a Bicyclist detector - but the model sometimes gets confused with cars (also have wheels) or people. Would it help if I also label those objects too? Would it help the model ignore them better?