Opencv图像拼接出错vector subscript out of range下标越界

#include "opencv2/opencv.hpp"
#include <opencv2/core/core.hpp>
#include <opencv2/features2d/features2d.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/nonfree/features2d.hpp>
#include <opencv2/legacy/legacy.hpp>
#include <iostream>
#include <vector>
#define __BEGIN__ 50


using namespace std;
using namespace cv;


char img1_file[] = "27.jpg";			//读取原图像
char img2_file[] = "28.jpg";


IplImage* stack_imgs1( IplImage* img1, IplImage* img2 )
{
	IplImage* stacked = cvCreateImage( cvSize( img1->width + img2->width,
										MAX (img1->height , img2->height) ),
										IPL_DEPTH_8U, 3 );

	cvZero( stacked );						//清空数组
	cvSetImageROI( stacked, cvRect( 0, 0, img1->width, img1->height ) );			//基于给定的矩形设置感兴趣区域
	cvAdd( img1, stacked, stacked, NULL );					//计算两个数组中每个元素的和
	cvSetImageROI( stacked, cvRect(img1->width, 0, img2->width, img2->height) );
	cvAdd( img2, stacked, stacked, NULL );
	cvResetImageROI( stacked );							//释放图像的ROI 

	return stacked;
}

int main(int argc, char* argv[])
{
	IplImage* img1_cvLoadImage, * img2_cvLoadImage, * stacked;    //表示图像的结构体  声明结构体指针，指向图像


		     //图像融合时用到的参数
			unsigned char* data1;   //temp_xformed_2
			int step1;
			int channels1;

			unsigned char* data2 ;   //img2
			int step2;
			int channels2;

			unsigned char* data3 ;   //temp_xformed_1
			int step3;
			int channels3;

			double w;   //使用加权平均法进行图像融合时的权值


	img1_cvLoadImage = cvLoadImage( img1_file, 1 );   //从文件中读取图像  从指定文件读入图像，返回读入图像的指针
	if( ! img1_cvLoadImage )
		printf( "unable to load image from %s", img1_file );
	img2_cvLoadImage = cvLoadImage( img2_file, 1 );
	if( ! img2_cvLoadImage )
		printf( "unable to load image from %s", img2_file );

    cvNamedWindow( "原图1 img1_cvLoadImage    ", 1 );   
	cvShowImage( "原图1 img1_cvLoadImage ", img1_cvLoadImage );

	cvNamedWindow( "原图2 img2_cvLoadImage  ", 1 );
	cvShowImage( "原图2 img2_cvLoadImage ", img2_cvLoadImage );

	//stacked = stack_imgs( img2_cvLoadImage, img1_cvLoadImage );			//上下组合两幅图像
	stacked = stack_imgs1( img2_cvLoadImage, img1_cvLoadImage );			//左右组合两幅图像


	vector<KeyPoint> keys1, keys2;   //存储关键点
	Mat descriptors1, descriptors2;

	SurfFeatureDetector detector_Freak(2000);
	BruteForceMatcher<L2<float>> matcher;
     std::vector< DMatch > matches;
	 
	FREAK freak;
	int64 st, et;
	st = cvGetTickCount();

	double t = (double)getTickCount();
	// detect
	t = (double)getTickCount();
	detector_Freak.detect(img1_cvLoadImage,keys1);
	detector_Freak.detect(img2_cvLoadImage, keys2);
	t = ((double)getTickCount() - t)/getTickFrequency();
	cout << "FREAK detection time [s]: " << t/1.0 << endl;

	// extract
	t = (double)getTickCount();
	freak.compute(img1_cvLoadImage, keys1, descriptors1);
	freak.compute(img2_cvLoadImage, keys2, descriptors2);
	t = ((double)getTickCount() - t)/getTickFrequency();
	cout << "FREAK extraction time [s]: " << t << endl;
	matcher.match(descriptors1, descriptors2, matches);

	double max_dist = 0;
	double min_dist = 100;

	for (int i=0; i<descriptors1.rows; i++)
	{ 
		double dist = matches[i].distance;
		if (dist < min_dist) min_dist = dist;
		if(dist > max_dist) max_dist = dist;
	}
	printf("-- Max dist : %f \n", max_dist);
	printf("-- Min dist : %f \n", min_dist);

	vector<DMatch> good_matches_Freak;
	for (int i=0; i<descriptors1.rows; i++)
	{ 
		if(matches[i].distance < 0.8*max_dist)
		{ 
			good_matches_Freak.push_back(matches[i]); 
		}
	}

	Mat imgMatch_Freak;
	drawMatches(img1_cvLoadImage, keys1, img2_cvLoadImage, keys2, good_matches_Freak, imgMatch_Freak,
		Scalar::all(-1), Scalar::all(-1),
		vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS);

	// display
	imshow("matchFREAK", imgMatch_Freak);


	//waitKey();

	vector<Point2f>	pt1,pt2;   //定义点容器，存储匹配的那些特征点
	pt1.resize(good_matches_Freak.size());
	pt2.resize(good_matches_Freak.size());//设置断点于此，前面运行正确
	for(int i = 0; i < (int)good_matches_Freak.size(); i++){
		pt1.push_back(Point2f(keys2[good_matches_Freak[i].queryIdx].pt.x, keys2[good_matches_Freak[i].queryIdx].pt.y));    

		pt2.push_back(Point2f(keys1[good_matches_Freak[i].trainIdx].pt.x, keys1[good_matches_Freak[i].trainIdx].pt.y));
	}


	Mat homo;

	//st = cvGetTickCount();
	homo = findHomography(pt1, pt2,CV_RANSAC);   //寻找单应变换矩阵
	//et = cvGetTickCount();
	//printf("ransac time: %f\n", (et-st)/(double)cvGetTickFrequency()/1000.);   //ransac所花费的时间

	printf("homo\n"     //是一个3*3的变换矩阵
		"%f %f %f\n"
		"%f %f %f\n"
		"%f %f %f\n",
		homo.at<double>(0,0), homo.at<double>(0,1), homo.at<double>(0,2),
		homo.at<double>(1,0), homo.at<double>(1,1), homo.at<double>(1,2),
		homo.at<double>(2,0), homo.at<double>(2,1), homo.at<double>(2,2));

程序不完全，后面太长，问题在vector的用法上，试了好多方法，还是提示下标越界，求高人指导。