Question

我想编写一个使用OpenCV进行视频捕获的跨平台应用程序。在所有示例中，我发现使用抓取功能处理来自摄像机的帧并等待一段时间。我想处理序列中的每一帧。我想定义我自己的回调函数，每当新帧准备好处理时就会执行（比如在用于Windows的 directshow 中，当您定义并将图形放入自己的过滤器时为此目的）。

所以问题是：我该怎么做？

Answer 1

根据以下代码，所有回调都必须遵循以下定义：

IplImage* custom_callback(IplImage* frame);

此签名表示将在系统检索的每个帧上执行回调。在我的例子中，make_it_gray（）分配一个新图像以保存灰度转换的结果并返回它。这意味着您必须稍后在代码中释放此框架。我添加了关于它的代码的评论。

请注意，如果您的回调需要大量处理，系统可能会从相机中跳过几帧。考虑 Paul R 和 diverscuba23 的建议。

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


typedef IplImage* (*callback_prototype)(IplImage*);


/* 
 * make_it_gray: our custom callback to convert a colored frame to its grayscale version.
 * Remember that you must deallocate the returned IplImage* yourself after calling this function.
 */
IplImage* make_it_gray(IplImage* frame)
{
    // Allocate space for a new image
    IplImage* gray_frame = 0;
    gray_frame = cvCreateImage(cvSize(frame->width, frame->height), frame->depth, 1);
    if (!gray_frame)
    {
      fprintf(stderr, "!!! cvCreateImage failed!\n" );
      return NULL;
    }

    cvCvtColor(frame, gray_frame, CV_RGB2GRAY);
    return gray_frame; 
}

/*
 * process_video: retrieves frames from camera and executes a callback to do individual frame processing.
 * Keep in mind that if your callback takes too much time to execute, you might loose a few frames from 
 * the camera.
 */
void process_video(callback_prototype custom_cb)
{           
    // Initialize camera
    CvCapture *capture = 0;
    capture = cvCaptureFromCAM(-1);
    if (!capture) 
    {
      fprintf(stderr, "!!! Cannot open initialize webcam!\n" );
      return;
    }

    // Create a window for the video 
    cvNamedWindow("result", CV_WINDOW_AUTOSIZE);

    IplImage* frame = 0;
    char key = 0;
    while (key != 27) // ESC
    {    
      frame = cvQueryFrame(capture);
      if(!frame) 
      {
          fprintf( stderr, "!!! cvQueryFrame failed!\n" );
          break;
      }

      // Execute callback on each frame
      IplImage* processed_frame = (*custom_cb)(frame);

      // Display processed frame
      cvShowImage("result", processed_frame);

      // Release resources
      cvReleaseImage(&processed_frame);

      // Exit when user press ESC
      key = cvWaitKey(10);
    }

    // Free memory
    cvDestroyWindow("result");
    cvReleaseCapture(&capture);
}

int main( int argc, char **argv )
{
    process_video(make_it_gray);

    return 0;
}

修改

我更改了上面的代码，因此打印当前帧速率并执行手动灰度转换。它们是对代码的小调整，我是出于教育目的而做的，所以我们知道如何在像素级别执行操作。

#include <stdio.h> #include <time.h> #include "cv.h" #include "highgui.h" typedef IplImage* (*callback_prototype)(IplImage*); /* * make_it_gray: our custom callback to convert a colored frame to its grayscale version. * Remember that you must deallocate the returned IplImage* yourself after calling this function. */ IplImage* make_it_gray(IplImage* frame) { // New IplImage* to store the processed image IplImage* gray_frame = 0; // Manual grayscale conversion: ugly, but shows how to access each channel of the pixels individually gray_frame = cvCreateImage(cvSize(frame->width, frame->height), frame->depth, frame->nChannels); if (!gray_frame) { fprintf(stderr, "!!! cvCreateImage failed!\n" ); return NULL; } for (int i = 0; i < frame->width * frame->height * frame->nChannels; i += frame->nChannels) { gray_frame->imageData[i] = (frame->imageData[i] + frame->imageData[i+1] + frame->imageData[i+2])/3; //B gray_frame->imageData[i+1] = (frame->imageData[i] + frame->imageData[i+1] + frame->imageData[i+2])/3; //G gray_frame->imageData[i+2] = (frame->imageData[i] + frame->imageData[i+1] + frame->imageData[i+2])/3; //R } return gray_frame; } /* * process_video: retrieves frames from camera and executes a callback to do individual frame processing. * Keep in mind that if your callback takes too much time to execute, you might loose a few frames from * the camera. */ void process_video(callback_prototype custom_cb) { // Initialize camera CvCapture *capture = 0; capture = cvCaptureFromCAM(-1); if (!capture) { fprintf(stderr, "!!! Cannot open initialize webcam!\n" ); return; } // Create a window for the video cvNamedWindow("result", CV_WINDOW_AUTOSIZE); double elapsed = 0; int last_time = 0; int num_frames = 0; IplImage* frame = 0; char key = 0; while (key != 27) // ESC { frame = cvQueryFrame(capture); if(!frame) { fprintf( stderr, "!!! cvQueryFrame failed!\n" ); break; } // Calculating framerate num_frames++; elapsed = clock() - last_time; int fps = 0; if (elapsed > 1) { fps = floor(num_frames / (float)(1 + (float)elapsed / (float)CLOCKS_PER_SEC)); num_frames = 0; last_time = clock() + 1 * CLOCKS_PER_SEC; printf("FPS: %d\n", fps); } // Execute callback on each frame IplImage* processed_frame = (*custom_cb)(frame); // Display processed frame cvShowImage("result", processed_frame); // Release resources cvReleaseImage(&processed_frame); // Exit when user press ESC key = cvWaitKey(10); } // Free memory cvDestroyWindow("result"); cvReleaseCapture(&capture); } int main( int argc, char **argv ) { process_video(make_it_gray); return 0; }

Answer 2

快速思考是拥有2个线程，第一个线程负责抓取帧并通知第二个线程可用时（将它们放在处理队列中），第二个线程在事件循环中完成所有处理类型的方式。

请参阅boost :: thread和boost :: signals2，因为这两者应该为我上面描述的内容提供大部分框架（队列除外）。

OpenCV：处理每一帧

2 个答案: