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1. Intel® FPGA AI Suite Getting Started Guide
2. Intel® FPGA AI Suite Components
3. Intel® FPGA AI Suite Installation Overview
4. Installing the Intel® FPGA AI Suite Compiler and IP Generation Tools
5. Installing the Intel® FPGA AI Suite PCIe-Based Design Example Prerequisites
6. Intel® FPGA AI Suite Quick Start Tutorial
A. Intel® FPGA AI Suite Getting Started Guide Archives
B. Intel® FPGA AI Suite Getting Started Guide Document Revision History
4.1. Supported FPGA Families
4.2. Operating System Prerequisites
4.3. Installing the Intel® FPGA AI Suite With System Package Management Tools
4.4. Installing OpenVINO™ Toolkit
4.5. Installing Intel® Quartus® Prime Pro Edition Software
4.6. Setting Required Environment Variables
4.7. Installing Intel® Threading Building Blocks (TBB)
4.8. Finalizing Your Intel® FPGA AI Suite Installation
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
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6.10. Preparing a ResNet50 v1 Model
OpenVINO™ Model Zoo 2022.3.1 does not include a ResNet50 v1 model.
The following commands create graph.xml and graph.bin files for ResNet50 v1, using the mo_caffe.py command from OpenVINO™ Model Optimizer. These commands assume that you have enabled OpenVINO™ Model Optimizer as described Preparing OpenVINO Model Zoo.
wget https://www.deepdetect.com/models/resnet/ResNet-50-model.caffemodel
wget https://raw.githubusercontent.com/yihui-he/\ resnet-imagenet-caffe/master/resnet_50/ResNet-50-deploy.prototxt
source ~/build-openvino-dev/openvino_env/bin/activate mo \ --input_shape=[1,3,224,224] \ --mean_values=[103.53,116.28,123.675] \ --input=data \ --output=prob \ --input_model=ResNet-50-model.caffemodel \ --input_proto=ResNet-50-deploy.prototxt \ --model_name=graph