Complete Guide: Edge Vision Acceleration with NVIDIA TensorRT INT8 Quantization

Step-by-Step Acceleration Guide: Convert PyTorch object detection models to INT8 TensorRT engines with zero-copy memory pipelines for Jetson AGX Orin.

Step 1: Export Network Graph to ONNX Format

import torch
model = torch.hub.load('ultralytics/yolov8', 'yolov8x')
torch.onnx.export(
    model, 
    torch.randn(1, 3, 640, 640), 
    "yolov8x.onnx",
    opset_version=17,
    input_names=["input"],
    output_names=["output"]
)

Step 2: Build TensorRT INT8 Entropy Calibrator

Use representative video frame samples to calibrate layer quantization bounds without accuracy degradation.