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EasyPR/include/easypr/preprocess/mc_data.h

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// learn data_prepare :
// 生成learn data的cpplearn data指的是train dataverify data test
// data的总和这个名字是我起的。
// learn
// data应该是贴好标签的数据因此即便通过EasyPR自动化处理以后也要人为的修正一下.
// 你应该按照如下的步骤和顺序组织learn data
// 1.用EasyPR对not label
// data进行处理通过EasyPR辅助来对车牌图片进行标签放到不同文件夹下
// 2.标签分两种,一种是有车牌的,一种是无车牌的;
// 2.EasyPR生成标签以后你还得需要肉眼确认下将被不正确标签的数据转移到它们该去的文件夹下
// 3.通过上面的步骤正确的车牌图片和非车牌图片已经被分别放到两个文件下假设是hasplate和noplate
// 4.将这两个文件夹放到EasyPR目录train/data/plate_detect_svm/learn下面
// 5.运行EasyPR选择“训练”目录下的“车牌检测not
// divide这个程序会自动把learn data分块训练测试
#ifndef EASYPR_CORE_MCDATA_H_
#define EASYPR_CORE_MCDATA_H_
#include <string>
namespace easypr {
namespace preprocess {
void create_learn_data(const char* raw_data_folder, const char* out_data_folder,
const int how_many = 5000);
void tag_data(const char* source_folder, const char* has_plate_folder,
const char* no_plate_folder, const char* svm_model);
}
}
#endif // EASYPR_CORE_MCDATA_H_