[Deepstream 6.1] Unable to use l4t container for python based application

Please provide complete information as applicable to your setup.

• Hardware Platform (Jetson / GPU) Jetson Xavier
• DeepStream Version 6.1
• JetPack Version (valid for Jetson only) 35.1.0
• TensorRT Version
• Issue Type( questions, new requirements, bugs) Question

I am trying to run my python based Deepstream application on Jetson Xavier. I have followed the steps for Deepstream installation and the application is working fine on the host.

Now, when i try to dockerize and run the application using the below Dockerfile, I am getting errors. Details are below:


FROM nvcr.io/nvidia/deepstream-l4t:6.1-samples

RUN apt update -y
RUN apt upgrade -y

RUN apt-get install -y python3-pip

# GStreamer Dependencies
RUN apt install -y libgstreamer1.0-dev libgstreamer-plugins-base1.0-dev libgstreamer-plugins-bad1.0-dev \
    gstreamer1.0-plugins-base gstreamer1.0-plugins-good gstreamer1.0-plugins-bad gstreamer1.0-plugins-ugly \
    gstreamer1.0-libav gstreamer1.0-doc gstreamer1.0-tools gstreamer1.0-x gstreamer1.0-alsa gstreamer1.0-gl \
    gstreamer1.0-gtk3 gstreamer1.0-qt5 gstreamer1.0-pulseaudio

RUN apt update && apt-get install -y libssl1.1 \
    libgstreamer1.0-0 \
    gstreamer1.0-tools \
    gstreamer1.0-plugins-good \
    gstreamer1.0-plugins-bad \
    gstreamer1.0-plugins-ugly \
    gstreamer1.0-libav \
    libgstreamer-plugins-base1.0-dev \
    libgstrtspserver-1.0-0 \
    libjansson4 \

# Gst RTSP Server
RUN apt install -y libgstrtspserver-1.0-dev gstreamer1.0-rtsp

# Deepstream Dependencies
RUN apt install -y python3-gi python3-dev python3-gst-1.0 python-gi-dev git python-dev \
    python3 python3-pip python3.8-dev cmake g++ build-essential libglib2.0-dev \
    libglib2.0-dev-bin libgstreamer1.0-dev libtool m4 autoconf automake libgirepository1.0-dev libcairo2-dev

# Clone the Deepstream Python Apps Repo into <deepstream>/sources
WORKDIR /opt/nvidia/deepstream/deepstream/sources
RUN git clone https://github.com/NVIDIA-AI-IOT/deepstream_python_apps.git

# Download and install the Deepstream Python Bindings
RUN mkdir /opt/nvidia/deepstream/deepstream/sources/deepstream_python_apps/bindings/build
WORKDIR /opt/nvidia/deepstream/deepstream/sources/deepstream_python_apps/bindings/build
RUN curl -O -L https://github.com/NVIDIA-AI-IOT/deepstream_python_apps/releases/download/v1.1.3/pyds-1.1.3-py3-none-linux_aarch64.whl
RUN pip install ./pyds-1.1.3-py3-none-linux_aarch64.whl

RUN apt-get install -y libgstrtspserver-1.0-0 gstreamer1.0-rtsp libgirepository1.0-dev gobject-introspection gir1.2-gst-rtsp-server-1.0

RUN mkdir /model

WORKDIR /model

COPY requirements.txt .

RUN pip install -r requirements.txt

COPY . .

CMD [ "python3", "main.py" ]


Creating Pipeline 
Creating streamux 
Creating source_bin  0  
Creating source bin
Creating Pgie 
Creating tiler 
Creating nvvidconv 
Creating nvosd 
Creating transform 
Creating H264 Encoder
Creating H264 rtppay
Adding elements to Pipeline 

Linking elements in the Pipeline 

 *** DeepStream: Launched RTSP Streaming at rtsp://localhost:8554/6d4e1564-b50d-4c9d-b245-d8f43c226792 ***

Now playing...
Starting pipeline 

gstnvtracker: Loading low-level lib at /opt/nvidia/deepstream/deepstream/lib/libnvds_nvmultiobjecttracker.so
gstnvtracker: Failed to open low-level lib at /opt/nvidia/deepstream/deepstream/lib/libnvds_nvmultiobjecttracker.so
 dlopen error: /opt/nvidia/vpi2/lib64/priv/libcupva_host.so: undefined symbol: PvaQueueSubmit
gstnvtracker: Failed to initilaize low level lib.

Please let me know how do I resolve this issue.

Can you confirm the same version and same installation steps can work on your Xavier?
Please be noted that BSP 35.1.0 comes together with JP5.0.2, and the corresponding DeepStream version is 6.1.1. But in your case it is 6.1, the versions seem to be a mismatch.

The same version is working on my Xavier. I have Deepstream6.1 with python bindings working on my machine.

If I upgrade to 6.1.1, do i need to change anything in the scripts?

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.

Could you try to use our docker directly to run the python demo? You can try to run it step by step in the demo docker and check whether there are still problems.