opencv保存视频

最新推荐文章于 2025-10-07 20:13:51 发布

原创最新推荐文章于 2025-10-07 20:13:51 发布 · 159 阅读

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本篇博客介绍了一个使用OpenCV进行视频处理的应用案例，包括将彩色视频转换为灰度图像，应用二值化阈值处理，并计算白色像素点占比。此外，还展示了如何在另一个图像上绘制处理结果的变化趋势，形成可视化的线条，用于跟踪视频帧内特征变化的过程。

#include <opencv2/opencv.hpp>
#include <iostream>
#include <vector>
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <string>
using namespace std;
using namespace cv;
Mat s1;
bool leftButtonDownFlag = false;
Point originalPoint;
Point processPoint;
double sum(Mat src)
{
	double counterw = 0;
	double counterz = 0;
	Mat_<uchar>::iterator it = src.begin<uchar>();
	Mat_<uchar>::iterator itend = src.end<uchar>();
	for (; it != itend; it++)
	{
		if ((*it) > 0)
			counterw += 1;
		if ((*it) == 0)
			counterz += 1;
	}
	double a = counterw * 1.0 / (counterz + counterw) * 100;
	return a;
}
int main()
{
	Mat huabu(Size(1280, 960), CV_8UC3, Scalar(0, 0, 0));
	line(huabu, Point(5, 0), Point(5, 950), Scalar(255, 255, 255), 2, LINE_AA);
	line(huabu, Point(5, 950), Point(950, 950), Scalar(255, 255, 255), 2, LINE_AA);
	VideoWriter write;
	string outvideo = "huabu25.avi";
	write.open(outvideo, 0, 4.016, Size(1000, 1000), true);
	if (!write.isOpened())
	{
		cerr << "Could not open the output video file for write\n";
		return -1;
	}
	VideoCapture capture("34.avi");

	int i = 15;
	float last = 0;
	double d1, d2, d3, d4, d5, d6;
	//double t1= (double)getTickCount();

	while (1)
	{

		capture >> s1;
		if (s1.empty()) //||waitKey(pauseTime)==27
		{
			cout << "n=vedio is over";
			waitKey(0);
			return 0;
		}
		Mat s2;
		cvtColor(s1, s2, COLOR_BGR2GRAY);

		threshold(s2, s2, 253, 255, THRESH_BINARY);

		double a = sum(s2);

		cout << "占比是：" << a << endl;
		//---------
		int h = 100;
		int w = 100;
		line(huabu, Point(i - 10, 950 - last * 10), Point(i, 950 - a * 10), Scalar(0, 0, 255), 2, LINE_AA);
		i += 10;
		last = a;

		imshow("s2", huabu);
		write.write(huabu);
		waitKey(0);
	}

	return 0;
}