Segmentation fault (core dumped) in loop.run()

Accelerated Computing Intelligent Video Analytics DeepStream SDK
1

Please provide complete information as applicable to your setup.

• Hardware Platform (Jetson / GPU) H100
• DeepStream Version 6.4
• JetPack Version (valid for Jetson only)
• TensorRT Version
• NVIDIA GPU Driver Version (valid for GPU only) 535
• Issue Type( questions, new requirements, bugs)
• How to reproduce the issue ? (This is for bugs. Including which sample app is using, the configuration files content, the command line used and other details for reproducing)
• Requirement details( This is for new requirement. Including the module name-for which plugin or for which sample application, the function description)

Let me explain my problem below.
I am working on the deepstream lpr application in python and is working totally fine on my PC (RTX3050). However, when i move the exact same code to my H100 server, the application will give Segmentation fault when i am running RTSP streams. Thus, i tried using a mp4 file instead of rtsp stream and the mp4 file can be used but unexpectedly it ended early as it received EOS when the video started to load approximately for 5seconds.

Please provide some advice. Both are using Deepstream 6.4.

3

H100 cannot support hardware encoder. You can try to change the encoder to x264enc.

4

Hi, instead of the encoder, after debugging i found out that the deepstream in my H100 fails to add the decodebin0. Any idea of this?

The error shows below:

Decodebin child added: source 

Segmentation fault (core dumped)

Below shows the output from my RTX3050:

Decodebin child added: source 

Decodebin child added: decodebin0 

Decodebin child added: qtdemux0 

Decodebin child added: multiqueue0 

Decodebin child added: h264parse0 

Decodebin child added: capsfilter0 

Decodebin child added: nvv4l2decoder0

Is there any specification or other plugins for H100 that is needed to use to decode the rtsp to raw media?

5

The code shows below:

def cb_newpad(decodebin, decoder_src_pad, data):
    print("In cb_newpad\n")
    caps = decoder_src_pad.get_current_caps()
    gststruct = caps.get_structure(0)
    gstname = gststruct.get_name()
    source_bin = data
    features = caps.get_features(0)

    # Need to check if the pad created by the decodebin is for video and not
    # audio.
    print("gstname=", gstname)
    if gstname.find("video") != -1:
        # Link the decodebin pad only if decodebin has picked nvidia
        # decoder plugin nvdec_*. We do this by checking if the pad caps contain
        # NVMM memory features.
        print("features=", features)
        if features.contains("memory:NVMM"):
            # Get the source bin ghost pad
            bin_ghost_pad = source_bin.get_static_pad("src")
            if not bin_ghost_pad.set_target(decoder_src_pad):
                sys.stderr.write(
                    "Failed to link decoder src pad to source bin ghost pad\n"
                )
        else:
            sys.stderr.write(" Error: Decodebin did not pick nvidia decoder plugin.\n")


def decodebin_child_added(child_proxy, Object, name, user_data):
    print("Decodebin child added:", name, "\n")
    print(Object)
    print(name)
    if name.find("decodebin") != -1:
        Object.connect("child-added", decodebin_child_added, user_data)

    if name.find("nvv4l2decoder") != -1:
        
        Object.set_property("drop-frame-interval", 3)
        Object.set_property("num-extra-surfaces", 16)
        if is_aarch64():
            print("Seting bufapi_version\n")
            Object.set_property("bufapi-version", True)


def create_source_bin(index, uri):
    print("Creating source bin")

    # Create a source GstBin to abstract this bin's content from the rest of the
    # pipeline
    bin_name = "source-bin-%02d" % index
    print(bin_name)
    nbin = Gst.Bin.new(bin_name)
    if not nbin:
        sys.stderr.write(" Unable to create source bin \n")

    # Source element for reading from the uri.
    # We will use decodebin and let it figure out the container format of the
    # stream and the codec and plug the appropriate demux and decode plugins.
    uri_decode_bin = Gst.ElementFactory.make("uridecodebin", "uri-decode-bin")
    if not uri_decode_bin:
        sys.stderr.write(" Unable to create uri decode bin \n")
    # We set the input uri to the source element
    uri_decode_bin.set_property("uri", uri)
    # Connect to the "pad-added" signal of the decodebin which generates a
    # callback once a new pad for raw data has beed created by the decodebin
    uri_decode_bin.connect("pad-added", cb_newpad, nbin)
    uri_decode_bin.connect("child-added", decodebin_child_added, nbin)
    # We need to create a ghost pad for the source bin which will act as a proxy
    # for the video decoder src pad. The ghost pad will not have a target right
    # now. Once the decode bin creates the video decoder and generates the
    # cb_newpad callback, we will set the ghost pad target to the video decoder
    # src pad.
    Gst.Bin.add(nbin, uri_decode_bin)
    bin_pad = nbin.add_pad(Gst.GhostPad.new_no_target("src", Gst.PadDirection.SRC))
    if not bin_pad:
        sys.stderr.write(" Failed to add ghost pad in source bin \n")
        return None
    return nbin
6

Could you attach the format of your source file? You can find the formats supported by the hardware decoder at the following page video-encode-and-decode-gpu-support-matrix-new.

7

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

8

This topic was automatically closed 14 days after the last reply. New replies are no longer allowed.