/// <summary>
/// 计算是否需要单独多设置一个线程处理尾数.
/// </summary>
/// <param name="nSetThread"></param>
/// <param name="nPiPeiSize"></param>
/// <returns></returns>
private int GetThreadNum(int nSetThread, MatrixCiCui nPiPeiSize)
{
int nRtn = 0;
int nTotal = nPiPeiSize.horSize * nPiPeiSize.verSize;
if (0 != (nTotal % nSetThread))
{
nRtn = nSetThread + 1;
}
else
{
nRtn = nSetThread;
}
return(nRtn);
}
/// <summary>
/// 根据小图和大图的尺寸 计算匹配的次数
/// 用于为各个线程分配
/// </summary>
/// <param name="PicMatch"></param>
/// <param name="PicBase"></param>
/// <returns></returns>
private MatrixCiCui GetPiPeiTime(double[,] PicMatch, double[,] PicBase)
{
MatrixCiCui nRtn = new MatrixCiCui();
int BaseHor = GetHorLength(PicBase);
int MatchHor = GetHorLength(PicMatch);
nRtn.horSize = BaseHor - MatchHor + 1;
int BaseVer = GetVerLength(PicBase);
int MatchVer = GetVerLength(PicMatch);
nRtn.verSize = BaseVer - MatchVer + 1;
return(nRtn);
}
public void Run()
{
// Console.WriteLine("Hello World!");
int nSetThread = 7;
// 先完成一个配置项
// 一个BasePic和一个目录=》 txt匹配结果
//String strBasePic = "";
//String StrDir = "";
// 先完成单个基础匹配策略.
// 一个BasePic和一个MatchPic => txt匹配结果
//String strBase = "../../../BasePics/ccd.tif";
//String strMatch = "../../../IR_Report/IR_256_256_20/Pic/ir_256_256_0_0.tif";
String strBase = "../../../BasePics/ccd3.tif";
String strMatch = "../../../IR3_Report/IR3_256_256_20/Pic/ir3_256_256_0_0.tif";
// 提取文件的Row和Col组合
String fileLocation = GetLocationForm(strMatch);
// 按照层次位置读取文件.
mySize BaseSize = GetPicSize(strBase);
double[,] PicBase = new double[BaseSize.ROW, BaseSize.COL];
mySize matchSize = GetPicSize(strMatch);
double[,] PicMatch = new double[matchSize.ROW, matchSize.COL];
// 把图片数字设置到分配的内存里
SetPicData(strBase, PicBase);
SetPicData(strMatch, PicMatch);
// 计算移动一个像素点时 需要匹配的次数.
MatrixCiCui nPiPeiSize = GetPiPeiTime(PicMatch, PicBase);
// 为每个线程对象分配 区域匹配任务.
// 计算是否单独多设置一个线程
int HandleUnitNUM = GetThreadNum(nSetThread, nPiPeiSize);
List <HandleUnit> HUnitList = new List <HandleUnit>();
for (int i = 0; i < HandleUnitNUM; i++)
{
HandleUnit hu = new HandleUnit();
HUnitList.Add(hu);
}
// 为每一个处理单元分配区域. 这里的值只是个数，从0计数
int TotalNum = nPiPeiSize.horSize * nPiPeiSize.verSize;
int baseTask = TotalNum / nSetThread;
for (int i = 0; i < HandleUnitNUM; i++)
{
HandleUnit each = HUnitList[i];
each.nStart = i * baseTask;
each.nEnd = each.nStart + baseTask - 1;
// 设置最后一个特殊值.
if (each.nEnd > (TotalNum - 1))
{
each.nEnd = TotalNum - 1;
}
each.mBasePic = PicBase;
each.mMatchPic = PicMatch;
each.mPiPeiSize = nPiPeiSize;
}
//设置线程.
List <Thread> threadList = new List <Thread>();
for (int i = 0; i < HandleUnitNUM; i++)
{
Thread HandleThread; // 发送数据的线程对象.
HandleUnit each = HUnitList[i];
HandleThread = new Thread(new ThreadStart(each.Matching));
threadList.Add(HandleThread);
}
// 同时启动线程
for (int i = 0; i < HandleUnitNUM; i++)
{
Thread each = threadList[i];
each.Start();
}
Console.WriteLine("Here");
bool bExit = false;
while (false == bExit)
{
bExit = CheckStop(threadList);
}
// 在分线程全部做完操作后 还可以整合资源
// 从HUnitList里找出最大的值 并输出文件结果
// 组合集合.
Hashtable TotalHT = GetTotalHT(HUnitList);
Location lResult = GetLocation(TotalHT);
// Console.WriteLine("{0},{1}",lResult.row,lResult.column);
// 写文件.
String strLog = "TestLog.txt";
//WriteLog(lResult, strMatch, strLog);
Console.ReadLine();
}
public String myRun(String strBase,
String strMatch,
int nSetThread)
{
String strRtn = string.Empty;
// 提取文件的Row和Col组合
String fileLocation = GetLocationForm(strMatch);
// 按照层次位置读取文件.
mySize BaseSize = GetPicSize(strBase);
double[,] PicBase = new double[BaseSize.ROW, BaseSize.COL];
mySize matchSize = GetPicSize(strMatch);
double[,] PicMatch = new double[matchSize.ROW, matchSize.COL];
// 把图片数字设置到分配的内存里
SetPicData(strBase, PicBase);
SetPicData(strMatch, PicMatch);
// 计算移动一个像素点时 需要匹配的次数.
MatrixCiCui nPiPeiSize = GetPiPeiTime(PicMatch, PicBase);
// 为每个线程对象分配 区域匹配任务.
// 计算是否单独多设置一个线程
int HandleUnitNUM = GetThreadNum(nSetThread, nPiPeiSize);
List <HandleUnit> HUnitList = new List <HandleUnit>();
for (int i = 0; i < HandleUnitNUM; i++)
{
HandleUnit hu = new HandleUnit();
HUnitList.Add(hu);
}
// 为每一个处理单元分配区域. 这里的值只是个数，从0计数
int TotalNum = nPiPeiSize.horSize * nPiPeiSize.verSize;
int baseTask = TotalNum / nSetThread;
for (int i = 0; i < HandleUnitNUM; i++)
{
HandleUnit each = HUnitList[i];
each.nStart = i * baseTask;
each.nEnd = each.nStart + baseTask - 1;
// 设置最后一个特殊值.
if (each.nEnd > (TotalNum - 1))
{
each.nEnd = TotalNum - 1;
}
each.mBasePic = PicBase;
each.mMatchPic = PicMatch;
each.mPiPeiSize = nPiPeiSize;
}
//设置线程.
List <Thread> threadList = new List <Thread>();
for (int i = 0; i < HandleUnitNUM; i++)
{
Thread HandleThread; // 发送数据的线程对象.
HandleUnit each = HUnitList[i];
HandleThread = new Thread(new ThreadStart(each.Matching));
threadList.Add(HandleThread);
}
// 同时启动线程
for (int i = 0; i < HandleUnitNUM; i++)
{
Thread each = threadList[i];
each.Start();
}
Console.WriteLine("Here");
bool bExit = false;
while (false == bExit)
{
bExit = CheckStop(threadList);
}
// 在分线程全部做完操作后 还可以整合资源
// 从HUnitList里找出最大的值 并输出文件结果
// 组合集合.
Hashtable TotalHT = GetTotalHT(HUnitList);
Location lResult = GetLocation(TotalHT);
String strLo = string.Format("{0},{1}", lResult.row, lResult.column);
// 写文件. 文件内容.
strRtn = string.Format("{0} {1}", fileLocation, strLo);
// 文件名字 大图+小图+小图位置.
String StrLogName = GetLogName(strBase, strMatch, fileLocation);
WriteLog(strRtn, StrLogName);
return(strRtn);
}