必威体育Betway必威体育官网
当前位置：首页 > IT技术

OpenCV实践之车流量统计（C++）

时间:2019-07-14 05:42:17来源:IT技术作者:seo实验室小编阅读:72次「手机版」
　

车流量

车流量统计

头文件

#ifndef MY_BLOB
#define MY_BLOB

#include<OpenCV2/core/core.hpp>
#include<opencv2/highgui/highgui.hpp>
#include<opencv2/imgproc/imgproc.hpp>

///////////////////////////////////////////////////////////////////////////////////////////////////
class Blob {
public:
	// member variables ///////////////////////////////////////////////////////////////////////////
	std::vector<cv::Point> currentContour;

	cv::Rect currentBoundingRect;

	std::vector<cv::Point> centerPositions;

	double dblCurrentDiagonalSize;
	double dblCurrentAspectRatio;

	bool blnCurrentMatchFoundOrNewBlob;

	bool blnStillBeingTracked;

	int intNumOfConsecutiveFramesWithoutAMatch;

	cv::Point predictedNextPosition;

	// function prototypes ////////////////////////////////////////////////////////////////////////
	Blob(std::vector<cv::Point> _contour);
	void predictNextPosition(void);

};

#endif    // MY_BLOB



// Blob.cpp

#include "Blob.h"

///////////////////////////////////////////////////////////////////////////////////////////////////
Blob::Blob(std::vector<cv::Point> _contour) {

	currentContour = _contour;

	currentBoundingRect = cv::boundingRect(currentContour);

	cv::Point currentCenter;

	currentCenter.x = (currentBoundingRect.x + currentBoundingRect.x + currentBoundingRect.width) / 2;
	currentCenter.y = (currentBoundingRect.y + currentBoundingRect.y + currentBoundingRect.height) / 2;

	centerPositions.push_back(currentCenter);

	dblCurrentDiagonalSize = sqrt(pow(currentBoundingRect.width, 2) + pow(currentBoundingRect.height, 2));

	dblCurrentAspectRatio = (float)currentBoundingRect.width / (float)currentBoundingRect.height;

	blnStillBeingTracked = true;
	blnCurrentMatchFoundOrNewBlob = true;

	intNumOfConsecutiveFramesWithoutAMatch = 0;
}

///////////////////////////////////////////////////////////////////////////////////////////////////
void Blob::predictNextPosition(void) {

	int numPositions = (int)centerPositions.size();

	if (numPositions == 1) {

		predictedNextPosition.x = centerPositions.back().x;
		predictedNextPosition.y = centerPositions.back().y;

	}
	else if (numPositions == 2) {

		int deltaX = centerPositions[1].x - centerPositions[0].x;
		int deltaY = centerPositions[1].y - centerPositions[0].y;

		predictedNextPosition.x = centerPositions.back().x + deltaX;
		predictedNextPosition.y = centerPositions.back().y + deltaY;

	}
	else if (numPositions == 3) {

		int sumOfXChanges = ((centerPositions[2].x - centerPositions[1].x) * 2) +
			((centerPositions[1].x - centerPositions[0].x) * 1);

		int deltaX = (int)std::round((float)sumOfXChanges / 3.0);

		int sumOfYChanges = ((centerPositions[2].y - centerPositions[1].y) * 2) +
			((centerPositions[1].y - centerPositions[0].y) * 1);

		int deltaY = (int)std::round((float)sumOfYChanges / 3.0);

		predictedNextPosition.x = centerPositions.back().x + deltaX;
		predictedNextPosition.y = centerPositions.back().y + deltaY;

	}
	else if (numPositions == 4) {

		int sumOfXChanges = ((centerPositions[3].x - centerPositions[2].x) * 3) +
			((centerPositions[2].x - centerPositions[1].x) * 2) +
			((centerPositions[1].x - centerPositions[0].x) * 1);

		int deltaX = (int)std::round((float)sumOfXChanges / 6.0);

		int sumOfYChanges = ((centerPositions[3].y - centerPositions[2].y) * 3) +
			((centerPositions[2].y - centerPositions[1].y) * 2) +
			((centerPositions[1].y - centerPositions[0].y) * 1);

		int deltaY = (int)std::round((float)sumOfYChanges / 6.0);

		predictedNextPosition.x = centerPositions.back().x + deltaX;
		predictedNextPosition.y = centerPositions.back().y + deltaY;

	}
	else if (numPositions >= 5) {

		int sumOfXChanges = ((centerPositions[numPositions - 1].x - centerPositions[numPositions - 2].x) * 4) +
			((centerPositions[numPositions - 2].x - centerPositions[numPositions - 3].x) * 3) +
			((centerPositions[numPositions - 3].x - centerPositions[numPositions - 4].x) * 2) +
			((centerPositions[numPositions - 4].x - centerPositions[numPositions - 5].x) * 1);

		int deltaX = (int)std::round((float)sumOfXChanges / 10.0);

		int sumOfYChanges = ((centerPositions[numPositions - 1].y - centerPositions[numPositions - 2].y) * 4) +
			((centerPositions[numPositions - 2].y - centerPositions[numPositions - 3].y) * 3) +
			((centerPositions[numPositions - 3].y - centerPositions[numPositions - 4].y) * 2) +
			((centerPositions[numPositions - 4].y - centerPositions[numPositions - 5].y) * 1);

		int deltaY = (int)std::round((float)sumOfYChanges / 10.0);

		predictedNextPosition.x = centerPositions.back().x + deltaX;
		predictedNextPosition.y = centerPositions.back().y + deltaY;

	}
	else {
		// should never get here
	}

}

主函数

// main.cpp

#include<opencv2/core/core.hpp>
#include<opencv2/highgui/highgui.hpp>
#include<opencv2/imgproc/imgproc.hpp>

#include<iOStream>
#include<conio.h>           // it may be necessary to change or remove this line if not using windows

#include "Blob.h"

#define SHOW_STEPS            // un-comment or comment this line to show steps or not

// global variables ///////////////////////////////////////////////////////////////////////////////
const cv::Scalar SCALAR_BLACK = cv::Scalar(0.0, 0.0, 0.0);
const cv::Scalar SCALAR_WHITE = cv::Scalar(255.0, 255.0, 255.0);
const cv::Scalar SCALAR_YELLOW = cv::Scalar(0.0, 255.0, 255.0);
const cv::Scalar SCALAR_GREEN = cv::Scalar(0.0, 200.0, 0.0);
const cv::Scalar SCALAR_RED = cv::Scalar(0.0, 0.0, 255.0);

// function prototypes ////////////////////////////////////////////////////////////////////////////
void matchCurrentFrameBlobsToExistingBlobs(std::vector<Blob> &existingBlobs, std::vector<Blob> &currentFrameBlobs);
void addBlobToExistingBlobs(Blob &currentFrameBlob, std::vector<Blob> &existingBlobs, int &intIndex);
void addNewBlob(Blob &currentFrameBlob, std::vector<Blob> &existingBlobs);
double distanceBetweenPoints(cv::Point point1, cv::Point point2);
void drawAndShowContours(cv::Size imageSize, std::vector<std::vector<cv::Point> > contours, std::string strImageName);
void drawAndShowContours(cv::Size imageSize, std::vector<Blob> blobs, std::string strImageName);
bool checkIfBlobsCrossedTheLine(std::vector<Blob> &blobs, int &intHorizontalLinePosition, int &carCount);
void drawBlobInfoOnImage(std::vector<Blob> &blobs, cv::Mat &imgFrame2Copy);
void drawCarCountOnImage(int &carCount, cv::Mat &imgFrame2Copy);

///////////////////////////////////////////////////////////////////////////////////////////////////
int main(void)
{

	cv::VideoCapture capVideo;

	cv::Mat imgFrame1;
	cv::Mat imgFrame2;

	std::vector<Blob> blobs;

	cv::Point crossingLine[2];

	int carCount = 0;

	capVideo.open("CarsDrivingUnderBridge.mp4");

	if (!capVideo.isOpened())
	{                                                 // if unable to open video file
		std::cout << "ERROR reading video file" << std::endl << std::endl;      // show error message
		_getch();                   // it may be necessary to change or remove this line if not using Windows
		return(0);                                                              // and exit program
	}

	if (capVideo.get(CV_CAP_PROP_FRAME_COUNT) < 2)
	{
		std::cout << "error: video file must have at least two frames";
		_getch();                   // it may be necessary to change or remove this line if not using Windows
		return(0);
	}

	capVideo.read(imgFrame1);
	capVideo.read(imgFrame2);

	int intHorizontalLinePosition = (int)std::round((double)imgFrame1.rows * 0.35);

	crossingLine[0].x = 0;
	crossingLine[0].y = intHorizontalLinePosition;

	crossingLine[1].x = imgFrame1.cols - 1;
	crossingLine[1].y = intHorizontalLinePosition;

	char chCheckForEscKey = 0;

	bool blnFirstFrame = true;

	int frameCount = 2;

	while (capVideo.isOpened() && chCheckForEscKey != 27) 
	{

		std::vector<Blob> currentFrameBlobs;

		cv::Mat imgFrame1Copy = imgFrame1.clone();
		cv::Mat imgFrame2Copy = imgFrame2.clone();

		cv::Mat imgDifference;
		cv::Mat imgThresh;

		cv::cvtcolor(imgFrame1Copy, imgFrame1Copy, CV_BGR2GRAY);
		cv::cvtColor(imgFrame2Copy, imgFrame2Copy, CV_BGR2GRAY);

		cv::GaussianBlur(imgFrame1Copy, imgFrame1Copy, cv::Size(5, 5), 0);
		cv::GaussianBlur(imgFrame2Copy, imgFrame2Copy, cv::Size(5, 5), 0);

		cv::absdiff(imgFrame1Copy, imgFrame2Copy, imgDifference);

		cv::threshold(imgDifference, imgThresh, 30, 255.0, CV_THRESH_binary);

		cv::imshow("imgThresh", imgThresh);

		cv::Mat structuringElement3x3 = cv::getStructuringElement(cv::MORPH_RECT, cv::Size(3, 3));
		cv::Mat structuringElement5x5 = cv::getStructuringElement(cv::MORPH_RECT, cv::Size(5, 5));
		cv::Mat structuringElement7x7 = cv::getStructuringElement(cv::MORPH_RECT, cv::Size(7, 7));
		cv::Mat structuringElement15x15 = cv::getStructuringElement(cv::MORPH_RECT, cv::Size(15, 15));

		for (unsigned int i = 0; i < 2; i++)
		{
			cv::dilate(imgThresh, imgThresh, structuringElement5x5);
			cv::dilate(imgThresh, imgThresh, structuringElement5x5);
			cv::erode(imgThresh, imgThresh, structuringElement5x5);
		}

		cv::Mat imgThreshCopy = imgThresh.clone();

		std::vector<std::vector<cv::Point> > contours;

		cv::findContours(imgThreshCopy, contours, cv::RETR_EXTERNAL, cv::CHAIN_APPROX_SIMPLE);

		drawAndShowContours(imgThresh.size(), contours, "imgContours");

		std::vector<std::vector<cv::Point> > convexHulls(contours.size());

		for (unsigned int i = 0; i < contours.size(); i++) 
		{
			cv::convexHull(contours[i], convexHulls[i]);
		}

		drawAndShowContours(imgThresh.size(), convexHulls, "imgConvexHulls");

		for (auto &convexHull : convexHulls)
		{
			Blob possibleBlob(convexHull);

			if (possibleBlob.currentBoundingRect.area() > 400 &&
				possibleBlob.dblCurrentAspectRatio > 0.2 &&
				possibleBlob.dblCurrentAspectRatio < 4.0 &&
				possibleBlob.currentBoundingRect.width > 30 &&
				possibleBlob.currentBoundingRect.height > 30 &&
				possibleBlob.dblCurrentDiagonalSize > 60.0 &&
				(cv::contourArea(possibleBlob.currentContour) / (double)possibleBlob.currentBoundingRect.area()) > 0.50) {
				currentFrameBlobs.push_back(possibleBlob);
			}
		}

		drawAndShowContours(imgThresh.size(), currentFrameBlobs, "imgCurrentFrameBlobs");

		if (blnFirstFrame == true) 
		{
			for (auto &currentFrameBlob : currentFrameBlobs) 
			{
				blobs.push_back(currentFrameBlob);
			}
		}
		else
		{
			matchCurrentFrameBlobsToExistingBlobs(blobs, currentFrameBlobs);
		}

		drawAndShowContours(imgThresh.size(), blobs, "imgBlobs");

		imgFrame2Copy = imgFrame2.clone();          // get another copy of frame 2 since we changed the previous frame 2 copy in the processing above

		drawBlobInfoOnImage(blobs, imgFrame2Copy);

		bool blnAtLeastOneBlobCrossedTheLine = checkIfBlobsCrossedTheLine(blobs, intHorizontalLinePosition, carCount);

		if (blnAtLeastOneBlobCrossedTheLine == true)
		{
			cv::line(imgFrame2Copy, crossingLine[0], crossingLine[1], SCALAR_GREEN, 2);
		}
		else 
		{
			cv::line(imgFrame2Copy, crossingLine[0], crossingLine[1], SCALAR_RED, 2);
		}

		drawCarCountOnImage(carCount, imgFrame2Copy);

		cv::imshow("imgFrame2Copy", imgFrame2Copy);

		//cv::waitKey(0);                 // uncomment this line to go frame by frame for debugging

		// now we prepare for the next iteration

		currentFrameBlobs.clear();

		imgFrame1 = imgFrame2.clone();           // move frame 1 up to where frame 2 is

		if ((capVideo.get(CV_CAP_PROP_POS_FRAMES) + 1) < capVideo.get(CV_CAP_PROP_FRAME_COUNT)) 
		{
			capVideo.read(imgFrame2);
		}
		else 
		{
			std::cout << "end of video\n";
			break;
		}

		blnFirstFrame = false;
		frameCount++;
		chCheckForEscKey = cv::waitKey(1);
	}

	if (chCheckForEscKey != 27) 
	{               // if the user did not press esc (i.e. we reached the end of the video)
		cv::waitKey(0);                         // hold the windows open to allow the "end of video" message to show
	}
	// note that if the user did press esc, we don't need to hold the windows open, we can simply let the program end which will close the windows

	return(0);
}

///////////////////////////////////////////////////////////////////////////////////////////////////
void matchCurrentFrameBlobsToExistingBlobs(std::vector<Blob> &existingBlobs, std::vector<Blob> &currentFrameBlobs) 
{

	for (auto &existingBlob : existingBlobs) 
	{

		existingBlob.blnCurrentMatchFoundOrNewBlob = false;

		existingBlob.predictNextPosition();
	}

	for (auto &currentFrameBlob : currentFrameBlobs) 
	{

		int intindexofLeastDistance = 0;
		double dblLeastDistance = 100000.0;

		for (unsigned int i = 0; i < existingBlobs.size(); i++) {

			if (existingBlobs[i].blnStillBeingTracked == true) {

				double dblDistance = distanceBetweenPoints(currentFrameBlob.centerPositions.back(), existingBlobs[i].predictedNextPosition);

				if (dblDistance < dblLeastDistance) {
					dblLeastDistance = dblDistance;
					intIndexOfLeastDistance = i;
				}
			}
		}

		if (dblLeastDistance < currentFrameBlob.dblCurrentDiagonalSize * 0.5) {
			addBlobToExistingBlobs(currentFrameBlob, existingBlobs, intIndexOfLeastDistance);
		}
		else {
			addNewBlob(currentFrameBlob, existingBlobs);
		}

	}

	for (auto &existingBlob : existingBlobs) {

		if (existingBlob.blnCurrentMatchFoundOrNewBlob == false) {
			existingBlob.intNumOfConsecutiveFramesWithoutAMatch++;
		}

		if (existingBlob.intNumOfConsecutiveFramesWithoutAMatch >= 5) {
			existingBlob.blnStillBeingTracked = false;
		}

	}

}

///////////////////////////////////////////////////////////////////////////////////////////////////
void addBlobToExistingBlobs(Blob &currentFrameBlob, std::vector<Blob> &existingBlobs, int &intIndex) {

	existingBlobs[intIndex].currentContour = currentFrameBlob.currentContour;
	existingBlobs[intIndex].currentBoundingRect = currentFrameBlob.currentBoundingRect;

	existingBlobs[intIndex].centerPositions.push_back(currentFrameBlob.centerPositions.back());

	existingBlobs[intIndex].dblCurrentDiagonalSize = currentFrameBlob.dblCurrentDiagonalSize;
	existingBlobs[intIndex].dblCurrentAspectRatio = currentFrameBlob.dblCurrentAspectRatio;

	existingBlobs[intIndex].blnStillBeingTracked = true;
	existingBlobs[intIndex].blnCurrentMatchFoundOrNewBlob = true;
}

///////////////////////////////////////////////////////////////////////////////////////////////////
void addNewBlob(Blob &currentFrameBlob, std::vector<Blob> &existingBlobs) {

	currentFrameBlob.blnCurrentMatchFoundOrNewBlob = true;

	existingBlobs.push_back(currentFrameBlob);
}

///////////////////////////////////////////////////////////////////////////////////////////////////
double distanceBetweenPoints(cv::Point point1, cv::Point point2) {

	int intX = abs(point1.x - point2.x);
	int intY = abs(point1.y - point2.y);

	return(sqrt(pow(intX, 2) + pow(intY, 2)));
}

///////////////////////////////////////////////////////////////////////////////////////////////////
void drawAndShowContours(cv::Size imageSize, std::vector<std::vector<cv::Point> > contours, std::string strImageName) {
	cv::Mat image(imageSize, CV_8UC3, SCALAR_BLACK);

	cv::drawContours(image, contours, -1, SCALAR_WHITE, -1);

	cv::imshow(strImageName, image);
}

///////////////////////////////////////////////////////////////////////////////////////////////////
void drawAndShowContours(cv::Size imageSize, std::vector<Blob> blobs, std::string strImageName) {

	cv::Mat image(imageSize, CV_8UC3, SCALAR_BLACK);

	std::vector<std::vector<cv::Point> > contours;

	for (auto &blob : blobs) {
		if (blob.blnStillBeingTracked == true) {
			contours.push_back(blob.currentContour);
		}
	}

	cv::drawContours(image, contours, -1, SCALAR_WHITE, -1);

	cv::imshow(strImageName, image);
}

///////////////////////////////////////////////////////////////////////////////////////////////////
bool checkIfBlobsCrossedTheLine(std::vector<Blob> &blobs, int &intHorizontalLinePosition, int &carCount) {
	bool blnAtLeastOneBlobCrossedTheLine = false;

	for (auto blob : blobs) {

		if (blob.blnStillBeingTracked == true && blob.centerPositions.size() >= 2) {
			int prevFrameIndex = (int)blob.centerPositions.size() - 2;
			int currFrameIndex = (int)blob.centerPositions.size() - 1;

			if (blob.centerPositions[prevFrameIndex].y > intHorizontalLinePosition && blob.centerPositions[currFrameIndex].y <= intHorizontalLinePosition) {
				carCount++;
				blnAtLeastOneBlobCrossedTheLine = true;
			}
		}

	}

	return blnAtLeastOneBlobCrossedTheLine;
}

///////////////////////////////////////////////////////////////////////////////////////////////////
void drawBlobInfoOnImage(std::vector<Blob> &blobs, cv::Mat &imgFrame2Copy) {

	for (unsigned int i = 0; i < blobs.size(); i++) {

		if (blobs[i].blnStillBeingTracked == true) {
			cv::rectangle(imgFrame2Copy, blobs[i].currentBoundingRect, SCALAR_RED, 2);

			int intFontFace = CV_FONT_HERSHEY_SIMPLEX;
			double dblFontscale = blobs[i].dblCurrentDiagonalSize / 60.0;
			int intFontThickness = (int)std::round(dblFontScale * 1.0);

			cv::putText(imgFrame2Copy, std::to_string(i), blobs[i].centerPositions.back(), intFontFace, dblFontScale, SCALAR_GREEN, intFontThickness);
		}
	}
}

///////////////////////////////////////////////////////////////////////////////////////////////////
void drawCarCountOnImage(int &carCount, cv::Mat &imgFrame2Copy) {

	int intFontFace = CV_FONT_HERSHEY_SIMPLEX;
	double dblFontScale = (imgFrame2Copy.rows * imgFrame2Copy.cols) / 300000.0;
	int intFontThickness = (int)std::round(dblFontScale * 1.5);

	cv::Size textSize = cv::getTextSize(std::to_string(carCount), intFontFace, dblFontScale, intFontThickness, 0);

	cv::Point ptTextBottomLeftPosition;

	ptTextBottomLeftPosition.x = imgFrame2Copy.cols - 1 - (int)((double)textSize.width * 1.25);
	ptTextBottomLeftPosition.y = (int)((double)textSize.height * 1.25);

	cv::putText(imgFrame2Copy, std::to_string(carCount), ptTextBottomLeftPosition, intFontFace, dblFontScale, SCALAR_GREEN, intFontThickness);

}

转自(https://github.com/MicrocontrollersAndMore/OpenCV_3_Car_Counting_Cpp)

相关阅读

pandas统计学-相关性系数（pearson、spearman、kendall，p

pandas统计学-相关性系数（pearson、spearman、kendall，pointbiserialr） 相关性检验函数 series.corr(other[, method, min_perio

关于Opencv中Rect和Rectangle函数

1）构造函数 Rect(x,y,width,height)，x, y 为左上角坐标, width, height 则为长和宽。2）方法 contain(Point) 可返回改点是否在矩形内

python实现opencv学习十四：图像二值化

图像二值化：基于图像的直方图来实现的，0白色 1黑色一：全局# -*- coding=GBK -*- import cv2 as cv import numpy as np #图像二值

Excel统计函数COUNTIF()的常规用法介绍

Excel统计函数COUNTIF()的常规用法介绍COUNTIF函数常规用法一基本简介作用 用来计算区域中满足给定条件的单元格的个数。语法讲

2018年Android版本分布（市场占有率、市场份额）统计

2018年8月7日，Google发布了Android 9.0 Pie，那目前的Android版本分布是个什么样子的呢？根据过去 7 天访问了 Google Play 商店的所有

赞()
分享到:

猜你喜欢

栏目导航

推荐阅读

热门阅读

seo实验室提供seo优化服务，有网站优化、网站建设、运营推广等需求请联系我们!
Copyright © 2001-2017 .seo实验室 版权所有 网站地图