如何从ac语言程序中调用LSD（LineSegmentDetector）？

Question

我正在使用 LSD 来检测图像中的直线，我下载的代码包含调用 LSD 的最小示例，但它是静态的（即它仅输出主函数中的值）我想将代码应用于视频，这是输出静态结果的最小示例。

#include <stdio.h>
#include "lsd.h"

int main(void)
{
  image_double image;
  ntuple_list out;
  unsigned int x,y,i,j;
  unsigned int X = 512;  /* x image size */
  unsigned int Y = 512;  /* y image size */

  /* create a simple image: left half black, right half gray */
  image = new_image_double(X,Y);
  for(x=0;x<X;x++)
    for(y=0;y<Y;y++)
      image->data[ x + y * image->xsize ] = x<X/2 ? 0.0 : 64.0; /* image(x,y) */
   IplImage* imgInTmp = cvLoadImage("C:\Documents and Settings\Eslam farag\My Documents\Visual Studio 2008\Projects\line\hand.JPEG", 0);

  /* call LSD */

  out = lsd(image);

  /* print output */
  printf("%u line segments found:\n",out->size);
  for(i=0;i<out->size;i++)
    {
      for(j=0;j<out->dim;j++)
        printf("%f ",out->values[ i * out->dim + j ]);
      printf("\n");
    }

  /* free memory */
  free_image_double(image);
  free_ntuple_list(out);

  return 0;
}

如果有人可以帮助我在视频上应用代码，我会很高兴。谢谢 此致，

Answer 1

由于我找不到完整的示例，因此我分享了我编写的代码，该代码使用 OpenCV 从磁盘加载视频文件并对其执行一些图像处理。

该应用程序将文件名作为输入（在命令行上），并使用 OpenCV 内置函数 cvCvtColor() 将视频的每一帧转换为其等效的灰度图像。

我在代码中添加了一些注释，以帮助您理解基本任务。

read_video.cpp：

#include <stdio.h>
#include <highgui.h>
#include <cv.h>

int main(int argc, char* argv[])
{
    cvNamedWindow("video", CV_WINDOW_AUTOSIZE);

    CvCapture *capture = cvCaptureFromAVI(argv[1]);
    if(!capture)
    {
        printf("!!! cvCaptureFromAVI failed (file not found?)\n");
        return -1;
    }

    IplImage* frame;
    char key = 0;
    while (key != 'q') // Loop for querying video frames. Pressing Q will quit
    {
        frame = cvQueryFrame( capture );
        if( !frame )
        {
            printf("!!! cvQueryFrame failed\n");
            break;
        }

        /* Let's do a grayscale conversion just 4 fun */

        // A grayscale image has only one channel, and most probably the original
        // video works with 3 channels (RGB). So, for the conversion to work, we
        // need to allocate an image with only 1 channel to store the result of 
        // this operation.
        IplImage* gray_frame = 0;
        gray_frame = cvCreateImage(cvSize(frame->width, frame->height), frame->depth, 1);
        if (!gray_frame)
        {
            printf("!!! cvCreateImage failed!\n" );
            return -1;
        }

        cvCvtColor(frame, gray_frame, CV_RGB2GRAY); // The conversion itself

        // Display processed frame on window
        cvShowImage("video", gray_frame);

        // Release allocated resources
        cvReleaseImage(&gray_frame);

        key = cvWaitKey(33);
    }

    cvReleaseCapture(&capture);
    cvDestroyWindow("video");
}

编译为：

g++ read_video.cpp -o read `pkg-config --cflags --libs opencv`

如果您想知道如何迭代帧的像素来进行自定义处理，您需要检查以下答案，因为它展示了如何进行手动灰度转换。就这样：OpenCV cvSet2d.....这是做什么的< /a>

Answer 2

的代码示例

#include "lsd.h"

void Test_LSD(IplImage* img)
{
    IplImage* grey = cvCreateImage(cvGetSize(img), IPL_DEPTH_8U, 1);
    cvCvtColor(img, grey, CV_BGR2GRAY);
    image_double image;
    ntuple_list out;
    unsigned int x,y,i,j;
    image = new_image_double(img->width,img->height);
    for(x=0;x<grey->width;x++)
    for(y=0;y<grey->height;y++)
    {
      CvScalar s= cvGet2D(grey,y,x);
      double pix= s.val[0];
      image->data[ x + y * image->xsize ]= pix; /* image(x,y) */
    }

    /* call LSD */
    out = lsd(image);
    //out= lsd_scale(image,1);

    /* print output */
    printf("%u line segments found:\n",out->size);
    vector<Line> vec;
    for(i=0;i<out->size;i++)
    {
      //for(j=0;j<out->dim;j++)
      {
        //printf("%f ",out->values[ i * out->dim + j ]);
          Line line;
          line.x1= out->values[ i * out->dim + 0];
          line.y1= out->values[ i * out->dim + 1];
          line.x2= out->values[ i * out->dim + 2];
          line.y2= out->values[ i * out->dim + 3];
          vec.push_back(line);
      }
      //printf("\n");
    }

    IplImage* black= cvCreateImage(cvGetSize(img), IPL_DEPTH_8U, 3);
    cvZero(black);
    draw_lines(vec,black);
    /*cvNamedWindow("img", 0);
    cvShowImage("img", img);*/
    cvSaveImage("lines_detect.png",black/*img*/);
    /* free memory */
    free_image_double(image);
    free_ntuple_list(out);
}

这是使用 LSD 与 opencv或这种方式

IplImage* get_lines(IplImage* img,vector<Line>& vec_lines)
{
    //to grey
    //IplImage* grey = cvCreateImage(cvGetSize(img), IPL_DEPTH_8U, 1);
    //cvCvtColor(img, grey, CV_BGR2GRAY);

    image_double image;
    ntuple_list out;
    unsigned int x,y,i,j;
    image = new_image_double(img->width,img->height);
    for(x=0;x</*grey*/img->width;x++)
    for(y=0;y</*grey*/img->height;y++)
    {
      CvScalar s= cvGet2D(/*grey*/img,y,x);
      double pix= s.val[0];
      image->data[ x + y * image->xsize ]= pix;
    }

    /* call LSD */
    out = lsd(image);
    //out= lsd_scale(image,1);

    /* print output */
    //printf("%u line segments found:\n",out->size);
    //vector<Line> vec;
    for(i=0;i<out->size;i++)
    {
      //for(j=0;j<out->dim;j++)
      {
        //printf("%f ",out->values[ i * out->dim + j ]);
          Line line;
          line.x1= out->values[ i * out->dim + 0];
          line.y1= out->values[ i * out->dim + 1];
          line.x2= out->values[ i * out->dim + 2];
          line.y2= out->values[ i * out->dim + 3];
          /*vec*/vec_lines.push_back(line);
      }
      //printf("\n");
    }

    IplImage* black= cvCreateImage(cvGetSize(img), IPL_DEPTH_8U, 1);
    cvZero(black);
    for(int i=0;i<vec_lines.size();++i)
    {
        //if(vec[i].x1==vec[i].x2||vec[i].y1==vec[i].y2)
        cvLine(black,cvPoint(vec_lines[i].x1,vec_lines[i].y1),cvPoint(vec_lines[i].x2,vec_lines[i].y2),CV_RGB(255,255,255),1, CV_AA);
    }
    /*cvNamedWindow("img", 0);
    cvShowImage("img", img);*/
    //cvSaveImage("lines_detect.png",black/*img*/);
    /* free memory */
    //cvReleaseImage(&grey);
    free_image_double(image);
    free_ntuple_list(out);

    return black;
}