• Hardware Platform (Jetson / GPU) : Jetson Nano
• DeepStream Version: 5.1
• JetPack Version (valid for Jetson only) : 4.5.1
• TensorRT Version : 126.96.36.199
I am using
deepstream_imagedata_multistream.py now I want to add some custom logic in this script.
I have already tried it but as soon as I add something fps drops drastically.
I am trying to change tiler_sink_pad_buffer_probe, changing anything in this function it increases the processing time and fps drops.
Is there any optimized way or method to do it?
Could you share the custom logic with us to check?
Since it is a multistream pipeline, please make sure your logic can support
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")
for i in range(number_sources):
os.mkdir(folder_name + "/stream_" + str(i))
frame_count["stream_" + str(i)] = 0
saved_count["stream_" + str(i)] = 0
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")
While I was going through the code I have worked on num_source. Currently I am working object tracking and for that I have Implemented tracker part in the code for different num_source. Right now it’s working fine. But as it in tiler_sink_pad_buffer_probe function. And that’s why I need more optimized way to intergrate it.
There is no update from you for a period, assuming this is not an issue any more.
Hence we are closing this topic. If need further support, please open a new one.
Would you mind sharing the source of your customized
So we can check the performance issue directly?
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