python，OpenCV，camShift，目标跟踪

之前一直都是用的网上c++版本的代码，最近想做一些拓展，要用python来实现。在网上找 了一下，感觉不是很好用。于是参照官方文档和c++版本的代码改写了一些。参数也没怎么调整就直接用了。

import cv2
import numpy as np


xs,ys,ws,hs = 0,0,0,0  #selection.x selection.y
xo,yo=0,0 #origin.x origin.y
selectObject = False
trackObject = 0
def onMouse(event, x, y, flags, prams): 
    global xs,ys,ws,hs,selectObject,xo,yo,trackObject
    if selectObject == True:
        xs = min(x, xo)
        ys = min(y, yo)
        ws = abs(x-xo)
        hs = abs(y-yo)
    if event == cv2.EVENT_LBUTTONDOWN:
        xo,yo = x, y
        xs,ys,ws,hs= x, y, 0, 0
        selectObject = True
    elif event == cv2.EVENT_LBUTTONUP:
        selectObject = False
        trackObject = -1

cap = cv2.VideoCapture(0)
ret,frame = cap.read()
cv2.namedWindow('imshow')
cv2.setMouseCallback('imshow',onMouse)
term_crit = ( cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 1 )
while(True):
    ret,frame = cap.read()
    if trackObject != 0:
        hsv =  cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
        mask = cv2.inRange(hsv, np.array((0., 30.,10.)), np.array((180.,256.,255.)))
        if trackObject == -1:
            track_window=(xs,ys,ws,hs)
            maskroi = mask[ys:ys+hs, xs:xs+ws]
            hsv_roi = hsv[ys:ys+hs, xs:xs+ws]
            roi_hist = cv2.calcHist([hsv_roi],[0],maskroi,[180],[0,180])
            cv2.normalize(roi_hist,roi_hist,0,255,cv2.NORM_MINMAX)
            trackObject = 1
        dst = cv2.calcBackProject([hsv], [0], roi_hist, [0, 180], 1)
        dst &= mask
        ret, track_window = cv2.CamShift(dst, track_window, term_crit)
        pts = cv2.boxPoints(ret)
        pts = np.int0(pts)
        img2 = cv2.polylines(frame,[pts],True, 255,2)
        
    if selectObject == True and ws>0 and hs>0:
        cv2.imshow('imshow1',frame[ys:ys+hs,xs:xs+ws])
        cv2.bitwise_not(frame[ys:ys+hs,xs:xs+ws],frame[ys:ys+hs,xs:xs+ws])
    cv2.imshow('imshow',frame)
    if  cv2.waitKey(10)==27:
        break
cv2.destroyAllWindows()

还有就是参考的c++代码

//---------------------------------【头文件、命名空间包含部分】----------------------------
//		描述：包含程序所使用的头文件和命名空间
//-------------------------------------------------------------------------------------------------
#include "opencv2/video/tracking.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
#include <iostream>
#include <ctype.h>
#include <windows.h>

using namespace cv;
using namespace std;



//-----------------------------------【全局变量声明】-----------------------------------------
//		描述：声明全局变量
//-------------------------------------------------------------------------------------------------
Mat image;
bool backprojMode = false;
bool selectObject = false;
int trackObject = 0;
bool showHist = true;
Point origin;
Rect selection;
int vmin = 10, vmax = 256, smin = 30;


//--------------------------------【onMouse( )回调函数】------------------------------------
//		描述：鼠标操作回调
//-------------------------------------------------------------------------------------------------
static void onMouse( int event, int x, int y, int, void* )
{
	if( selectObject )
	{
		selection.x = MIN(x, origin.x);
		selection.y = MIN(y, origin.y);
		selection.width = std::abs(x - origin.x);
		selection.height = std::abs(y - origin.y);

		selection &= Rect(0, 0, image.cols, image.rows);
	}

	switch( event )
	{
	//此句代码的OpenCV2版为：
	//case CV_EVENT_LBUTTONDOWN:
	//此句代码的OpenCV3版为：
	case EVENT_LBUTTONDOWN:
		origin = Point(x,y);
		selection = Rect(x,y,0,0);
		selectObject = true;
		break;
	//此句代码的OpenCV2版为：
	//case CV_EVENT_LBUTTONUP:
	//此句代码的OpenCV3版为：
	case EVENT_LBUTTONUP:
		selectObject = false;
		if( selection.width > 0 && selection.height > 0 )
			trackObject = -1;
		break;
	}
}

//--------------------------------【help( )函数】----------------------------------------------
//		描述：输出帮助信息
//-------------------------------------------------------------------------------------------------
static void ShowHelpText()
{
	cout <<"\n\n\t\t\t非常感谢购买《OpenCV3编程入门》一书！\n"
		<<"\n\n\t\t\t此为本书OpenCV3版的第8个配套示例程序\n"
		<<	"\n\n\t\t\t   当前使用的OpenCV版本为：" << CV_VERSION 
		<<"\n\n  ----------------------------------------------------------------------------" ;

	cout << "\n\n\t此Demo显示了基于均值漂移的追踪（tracking）技术\n"
		"\t请用鼠标框选一个有颜色的物体，对它进行追踪操作\n";

	cout << "\n\n\t操作说明： \n"
		"\t\t用鼠标框选对象来初始化跟踪\n"
		"\t\tESC - 退出程序\n"
		"\t\tc - 停止追踪\n"
		"\t\tb - 开/关-投影视图\n"
		"\t\th - 显示/隐藏-对象直方图\n"
		"\t\tp - 暂停视频\n";
}

const char* keys =
{
	"{1|  | 0 | camera number}"
};


//-----------------------------------【main( )函数】--------------------------------------------
//		描述：控制台应用程序的入口函数，我们的程序从这里开始
//-------------------------------------------------------------------------------------------------
int main( int argc, const char** argv )
{
	ShowHelpText();

	VideoCapture cap;
	Rect trackWindow;
	int hsize = 16;
	float hranges[] = {0,180};
	const float* phranges = hranges;

	cap.open(0);
	//cap.open("H:\\opencv\\ai.avi");

	if( !cap.isOpened() )
	{
		cout << "不能初始化摄像头\n";
	}

	namedWindow( "Histogram", 0 );//颜色直方图窗口
	namedWindow( "CamShift Demo", 0 );//跟踪图像窗口
	setMouseCallback( "CamShift Demo", onMouse, 0 );//关联鼠标事件
	createTrackbar( "Vmin", "CamShift Demo", &vmin, 256, 0 );//颜色空间参数设置
	createTrackbar( "Vmax", "CamShift Demo", &vmax, 256, 0 );
	createTrackbar( "Smin", "CamShift Demo", &smin, 256, 0 );

	Mat frame, hsv, hue, mask, hist, histimg = Mat::zeros(200, 320, CV_8UC3), backproj;
	bool paused = false;//暂停
	LARGE_INTEGER  _start, _stop;
	double   start, stop;
	for(;;)
	{
		QueryPerformanceCounter(&_start);
		start = (double)_start.QuadPart;          //获得计数器计数初值 
		if( !paused )
		{
			cap >> frame;
			if( frame.empty() )
				break;
		}
		QueryPerformanceCounter(&_stop);    //获取计数器当前值
		stop = (double)_stop.QuadPart;
		cout << (stop - start) * 10 / 25332 << endl;;
		frame.copyTo(image);

		if( !paused )//如果么有暂停。。。要是我就不会那么多事设置一个暂停在这
		{
			cvtColor(image, hsv, COLOR_BGR2HSV);//将图像转换为hsv颜色空间

			if( trackObject )//只有等于0的时候不跟踪？
			{
				int _vmin = vmin, _vmax = vmax;//颜色空间参数

				inRange(hsv, Scalar(0, smin, MIN(_vmin,_vmax)),
					Scalar(180, 256, MAX(_vmin, _vmax)), mask);
				int ch[] = {0, 0};
				hue.create(hsv.size(), hsv.depth());//反向直方图
				mixChannels(&hsv, 1, &hue, 1, ch, 1);

				if( trackObject < 0 )//已经用鼠标选取完区域后就可以跟踪了。。
				{
					Mat roi(hue, selection), maskroi(mask, selection);
					calcHist(&roi, 1, 0, maskroi, hist, 1, &hsize, &phranges);
					//此句代码的OpenCV3版为：
					normalize(hist, hist, 0, 255, NORM_MINMAX);
					//此句代码的OpenCV2版为：
					//normalize(hist, hist, 0, 255, CV_MINMAX);

					trackWindow = selection;
					trackObject = 1;
					histimg = Scalar::all(0);
					int binW = histimg.cols / hsize;
					Mat buf(1, hsize, CV_8UC3);
					for( int i = 0; i < hsize; i++ )
						buf.at<Vec3b>(i) = Vec3b(saturate_cast<uchar>(i*180./hsize), 255, 255);

					//此句代码的OpenCV3版为：
					cvtColor(buf, buf, COLOR_HSV2BGR);
					//此句代码的OpenCV2版为：
					//cvtColor(buf, buf, CV_HSV2BGR);

					for( int i = 0; i < hsize; i++ )
					{
						int val = saturate_cast<int>(hist.at<float>(i)*histimg.rows/255);
						rectangle( histimg, Point(i*binW,histimg.rows),
							Point((i+1)*binW,histimg.rows - val),
							Scalar(buf.at<Vec3b>(i)), -1, 8 );
					}
				}
				calcBackProject(&hue, 1, 0, hist, backproj, &phranges);
				cv::imshow("backproj", backproj);
				backproj &= mask;
				RotatedRect trackBox = CamShift(backproj, trackWindow,

				//此句代码的OpenCV3版为：
				TermCriteria( TermCriteria::EPS | TermCriteria::COUNT, 10, 1 ));
				//此句代码的OpenCV2版为：
				//TermCriteria( CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 10, 1 ));

				if( trackWindow.area() <= 1 )
				{
					int cols = backproj.cols, rows = backproj.rows, r = (MIN(cols, rows) + 5)/6;
					trackWindow = Rect(trackWindow.x - r, trackWindow.y - r,
						trackWindow.x + r, trackWindow.y + r) &
						Rect(0, 0, cols, rows);
				}

				if( backprojMode )
					cvtColor( backproj, image, COLOR_GRAY2BGR );

				//此句代码的OpenCV3版为：
				ellipse( image, trackBox, Scalar(0,0,255), 3, LINE_AA );
				//此句代码的OpenCV2版为：
				//ellipse( image, trackBox, Scalar(0,0,255), 3, CV_AA );

			}
		}
		else if( trackObject < 0 )//也就是说鼠标选定区域后，暂停键失效
			paused = false;

		if( selectObject && selection.width > 0 && selection.height > 0 )
		{
			Mat roi(image, selection);
			bitwise_not(roi, roi);
		}

		cv::imshow( "CamShift Demo", image );
		cv::imshow( "Histogram", histimg );
		char c = (char)waitKey(90);
		if( c == 27 )
			break;
		switch(c)
		{
		case 'b':
			backprojMode = !backprojMode;
			break;
		case 'c':
			trackObject = 0;
			histimg = Scalar::all(0);
			break;
		case 'h':
			showHist = !showHist;
			if( !showHist )
				destroyWindow( "Histogram" );
			else
				namedWindow( "Histogram", 1 );
			break;
		case 'p':
			paused = !paused;
			break;
		case 'k':
		{
			imwrite("pic.jpg", image);
			break;
		}
		default:
			;
		}
	}

	return 0;
}