在 Qt 和 Raspberry Pi 中使用 qtgstreamer

Using qtgstreamer with Qt and Raspberry Pi

我在将视频流从 raspberry pi 解码到带有 Qt GUI 的笔记本电脑时遇到问题。

我的 pi 管道是(使用 adafruit raspberry pi 相机):

raspivid -t 999999 -h 480 -w 640 -fps 25 -hf -b 2000000 -o - | gst-launch-1.0 -v fdsrc ! h264parse !  rtph264pay config-interval=1 pt=96 ! gdppay ! tcpserversink host=10.0.0.128 port=5000 

只需在带管道的笔记本电脑上使用查看器:

gst-launch-1.0 -v tcpclientsrc host=10.0.0.128 port=5000  ! gdpdepay !  rtph264depay ! avdec_h264 ! videoconvert ! autovideosink sync=false 

虽然我没有测量帧速率,但以相当不错的速率提供了非常漂亮的彩色视频。

当我在我的 GUI 应用程序中使用 qtgstreamer 时(源宽度 = 640,高度 = 480,我假设一个 8 位 RGB 图像)我在下面的代码中得到缓冲区大小 460800,我期望它是 921600。如果我使用 QImage::Format_RGB888 程序将崩溃,因为图像缓冲区太小。如果我使用 QImage::Format_Index8 它将 运行 正常,在我的 GUI 中显示视频,除了黑白之外都是。谁有想法?这是我的相关代码:

bool CameraStreamer::initStreamer()
{
    gst_init (NULL, NULL);
    //gst-launch-1.0 -v tcpclientsrc host=10.0.0.128 port=5000  ! gdpdepay !  rtph264depay ! avdec_h264 ! videoconvert ! autovideosink sync=false
    pipeline = gst_pipeline_new("Camera");
    source                  = gst_element_factory_make ("tcpclientsrc",           "cam-source");
    depay                   = gst_element_factory_make("gdpdepay",      "depay");
    rtpdepay                = gst_element_factory_make("rtph264depay","rtp-depay");
    decoder                 = gst_element_factory_make ("avdec_h264",          "videodecoder");
    videoconvert            = gst_element_factory_make("videoconvert","video-convert");
    sink                    = gst_element_factory_make ("appsink",          "video-output");
    if (!pipeline || !source  || !depay || !rtpdepay || !decoder || !videoconvert || !sink ) {
      qDebug() << "One element could not be created. Exiting.\n";
      return false;
    }
    callbacks.eos = NULL;
    callbacks.new_sample = newBufferCallback;
    callbacks.new_preroll = NULL;
    gst_app_sink_set_callbacks((GstAppSink *) sink, &callbacks, this, NULL);
    g_object_set (G_OBJECT(source), "port", 5001, NULL);
    g_object_set (G_OBJECT(source),"host","10.0.0.128",NULL);
    gst_bin_add_many (GST_BIN (pipeline),
                      source, depay,rtpdepay,decoder, videoconvert,sink, NULL);
    if (!gst_element_link_many (source, depay,rtpdepay,decoder, videoconvert,sink, NULL))
        g_warning ("Main pipeline link Fail...");
    ret = gst_element_set_state (pipeline, GST_STATE_PLAYING);
    if (ret == GST_STATE_CHANGE_FAILURE)
    {
        g_printerr ("Unable to set the pipeline to the playing state.");
        gst_object_unref (pipeline);
        return false;
    }
    return true;
}

GstFlowReturn CameraStreamer::newBufferCallback(GstAppSink *app_sink, void *obj)
{
    if(app_sink == NULL)
    {
        qDebug() << "app_sink is NULL";
        return GST_FLOW_ERROR;
    }
    GstSample* sample = gst_app_sink_pull_sample(app_sink);
    if(!sample)
    {
        qDebug() << "Error retreiving buffer...";
        return GST_FLOW_ERROR;
    }
    GstCaps* caps = gst_sample_get_caps (sample);
    if (!caps) {
        qDebug() << "could not get snapshot format\n";
        exit (-1);
    }
    gint width, height;
    GstStructure* s = gst_caps_get_structure (caps, 0);
    int res = gst_structure_get_int (s, "width", &width)
        | gst_structure_get_int (s, "height", &height);
    if (!res) {
        qDebug() << "could not get snapshot dimension\n";
        exit (-1);
    }
    GstMapInfo map;

    GstBuffer *buffer = gst_sample_get_buffer (sample);
    qDebug() << "size: " << gst_buffer_get_size(buffer);
    gst_buffer_map (buffer, &map, GST_MAP_READ);
    QImage img(map.data,width,height, QImage::Format_RGB888);
    img = img.copy();
    ((CameraStreamer*)obj)->emitNewImage(img);
    gst_buffer_unmap (buffer, &map);
    gst_sample_unref (sample);
    return GST_FLOW_OK;
}

如果是 I420,则布局为:

460800 = 640 * 480 + 320 * 240 + 320 * 240

亮度平面 Y 为 640 * 480,色度平面 U 和 V 均为 320 * 240。因此 UV 平面的分辨率较小,在循环这些数组时将其考虑在内。

来自维基百科的颜色转换公式:

R = Y + 1.140 * V
G = Y - 0.395 * U - 0.581 * V
B = Y + 2.032 * U

因此,经过大量时间和谷歌搜索后,我找到了答案。我最终使用 opencv 进行了实际的颜色转换。这是我的方法(从上面继续):

GstBuffer *buffer = gst_sample_get_buffer (sample);
gst_buffer_map (buffer, &map, GST_MAP_READ);
cv::Mat temp_mat = cv::Mat(cv::Size(width, height+height/2), CV_8UC1, (char*)map.data);
cv::Mat result(height,width,3);
cv::cvtColor(temp_mat,result,CV_YUV2RGB_I420,3);
QImage rgb(result.size().width,result.size().height,QImage::Format_RGB888);
memcpy(rgb.scanLine(0), (unsigned char*)result.data, rgb.width() * rgb.height() * result.channels());
((CameraStreamer*)obj)->emitNewImage(rgb);
gst_buffer_unmap (buffer, &map);
gst_sample_unref (sample);

我会 post 关于我的应用程序 git 存储库的更多信息,但我认为这可能会对其他人有所帮助。

这是 link:camera streamer example