NVIDIA Jetson Xavier - Parsing Caffe model for TensorRT

NVIDIA®Jetson Xavier™
Introduction
SoM Overview Carrier Boards NVIDIA Xavier Developer Kit Connect Tech Rogue Connect Tech Mimic Software Support NVIDIA JetPack
JetPack 5.0.2
Getting Started Installing JetPack Flashing the board with GUI installer JetPack Components Compiling Source Code Flashing the Board from Cmdline Performance Tuning Evaluating Performance Set Values Manually Tuning Power Maximizing Performance
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Getting into the Board Using Serial Console Using SSH Using Ubuntu Login Installing Packages
Video Capture and Display
Description Supported Cameras Imx219 Driver Software Support Using GStreamer Using Libargus
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HD Audio and Video Subystem Video Encoder Video Decoder JPEG Encoder and Decoder Video Image Compositor Audio Processing Engine Deep Learning Accelerator Volta GPU Description Using CUDA Using OpenGL
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I2C SD/eMMC Controller USB Controller
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Deep Learning
TensorRT Using TensorRT integrated with Tensorflow Parsing a Tensorflow model for TensorRT Parsing Caffe model for TensorRT Building TensorRT API examples Deep Learning Accelerator Software Support Deep Learning Tutorials Jetson Inference Jetson Reinforcement
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Reference Documentation
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Parsing Caffe model for TensorRT

The process for Caffe models is fairly similar to Tensorflow models. The key difference is that you don't need to generate a uff model file. Caffe model file (.caffemodel) can be imported directly from tensorrt.

Loading a Caffe model is an actual example provided by NVIDIA with TensorRT named sample_mnist. For more details on this example please refer to the C++ API section.