right such because the images are consistent throughout so there needs to be some some notion of what is in that image as a whole and that's the exact information that we need for classification and the only way that could actually be is here in the middle since you know that's the place so the hypothesis is that the these models somehow learn a higher-level representation of global information somewhere in the middle before they then specify that information again down to predict the actual pixel and that's why