Hi,
I am currently using the new Streammux configuration, which works correctly when both streams are running over a stable connection. However, when the connection becomes unstable, only one of the two streams remains functional, while the other stops working.
It is important to note that when each stream is run separately in its own pipeline, they both function properly, even under the same network conditions.
I would like to know how to ensure that both streams remain functional within the same pipeline, even when the connection is unstable—similar to the behavior observed when using local streams.
Thank you for your support.
os.environ['USE_NEW_NVSTREAMMUX'] = 'yes'
os.environ['NVSTREAMMUX_ADAPTIVE_BATCHING'] = 'yes'
self.streammux = Gst.ElementFactory.make("nvstreammux", "Stream-muxer")
if not self.streammux:
sys.stderr.write(" Unable to create NvStreamMux \n")
self.pipeline.add(self.streammux)
batched_push_timeout=2560
max_same_source_frames=85
max_latency_ms = 500
max_latency_us = max_latency_ms * 1000 # Convertir en microsecondes
self.streammux.set_property("batch-size", self.number_sources)
self.streammux.set_property("attach-sys-ts", True)
self.streammux.set_property("sync-inputs", 0)
self.streammux.set_property('max-latency', max_latency_us)
• Hardware Platform: GPU
• DeepStream Version 6.4
• TensorRT Version 8.6.1
• Issue Type questions,bugs