Gstnvinfer error while runnin the python apps

Accelerated Computing Intelligent Video Analytics DeepStream SDK
1

•Hardware Platform (Jetson / GPU): GPU- TITAN RTX
•DeepStream Version: 5.1
•TensorRT Version: 7.2.2
•NVIDIA GPU Driver Version: 460.56
•Issue Type: plugin error.

Following is the flow of my project.
I’m using TLT 3.0 for for the object detection application. The model is yolov4.
Then I pulled the docker image of deepstream-5.1-triton.
For the deployment purpose, I followed the deployment section of tlt models in deepstream:

  1. installation of Tensorrt oss for X86.
  2. TLT conveter installation
    3)Modifying config file.

But when I try to run the python apps, I get an error related to nvinfer plugin.
Below is the error that I get,

**Creating Pipeline

Creating streamux

Creating source_bin 0

Creating source bin
source-bin-00
Creating Pgie

Creating tiler

Creating nvvidconv

Creating nvosd

Creating EGLSink

Atleast one of the sources is live
Error: Could not parse model engine file path
Failed to parse group property
** ERROR: <gst_nvinfer_parse_config_file:1242>: failed
Adding elements to Pipeline

Linking elements in the Pipeline

Now playing…
1 : rtsp://admin:Mukesh_M@192.168.0.132:554/Streaming/Channels/301
Starting pipeline

0:00:00.324415772 736 0x1fa08d0 WARN nvinfer gstnvinfer.cpp:766:gst_nvinfer_start: error: Configuration file parsing failed
0:00:00.324442800 736 0x1fa08d0 WARN nvinfer gstnvinfer.cpp:766:gst_nvinfer_start: error: Config file path: dstest3_pgie_config.txt
Error: gst-library-error-quark: Configuration file parsing failed (5): gstnvinfer.cpp(766): gst_nvinfer_start (): /GstPipeline:pipeline0/GstNvInfer:primary-inference:
Config file path: dstest3_pgie_config.txt
Exiting app**

I checked the model path as well as the config file path and everything is correct.
What could be the possible way to bypass this error?

**Note: For the same procedure (Considering small changes like GPU_ARCH), the same setup works well on my PC (Quadro P1000) and jetson tx2.

3

Do you mean you run the same sample app with deepstream-5.1-triton docker image on two different platform?

4

tensorRT version is 7.2.x, it does not support TLT3.0 yolov4.

6

Hi! I hope you are doing great.
I am trying to make something similar to you. The goal is to run inference on a model trained in TLT 3.0 with python in deepstream tritan 5.1 docker.
I am quite new to Deepstream, have the only basic knowledge. Would you be kind enough to share some knowledge or maybe code snippets so I have a kickstart?
Thankyou