What is the real number of CNN layers in yolov3?
YOLO v3 has 107 layers in total, you should also count shortcut layers, route layers, upsample layers, and YOLO layers(32 in total). So, there are 75+32=107 layers in total. When you see indexes in shortcut or route layers, you will find that we count from 0. Therefore, yolo layers are in 82,94,106 layers.
I'm really confused with the architecture of yolov3. I've read the documentation and paper about it. Some people say that it has 103 convolutional layers, some others say that it has 53 layers. But when you count the convolutional layers in the .cfg file (after downloading it) it comes to about 75! ...What is missed here? What should I do to find it? This question is important for us because we need to cite this architecture in a paper and we need to know the exact size of the layers...