全景视频拼接（四）：循环将两幅图像拼接为全景图片

项目要求：利用双摄像头同时采集两个视频，离线拼接，将两个视频拼接成一个视频。

该部分代码实现功能：循环将两幅图像拼接为全景图片，储存为有顺序的图像序列，方便后续拼成视频。

方法：以stitch为模板，进行改动，只计算第一帧的拼接模板，加快拼接速度，后续的均以第一帧的拼接模板进行拼接

不足：只适合拼接远景，近距离拍摄拼接易造成重影，没有解决大视差的问题，主要原因可参见全景视频拼接（一）；

代码如下：

#include 
#include 
#include 
#include "opencv2/core/core.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/opencv_modules.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/stitching/detail/autocalib.hpp"
#include "opencv2/stitching/detail/blenders.hpp"
#include "opencv2/stitching/detail/camera.hpp"
#include "opencv2/stitching/detail/exposure_compensate.hpp"
#include "opencv2/stitching/detail/matchers.hpp"
#include "opencv2/stitching/detail/motion_estimators.hpp"
#include "opencv2/stitching/detail/seam_finders.hpp"
#include "opencv2/stitching/detail/util.hpp"
#include "opencv2/stitching/detail/warpers.hpp"
#include "opencv2/stitching/warpers.hpp"

using namespace cv;
using namespace std;
using namespace cv::detail;

#define ENABLE_LOG 1



//int stich_xiu( vectorpic_savea, vectorpic_saveb, Mat frame11, Mat frame22)
//{
	// Default command line args

//}


int main ()

{   vector  pic_savea;
    vector  pic_saveb;
    Mat srca,srcb;  
    int i; 
	int m = 1;
	const int numberc = 150;
	//const int number = 150;
    string src_image_namea = "..\\pic_a\\105_fmlaf_pica\\";  
    const int num00 = 150;    
    char numa[num00],numa1[4] = "1(",numa2[6] = ")"; 

    string numa3 = ".jpg"; 
	//int numbera = 1;
    for (int i = 1;i <= num00 ;i++)    
    {   
		itoa(i, numa, 10);
		Mat srca = imread(src_image_namea+numa1+numa+numa2+numa3);
		resize(srca, srca, Size(640, 480));
	
      //numbera++;
		if(srca.empty())
			cout << "empty"<< endl;
		else 
			cout << "yse" < img_names;
    bool preview = false;
   // bool try_gpu = true;
	bool try_gpu = false;
    double work_megapix = 0.6;
    double seam_megapix = 0.1;
   // double compose_megapix = 1;
	double compose_megapix = -1;
    float conf_thresh = 1.f;
    string features_type = "surf";
	//string features_type = "orb";
    string ba_cost_func = "ray";
    string ba_refine_mask = "xxxxx";
   // bool do_wave_correct = false;
	bool do_wave_correct = true;
    WaveCorrectKind wave_correct = detail::WAVE_CORRECT_HORIZ;
    bool save_graph = false;
    std::string save_graph_to;
     string warp_type = "spherical";
    //string warp_type = "cylindrical";
    int expos_comp_type = ExposureCompensator::GAIN_BLOCKS;
    //int expos_comp_type = ExposureCompensator::NO;
    float match_conf = 0.3f;
    string seam_find_type = "gc_color";
    //string seam_find_type = "no";
    //int blend_type = Blender::MULTI_BAND;
	int blend_type = Blender::FEATHER;
    //float blend_strength = 3;
	float blend_strength = 2;
    string result_name = "result.jpg";
    vector  frames;
	
    //打开摄像头
    //VideoCapture cap1(0);
   // VideoCapture cap2(1);

    double rate = 60;
    int delay = 1000 / rate;
    bool stop(false);
   // Mat frame11;
   // Mat frame22;
    Mat frame;
    int k = 100;

    //namedWindow("cam1", CV_WINDOW_AUTOSIZE);
    //namedWindow("cam2", CV_WINDOW_AUTOSIZE);
    //namedWindow("stitch", CV_WINDOW_AUTOSIZE);

   /* if (cap1.isOpened() && cap2.isOpened())

    {
        cout << "*** ***" << endl;
        cout << "摄像头已启动！" << endl;
    }
    else
    {
        cout << "*** ***" << endl;
        cout << "警告：请检查摄像头是否安装好!" << endl;
        cout << "程序结束！" << endl << "*** ***" << endl;
        return -1;
    }

    cap1.set(CV_CAP_PROP_FRAME_WIDTH, 320);
    cap1.set(CV_CAP_PROP_FRAME_HEIGHT, 240);
    cap2.set(CV_CAP_PROP_FRAME_WIDTH, 320);
    cap2.set(CV_CAP_PROP_FRAME_HEIGHT, 240);
    cap1.set(CV_CAP_PROP_FOCUS, 0);
    cap2.set(CV_CAP_PROP_FOCUS, 0);

	*/
	
    //获取两幅图像，通过这两幅图像来估计摄像机参数
   // while (k--)
	vector::iterator im = pic_savea.begin();
	vector::iterator in = pic_saveb.begin();
	//for(vector::iterator im = pic_savea.begin(); im != pic_savea.end(); im++)
    //{
        //if (cap1.read(frame1) && cap2.read(frame2))
		//if((!frame11.empty()) && (!frame22.empty()))
        //{
           // imshow("cam1", frame11);
            //imshow("cam2", frame22);
			//waitKey(30);
			imwrite("frame11.jpg", *im);
            imwrite("frame22.jpg", *in);
			//in++;
			
      //  }
		
   // }

    //计算相机内参数及旋转矩阵等参数
#if ENABLE_LOG
    int64 app_start_time = getTickCount();
#endif

    cv::setBreakOnError(true);

    //读入图片
  
    img_names.push_back("frame11.jpg");
    img_names.push_back("frame22.jpg");
	for (vector:: iterator ia= img_names.begin(); ia != img_names.end(); ia++)
	{
		
		if((*ia).empty())
			cout << "no"<< endl;
		else 
		{
			cout << *ia << endl;
		    cout << "yes" << endl;
		
		}

	}
	
	
    // Check if have enough images
    int num_images = static_cast(img_names.size());
    if (num_images < 2)
    {
        LOGLN("Need more images");
        return -1;
    }

    double work_scale = 1, seam_scale = 1, compose_scale = 0.5;
    bool is_work_scale_set = false, is_seam_scale_set = false, is_compose_scale_set = false;

    cout << "Finding features..." << endl;
#if ENABLE_LOG
    int64 t = getTickCount();
#endif

    Ptr finder;
    if (features_type == "surf")
    {
#if defined(HAVE_OPENCV_NONFREE) && defined(HAVE_OPENCV_GPU)
        if (try_gpu && gpu::getCudaEnabledDeviceCount() > 0)
            finder = new SurfFeaturesFinderGpu();
        else
#endif
            finder = new SurfFeaturesFinder();
    }
    else if (features_type == "orb")
    {
        finder = new OrbFeaturesFinder();
    }
    else
    {
        cout << "Unknown 2D features type: '" << features_type << "'.\n";
        return -1;
    }
	cout << "have finding the feature" < features(num_images);
    vector images(num_images);
    vector full_img_sizes(num_images);
    double seam_work_aspect = 1;
	

    for (int i = 0; i < num_images; ++i)
    {
        full_img = imread(img_names[i]);
	    if(full_img.empty())
			cout << "no" << endl;
		else
			cout << "yes" << endl;
		//imshow( "1",full_img);
	    cout << img_names[0] << endl;
		//system("pause");	
		//waitKey(50);
		
	         
        full_img_sizes[i] = full_img.size();

        if (full_img.empty())
        {
            LOGLN("Can't open image " << img_names[i]);
		    
            return -1;
        }
        if (work_megapix < 0)
        {
            img = full_img;
            work_scale = 1;
            is_work_scale_set = true;
			cout << "have this step1" << endl;
        }
        else
        {
            if (!is_work_scale_set)
            {
                work_scale = min(1.0, sqrt(work_megapix * 1e6 / full_img.size().area()));
                is_work_scale_set = true;
				cout << "have this step2" << endl;
            }
            resize(full_img, img, Size(), work_scale, work_scale);
        }
        if (!is_seam_scale_set)
        {
            seam_scale = min(1.0, sqrt(seam_megapix * 1e6 / full_img.size().area()));
            seam_work_aspect = seam_scale / work_scale;
            is_seam_scale_set = true;
			cout << "have this step3" << endl;
        }

        (*finder)(img, features[i]);
        features[i].img_idx = i;
        LOGLN("Features in image #" << i + 1 << ": " << features[i].keypoints.size());

        resize(full_img, img, Size(), seam_scale, seam_scale);
        images[i] = img.clone();
    }
	
    finder->collectGarbage();
    full_img.release();
    img.release();

    cout << "Finding features, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec" << endl;

    cout << ("Pairwise matching") << endl;
#if ENABLE_LOG
    t = getTickCount();
#endif
    vector pairwise_matches;
    BestOf2NearestMatcher matcher(try_gpu, match_conf);
    matcher(features, pairwise_matches);
    matcher.collectGarbage();
    cout << ("Pairwise matching, time: ") << ((getTickCount() - t) / getTickFrequency()) << " sec" << endl;

    // Check if we should save matches graph
    if (save_graph)
    {
        LOGLN("Saving matches graph...");
        ofstream f(save_graph_to.c_str());
        f << matchesGraphAsString(img_names, pairwise_matches, conf_thresh);
    }

    // Leave only images we are sure are from the same panorama
    vector indices = leaveBiggestComponent(features, pairwise_matches, conf_thresh);
    vector img_subset;
    vector img_names_subset;
    vector full_img_sizes_subset;
    for (size_t i = 0; i < indices.size(); ++i)
    {
        img_names_subset.push_back(img_names[indices[i]]);
        img_subset.push_back(images[indices[i]]);
        full_img_sizes_subset.push_back(full_img_sizes[indices[i]]);
    }

    images = img_subset;
    img_names = img_names_subset;
    full_img_sizes = full_img_sizes_subset;

    // Check if we still have enough images
    num_images = static_cast(img_names.size());
    if (num_images < 2)
    {
        LOGLN("Need more images");
        return -1;
    }

    HomographyBasedEstimator estimator;
    vector cameras;
    estimator(features, pairwise_matches, cameras);

    for (size_t i = 0; i < cameras.size(); ++i)
    {
        Mat R;
        cameras[i].R.convertTo(R, CV_32F);
        cameras[i].R = R;
        cout << ("Initial intrinsics #") << indices[i] + 1 << ":\n" << cameras[i].K() << endl;
    }

    Ptr adjuster;
    if (ba_cost_func == "reproj") adjuster = new detail::BundleAdjusterReproj();
    else if (ba_cost_func == "ray") adjuster = new detail::BundleAdjusterRay();
    else
    {
        cout << "Unknown bundle adjustment cost function: '" << ba_cost_func << "'.\n";
        return -1;
    }
    adjuster->setConfThresh(conf_thresh);
    Mat_ refine_mask = Mat::zeros(3, 3, CV_8U);
    if (ba_refine_mask[0] == 'x') refine_mask(0, 0) = 1;
    if (ba_refine_mask[1] == 'x') refine_mask(0, 1) = 1;
    if (ba_refine_mask[2] == 'x') refine_mask(0, 2) = 1;
    if (ba_refine_mask[3] == 'x') refine_mask(1, 1) = 1;
    if (ba_refine_mask[4] == 'x') refine_mask(1, 2) = 1;
    adjuster->setRefinementMask(refine_mask);
    (*adjuster)(features, pairwise_matches, cameras);

    // Find median focal length

    vector focals;
    for (size_t i = 0; i < cameras.size(); ++i)
    {
        cout << ("Camera #") << indices[i] + 1 << ":\n" << cameras[i].K() << endl;
        focals.push_back(cameras[i].focal);
    }

    sort(focals.begin(), focals.end());
    float warped_image_scale;
    if (focals.size() % 2 == 1)
        warped_image_scale = static_cast(focals[focals.size() / 2]);
    else
        warped_image_scale = static_cast(focals[focals.size() / 2 - 1] + focals[focals.size() / 2]) * 0.5f;

    if (do_wave_correct)
    {
        vector rmats;
        for (size_t i = 0; i < cameras.size(); ++i)
            rmats.push_back(cameras[i].R.clone());
        waveCorrect(rmats, wave_correct);
        for (size_t i = 0; i < cameras.size(); ++i)
            cameras[i].R = rmats[i];
    }
    ///////////////////////////////////////////////////////////////////////////////////////////////////////////////////
    cout << ("Warping images (auxiliary)... ") << endl;
#if ENABLE_LOG
    t = getTickCount();
#endif

    vector corners(num_images);
    vector masks_warped(num_images);
    vector images_warped(num_images);
    vector sizes(num_images);
    vector masks(num_images);

    // Preapre images masks
    for (int i = 0; i < num_images; ++i)
    {
        masks[i].create(images[i].size(), CV_8U);
        masks[i].setTo(Scalar::all(255));
    }

    // Warp images and their masks

    Ptr warper_creator;
#if defined(HAVE_OPENCV_GPU)
    if (try_gpu && gpu::getCudaEnabledDeviceCount() > 0)
    {
        if (warp_type == "plane") warper_creator = new cv::PlaneWarperGpu();
        else if (warp_type == "cylindrical") warper_creator = new cv::CylindricalWarperGpu();
        else if (warp_type == "spherical") warper_creator = new cv::SphericalWarperGpu();
    }
    else
#endif
    {
        if (warp_type == "plane") warper_creator = new cv::PlaneWarper();
        else if (warp_type == "cylindrical") warper_creator = new cv::CylindricalWarper();
        else if (warp_type == "spherical") warper_creator = new cv::SphericalWarper();
        else if (warp_type == "fisheye") warper_creator = new cv::FisheyeWarper();
        else if (warp_type == "stereographic") warper_creator = new cv::StereographicWarper();
        else if (warp_type == "compressedPlaneA2B1") warper_creator = new cv::CompressedRectilinearWarper(2, 1);
        else if (warp_type == "compressedPlaneA1.5B1") warper_creator = new cv::CompressedRectilinearWarper(1.5, 1);
        else if (warp_type == "compressedPlanePortraitA2B1") warper_creator = new cv::CompressedRectilinearPortraitWarper(2, 1);
        else if (warp_type == "compressedPlanePortraitA1.5B1") warper_creator = new cv::CompressedRectilinearPortraitWarper(1.5, 1);
        else if (warp_type == "paniniA2B1") warper_creator = new cv::PaniniWarper(2, 1);
        else if (warp_type == "paniniA1.5B1") warper_creator = new cv::PaniniWarper(1.5, 1);
        else if (warp_type == "paniniPortraitA2B1") warper_creator = new cv::PaniniPortraitWarper(2, 1);
        else if (warp_type == "paniniPortraitA1.5B1") warper_creator = new cv::PaniniPortraitWarper(1.5, 1);
        else if (warp_type == "mercator") warper_creator = new cv::MercatorWarper();
        else if (warp_type == "transverseMercator") warper_creator = new cv::TransverseMercatorWarper();
    }

    if (warper_creator.empty())
    {
        cout << "Can't create the following warper '" << warp_type << "'\n";
        return 1;
    }

    Ptr warper = warper_creator->create(static_cast(warped_image_scale * seam_work_aspect));

    for (int i = 0; i < num_images; ++i)
    {
        Mat_ K;
        cameras[i].K().convertTo(K, CV_32F);
        float swa = (float)seam_work_aspect;
        K(0, 0) *= swa; K(0, 2) *= swa;
        K(1, 1) *= swa; K(1, 2) *= swa;

        corners[i] = warper->warp(images[i], K, cameras[i].R, INTER_LINEAR, BORDER_REFLECT, images_warped[i]);
        sizes[i] = images_warped[i].size();

        warper->warp(masks[i], K, cameras[i].R, INTER_NEAREST, BORDER_CONSTANT, masks_warped[i]);
    }

    vector images_warped_f(num_images);
    for (int i = 0; i < num_images; ++i)
        images_warped[i].convertTo(images_warped_f[i], CV_32F);

    cout << "Warping images, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec" << endl;
    ////////////////////////////////////warp end/////////////////////////////////////////////////////////////////////////////////////
    Ptr compensator = ExposureCompensator::createDefault(expos_comp_type);
    compensator->feed(corners, images_warped, masks_warped);

    Ptr seam_finder;
    if (seam_find_type == "no")
        seam_finder = new detail::NoSeamFinder();
    else if (seam_find_type == "voronoi")
        seam_finder = new detail::VoronoiSeamFinder();
    else if (seam_find_type == "gc_color")
    {
#if defined(HAVE_OPENCV_GPU)
        if (try_gpu && gpu::getCudaEnabledDeviceCount() > 0)
            seam_finder = new detail::GraphCutSeamFinderGpu(GraphCutSeamFinderBase::COST_COLOR);
        else
#endif
            seam_finder = new detail::GraphCutSeamFinder(GraphCutSeamFinderBase::COST_COLOR);
    }
    else if (seam_find_type == "gc_colorgrad")
    {
#if defined(HAVE_OPENCV_GPU)
        if (try_gpu && gpu::getCudaEnabledDeviceCount() > 0)
            seam_finder = new detail::GraphCutSeamFinderGpu(GraphCutSeamFinderBase::COST_COLOR_GRAD);
        else
#endif
            seam_finder = new detail::GraphCutSeamFinder(GraphCutSeamFinderBase::COST_COLOR_GRAD);
    }
    else if (seam_find_type == "dp_color")
        seam_finder = new detail::DpSeamFinder(DpSeamFinder::COLOR);
    else if (seam_find_type == "dp_colorgrad")
        seam_finder = new detail::DpSeamFinder(DpSeamFinder::COLOR_GRAD);
    if (seam_finder.empty())
    {
        cout << "Can't create the following seam finder '" << seam_find_type << "'\n";
        return 1;
    }

    seam_finder->find(images_warped_f, corners, masks_warped);


    // Release unused memory
    images.clear();
    images_warped.clear();
    images_warped_f.clear();
    masks.clear();
    ///////////////////////////////////exposure&seam end///////////////////////////////////////////////////////////////////////

    //实时拼接
  //  while (!stop)
	
	 //while(it != pic_savea.end())
	 vector::iterator itb = pic_saveb.begin();
	 for ( vector::iterator ita = pic_savea.begin(); ita != pic_savea.end(); ita++)
    {
		Mat frame1 = *ita;
		Mat frame2 = *itb;
		resize(frame1, frame1, Size(640,480));
		resize(frame2, frame2, Size(640,480));
		//imshow("1",frame1);
		//imshow("2",frame2);
		itb++;
        if (!frame1.empty() && !frame2.empty())
        {
           //imshow("cam1", frame1);
           //imshow("cam2", frame2);
           imwrite("frame1.bmp", frame1);
           imwrite("frame2.bmp", frame2);

            //彩色帧转灰度
            //cvtColor(frame1, frame1, CV_RGB2GRAY);
            //cvtColor(frame2, frame2, CV_RGB2GRAY);


            //拼接过程
            //读入图片
            cout << "Compositing..." << endl;
#if ENABLE_LOG
            t = getTickCount();
#endif

            Mat img_warped, img_warped_s;
            Mat dilated_mask, seam_mask, mask, mask_warped;
            Ptr blender;
            //double compose_seam_aspect = 1;
            double compose_work_aspect = 1;

            img_names.pop_back();
            img_names.pop_back();
            img_names.push_back("frame1.bmp");
            img_names.push_back("frame2.bmp");

            for (int img_idx = 0; img_idx < num_images; ++img_idx)
            {
                LOGLN("Compositing image #" << indices[img_idx] + 1);

                // Read image and resize it if necessary
                full_img = imread(img_names[img_idx]);/////////////////!!!!!!!!!!!!!!!!!!!!!!!!!!参数固定，可以试着读取不同图像
                if (!is_compose_scale_set)
                {
                    if (compose_megapix > 0)
                        compose_scale = min(1.0, sqrt(compose_megapix * 1e6 / full_img.size().area()));
                    is_compose_scale_set = true;

                    // Compute relative scales
                    //compose_seam_aspect = compose_scale / seam_scale;
                    compose_work_aspect = compose_scale / work_scale;

                    // Update warped image scale
                    warped_image_scale *= static_cast(compose_work_aspect);
                    warper = warper_creator->create(warped_image_scale);

                    // Update corners and sizes
                    for (int i = 0; i < num_images; ++i)
                    {
                        // Update intrinsics
                        cameras[i].focal *= compose_work_aspect;
                        cameras[i].ppx *= compose_work_aspect;
                        cameras[i].ppy *= compose_work_aspect;

                        // Update corner and size
                        Size sz = full_img_sizes[i];
                        if (std::abs(compose_scale - 1) > 1e-1)
                        {
                            sz.width = cvRound(full_img_sizes[i].width * compose_scale);
                            sz.height = cvRound(full_img_sizes[i].height * compose_scale);
                        }

                        Mat K;
                        cameras[i].K().convertTo(K, CV_32F);
                        Rect roi = warper->warpRoi(sz, K, cameras[i].R);
                        corners[i] = roi.tl();
                        sizes[i] = roi.size();
                    }
                }
                if (abs(compose_scale - 1) > 1e-1)
                    resize(full_img, img, Size(), compose_scale, compose_scale);
                else
                    img = full_img;
                full_img.release();
                Size img_size = img.size();

                Mat K;
                cameras[img_idx].K().convertTo(K, CV_32F);

                // Warp the current image
                warper->warp(img, K, cameras[img_idx].R, INTER_LINEAR, BORDER_REFLECT, img_warped);

                // Warp the current image mask
                mask.create(img_size, CV_8U);
                mask.setTo(Scalar::all(255));
                warper->warp(mask, K, cameras[img_idx].R, INTER_NEAREST, BORDER_CONSTANT, mask_warped);

                // Compensate exposure
                compensator->apply(img_idx, corners[img_idx], img_warped, mask_warped);

                img_warped.convertTo(img_warped_s, CV_16S);
                img_warped.release();
                img.release();
                mask.release();

                dilate(masks_warped[img_idx], dilated_mask, Mat());
                resize(dilated_mask, seam_mask, mask_warped.size());
                mask_warped = seam_mask & mask_warped;

                if (blender.empty())
                {
                    blender = Blender::createDefault(blend_type, try_gpu);
                    Size dst_sz = resultRoi(corners, sizes).size();
                    float blend_width = sqrt(static_cast(dst_sz.area())) * blend_strength / 100.f;
                    if (blend_width < 1.f)
                        blender = Blender::createDefault(Blender::NO, try_gpu);
                    else if (blend_type == Blender::MULTI_BAND)
                    {
                        MultiBandBlender* mb = dynamic_cast(static_cast(blender));
                        mb->setNumBands(static_cast(ceil(log(blend_width) / log(2.)) - 1.));
                        cout << "Multi-band blender, number of bands: " << mb->numBands() << endl;
                    }
                    else if (blend_type == Blender::FEATHER)
                    {
                        FeatherBlender* fb = dynamic_cast(static_cast(blender));
                        fb->setSharpness(1.f / blend_width);
                        LOGLN("Feather blender, sharpness: " << fb->sharpness());
                    }
                    blender->prepare(corners, sizes);
                }

                // Blend the current image
                blender->feed(img_warped_s, mask_warped, corners[img_idx]);
            }
            Mat result, result_mask;
            blender->blend(result, result_mask);

            cout << "Compositing, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec" << endl;

            result.convertTo(frame, CV_8UC1);
			//resize(frame,frame,Size(640,480));
			frames.push_back(frame.clone());
            imshow("stitch", frame);
			imwrite("stitch.jpg",frame);
			//waitKey(30);

		

        }
        else
        {
            cout << "----------------------" << endl;
            cout << "waitting..." << endl;
        }

		Mat src;  
        int i; 
	    const int number = 150;
		
       //string src_image_name = "C:\\Users\\Administrator\\Desktop\\pic_save\\angle_x\\";  
        string src_image_name = "..\\stitch9\\";  
       // string src_image_name1 = src_image_name;  
        char num[number],num1[4] = "1(",num2[6] = ")";  
        string num3 = ".jpg";  
		int j = 1;
		for (vector::iterator ix = frames.begin(); ix!= frames.end(); ix++ )
        {  
           itoa(j,num,10);
		   //resize(*ix,*ix,Size(640,480));
           imwrite(src_image_name+num1+num+num2+num3,*ix);  
		   
		   j++;
         
    }  
	







        if (waitKey(1) == 13)
        {
            stop = true;
            cout << "程序结束！" << endl;
            cout << "*** ***" << endl;
        }
    }
 
	   //stich_xiu(pic_savea, pic_saveb,frame11,  frame22);
	   system("pause");
	   return 0;
	
}