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Unable to run RTSP camera - "[ERROR] Error pulling tensor from GST Pipeline #159

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@billson16

Hello, I am new to Texas Instrument AM69A edge-ai device, I am testing example code and I am having some issue when I run app_edgeai.py and rtsp_src_example.yaml for displaying RTSP camera video streaming.
I have set config file (rtsp_src_exmaple.yaml) to my IP camera, however, when I run
./app_edgeai.py ../configs/rtsp_src_example.yaml
I keep getting "[ERROR] Error pulling tensor from GST Pipeline", What is the problem ?
Below is my config file (rtsp_src_example.yaml)

title: "RTSP stream"
log_level: 2
inputs:
    # https://gist.github.com/Santiago-vdk/80c378a315722a1b813ae5da1661f890
    # Steps given in the above url can be used to create an rtsp src in a
    # linux machine
    input0:
        source: rtsp://admin:admin@192.168.0.1:554/cam/realmonitor?channel=1&subtype=0&unaicast=true&proto=Onvif
        format: h264
        width: 1280
        height: 720
        framerate: 30
        loop: True
models:
    model0:
        model_path: /opt/model_zoo/ONR-CL-6360-regNetx-200mf
        topN: 5
    model1:
        model_path: /opt/model_zoo/TFL-OD-2020-ssdLite-mobDet-DSP-coco-320x320
        viz_threshold: 0.6
    model2:
        model_path: /opt/model_zoo/ONR-SS-8610-deeplabv3lite-mobv2-ade20k32-512x512
        alpha: 0.4
    model3:
        model_path: /opt/model_zoo/ONR-OD-8200-yolox-nano-lite-mmdet-coco-416x416
        viz_threshold: 0.6
outputs:
    output0:
        sink: kmssink
        width: 1920
        height: 1080
        overlay-perf-type: graph
        connector: 50
    output1:
        sink: /opt/edgeai-test-data/output/output_video.mkv
        width: 1920
        height: 1080
    output2:
        sink: /opt/edgeai-test-data/output/output_image_%04d.jpg
        width: 1920
        height: 1080
    output3:
        sink: remote
        width: 1920
        height: 1080
        port: 8081
        host: 127.0.0.1
        encoding: jpeg
        overlay-perf-type: graph

flows:
    flow0: [input0,model1,output0,[320,150,1280,720]]

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