# Intel-Edge-AI-Performance-Evaluation-Toolkit **Repository Path**: mirrors_intel/Intel-Edge-AI-Performance-Evaluation-Toolkit ## Basic Information - **Project Name**: Intel-Edge-AI-Performance-Evaluation-Toolkit - **Description**: No description available - **Primary Language**: Unknown - **License**: MIT - **Default Branch**: main - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2022-10-24 - **Last Updated**: 2025-09-27 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # Intel Edge AI Performance Evaluation Toolkit User Guide Intel Edge AI Performance Evaluation Toolkit is an Edge AI customer enabling tool that has been designed to easily qualify and evaluate platform deep learning inference performance. ## Components It consists of scripts, configuration files, Intel Thermal Analysis Tool (TAT) workspace file and optimized OpenVINO INT8 IR model and brief explanation below, * **OS setup scripts** - are used to setup container running environment on both Ubuntu Linux and Windows OS. * **OpenVINO POT quantization scripts and configuration files** - are used to quantize OpenVINO FP32/FP16 IR models to INT8 by OpenVINO Post-Training Optimization Tool. * **Benchmark scripts and Intel PTAT workspace file** - are used to benchmark optimized INT8 IR model and monitor system frequency and thermal condition to qualify system performance. ## Supported HW * Intel Core i7-1165G7 Processor * Intel Core i7-1185G7E Processor * Intel Celeron 6305E * Intel Core i7-1265U Processor * Intel Core i9-12900 Processor ## License Intel Edge AI Performance Evaluation is licensed under MIT License. By contributing to the project, you agree to the license and copyright terms therein and release your contribution under these terms. ## User Guide Below are steps to get started for Ubuntu 20.04.4 and Windows 10 21H2 ### User Guide for Ubuntu 20.04 **Install Ubuntu 20.04.4** https://ubuntu.com/tutorials/install-ubuntu-desktop#1-overview **Clone Intel Edge AI Performance Evaluation Toolkit** ```=bash sudo apt update sudo apt upgrade sudo apt install git git clone https://github.com/intel/Intel-Edge-AI-Performance-Evaluation-Toolkit.git ``` **Install docker utility by running** ```=bash cd Intel-Edge-AI-Performance-Evaluation-Toolkit bash tools/install_docker.sh ``` Reboot system. **Install Intel Power and Thermal Analysis Tool** Tool download link : [Intel Power And Thermal Analysis Tool](https://www.intel.com/content/www/us/en/secure/design/confidential/software-kits/kit-details.html?kitId=637737) ![](https://i.imgur.com/JQ9QPDp.png) **Loading Intel PTAT workspace file from ptat_workspace.xml** ![](https://i.imgur.com/FcvpSv0.png) **Run Benchmark and Quantization Scripts** 1. **Copy yolo-v4-tf FP16_INT8 IR model to Downloads folder in Home directory** ```=bash cd Intel-Edge-AI-Performance-Evaluation-Toolkit cp -ar openvino_models/ $HOME/Downloads ``` 2. **Run benchmark_app on yolo-v4-tf FP16_INT8 IR model on CPU** ```=bash bash run_yolo-v4-tf-int8-cpu_benchmark.sh ``` ![](https://i.imgur.com/aOpi5ZF.png) 3. **Run benchmark_app on yolo-v4-tf FP16_INT8 IR model on GPU** ```=bash bash run_yolo-v4-tf-int8-gpu_benchmark.sh ``` ![](https://i.imgur.com/G6yS6wp.png) 4. **Run quantization on yolo-v3-tf FP16 IR model** ```=bash bash quantize_yolo-v3-tf_int8.sh ``` ### User Guide for Windows 10 **Install Windows 10 21H1** * Download Windows Insider Preview ISO (microsoft.com) and install * Install required graphic driver (30.0.101.xxxx) **Download Intel Edge AI Performance Evaluation Toolkit github link below** https://github.com/intel/Intel-Edge-AI-Performance-Evaluation-Toolkit/archive/refs/heads/main.zip Extract to C:\Users\Public\Intel-Edge-AI-Performance-Evaluation-Toolkit. **Enable Hypher-V (Run as Administator in PowerShell)** Please refere to tools\enable-hyper-v.p1 and run below, ``` Enable-WindowsOptionalFeature -Online -FeatureName Microsoft-Hyper-V All ``` Press Y to reboot system. **Install WSL2 (Run as Administator in PowerShell) and Reboot** Please refere to tools\install_wsl2.p1 and run below, ``` wsl --install Restart-Computer ``` After reboot, WSL will start automatically to install Ubuntu. Enter user name and password for WSL Ubuntu when prompt. **Install docker utility by running in WSL** ```=bash cd /mnt/c/Users/Public/Intel-Edge-AI-Performance-Evaluation-Toolkit bash tools/install_docker.sh ``` Reboot to activate docker settings. **Install Intel Power and Thermal Analysis Tool** Tool download link : [Intel Power And Thermal Analysis Tool](https://www.intel.com/content/www/us/en/secure/design/confidential/software-kits/kit-details.html?kitId=637737) ![](https://i.imgur.com/eIBHHVw.png) ![](https://i.imgur.com/GorsHl2.png) **Launch Intel PTAT tool as administrator** ![](https://i.imgur.com/pUyTewz.png) **Loading Intel PTAT workspace file from ptat_workspace.json** ![](https://i.imgur.com/RGt1qd9.png) **Run Benchmark and Quantization Scripts in WSL** 1. **Copy yolo-v4-tf FP16_INT8 IR model to Downloads folder in Home directory** ```=bash cd /mnt/c/Users/Public/Intel-Edge-AI-Performance-Evaluation-Toolkit mkdir $HOME/Downloads cp -ar openvino_models/ $HOME/Downloads ``` 2. **Run benchmark_app on yolo-v4-tf FP16_INT8 IR model on CPU** ```=bash bash run_yolo-v4-tf-int8-cpu_benchmark.sh ``` ![](https://i.imgur.com/rXvPvTF.png) 3. **Run benchmark_app on yolo-v4-tf FP16_INT8 IR model on GPU** ```=bash bash run_yolo-v4-tf-int8-gpu_benchmark.sh ``` ![](https://i.imgur.com/dXLwmhI.png) 4. **Run quantization on yolo-v3-tf FP16 IR model** ```=bash sudo apt install unzip bash tools/download_coco_dataset.sh bash quantize_yolo-v3-tf_int8.sh ``` ## Intel Arc Graphics and Data Center GPU There are detail installation guides For Intel Data Center GPU Max Series and Intel Data Center GPU Flex Series, please refer to https://dgpu-docs.intel.com/driver/installation.html. For Arc GPUs, please refer to https://dgpu-docs.intel.com/driver/client/overview.html ## How to contribute See [CONTRIBUTING](https://github.com/intel/Intel-Edge-AI-Performance-Evaluation-Toolkit/blob/main/CONTRIBUTING.md) for details. Thank you! ## Get a support Please report questions, issues and suggestions using: [GitHub* Issues](https://github.com/intel/Intel-Edge-AI-Performance-Evaluation-Toolkit/issues)