Learn TensorRT: a C++17 path from YOLOv8 to async inference
I open-sourced Learn TensorRT, a hands-on course for developers moving from PyTorch models to C++ deployment. The baseline is TensorRT 10.14, CUDA 13.0 and C++17, in a pinned NVIDIA development container. The core path uses YOLOv8 to connect three parts of deployment: Correctness: export to ONNX, inspect outputs with Polygraphy, then implement preprocessing, TensorRT inference and postprocessing in C++. Optimization: compare FP32/FP16/INT8, use explicit Q/DQ quantization, and profile with Nsigh…