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c++ - 从.oni文件读取导致帧困惑

我的问题是this one的副本。没有解决办法。为了找到解决方案并详细说明我的特定设置，下面显示了用于从.oni文件读取帧的函数。如果此函数在Type==2的情况下运行（即运行于#的RGBD图像，其中条件为#），则在for循环中运行此函数应允许用户访问每个图像。但是，彩色图像和深度图像的索引不匹配，并且顺序不对。这将一直持续到waitForAnyStream对于以下所有对IMG_pipeline：：listen（…）的调用超时为止。

void IMG_pipeline::listen(int Type, int Criteria){
    int exitNumber;
    clock_t start = clock();
    double elapsedtime;
    openni::VideoFrameRef frame;
    int CurrentIMGCount=0;

    switch (Type){
    case 0:
    {
        exitNumber = -1;
        break;
    }
    case 1:
    {
        exitNumber = Criteria;
        break;
    }
    case 2:
    {
        exitNumber = -1;
        break;
    }
    }


    for (int i = 0;i!=exitNumber;i++){
        readyStream = -1;
        rc = openni::OpenNI::waitForAnyStream(streams, 2, &readyStream, SAMPLE_READ_WAIT_TIMEOUT);
        if (rc != openni::STATUS_OK)
        {
            printf("Wait failed! (timeout is %d ms)\n%s\n", SAMPLE_READ_WAIT_TIMEOUT, openni::OpenNI::getExtendedError());
            //break;
        }

        switch (readyStream)
        {
        case 0:
        {
            // Depth
            depth.readFrame(&frame);
            break;
        }
        case 1:
        {
            // Color
            color.readFrame(&frame);
            break;
        }
        default:
        {
            printf("Unexpected stream: %i\n", readyStream);
            continue;
        }
        }


        int Height = frame.getHeight();
        int Width = frame.getWidth();

        cvColor.release();
        cvX.release();
        cvY.release();
        cvZ.release();

        cvColor = cv::Mat(Height, Width, CV_8UC3);
        cvX = cv::Mat(Height, Width, CV_32F);
        cvY = cv::Mat(Height, Width, CV_32F);
        cvZ = cv::Mat(Height, Width, CV_32F);

        switch (frame.getVideoMode().getPixelFormat())
        {
        case openni::PIXEL_FORMAT_DEPTH_1_MM:
        case openni::PIXEL_FORMAT_DEPTH_100_UM:
        {
            openni::DepthPixel* pDepth = (openni::DepthPixel*)frame.getData();
            int k =0;
            for (int ri = 0; ri<Height; ri++)
            {
                for (int ci = 0; ci<Width; ci++)
                {
                    float pdepth_val = pDepth[k];
                    openni::CoordinateConverter::convertDepthToWorld(depth, (float)ri, (float)ci, pdepth_val, &cvX.at<float>(ri,ci), &cvY.at<float>(ri,ci), &cvZ.at<float>(ri,ci));
                    k++;
                }
            }
            TotalFrames[0]++;
            XYZCaptured = true;
            printf("Frame Index: %i \n", frame.getFrameIndex());
            printf("Depth Captured. \n");
            break;
        }
        case openni::PIXEL_FORMAT_RGB888:
        {
            cvColor.data = (uchar*)frame.getData();
            TotalFrames[1]++;
            ColorCaptured = true;
            printf("Frame Index: %i \n", frame.getFrameIndex());
            printf("Color Captured. \n");
            break;
        }
        default:
            printf("Unknown format \n");
        }

        printf("Frame extracted. \n");
        if (ColorCaptured && XYZCaptured){
            if (NewButNotRead == true){
                IMGsMissed++;


            }
            else
                NewButNotRead = true;

            ColorCaptured = false;
            XYZCaptured = false;
            RGBD_out.clear();
            RGBD_out.push_back(cvX);
            RGBD_out.push_back(cvY);
            RGBD_out.push_back(cvZ);
            RGBD_out.push_back(cvColor);
            CurrentIMGCount++;
            printf("Image overwritten. \n");

        }
        elapsedtime=(clock()-start)/((double)CLOCKS_PER_SEC);

        printf("Time since listen initiation: %f \n \n", elapsedtime);
        if (CurrentIMGCount ==Criteria && Type == 2)
            return;
        else if (elapsedtime>(double)Criteria && Type==0)
            return;

    }
    frame.release();

}

下面是控制台输出示例：
Frame Index: 1
Depth Captured.
Frame extracted.
Time since listen initiation: 0.004846

Frame Index: 2
Depth Captured.
Frame extracted.
Time since listen initiation: 0.011601

Frame Index: 1
Color Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.012640

Depth frame count: 3
Color frame count: 2
Frame Index: 54
Color Captured.
Frame extracted.
Time since listen initiation: 0.000067

Frame Index: 57
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.005878

Depth frame count: 4
Color frame count: 3
Frame Index: 96
Color Captured.
Frame extracted.
Time since listen initiation: 0.000079

Frame Index: 99
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.003628

Depth frame count: 5
Color frame count: 4
Frame Index: 126
Color Captured.
Frame extracted.
Time since listen initiation: 0.000048

Frame Index: 130
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.004782

Depth frame count: 6
Color frame count: 5
Frame Index: 152
Color Captured.
Frame extracted.
Time since listen initiation: 0.000065

Frame Index: 156
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.008294

Depth frame count: 7
Color frame count: 6
Frame Index: 181
Color Captured.
Frame extracted.
Time since listen initiation: 0.000045

Frame Index: 185
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.004095

Depth frame count: 8
Color frame count: 7
Frame Index: 208
Color Captured.
Frame extracted.
Time since listen initiation: 0.000054

Frame Index: 212
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.004242

Depth frame count: 9
Color frame count: 8
Frame Index: 236
Color Captured.
Frame extracted.
Time since listen initiation: 0.000092

Frame Index: 240
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.005918

Depth frame count: 10
Color frame count: 9
Frame Index: 261
Color Captured.
Frame extracted.
Time since listen initiation: 0.000731

Frame Index: 262
Color Captured.
Frame extracted.
Time since listen initiation: 0.000877

Frame Index: 266
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.009347

Depth frame count: 11
Color frame count: 11
Frame Index: 286
Color Captured.
Frame extracted.
Time since listen initiation: 0.000047

Frame Index: 290
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.006080

Depth frame count: 12
Color frame count: 12
Frame Index: 311
Color Captured.
Frame extracted.
Time since listen initiation: 0.000072

Frame Index: 315
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.006453

Depth frame count: 13
Color frame count: 13
Frame Index: 337
Color Captured.
Frame extracted.
Time since listen initiation: 0.000062

Frame Index: 341
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.007485

Depth frame count: 14
Color frame count: 14
Frame Index: 367
Color Captured.
Frame extracted.
Time since listen initiation: 0.000042

Frame Index: 371
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.003758

Depth frame count: 15
Color frame count: 15
Frame Index: 390
Color Captured.
Frame extracted.
Time since listen initiation: 0.000073

Frame Index: 395
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.007917

Depth frame count: 16
Color frame count: 16
Frame Index: 416
Color Captured.
Frame extracted.
Time since listen initiation: 0.000105

Frame Index: 421
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.007554

Depth frame count: 17
Color frame count: 17
Frame Index: 453
Color Captured.
Frame extracted.
Time since listen initiation: 0.000060

Frame Index: 458
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.006150

Depth frame count: 18
Color frame count: 18
Frame Index: 481
Color Captured.
Frame extracted.
Time since listen initiation: 0.000074

Frame Index: 486
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.007169

Depth frame count: 19
Color frame count: 19
Frame Index: 517
Color Captured.
Frame extracted.
Time since listen initiation: 0.000045

Frame Index: 522
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.004196

Depth frame count: 20
Color frame count: 20
Frame Index: 547
Color Captured.
Frame extracted.
Time since listen initiation: 0.000071

Frame Index: 552
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.007375

Depth frame count: 21
Color frame count: 21
Frame Index: 625
Color Captured.
Frame extracted.
Time since listen initiation: 0.000179

Frame Index: 631
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.007922

Depth frame count: 22
Color frame count: 22
Wait failed! (timeout is 2000 ms)
    waitForStreams: timeout reached

Unexpected stream: -1
Wait failed! (timeout is 2000 ms)
    waitForStreams: timeout reached

Unexpected stream: -1
Wait failed! (timeout is 2000 ms)
    waitForStreams: timeout reached

Unexpected stream: -1
Wait failed! (timeout is 2000 ms)
    waitForStreams: timeout reached

Unexpected stream: -1
Wait failed! (timeout is 2000 ms)
    waitForStreams: timeout reached

Unexpected stream: -1
Wait failed! (timeout is 2000 ms)
    waitForStreams: timeout reached

Unexpected stream: -1
Wait failed! (timeout is 2000 ms)
    waitForStreams: timeout reached

Unexpected stream: -1

下面是对IMG_pipeline：：listen（…）的调用：
IMG_pipeline pip_inst;
std::string FileName = "/home/derek/Test Data/RGBD/RGBD_S2_R1";
int Type = 2;
int Criteria = 1;
std::vector<cv::Mat> OUT;
int NumMissedIMGs;

int Start;
int Stop;

pip_inst.connect(FileName);

while (true)
{
  pip_inst.listen(Type, Criteria);
  if (pip_inst.IsNewIMG()){
    OUT = pip_inst.GetImage();
    cv::imshow("Current Frame", OUT.at(3));
    char c = cv::waitKey(0);
    if (c == 'f')
    {
      printf("Depth frame count: %i \n", pip_inst.GetDepthFrameCount());
      printf("Color frame count: %i \n", pip_inst.GetColorFrameCount());

    }
    else
    {
      Start = pip_inst.GetColorFrameCount();
      break;
    }
    cv::destroyWindow("Current Frame");

  }


}

彩色图像也是交替的R，G，B色调。不过，我确信这是cv：：Mat中数据的顺序问题。
更有趣的是，对IMG_pipeline：：listen（…）的调用经过多个帧，其索引结果不同，然后多次运行IMG_pipeline：：listen（…），并通过.oni文件递增。

最佳答案

您可以使用oni命令从setSpeed文件控制播放速度。将speed设置为-1将确保可以按顺序从oni流中手动读取帧，即每次调用waitForAnyStream时，都保证获得流中的下一帧。详见“播放速度”here。

10-04 13:01
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