Question

背景场景经常随着时间的推移而发展，例如，照明条件可能会发生变化（例如，从日出到日落），或者因为可以在背景中添加或删除新对象。因此，有必要动态构建背景场景的模型。基于上面，我写了一个简单的帧差分代码。它运行良好但它很慢。我怎样才能让它更快？有什么建议吗？

 #include <opencv2/highgui/highgui.hpp>
#include <opencv2/core/core.hpp>
#include <iostream>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/video/background_segm.hpp >
using namespace cv;
using namespace std;
#include <iostream>
#include <opencv2/features2d/features2d.hpp>
#include <opencv2/video/tracking.hpp>

    int main()
    {
        cv::Mat gray; // current gray-level image
     cv::Mat background; // accumulated background
     cv::Mat backImage; // background image
     cv::Mat foreground; // foreground image
     // learning rate in background accumulation
     double learningRate;
     int threshold; // threshold for foreground extraction
     cv::VideoCapture capture("video.mp4");

     // check if video successfully opened
     if (!capture.isOpened())
     return 0;
     // current video frame
     cv::Mat frame;
     double rate= capture.get(CV_CAP_PROP_FPS);
     int delay= 1000/rate;
     // foreground binary image
     //cv::Mat foreground;
      cv::Mat output;
      bool stop(false);
      while (!stop){
          if(!capture.read(frame))
              break;

          cv::cvtColor(frame, gray, CV_BGR2GRAY);
      cv::namedWindow("back");
         cv::imshow("back",gray);

      // initialize background to 1st frame
     if (background.empty())
     gray.convertTo(background, CV_32F);
     // convert background to 8U
     background.convertTo(backImage,CV_8U);
     // compute difference between image and background
     cv::absdiff(backImage,gray,foreground);

         // apply threshold to foreground image
     cv::threshold(foreground,output, 10,255,cv::THRESH_BINARY_INV);
     // accumulate background
     cv::accumulateWeighted(gray, background, 0.01, output);


         cv::namedWindow("out");
         cv::imshow("out",output);
     if (cv::waitKey(delay)>=0)
     stop= true; 
      }

     }

Answer 1

我修改并更正了代码的某些部分：

在您致电cv::namedWindow("back")和cv::namedWindow("out")的while循环中，只需执行一次。
您使用if (background.empty())查看数组是否为空，这对于矩阵background为空的第一个循环是必要的，因为剩余的矩阵将被填充，因此考虑到迭代while循环中所需的类型和大小，您的代码不会在第一个周期初始化为零background=cv::Mat::zeros(rows,cols,CV_32F)时出错。它也不会影响积累的运作。

此处更新的代码：

int main()
{
    cv::Mat gray; // current gray-level image
 cv::Mat background; // accumulated background
 cv::Mat backImage; // background image
 cv::Mat foreground; // foreground image
 // learning rate in background accumulation
 double learningRate;
 int threshold; // threshold for foreground extraction
 cv::VideoCapture capture("C:/Users/Pedram91/Pictures/Camera   Roll/videoplayback.mp4");////C:/Users/Pedram91/Downloads/Video/videoplayback.mp4//C:/FLIR.mp4

 // check if video successfully opened
 if (!capture.isOpened())
 return 0;
 // current video frame
 cv::Mat frame;
 double rate= capture.get(CV_CAP_PROP_FPS);
 int delay= 1000/rate;
 // foreground binary image
 //cv::Mat foreground;
  cv::Mat output;
  bool stop(false);

  cv::namedWindow("back");//This should go here,You only need to call once
  cv::namedWindow("out");//This should go here,You only need to call once

  int cols=capture.get(CV_CAP_PROP_FRAME_HEIGHT);
  int rows=capture.get(CV_CAP_PROP_FRAME_WIDTH);      

  background=cv::Mat::zeros(rows,cols,CV_32F);//this will save the "if (background.empty())" in the while loop


  while (!stop){
      if(!capture.read(frame))
          break;

     cv::cvtColor(frame, gray, CV_BGR2GRAY);

     cv::imshow("back",gray);

  // initialize background to 1st frame
// if (background.empty())
 gray.convertTo(background, CV_32F);
 // convert background to 8U
 background.convertTo(backImage,CV_8U);
 // compute difference between image and background
 cv::absdiff(backImage,gray,foreground);

     // apply threshold to foreground image
 cv::threshold(foreground,output, 10,255,cv::THRESH_BINARY_INV);
 // accumulate background
 cv::accumulateWeighted(gray, background, 0.01, output);



  cv::imshow("out",output);
 if (cv::waitKey(delay)>=0)
 stop= true; 
  }

 }

一个简单的帧差分

1 个答案: