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Labeling images for yolo v4

I'm trying to label some images for train a YOLO model and I have two questions:

1 - I will try to locate standing persons on the images, (the images consists of standing persons and/or persons lying on the ground, or no person at all) so I basically have to only label the standing person? the person laying on the ground (basically rotated 90º) will not be a problem to the model training?

2 - Shoud I pass some images with no person at all to the model training? or only images with one or more people?

thanks in advance!

Solution

    1. In this case, theoretically deep learning based object detection model should be able to learn standing persons with only labelling standing persons, but I would recommend labelling persons laying on the ground as well with another class label. This will help the model learn discriminating features between standing and laying persons.

    2. Any object detection model suffers from class imbalance between foreground and background, since majority of the time in any real world scene image region/pixels occupied by foreground object (in this case Persons) are very small as compared to the background region which create class imbalance between foreground and background region. This kind of class imbalance makes the object detection model biased towards the background class. Go through this article for more details. So, adding images with zero persons will increase the foreground/background class imbalance problem even more.