KNOWLEDGE
Pages that explain concepts by letting you try them yourself.
How YOLOv2 shares objects among five anchor boxes per cell and folds fine 26 × 26 features into the 13 × 13 grid with a passthrough layer: drag objects, pick anchors, and fold a feature map. It follows the YOLOv1 page.
IOU measures how much two boxes overlap, and NMS keeps one of the boxes that overlap on an object: move the boxes and step through the algorithm. Background for the YOLOv1 page.
How YOLOv1 splits an image into a 7×7 grid and finds every object in one pass of the network, explored through the architecture and outputs of a model built from the paper.