我正在为我正在学习php的项目编写url缩短函数,这是代码(顺便说一句,我认为global在这里不是一件好事:P):$alphabet=array(1=>"a","b","c","d","e","f","g","h","i","j","k","l","m","n","o","p","q","r","s","t","u","v","w","x","y","z","A","B","C","D","E","F","G","H","I","J","K","L","M","N","O","P","Q","R","S","T","U","V","W","X","Y","Z","0","1","2"
本文章基于yolov5-6.2版本。主要讲解的是yolov5在训练过程中是怎么由推理结果和标签来进行损失计算的。损失函数往往可以作为调优的一个切入点,所以我们首先要了解它。 一。代码入口损失函数的调用点如下,在train.py里 代码入口:utils/loss.py1.先说一下两个入参:p: 推理结果列表,3个元素对应三个输出层,每层都是bs,na,ny,nx,no具体的输出可以参考上一篇博客yolov5源码解析(9)--输出_扫地僧1234的博客-CSDN博客_yolov5三个输出targets: 标签tensor,n行6列,每一行是image_index,class,x,y,w,h,ima