In this blog post, we will show you how to integrate custom classification model into Jetson™ modules using NVIDIA® Transfer Learning Toolkit  with Deepstream.

Before we get started, you will need to download tlt-converter to generate an engine and ds-tlt-classification to test the model.

To install tlt-converter go to the following page, download and unzip the zip file for Jetpack 4.5:

https://docs.nvidia.com/metropolis/TLT/tlt-user-guide/text/image_classification.html

You need to install OpenSSL package as well.

Export the following environment variables.

To install ds-tlt , visit the link below and download deepstream-tlt-apps according to the instructions. You do not need to download the models since we will be using our own model.

https://github.com/NVIDIA-AI-IOT/deepstream_tlt_apps#2-build-sample-application

Make sure you have exported models that you previously trained.

Now, we will generate an engine using tlt-converter. You can find the usage of tlt-converter by running the following command.

We will show the steps for f16 model but it can be used in both f16 and f32.

Finally, you can run ds-tlt-classification to test the model. Supported formats for the test input are jpeg and h264. You can use the sample videos and pictures as well.