car-detection:基于YOLOv2的车辆检测系统-源码

上传者: 42134234 | 上传时间: 2021-06-21 10:44:54 | 文件大小: 8.77MB | 文件类型: ZIP
汽车检测 基于对YOLOv2的迁移学习内置的神经网络模型 训练集来自于drive.ai 项目图文介绍及核心代码见 如无法打开,可参考以下文字介绍 以下对项目实现原理做一个简要介绍 这是我在coursera的深度学习课程上完成的一个项目的源代码,属于一个自动驾驶项目的一部分,用于检测道路上的车辆及其他障碍物 数据的采集是通过汽车初步摄像头拍摄,输入数据是多个维度为(608,608,3)的RGB格式图片 输出是一个四维向量(19,19,5,85)的向量,最后一维结构为(p,x,y,h,w,c1,c2……c80): p表示图片上检测出目标物体的概率,取值(0,1) x,y表示物体中心点坐标(这里需要注意的是这个坐标表示的是每个网格内的坐标而不是整个图片的) h,w表示用于标记物体的方格的高度和宽度 c1-c80表示可以识别的80种物体类型的概率,取值在(0,1),可以检测的物体类型在coc

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