FPGA AI Suite: Getting Started Guide

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ID 768970
Date 11/25/2024
Public
Document Table of Contents
Document Table of Contents x
1. FPGA AI Suite Getting Started Guide 2. FPGA AI Suite Components 3. FPGA AI Suite Installation Overview 4. Installing the FPGA AI Suite Compiler and IP Generation Tools 5. Installing the FPGA AI Suite PCIe-Based Design Example Prerequisites 6. FPGA AI Suite Quick Start Tutorial 7. Running the Hostless DDR-Free Design Example A. FPGA AI Suite Getting Started Guide Archives B. FPGA AI Suite Getting Started Guide Document Revision History
3. FPGA AI Suite Installation Overview x
3.1. FPGA AI Suite Directory Structure
4. Installing the FPGA AI Suite Compiler and IP Generation Tools x
4.1. Supported FPGA Families 4.2. Operating System Prerequisites 4.3. Installing the FPGA AI Suite with System Package Management Tools 4.4. Installing OpenVINO™ Toolkit 4.5. Installing Quartus® Prime Pro Edition Software 4.6. Setting Required Environment Variables 4.7. Installing Intel® Threading Building Blocks (TBB) 4.8. Finalizing Your FPGA AI Suite Installation
4.3. Installing the FPGA AI Suite with System Package Management Tools x
4.3.1. Installing the FPGA AI Suite Into an Alternative Location
5. Installing the FPGA AI Suite PCIe-Based Design Example Prerequisites x
5.1. PCIe-based Design Example Hardware Prerequisites 5.2. PCIe-based Design Example Operating System Prerequisites 5.3. PCIe-based Design Example Software Prerequisites
5.3. PCIe-based Design Example Software Prerequisites x
5.3.1. Additional Software Prerequisites for the PCIe-based Design Example for Agilex™ 7 Devices
6. FPGA AI Suite Quick Start Tutorial x
6.1. Creating a Working Directory 6.2. Preparing OpenVINO™ Model Zoo 6.3. Preparing a Model 6.4. Running the Graph Compiler 6.5. Preparing an Image Set 6.6. Programming the FPGA Device 6.7. Performing Inference on the PCIe-Based Example Design 6.8. Building an FPGA Bitstream for the PCIe Example Design 6.9. Building the Example FPGA Bitstreams 6.10. Preparing a ResNet50 v1 Model 6.11. Performing Inference on the Inflated 3D (I3D) Graph 6.12. Performing Inference on YOLOv3 and Calculating Accuracy Metrics 6.13. Performing Inference Without an FPGA Board
6.12. Performing Inference on YOLOv3 and Calculating Accuracy Metrics x
6.12.1. Preparing a YOLOv3 Model 6.12.2. Preparing a COCO Validation Dataset and Annotations 6.12.3. Inference on YOLOv3 and Calculating Accuracy Scores
1. FPGA AI Suite Getting Started Guide
2. FPGA AI Suite Components
3. FPGA AI Suite Installation Overview
4. Installing the FPGA AI Suite Compiler and IP Generation Tools
5. Installing the FPGA AI Suite PCIe-Based Design Example Prerequisites
6. FPGA AI Suite Quick Start Tutorial
7. Running the Hostless DDR-Free Design Example
A. FPGA AI Suite Getting Started Guide Archives
B. FPGA AI Suite Getting Started Guide Document Revision History

6.12.1. Preparing a YOLOv3 Model

As stated in Preparing a Model, a model must be converted from a framework (such as TensorFlow, Caffe, or Pytorch) into a pair of .bin and .xml files before the FPGA AI Suite compiler (dla_compiler command) can ingest the model.

The following commands download the YOLOv3 TensorFlow model and run Model Optimizer: 
source ~/build-openvino-dev/openvino_env/bin/activate
omz_downloader --name yolo-v3-tf \ 
    --output_dir $COREDLA_WORK/demo/models/ 
omz_converter --name yolo-v3-tf \
    --download_dir $COREDLA_WORK/demo/models/ \
    --output_dir $COREDLA_WORK/demo/models/

These commands create .bin and .xml files in the demo/models/public/yolo-v3-tf/FP32/ directory. 

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