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yolov8 notebook
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notebooks/230-yolov8-optimization/230-yolov8-optimization.ipynb
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# Convert and Optimize YOLOv8 with OpenVINO™ | ||
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![YOLOv8 results](https://user-images.githubusercontent.com/29454499/212105105-f61c8aab-c1ff-40af-a33f-d0ed1fccc72e.png) | ||
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This tutorial explains how to convert and optimize the [YOLOv8](https://github.com/ultralytics/) PyTorch\* model with OpenVNO. | ||
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## Notebook Contents | ||
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This tutorial demonstrates step-by-step instructions on how to run and optimize PyTorch\* Yolo V8 with OpenVINO. | ||
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The tutorial consists of the following steps: | ||
- Prepare PyTorch model | ||
- Download and prepare dataset | ||
- Validate original model | ||
- Convert PyTorch 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 | ||
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## Installation Instructions | ||
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If you have not installed all required dependencies, follow the [Installation Guide](../../README.md). |
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