人群计数[CAN](Context-Aware Crowd Counting复现过程记录) 目录 一、开发环境及其配置 二、论文代码+数据集 三、代码复现 四、总结 一、开发环境 windows 10+Anaconda 3+python 3.7+CUDA 11.1+Pytorch 1.8.0+Pycharm 1、Anaconda3的配置 Anaconda安装教程.这篇文章十分简洁明了,并且很有用,直接照着他来就行。...
State-of-the-art methods for counting people in crowded scenes rely on deep networks to estimate crowd density. They typically use the same filters over the whole image or over large image patches. Only then do they estimate local scale to compensate for perspective distortion. This is typically...
论文《Body Structure Aware Deep Crowd Counting》 IEEE TRANSACTIONS ON IMAGE PROCESSING 创新点:从语义场景分析作为出发点,进行人群计数;包含三个关键因素:行人,头部和他们地上下文结构(context structure);行人的语义结构可以提供更丰富的信息用于行人识别; 解决问题:现存的方法,大多是直接模拟行人的整个身体... ...
git clone https://github.com/CommissarMa/Context-Aware_Crowd_Counting-pytorch.gitWe'll call the directory that you cloned Context-Aware_Crowd_Counting-pytorch as ROOT.Data Setup 1. Download ShanghaiTech Dataset from Dropbox: link or Baidu Disk: link 2. Put ShanghaiTech Dataset in ROOT...