notebooks/yolov7-optimization/README.md

Convert and Optimize YOLOv7 with OpenVINO™

YOLOv7 results

This tutorial explains how to convert and optimize the YOLOv7 PyTorch model with OpenVINO.

Notebook Contents

This tutorial demonstrates step-by-step instructions on how to run and optimize PyTorch YOLOv7 with OpenVINO.

The tutorial consists of the following steps:

• Prepare PyTorch model
• Download and prepare dataset
• Validate original model
• Convert PyTorch model to ONNX
• Convert ONNX model to OpenVINO IR
• Validate converted model
• Prepare and run NNCF Post-training optimization pipeline
• Compare accuracy of the FP32 and quantized models
• Compare performance of the FP32 and quantized models

Installation Instructions

This is a self-contained example that relies solely on its own code.
We recommend running the notebook in a virtual environment. You only need a Jupyter server to start. For details, please refer to Installation Guide