226 lines
6.5 KiB
C++
226 lines
6.5 KiB
C++
/*
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主函数文件：segmentation.cpp 主函数的实现文件
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*/
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#include "segmentation.h"
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//#pragma comment( linker, "/subsystem:windows /entry:mainCRTStartup" )//无界面运行
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/*主函数*/
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int ComputeImage(vector<string> files, double bzckesa[50][50], double *wcd, int conti)
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{
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int i, ii, jj, k, size;
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double bzcu[50][50] = { 0 }; //标准差中的u
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double featurep[50][50][30] = { 0 }; //所有图像的轮廓方向特征初始化//干什么 //30
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int feature[50][50][30] = { 0 }; //所有图像的特征值初始化 //所有图像指的什么意思 //30找出30的位置或者50的位置限制。。。。带入num_dir==49的情况进行类比
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int featx[50][50] = { 0 }; //循环赋值的feature
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int featureall; //图像特征值和 //做什么用
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size = files.size();
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for (i = 0; i < size; i++)
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{
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memset(featx, 0, sizeof(featx));
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// strcpy(str,files[i].c_str());
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singlefeature((char*)files[i].c_str(), featx); //featx[][50]
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featureall = 0; //图像特征值和的初始化
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for (ii = 0; ii < 48; ii++) //将featx存起来,回头看能不能用函数换掉
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for (jj = ii + 1; jj < 47; jj++)
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{
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feature[ii][jj][i] = featx[ii][jj];
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featureall = featureall + featx[ii][jj];
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}
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//求轮廓方向特征featurep，式(5) 与标准差中的u的和
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for (ii = 0; ii < 48; ii++)
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for (jj = ii + 1; jj < 47; jj++)
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{
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featurep[ii][jj][i] = (double)featx[ii][jj] / featureall;
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bzcu[ii][jj] += (double)featx[ii][jj] / featureall * 1000; //标准差的值过小,进行放大（1）
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}
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}
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//处理完一个人的每一张图片后
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for (ii = 0; ii < 48; ii++)//求标准差中的u
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for (jj = ii + 1; jj < 47; jj++)
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bzcu[ii][jj] = bzcu[ii][jj] / size;
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//求相似性就是带权卡方wcd
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for (i = 0; i < size; i++)
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for (ii = 0; ii < 48; ii++)
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for (jj = ii + 1; jj < 47; jj++)
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if (featurep[ii][jj][i] * featurep[ii][jj][conti] != 0 && bzckesa[ii][jj] != -1)
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wcd[i] += pow((featurep[ii][jj][i] - featurep[ii][jj][conti]), 2) / ((featurep[ii][jj][i] + featurep[ii][jj][conti])*bzckesa[ii][jj]);
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memset(feature, 0, sizeof(feature));
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memset(featurep, 0, sizeof(featurep));
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return 1;
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}
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int main(int argc, char* argv[])
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{
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/*变量定义*/
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//string dir;
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//if (argc < 2)
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// return -1;
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//else
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// dir = argv[1];
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// 调试
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// string dir = "E:/xiangmu/Img/imgjiaobiao/010211100518"; //存储目录
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// 定义变量
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vector<string> dir; //存储目录
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int conti = 1; //对比图像的标号
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int size_dir, num_dir;
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char record[2400] = { 0 };
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// 获取待检测文件夹到size
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char path[100] = "E:/xiangmu/Img/imgjiaobiao/";//D:/xiangmu/Img/imgjiaobiao/
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searchDir(path, dir);//获取filePath下的所有一级目录并存储到dir中
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// dir.push_back("E:/xiangmu/Img/imgjiaobiao/010211100518"); //存储目录
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size_dir = dir.size(); //dir的大小就是学生的数量
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stuAll = size_dir;
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cout << "学生总数为" << stuAll << endl;
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// 开始检测每个文件夹下的
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for (num_dir = 0; num_dir < size_dir; num_dir++)//对每一个学生目录进行循环
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{
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cout <<(char*)dir[num_dir].c_str();
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char record[2400] = { 0 };
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FILE* fpzz = NULL;//需要注意
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int i, ii, jj, feature[50][50][30] = { 0 }, featureall = 0;
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double featurep[50][50][30] = { 0 };
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double bzcu[50][50] = { 0 };
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double bzckesa[50][50] = { 0 };
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double wcd[30] = { 0 };
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int featx[50][50] = { 0 };
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int featdif[30] = { 0 };
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float maxx = 0; //最大特征值的标号与值
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int xyimgnum = 0; //嫌疑图片的数目
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char str[80]; //存储地址
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vector<string> suspict; //记录嫌疑图片地址
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vector<float> suspict_wcd; //嫌疑图片的wcd值
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vector<string> files; //存储该生所有考试文件路径
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/*读取配置文件，并配置各项参数*/
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if (!ReadConfig("D:/HWCV/config/configure.cfg"))
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{
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// SaveLog("\t配置文件读取失败\n", g_log_adr, "a");
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SaveLog("\n0\n", g_log_adr, "a");
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return 0;
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}
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char path[100] = "E:/xiangmu/Img/imgjiaobiao/";
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/*步骤：读取标准差文件*/
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int bzccolumns = 47;//txt文件中有47列
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vector<double *> output_bzc;
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if (!ReadScanf("D:\\HWCV\\config\\stdfile.db", bzccolumns, output_bzc))
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{
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memset(g_log_rec, 0, sizeof(g_log_rec));
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// SaveLog("\n读取路径：D:\\HWCV\\config\\stdfile.db 的标准差文件失败！\n", g_log_adr, "a");
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SaveLog("\n0\n", g_log_adr, "a");
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return 0;
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}
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for (ii = 0; ii < 48; ii++)//output_vector可视为二维数组;输出数组元素：
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for (jj = ii + 1; jj < 47; jj++)
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bzckesa[ii][jj] = output_bzc[ii][jj];
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//开始检测
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//-------------------------------------------------------------//
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getFiles(dir[num_dir].c_str(), files); //遍历当前文件夹下的所有文件
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int size = files.size();
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cout << " 文件数：" << size;
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//开始对每一张图片进行处理
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for (int r = 0; r < size; r++)
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{
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memset(wcd, 0, sizeof(wcd));
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ComputeImage(files, bzckesa, wcd, r);
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xyimgnum = 0;
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//求卡方距离的最大值
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for (i = 0; i < size; i++)
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{
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// cout << files[i].c_str() << " " << wcd[i] << endl;
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if (wcd[i]>0.12)
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{
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xyimgnum++;
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suspict.push_back(files[i].c_str());
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suspict_wcd.push_back(wcd[i]);
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}
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}
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if (xyimgnum < 3) break;
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}
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/*将结果存入log文件*/
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memset(g_log_rec, 0, sizeof(g_log_rec));
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// strcat(g_log_rec, GetTime());
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// strcat(g_log_rec, "\t考生考号：");
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strcat(g_log_rec, dir[num_dir].substr(27, 22).c_str());//学号
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strcat(g_log_rec, ",");//图片总数为：
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char pic_num[20];
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_itoa(size, pic_num, 10);
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strcat(g_log_rec, pic_num);
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if (xyimgnum > 0)
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{
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stuSus++;
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char b[20];
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sprintf(b, ",%d", xyimgnum);
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strcat(g_log_rec, b);
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strcat(g_log_rec, "\n");
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for (i = 0; i < xyimgnum; i++)
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{
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// cout << "嫌疑图像：" << files[i].c_str() << endl;
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strcat(g_log_rec, ",,,");//\t嫌疑图像：
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strcat(g_log_rec, suspict[i].c_str());
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strcat(g_log_rec, ",");//相似度：
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float sim = (1.0 - suspict_wcd[i]) * 100;
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char a[20];
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sprintf(a, "%g", sim);
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strcat(g_log_rec, a);
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strcat(g_log_rec, "%%\n");
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}
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}
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else
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{
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// strcat(g_log_rec, "\t该考生没有嫌疑图像！\n");
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strcat(g_log_rec, ",0,");
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// cout << "该考生无嫌疑图像！" << endl;
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}
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SaveLog(g_log_rec, g_log_adr, "a");
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printf("嫌疑数量：%d, ", xyimgnum);
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picAll += size;
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picSus += xyimgnum;
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printf("全部:%d嫌疑：%d比例为：%g\n", picAll, picSus, ((float)picSus) / ((float)picAll));
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xyimgnum = 0;
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/*善后*/
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suspict.clear();
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suspict_wcd.clear();
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memset(g_log_rec, 0, sizeof(g_log_rec));
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memset(feature, 0, sizeof(feature));
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memset(featurep, 0, sizeof(featurep));
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memset(bzckesa, 0, sizeof(bzckesa));
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memset(wcd, 0, sizeof(wcd));
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memset(featdif, 0, sizeof(featdif));
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files.clear();
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memset(g_log_rec, 0, sizeof(g_log_rec));
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/*返回值*/
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}
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dir.clear();
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cout << "学生总数:" << stuAll << " 作弊人数：" << stuSus << endl;
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printf("已经打印到txt中！");
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string open = "start " + (string)g_log_adr;
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system(open.c_str());
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system("pause");
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return 0; //(1-wcd[maxi])*100
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}
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