reg = torch.unsqueeze(anchor,1) + regression
时间: 2024-05-20 20:15:55 浏览: 13
This code uses PyTorch's `unsqueeze()` function to add an extra dimension to the `anchor` tensor. Specifically, it adds a new dimension at index 1, which means that the tensor will have shape `(num_anchors, 1, 4)`, where `num_anchors` is the number of anchors and `4` represents the four values that define each anchor (i.e. the x and y coordinates of the top-left corner, and the width and height of the anchor box).
The purpose of adding this extra dimension is to prepare the `anchor` tensor for use in regression calculations. In object detection, regression is the process of adjusting the coordinates of the anchor boxes to better fit the object being detected. The `reg` tensor will be used to store the regression values for each anchor box, which will be used to adjust the box coordinates during training.