视频处理中改变fps的问题有哪些?
What are the problems that changes the fps in video processing?
我正在尝试使用 OpenCV 和 OpenCL 检测运动中的白色物体。我使用的相机是我的 30 fps 笔记本电脑相机。我观察到的是,在不同的位置,我得到不同的 fps,相机和代码是相同的。对于我房间里的 Ex,当我执行代码时,我得到了 30 的完整 fps,而在实验室中它是 22 ...请任何人告诉它可能的原因是什么以及如何纠正它...我使用的代码如下...提前谢谢...
#include <iostream>
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <opencv2\ocl\ocl.hpp>
#include <time.h>
#include <iostream>
using namespace cv;
using namespace std;
int main( int argc, char** argv )
{
time_t t= time(0);
VideoCapture cap(0); //capture the video from web cam
if ( !cap.isOpened() ) // if not success, exit program
{
cout << "Cannot open the web cam" << endl;
return -1;
}
namedWindow("Control", CV_WINDOW_AUTOSIZE); //create a window called "Control"
int iLowH = 0;
int iHighH = 255;
int iLowS = 0;
int iHighS = 255;
int iLowV = 0;
int iHighV = 255;
//Create trackbars in "Control" window
cvCreateTrackbar("LowH", "Control", &iLowH, 255); //Hue (0 - 179)
cvCreateTrackbar("HighH", "Control", &iHighH, 255);
cvCreateTrackbar("LowS", "Control", &iLowS, 255); //Saturation (0 - 255)
cvCreateTrackbar("HighS", "Control", &iHighS, 255);
cvCreateTrackbar("LowV", "Control", &iLowV, 255); //Value (0 - 255)
cvCreateTrackbar("HighV", "Control", &iHighV, 255);
ocl::oclMat alpha;
int fps=0;
int cur=0;
while (true)
{
fps++;
t=time(0);
struct tm *tmp = gmtime(&t);
int h= (t/360) %24;
int m= (t/60) %60;
int s = t%60;
if(cur !=s)
{
cout<<fps;
fps=0;
cur=s;
}
Mat imgOriginal;
bool bSuccess = cap.read(imgOriginal); // read a new frame from video
if (!bSuccess) //if not success, break loop
{
cout << "Cannot read a frame from video stream" << endl;
break;
}
alpha.upload(imgOriginal);
ocl::oclMat imgHSV;
ocl::cvtColor(alpha, imgHSV, CV_RGB2HSV); //Convert the captured frame from BGR to HSV
ocl::oclMat channel[4];
ocl::split(alpha,channel);
ocl::oclMat imgThresholded[2];
ocl::threshold(channel[0], imgThresholded[0] , iLowH , 255 , 0 );
ocl::threshold(channel[0], imgThresholded[1] , iHighH , 255 , 1 );
ocl::bitwise_and(imgThresholded[0],imgThresholded[1],channel[0]);
ocl::threshold(channel[1], imgThresholded[0] , iLowS , 255 , 0 );
ocl::threshold(channel[1], imgThresholded[1] , iHighS , 255 , 1 );
ocl::bitwise_and(imgThresholded[0],imgThresholded[1],channel[1]);
ocl::threshold(channel[2], imgThresholded[0] , iLowV , 255 , 0 );
ocl::threshold(channel[2], imgThresholded[1] , iHighV , 255 , 1 );
ocl::bitwise_and(imgThresholded[0],imgThresholded[1],channel[2]);
ocl::bitwise_and(channel[0],channel[1],imgThresholded[0]);
ocl::bitwise_and(imgThresholded[0],channel[2],imgThresholded[1]);
//morphological opening (remove small objects from the foreground)
ocl::erode(imgThresholded[1], imgThresholded[1], getStructuringElement(MORPH_ELLIPSE, Size(5, 5)) );
ocl::dilate( imgThresholded[1], imgThresholded[1], getStructuringElement(MORPH_ELLIPSE, Size(5, 5)) );
//morphological closing (fill small holes in the foreground)
ocl::dilate( imgThresholded[1], imgThresholded[1], getStructuringElement(MORPH_ELLIPSE, Size(5, 5)) );
ocl::erode(imgThresholded[1], imgThresholded[1], getStructuringElement(MORPH_ELLIPSE, Size(5, 5)) );
int c= ocl::countNonZero(imgThresholded[1]);
Mat result = imgThresholded[1];
//Mat r2 = channel[0];
imshow("Thresholded Image", result); //show the thresholded image
//imshow("Original", r2); //show the original image
cout<<"\t"<<c<<endl;
if (waitKey(30) == 27) //wait for 'esc' key press for 30ms. If 'esc' key is pressed, break loop
{
cout << "esc key is pressed by user" << endl;
break;
}
}
return 0;
}
您正在图像捕获循环中进行图像处理。图像处理的时间取决于输入,因为例如腐蚀操作不会在每个图像像素上执行,而是在满足特定条件的像素上执行。因此,您在不同的环境中获得不同的执行时间也就不足为奇了。
我还可以想象笔记本电脑摄像头驱动程序正在执行一些预处理操作,例如在设置帧已准备好输出的标志之前进行亮度调整。如果您对恒定帧率感兴趣,或者使用 SDK 无法提供此类功能的其他相机,则应禁用此类预处理。
我正在尝试使用 OpenCV 和 OpenCL 检测运动中的白色物体。我使用的相机是我的 30 fps 笔记本电脑相机。我观察到的是,在不同的位置,我得到不同的 fps,相机和代码是相同的。对于我房间里的 Ex,当我执行代码时,我得到了 30 的完整 fps,而在实验室中它是 22 ...请任何人告诉它可能的原因是什么以及如何纠正它...我使用的代码如下...提前谢谢...
#include <iostream>
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <opencv2\ocl\ocl.hpp>
#include <time.h>
#include <iostream>
using namespace cv;
using namespace std;
int main( int argc, char** argv )
{
time_t t= time(0);
VideoCapture cap(0); //capture the video from web cam
if ( !cap.isOpened() ) // if not success, exit program
{
cout << "Cannot open the web cam" << endl;
return -1;
}
namedWindow("Control", CV_WINDOW_AUTOSIZE); //create a window called "Control"
int iLowH = 0;
int iHighH = 255;
int iLowS = 0;
int iHighS = 255;
int iLowV = 0;
int iHighV = 255;
//Create trackbars in "Control" window
cvCreateTrackbar("LowH", "Control", &iLowH, 255); //Hue (0 - 179)
cvCreateTrackbar("HighH", "Control", &iHighH, 255);
cvCreateTrackbar("LowS", "Control", &iLowS, 255); //Saturation (0 - 255)
cvCreateTrackbar("HighS", "Control", &iHighS, 255);
cvCreateTrackbar("LowV", "Control", &iLowV, 255); //Value (0 - 255)
cvCreateTrackbar("HighV", "Control", &iHighV, 255);
ocl::oclMat alpha;
int fps=0;
int cur=0;
while (true)
{
fps++;
t=time(0);
struct tm *tmp = gmtime(&t);
int h= (t/360) %24;
int m= (t/60) %60;
int s = t%60;
if(cur !=s)
{
cout<<fps;
fps=0;
cur=s;
}
Mat imgOriginal;
bool bSuccess = cap.read(imgOriginal); // read a new frame from video
if (!bSuccess) //if not success, break loop
{
cout << "Cannot read a frame from video stream" << endl;
break;
}
alpha.upload(imgOriginal);
ocl::oclMat imgHSV;
ocl::cvtColor(alpha, imgHSV, CV_RGB2HSV); //Convert the captured frame from BGR to HSV
ocl::oclMat channel[4];
ocl::split(alpha,channel);
ocl::oclMat imgThresholded[2];
ocl::threshold(channel[0], imgThresholded[0] , iLowH , 255 , 0 );
ocl::threshold(channel[0], imgThresholded[1] , iHighH , 255 , 1 );
ocl::bitwise_and(imgThresholded[0],imgThresholded[1],channel[0]);
ocl::threshold(channel[1], imgThresholded[0] , iLowS , 255 , 0 );
ocl::threshold(channel[1], imgThresholded[1] , iHighS , 255 , 1 );
ocl::bitwise_and(imgThresholded[0],imgThresholded[1],channel[1]);
ocl::threshold(channel[2], imgThresholded[0] , iLowV , 255 , 0 );
ocl::threshold(channel[2], imgThresholded[1] , iHighV , 255 , 1 );
ocl::bitwise_and(imgThresholded[0],imgThresholded[1],channel[2]);
ocl::bitwise_and(channel[0],channel[1],imgThresholded[0]);
ocl::bitwise_and(imgThresholded[0],channel[2],imgThresholded[1]);
//morphological opening (remove small objects from the foreground)
ocl::erode(imgThresholded[1], imgThresholded[1], getStructuringElement(MORPH_ELLIPSE, Size(5, 5)) );
ocl::dilate( imgThresholded[1], imgThresholded[1], getStructuringElement(MORPH_ELLIPSE, Size(5, 5)) );
//morphological closing (fill small holes in the foreground)
ocl::dilate( imgThresholded[1], imgThresholded[1], getStructuringElement(MORPH_ELLIPSE, Size(5, 5)) );
ocl::erode(imgThresholded[1], imgThresholded[1], getStructuringElement(MORPH_ELLIPSE, Size(5, 5)) );
int c= ocl::countNonZero(imgThresholded[1]);
Mat result = imgThresholded[1];
//Mat r2 = channel[0];
imshow("Thresholded Image", result); //show the thresholded image
//imshow("Original", r2); //show the original image
cout<<"\t"<<c<<endl;
if (waitKey(30) == 27) //wait for 'esc' key press for 30ms. If 'esc' key is pressed, break loop
{
cout << "esc key is pressed by user" << endl;
break;
}
}
return 0;
}
您正在图像捕获循环中进行图像处理。图像处理的时间取决于输入,因为例如腐蚀操作不会在每个图像像素上执行,而是在满足特定条件的像素上执行。因此,您在不同的环境中获得不同的执行时间也就不足为奇了。 我还可以想象笔记本电脑摄像头驱动程序正在执行一些预处理操作,例如在设置帧已准备好输出的标志之前进行亮度调整。如果您对恒定帧率感兴趣,或者使用 SDK 无法提供此类功能的其他相机,则应禁用此类预处理。