I have two traffic related datasets. One contains traffic signs and the other traffic lights. I want to merge the two datasets and train the model to detect both of them.
Will unlabeled traffic-signs from the traffic-light dataset affect the training process and vice versa?
From what I've read so far YOLO also learns contextual information about the objects and that's why this concern.
As you mentioned and as I found there, "YOLO sees the entire image during training and test time so it implicitly encodes contextual information about classes as well as their appearance", but I see that the meaning is that it considers the direct areas around the labels to add their information to the trained network, thus, you will likely only lose the information from the unlabeled items, but it will not impact the labeled items negatively.