How to save output of rtsp video in Deepstream 6.1

Please provide complete information as applicable to your setup.

• Hardware Platform (Jetson / GPU) dGPU
• DeepStream Version 6,1
• JetPack Version (valid for Jetson only)
• TensorRT Version
• NVIDIA GPU Driver Version (valid for GPU only)

I have modified deepstream nvanalytics example to save the video and tested the code on the sample video and the code is working perfectly. The problem is that I can’t open the video before the execution is completed. I have to execute this code on RTSP input. Is there any way that I can open the generated video during the execution?

Modified Code

def main(args):
    if len(args) < 2:
        sys.stderr.write("usage: %s <uri1> [uri2] ... [uriN]\n" % args[0])
        sys.exit(1)

    global perf_data
    perf_data = PERF_DATA(len(args) - 1)
    number_sources=len(args)-1

    # Standard GStreamer initialization
    Gst.init(None)

    # Create gstreamer elements */
    # Create Pipeline element that will form a connection of other elements
    print("Creating Pipeline \n ")
    pipeline = Gst.Pipeline()
    is_live = False

    if not pipeline:
        sys.stderr.write(" Unable to create Pipeline \n")
    print("Creating streamux \n ")

    # Create nvstreammux instance to form batches from one or more sources.
    streammux = Gst.ElementFactory.make("nvstreammux", "Stream-muxer")
    if not streammux:
        sys.stderr.write(" Unable to create NvStreamMux \n")

    pipeline.add(streammux)
    for i in range(number_sources):
        print("Creating source_bin ",i," \n ")
        uri_name=args[i+1]
        if uri_name.find("rtsp://") == 0 :
            is_live = True
        source_bin=create_source_bin(i, uri_name)
        if not source_bin:
            sys.stderr.write("Unable to create source bin \n")
        pipeline.add(source_bin)
        padname="sink_%u" %i
        sinkpad= streammux.get_request_pad(padname) 
        if not sinkpad:
            sys.stderr.write("Unable to create sink pad bin \n")
        srcpad=source_bin.get_static_pad("src")
        if not srcpad:
            sys.stderr.write("Unable to create src pad bin \n")
        srcpad.link(sinkpad)
    queue1=Gst.ElementFactory.make("queue","queue1")
    queue2=Gst.ElementFactory.make("queue","queue2")
    queue3=Gst.ElementFactory.make("queue","queue3")
    queue4=Gst.ElementFactory.make("queue","queue4")
    queue5=Gst.ElementFactory.make("queue","queue5")
    queue6=Gst.ElementFactory.make("queue","queue6")
    queue7=Gst.ElementFactory.make("queue","queue7")
    pipeline.add(queue1)
    pipeline.add(queue2)
    pipeline.add(queue3)
    pipeline.add(queue4)
    pipeline.add(queue5)
    pipeline.add(queue6)
    pipeline.add(queue7)

    print("Creating Pgie \n ")
    pgie = Gst.ElementFactory.make("nvinfer", "primary-inference")
    if not pgie:
        sys.stderr.write(" Unable to create pgie \n")

    print("Creating nvtracker \n ")
    tracker = Gst.ElementFactory.make("nvtracker", "tracker")
    if not tracker:
        sys.stderr.write(" Unable to create tracker \n")

    print("Creating nvdsanalytics \n ")
    nvanalytics = Gst.ElementFactory.make("nvdsanalytics", "analytics")
    if not nvanalytics:
        sys.stderr.write(" Unable to create nvanalytics \n")
    nvanalytics.set_property("config-file", "config_nvdsanalytics copy.txt")

    print("Creating tiler \n ")
    tiler=Gst.ElementFactory.make("nvmultistreamtiler", "nvtiler")
    if not tiler:
        sys.stderr.write(" Unable to create tiler \n")

    print("Creating nvvidconv \n ")
    nvvidconv = Gst.ElementFactory.make("nvvideoconvert", "convertor")
    if not nvvidconv:
        sys.stderr.write(" Unable to create nvvidconv \n")

    print("Creating nvosd \n ")
    nvosd = Gst.ElementFactory.make("nvdsosd", "onscreendisplay")
    if not nvosd:
        sys.stderr.write(" Unable to create nvosd \n")
    nvosd.set_property('process-mode',OSD_PROCESS_MODE)
    nvosd.set_property('display-text',OSD_DISPLAY_TEXT)
    """Modified Start"""
    nvvidconv2 = Gst.ElementFactory.make("nvvideoconvert", "convertor2")
    if not nvvidconv2:
        sys.stderr.write(" Unable to create nvvidconv2 \n")

    capsfilter = Gst.ElementFactory.make("capsfilter", "capsfilter")
    if not capsfilter:
        sys.stderr.write(" Unable to create capsfilter \n")

    caps = Gst.Caps.from_string("video/x-raw, format=I420")
    capsfilter.set_property("caps", caps)

    encoder = Gst.ElementFactory.make("avenc_mpeg4", "encoder")
    if not encoder:
        sys.stderr.write(" Unable to create encoder \n")
    encoder.set_property("bitrate", 2000000)

    print("Creating Code Parser \n")
    codeparser = Gst.ElementFactory.make("mpeg4videoparse", "mpeg4-parser")
    if not codeparser:
        sys.stderr.write(" Unable to create code parser \n")

    print("Creating Container \n")
    container = Gst.ElementFactory.make("qtmux", "qtmux")
    if not container:
        sys.stderr.write(" Unable to create code parser \n")

    print("Creating Sink \n")
    sink = Gst.ElementFactory.make("filesink", "filesink")
    if not sink:
        sys.stderr.write(" Unable to create file sink \n")

    sink.set_property("location", "./out.mp4")
    sink.set_property("sync", 1)
    sink.set_property("async", 0)
    """Modified End"""


    if is_live:
        print("Atleast one of the sources is live")
        streammux.set_property('live-source', 1)

    streammux.set_property('width', 1920)
    streammux.set_property('height', 1080)
    streammux.set_property('batch-size', number_sources)
    streammux.set_property('batched-push-timeout', 4000000)
    pgie.set_property('config-file-path', "dsnvanalytics_pgie_config.txt")
    pgie_batch_size=pgie.get_property("batch-size")
    if(pgie_batch_size != number_sources):
        print("WARNING: Overriding infer-config batch-size",pgie_batch_size," with number of sources ", number_sources," \n")
        pgie.set_property("batch-size",number_sources)
    tiler_rows=int(math.sqrt(number_sources))
    tiler_columns=int(math.ceil((1.0*number_sources)/tiler_rows))
    tiler.set_property("rows",tiler_rows)
    tiler.set_property("columns",tiler_columns)
    tiler.set_property("width", TILED_OUTPUT_WIDTH)
    tiler.set_property("height", TILED_OUTPUT_HEIGHT)
    sink.set_property("qos",0)

    #Set properties of tracker
    config = configparser.ConfigParser()
    config.read('dsnvanalytics_tracker_config.txt')
    config.sections()

    for key in config['tracker']:
        if key == 'tracker-width' :
            tracker_width = config.getint('tracker', key)
            tracker.set_property('tracker-width', tracker_width)
        if key == 'tracker-height' :
            tracker_height = config.getint('tracker', key)
            tracker.set_property('tracker-height', tracker_height)
        if key == 'gpu-id' :
            tracker_gpu_id = config.getint('tracker', key)
            tracker.set_property('gpu_id', tracker_gpu_id)
        if key == 'll-lib-file' :
            tracker_ll_lib_file = config.get('tracker', key)
            tracker.set_property('ll-lib-file', tracker_ll_lib_file)
        if key == 'll-config-file' :
            tracker_ll_config_file = config.get('tracker', key)
            tracker.set_property('ll-config-file', tracker_ll_config_file)
        if key == 'enable-batch-process' :
            tracker_enable_batch_process = config.getint('tracker', key)
            tracker.set_property('enable_batch_process', tracker_enable_batch_process)
        if key == 'enable-past-frame' :
            tracker_enable_past_frame = config.getint('tracker', key)
            tracker.set_property('enable_past_frame', tracker_enable_past_frame)

    print("Adding elements to Pipeline \n")
    pipeline.add(pgie)
    pipeline.add(tracker)
    pipeline.add(nvanalytics)
    pipeline.add(tiler)
    pipeline.add(nvvidconv)
    """Modified Start"""
    pipeline.add(nvvidconv2)
    pipeline.add(encoder)
    pipeline.add(capsfilter)
    pipeline.add(codeparser)
    pipeline.add(container)
    """Modified End"""
    pipeline.add(nvosd)

    # if is_aarch64():
    #     pipeline.add(transform)
    pipeline.add(sink)

    # We link elements in the following order:
    # sourcebin -> streammux -> nvinfer -> nvtracker -> nvdsanalytics ->
    # nvtiler -> nvvideoconvert -> nvdsosd -> sink
    print("Linking elements in the Pipeline \n")
    streammux.link(queue1)
    queue1.link(pgie)
    pgie.link(queue2)
    queue2.link(tracker)
    tracker.link(queue3)
    queue3.link(nvanalytics)
    nvanalytics.link(queue4)
    queue4.link(tiler)
    tiler.link(queue5)
    queue5.link(nvvidconv)
    nvvidconv.link(queue6)
    queue6.link(nvosd)
    nvosd.link(queue7)
    queue7.link(nvvidconv2)
    nvvidconv2.link(capsfilter)
    capsfilter.link(encoder)
    encoder.link(codeparser)
    sinkpad1 = container.get_request_pad("video_0")
    if not sinkpad1:
        sys.stderr.write(" Unable to get the sink pad of qtmux \n")
    srcpad1 = codeparser.get_static_pad("src")
    if not srcpad1:
        sys.stderr.write(" Unable to get mpeg4 parse src pad \n")
    srcpad1.link(sinkpad1)
    container.link(sink)


    # create an event loop and feed gstreamer bus mesages to it
    loop = GLib.MainLoop()
    bus = pipeline.get_bus()
    bus.add_signal_watch()
    bus.connect ("message", bus_call, loop)
    nvanalytics_src_pad=nvanalytics.get_static_pad("src")

    if not nvanalytics_src_pad:
        sys.stderr.write(" Unable to get src pad \n")
    else:
        nvanalytics_src_pad.add_probe(Gst.PadProbeType.BUFFER, nvanalytics_src_pad_buffer_probe, 0)
        # perf callback function to print fps every 5 sec
        GLib.timeout_add(5000, perf_data.perf_print_callback)

    # List the sources
    print("Now playing...")
    for i, source in enumerate(args):
        if (i != 0):
            print(i, ": ", source)

    print("Starting pipeline \n")
    # start play back and listed to events		
    pipeline.set_state(Gst.State.PLAYING)
    try:
        loop.run()
    except:
        pass
    # cleanup
    print("Exiting app\n")
    pipeline.set_state(Gst.State.NULL)

There is no update from you for a period, assuming this is not an issue anymore. Hence we are closing this topic. If need further support, please open a new one. Thanks

You can refer to the deepstream_test_4.py to use a tee plugin. It will split data to multiple pads. Then one stream is used for saving to mp4 and the other is used for rtsp output.

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