Tracker not running inside docker l4t container


I get the following error, when i try to run the people counting pipeline with a tracker.

gst-launch-1.0 videotestsrc ! nvvideoconvert ! "video/x-raw(memory:NVMM), format=(string)NV12" ! m.sink_0 nvstreammux name=m batch-size=1 width=1080 height=800 ! nvinfer unique-id=1 config-file-path=/ai_vision_mounted/configs/dstest1_pgie_config.txt model-engine-file=/opt/nvidia/deepstream/deepstream-6.1/samples/models/Primary_Detector/resnet10.caffemodel_b1_gpu0_int8.engine batch-size=1 interval=1 ! nvtracker ll-config-file=/opt/nvidia/deepstream/deepstream-6.1/samples/configs/deepstream-app/config_tracker_NvDCF_accuracy.yml ll-lib-file=/opt/nvidia/deepstream/deepstream-6.1/lib/ ! nvvideoconvert ! nvdsosd ! fakesink
Setting pipeline to PAUSED ...
gstnvtracker: Loading low-level lib at /opt/nvidia/deepstream/deepstream-6.1/lib/
gstnvtracker: Failed to open low-level lib at /opt/nvidia/deepstream/deepstream-6.1/lib/
 dlopen error: /opt/nvidia/vpi2/lib64/priv/ undefined symbol: PvaQueueSubmit
gstnvtracker: Failed to initilaize low level lib.
ERROR: Pipeline doesn't want to pause.
Setting pipeline to NULL ...
Freeing pipeline ...


• Hardware Platform Jetson
• JetPack Version: JetPack 5.0.2
• Docker Image deepstream-l4t:6.1-samples
• Issue Type: questions and errors

Please refer to below links related custom plugin implementation and sample:

While IPluginV2 and IPluginV2Ext interfaces are still supported for backward compatibility with TensorRT 5.1 and 6.0.x respectively, however, we recommend that you write new plugins or refactor existing ones to target the IPluginV2DynamicExt or IPluginV2IOExt interfaces instead.


I am not trying to implement custom plugins. The tracker element is just not running. The same error occurs when trying to run the deepstream-test2 app. I don’t undestand why this is not working inside the docker container.


This looks more related to Deepstream. We are moving this post to the Deepstream forum to get better help.

Thank you.

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.

Do you see the issue outside docker?

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