how I should label objects to detect them, if the object is larger than the image, e.g. I want to label a building, but in the picture is visible only part of the building (windows and doors, without roof). Or should I remove these pictures from my dataset?
Thank you!
Nicolas Gervais - Open to Work
On
Don't label them. Discard them from your training set. The model needs to learn the difference between the negative class (background) and positive classes (windows, doors). If the positive class takes the whole image, the model will have a massive false positive problem.
In every object detection dataset I've seen, such objects will just have the label cover whatever is visible, so the bounding box will go up to the border of the image.
It really depends what you want your model to do if it sees an image like this. If you want it to be able to recognise partial buildings, then you should keep them in your dataset and label whatever is visible.