What is an acceptable percentage of '' error'' in the training data?

Hello everyone! I am currently doing a project to recognize satellites in the night sky, and I am tackling it by cutting my images in very small images and trying to deal with it as a classification problem (the cropped image does or doesn't contain a satellite).

In order to train, I'm uncertain what's the right size to crop my images, as there is a possibility that there are two satellites close to each other. Based on distances between each satellites in my images, I have found that in the case where an image does contain more than one satellite, about only 2% of those satellites are less than 15 pixels from each other.

Essentially, I am undecisive whether I should keep those cropped images (and accept that about 2% of my training data might have an additional satellite in the images when my AI is only trying to recognize one), or if it would be wiser (but also much more time consuming for me) to instead train my AI with data that contains info for maybe 2 satellites and have my output be in the form (Yes Yes / Yes No / No No).

So long story short, is it acceptable for my training data to have about 2% error, and what should be an acceptable level of error?