I came across this piece of code. Can anyone explain what the ... means?
x = torch.sigmoid(prediction[..., 0]) # Center x
y = torch.sigmoid(prediction[..., 1]) # Center y
w = prediction[..., 2] # Width
h = prediction[..., 3] # Height
Yolo tries to find objects in the image. It outputs predictions in the form of boxes. Each box has a coordinate x,y which determines its location. It also has a width and a height which determines the predictions size. That’s the basics. If you want to understand it deeper, have a look at this blog or google around Good luck!
Edit2: Shit, I misread the question. The ... means that it slices in all the dimensions that aren’t specified. In this case it’s all the dimension but the last. It’s basically doing prediction[:,:,:,:,0]