GetTickCount() 函数是 Windows API 中的一个重要函数,用于获取自系统启动以来经过的毫秒数。这个函数通常用于计算时间间隔、性能分析和定时等场景。 常见用途测量时间间隔:GetTickCount() 可用于计算某个操作的时间间隔,尤其是在没有高精度计时器的情况下,适用于需要较为粗略时间计算的场景。 再次调用 GetTickCount() 获取结束时间。计算起始时间和结束时间的差值,即为操作执行的时间间隔。 如果需要避免溢出问题,推荐使用 GetTickCount64()(在 64 位系统中可用)来获取更大的计时范围。 使用 GetTickCount64() 代替如果你需要避免 GetTickCount() 溢出的问题,可以使用 GetTickCount64(),这是一个类似的函数,返回一个 64 位的值,计时范围大大增加
double t1 = (double)getTickCount(); . . . double t2 = (double)getTickCount(); cout<<"time:"<<(t2-t1)* 1000/getTickFrequency()<<endl; getTickCount()与getTickFrequency()都被定义在core.hpp文件下: //! Use cv::getTickFrequency() to convert ticks to seconds. */ CV_EXPORTS_W int64 getTickCount(); /*! The function returns the number of ticks (as returned by cv::getTickCount()) per second. exec_time = ((double)getTickCount() - exec_time)*1000.
< n; i++) ptr[i] = rand() % 50 - 25; // adopt algorithm 1 unsigned int utimecost = GetTickCount (); int result = maxsubsum1(ptr, n); utimecost = GetTickCount() - utimecost; printf("max (); result = maxsubsum2(ptr, n); utimecost = GetTickCount() - utimecost; printf("max subsequence (); int result = divide_conquer(ptr, 0, n - 1); utimecost = GetTickCount() - utimecost; printf (); result = maxsubsum3(ptr, n); utimecost = GetTickCount() - utimecost; printf("max subsequence
float t1, t2, tdelt; vector<Mat> results; Mat fullSplitImage; if(aamed) { t1 = cv::getTickCount (); AAMED_Fled(markerImage, fullSplitImage, results); t2 = cv::getTickCount(); tdelt /img/4.jpg", 1); t1 = cv::getTickCount(); fullSplitImage = testDetect(markerImage, false, false , true); t2 = cv::getTickCount(); tdelt = 1000.0*(t2-t1) / cv::getTickFrequency(); std::cout = testDetect(frame, false, false); t2 = cv::getTickCount(); tdelt = 1000.0*(t2-t1) / cv
(); srcimage.copyTo(firstimage); t1 = (double)getTickCount() - t1; double t2 = (double)getTickCount (); secondimage = srcimage.clone(); t2 = (double)getTickCount() - t2; double t3 = (double)getTickCount (); thirdimage = srcimage; t3 = (double)getTickCount() - t3; double t4 = (double)getTickCount (); t2 = (double)getTickCount() - t2; double t3 = (double)getTickCount(); thirdimage = srcimage ; t3 = (double)getTickCount() - t3; double t4 = (double)getTickCount(); Mat fourthimage(srcimage
运行时间的函数:所用函数为 getTickCount() 和 getTickFrequency() getTickCount():返回CPU自某个时间(如启动电脑)以来走过的时钟周期数。 使用方法: //记录当前时间 double start = static_cast<double>(getTickCount()); /* 中间为耗时程序 */ //再次获取时间减去上一次记录的时间,即为运行时间 double time = ((double)getTickCount() - start) / getTickFrequency 并打印到输出图像左上角 cv::Mat imageIn, imageOut; stringstream buffer; double start = static_cast<double>(getTickCount imageIn = imread("picture.jpg"); imageOut = dosomething(imageIn); double time = ((double)getTickCount
(); AAMED_Fled(markerImage, fullSplitImage, results); t2 = cv::getTickCount(); vector<int> markerIds; vector<vector<Point2f>> rejectedCandidates; t1 = cv::getTickCount /img/4.jpg", 1); t1 = cv::getTickCount(); fullSplitImage = testDetect(markerImage, false, false , true); t2 = cv::getTickCount(); tdelt = 1000.0*(t2-t1) / cv::getTickFrequency(); std::cout = testDetect(frame, false, false); t2 = cv::getTickCount(); tdelt = 1000.0*(t2-t1) /
; double result[2]; time1 = 0; time2 = 0; value1 = 0.0; time1 = GetTickCount for(index = 1; index < MAX_VALUE; index ++) value1 += 1.0 / index; time1 = GetTickCount () - time1; value2 = 0.0; memset(result , 0, sizeof(double) * 2); time2 = GetTickCount index++) result[index] = _test(index); value2 = result[0] + result[1]; time2 = GetTickCount
计算特征点 t1 = cv::getTickCount(); sift->detect(image1, keypoints1); t2 = cv::getTickCount(); 计算特征描述符 cv::Mat descriptors1, descriptors2; t1 = cv::getTickCount(); sift->compute(image1 , keypoints1, descriptors1); t2 = cv::getTickCount(); tdes = 1000.0*(t2-t1) / cv::getTickFrequency BFMatcher matcher(cv::NORM_L2); // (1) 直接暴力匹配 std::vector<cv::DMatch> matches; t1 = cv::getTickCount (); matcher->match(descriptors1, descriptors2, matches); t2 = cv::getTickCount(); tmatch_bf
根据综合网上的一些文章,精确计时主要有以下几种方式 1 调用WIN API中的GetTickCount [DllImport("kernel32")]static extern uint GetTickCount (); Thread.Sleep(2719); Console.WriteLine(GetTickCount() - s1); //单位毫秒 2 调用WIN API中的timeGetTime 推荐 [DllImport("winmm")] static extern uint timeGetTime(); 常用于多媒体定时器中,与GetTickCount类似,也是返回操作系统启动到现在所经过的毫秒数 经反编译猜测它可能也是调用的GetTickCount,但是它的返回值是int,而GetTickCount与timeGetTime方法的原型中返回值是DWORD,对应C#中的uint,难道.NET对System.Environment.TickCount 缺点:与GetTickCount一样,受返回值的最大位数限制。
计算执行时间 cv.getTickCount, 返回CPU执行的时间周期数, cv.getTickFrequency 每秒CPU时间周期总数 计算一段算法处理执行的时间秒数,代码结构如下: e1 = cv.getTickCount () # your code execution e2 = cv.getTickCount() time = (e2 - e1)/ cv.getTickFrequency() time是以秒位单位。 计算秒/毫秒/FPS 在算法执行阶段,有三个经常使用的速度性能计量指标分别是秒、毫秒、FPS(每秒多少帧),根据上面的cv.getTickCount与cv.getTickFrequency两个函数,这三个指标的计算代码如下 : e1 = cv.getTickCount() # your code execution e2 = cv.getTickCount() ## 计算秒 time = (e2 - e1)/ cv.getTickFrequency score:%.2f"%score, (int(left), int(top)), cv.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 1) e2 = cv.getTickCount
end-start; printf("%f/n",cost); return 0; } 二、C++中(此处针对windows环境,标准c中则linux和windows都可以) 1、GetTickCount include <iostream> #include <windows.h> using namespace std; int main() { double start = GetTickCount (); Sleep(1000); double end=GetTickCount(); cout << "GetTickCount:" << end-start << 精度:毫秒,与GetTickCount()相当。使用需要包含windows.h,并加入Winmm.lib(虽然查到资料说需要包含mmsystem.h,不过经验证,可以不用包含)。 测试代码如下: [c-sharp] view plain copy #include <iostream> #include <windows.h>//GetTickCount
test_pixs.jpg"); typedef cv::Point3_<uint8_t> Pixel; // forEach方式的像素遍历 double start = (double)cv::getTickCount position) -> void { p.x = 255 - p.x; p.y = 255 - p.y; p.z = 255 - p.z; }); double time = (((double)cv::getTickCount time : %.4f seconds\n", time); 传统高效的OpenCV指针方式的像素遍历访问代码如下: // raw pointer access. start = (double)cv::getTickCount >x = 255 - ptr->x; ptr->y = 255 - ptr->y; ptr->z = 255 - ptr->z; } } time = (((double)cv::getTickCount
评估代码运行时间 import cv2 start = cv2.getTickCount() # 这里写测试代码... end = cv2.getTickCount() print((end - start ) / cv2.getTickFrequency())Copy to clipboardErrorCopied 这段代码就是用来测量程序运行时间的(单位:s),其中cv2.getTickCount()函数得到电脑启动以来的时钟周期数 优先使用OpenCV/Numpy中封装好的函数 尽量将数据向量化,变成Numpy的数据格式 尽量避免数组的复制操作 接口文档 cv2.getTickCount() cv2.getTickFrequency
fclose(fp); } 暴力 image.png void method1() { //O(n^2) int cnt[maxn] = { 0 }; DWORD start_time = GetTickCount ); } for (int i = 1; i <= n; i++) if (cnt[i] >= half) fprintf(f,"%d ", i); DWORD end_time = GetTickCount 用list list<int>::iterator it, ij; for (int i = 1; i <= n; i++)l.push_back(i); DWORD start_time = GetTickCount (0); } for (int i = 1; i <= n; i++) if (m[right][i]) fprintf(f, "%d ", i); DWORD end_time = GetTickCount (fp, "\n"); } fclose(fp); } void method1() { //O(n^2) int cnt[maxn] = { 0 }; DWORD start_time = GetTickCount
代码实现如下 void method_1(Mat &image) { double t1 = getTickCount(); int w = image.cols; int h bgr[2] = 255 - bgr[2]; image.at<Vec3b>(row, col) = bgr; } } double t2 = getTickCount result", image); } 方法二 基于Mat对象的行随机访问指针方式实现对每个像素的遍历,代码实现如下: void method_2(Mat &image) { double t1 = getTickCount bgr[1] = 255 - bgr[1]; bgr[2] = 255 - bgr[2]; } } double t2 = getTickCount row_index); 方法三 直接获取Mat对象的像素块的数据指针,基于指针操作,实现快速像素方法,代码实现如下: void method_3(Mat &image) { double t1 = getTickCount
下面的示例演示了一个 Environment.TickCount 属性,它可包装来自 kernel32.dll 的 GetTickCount 函数 。 ' No need to demand a permission in place of ' UnmanagedCode as GetTickCount <DllImport("kernel32.dll", CharSet:=CharSet.Auto, ExactSpelling:=True)> Friend Shared Function GetTickCount // No need to demand a permission in place of // UnmanagedCode as GetTickCount DllImport("kernel32.dll", CharSet = CharSet.Auto, ExactSpelling = true)] internal static extern int GetTickCount
你将看到以下功能:cv.getTickCount,cv.getTickFrequency等。 除了OpenCV,Python还提供了一个模块time,这有助于衡量执行时间。 1、使用opencv衡量性能 cv.getTickCount函数返回从参考事件(如打开机器的那一刻)到调用此函数那一刻之间的时钟周期数。 因此,要找到执行时间(以秒为单位),你可以执行以下操作: e1 = cv.getTickCount() # 你的执行代码 e2 = cv.getTickCount() time = (e2 - e1)/ (不必担心结果会是什么样,这不是我们的目标): img1 = cv.imread('messi5.jpg') e1 = cv.getTickCount() for i in range(5,49,2): 代替cv.getTickCount,使用time.time()函数。然后取两次相差。 2、opencv的默认优化 许多 OpenCV 函数都是使用 SSE2、 AVX 等进行优化的。
(); for (int i = 0; i < TIMES; ++i) result = getPSNR(I1,I2); time = 1000*((double)getTickCount (); for (int i = 0; i < TIMES; ++i) result = getPSNR_GPU(I1,I2); time = 1000*((double)getTickCount (); for (int i = 0; i < TIMES; ++i) x = getMSSIM(I1,I2); time = 1000*((double)getTickCount( (); for (int i = 0; i < TIMES; ++i) x = getMSSIM_GPU(I1,I2); time = 1000*((double)getTickCount (); x = getMSSIM_GPU_optimized(I1,I2, bufferMSSIM); time = 1000*((double)getTickCount() - time)
7//障碍间隔 #defineL ((K-2)*7/8)//障碍最长值 intmain(){ relife://重玩 chara[K][C],game; DWORD S,E;//系统运行时间 S=GetTickCount =0; score++; speed=1000/score; } elsefor(inti=1;i<=K-2;i++) a[i][C-1]=' '; printf("得分:%d",score); E=GetTickCount (); if(v<1000/((float)(E-S))&&start>=7) v=1000/((float)(E-S)); printf(" 速度:%.3lf格/秒",v); S=GetTickCount