我在解码从raspberry pi到带有Qt的笔记本电脑的视频流时遇到了问题。
我的pi管道是(使用adafruit raspberry pi摄像机):
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 只需在笔记本上使用查看器和管道:
gst-launch-1.0 -v tcpclientsrc host=10.0.0.128 port=5000 ! gdpdepay ! rtph264depay ! avdec_h264 ! videoconvert ! autovideosink sync=false 提供非常好的彩色视频,以一个相当不错的速度,虽然我没有测量的帧率。
当我在我的图形用户界面应用程序中使用qtgstreamer (有一个源width=640、height=480和我假设一个8位RGB映像)时,我在下面的代码中得到了460800的缓冲区大小,并且我希望它是921600。如果我使用QImage::Format_RGB888,程序会崩溃,因为图像缓冲区太小了。如果我使用QImage::Format_Index8,它将运行良好,显示视频在我的图形用户界面和一切,但是黑色和白色。有人有什么想法吗?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;
}发布于 2017-10-06 17:27:53
所以,经过一段可笑的时间和谷歌搜索,我找到了答案。最后,我使用opencv进行了实际的颜色转换。下面是我的方法(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);我会发布更多的信息,我的申请git回购,但我认为这可能有助于其他人。
下面是链接:相机流光实例
发布于 2017-10-02 07:16:33
如果是I420,那么布局是:
460800 = 640 * 480 + 320 * 240 + 320 * 240卢马平原Y为640 * 480,色度平原U和V均为320 * 240。所以UV平原的分辨率较小,在这些阵列上循环时要考虑到这一点。
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 * Uhttps://stackoverflow.com/questions/46467934
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