pytorch实现R-CNN目标检测项目
工程流程
本文档实现了R-CNN算法进行目标检测的完整过程，包括
数据集创建
卷积神经网络训练
分类器训练
边界框回归器训练
目标检测器实现
本仓库最终实现一个汽车类别目标检测器
模块构成
区域建议生成：selectivesearch算法实现，生成类别独立的区域建议
特征提取：卷积神经网络AlexNet实现，从每个区域建议中提取固定长度的特征向量
线性SVM实现，输入特征向量，输出每类成绩
使用类指定的边界框回归器计算候选建议的坐标偏移
非最大抑制方法实现，得到最终的候选建议
关于区域建议算法selectivesearch实现，在训练阶段使用高质量模式，在测试阶段使用快速模式
文件下载
资源详情
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