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Convert and Optimize YOLOv7 with OpenVINO™

YOLOv7 results

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

Notebook Contents

This tutorial demonstrates step-by-step instructions on how to run and optimize PyTorch* Yolo V7 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 Postraining optimization pipeline
  • Compare accuracy of the FP32 and quantized models
  • Compare performance of the FP32 and quantized models

Installation Instructions

If you have not installed all required dependencies, follow the Installation Guide.