Intel® FPGA AI Suite: Getting Started Guide

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ID 768970
Date 4/05/2023
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Document Table of Contents
Document Table of Contents x
1. Intel® FPGA AI Suite Getting Started Guide 2. About the Intel® FPGA AI Suite 3. Installing the Intel® FPGA AI Suite 4. Installing the Intel® FPGA AI Suite PCIe-Based Design Example Prerequisites 5. Installing the Intel FPGA AI Suite Compiler and IP Generation Tools 6. Intel® FPGA AI Suite Quick Start Tutorial A. Installation Notes for Other Operating Systems B. Intel® FPGA AI Suite Getting Started Guide Archives C. Intel® FPGA AI Suite Getting Started Guide Document Revision History
3. Installing the Intel® FPGA AI Suite x
3.1. Intel® FPGA AI Suite Directory Structure
4. Installing the Intel® FPGA AI Suite PCIe-Based Design Example Prerequisites x
4.1. PCIe-based Design Example Hardware Prerequisites 4.2. PCIe-based Design Example Operating System Prerequisites 4.3. PCIe-based Design Example Software Prerequisites
4.3. PCIe-based Design Example Software Prerequisites x
4.3.1. Additional Software Prerequisites for the PCIe-based Design Example for Intel Agilex® 7 Devices 4.3.2. Additional Software Prerequisites for the PCIe-Based Design Example for Intel® Arria® 10 Devices
5. Installing the Intel FPGA AI Suite Compiler and IP Generation Tools x
5.1. Supported FPGA Families 5.2. Operating System Prerequisites 5.3. Software Prerequisites 5.4. Installing the Intel® FPGA AI Suite Using System Package Management Tools 5.5. Installing the Intel® FPGA AI Suite Into an Alternative Location
5.3. Software Prerequisites x
5.3.1. OpenVINO™ Toolkit 5.3.2. Intel® Quartus® Prime Pro Edition Software
6. Intel® FPGA AI Suite Quick Start Tutorial x
6.1. Creating a Working Directory 6.2. Preparing OpenVINO™ Model Zoo and Model Optimizer 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
6.12. 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
A. Installation Notes for Other Operating Systems x
A.1. CentOS* 7 Installation Notes
1. Intel® FPGA AI Suite Getting Started Guide
2. About the Intel® FPGA AI Suite
3. Installing the Intel® FPGA AI Suite
4. Installing the Intel® FPGA AI Suite PCIe-Based Design Example Prerequisites
5. Installing the Intel FPGA AI Suite Compiler and IP Generation Tools
6. Intel® FPGA AI Suite Quick Start Tutorial
A. Installation Notes for Other Operating Systems
B. Intel® FPGA AI Suite Getting Started Guide Archives
C. Intel® FPGA AI Suite Getting Started Guide Document Revision History

6.2. Preparing OpenVINO™ Model Zoo and Model Optimizer

These instructions assume that you have a copy of OpenVINO™ Model Zoo 2021.4.2 in your $COREDLA_ROOT/demo/open_model_zoo/ directory. You can use the copy of Model Zoo that was installed with OpenVINO™ or download a fresh copy.

To use the copy of Model Zoo that was installed with OpenVINO™ , run the following commands: 
cp -r $INTEL_OPENVINO_DIR/deployment_tools/open_model_zoo \
    $COREDLA_WORK/demo
If you want to download a fresh copy of Model Zoo instead, run the following commands: 
cd $COREDLA_WORK/demo
git clone https://github.com/openvinotoolkit/open_model_zoo.git
cd open_model_zoo
git checkout 2021.4.2

Although have already installed OpenVINO™ (for instructions, see Related Links that follow)), you must install additional dependencies to enable the Model Optimizer tool within OpenVINO™ .

The set of required dependencies varies depending on the framework (such as Caffe, TensorFlow, or TensorFlow 2). The following commands enable the Model Optimizer with the TensorFlow 1 framework, which is used in this tutorial.

To create the Python virtual environment that supports the OpenVINO™ Model Optimizer, run the following commands:

Red Hat* Enterprise Linux* 8.7 

cd $COREDLA_WORK/demo/open_model_zoo
python3.6 -m venv venv
. venv/bin/activate
pip3 install --upgrade pip
mo_dir=$INTEL_OPENVINO_DIR/deployment_tools/model_optimizer
cp $mo_dir/requirements.txt .
sed -i -e 's/onnx>=/onnx==/' requirements.txt
pip3 install -r requirements.txt
pip3 install -r $mo_dir/requirements_tf.txt
pip3 install -r tools/downloader/requirements.in
pip3 install -r tools/downloader/requirements-tensorflow.in

Ubuntu* 18.04 

cd $COREDLA_WORK/demo/open_model_zoo
python3.7 -m venv venv
. venv/bin/activate
pip3 install --upgrade pip
mo_dir=$INTEL_OPENVINO_DIR/deployment_tools/model_optimizer
pip3 install -r $mo_dir/requirements.txt
pip3 install -r $mo_dir/requirements_tf.txt
pip3 install -r tools/downloader/requirements.in
pip3 install -r tools/downloader/requirements-tensorflow.in

Ubuntu* 20.04 

sudo apt-get install software-properties-common
# The -E sudo option in the following command
# helps with some proxy configurations 
sudo -E add-apt-repository ppa:deadsnakes/ppa
sudo apt update 
sudo apt install python3.7
sudo apt install python3.7-venv
cd $COREDLA_WORK/demo/open_model_zoo
python3.7 -m venv venv
. venv/bin/activate
pip3 install --upgrade pip
mo_dir=$INTEL_OPENVINO_DIR/deployment_tools/model_optimizer
pip3 install -r $mo_dir/requirements.txt
pip3 install -r $mo_dir/requirements_tf.txt
pip3 install -r tools/downloader/requirements.in
pip3 install -r tools/downloader/requirements-tensorflow.in

You need to run these commands only once, but you must activate the virtual environment with the venv/bin/activate command whenever you have a new shell and want to use OpenVINO™ Model Optimizer with a model based on TensorFlow 1.0.

Use the following command to activate the Model Optimizer virtual environment: 
source $COREDLA_WORK/demo/open_model_zoo/venv/bin/activate
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