I want to build a custom model to recognize only people in a very “noisy” environment, where using the built-in model results with many mistakes (i.e. identify non-people objects as people).
Should I tag on my dataset only people, or should I tag as many objects I can? Preferably the objects wrongly identified as people?
Any tip or recommendation will be appreciated.