FPGA AI Suite: PCIe-based Design Example User Guide

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ID 768977
Date 3/29/2024
Public
Document Table of Contents
Document Table of Contents x
1. FPGA AI Suite PCIe-based Design Example User Guide 2. About the PCIe* -based Design Example 3. Getting Started with the FPGA AI Suite PCIe* -based Design Example 4. Building the FPGA AI Suite Runtime 5. Running the Design Example Demonstration Applications 6. Design Example Components 7. Design Example System Architecture for the Intel PAC with Arria® 10 GX FPGA A. FPGA AI Suite PCIe-based Design Example User Guide Archives B. FPGA AI Suite PCIe-based Design Example User Guide Document Revision History
4. Building the FPGA AI Suite Runtime x
4.1. CMake Targets 4.2. Build Options
5. Running the Design Example Demonstration Applications x
5.1. Exporting Trained Graphs from Source Frameworks 5.2. Compiling Exported Graphs Through the FPGA AI Suite 5.3. Compiling the PCIe* -based Example Design 5.4. Programming the FPGA Device ( Arria® 10) 5.5. Programming the FPGA Device ( Agilex™ 7) 5.6. Performing Accelerated Inference with the dla_benchmark Application 5.7. Running the Ported OpenVINO™ Demonstration Applications
5.6. Performing Accelerated Inference with the dla_benchmark Application x
5.6.1. Inference on Image Classification Graphs 5.6.2. Inference on Object Detection Graphs 5.6.3. Additional dla_benchmark Options
5.6.2. Inference on Object Detection Graphs x
5.6.2.1. The mAP and COCO AP Metrics 5.6.2.2. Specifying Ground Truth 5.6.2.3. Example of Inference on Object Detection Graphs
5.7. Running the Ported OpenVINO™ Demonstration Applications x
5.7.1. Example Running the Object Detection Demonstration Application
6. Design Example Components x
6.1. Build Script 6.2. Example Architecture Bitstream Files 6.3. Software Components 6.4. Software Interface to the BSP
6.1. Build Script x
6.1.1. Build Script Options 6.1.2. Script Flow
6.3. Software Components x
6.3.1. OpenVINO™ FPGA Runtime Plugin 6.3.2. FPGA AI Suite Runtime 6.3.3. BSP Driver
7. Design Example System Architecture for the Intel PAC with Arria® 10 GX FPGA x
7.1. System Overview 7.2. Hardware
7.2. Hardware x
7.2.1. PLL Adjustment
1. FPGA AI Suite PCIe-based Design Example User Guide
2. About the PCIe* -based Design Example
3. Getting Started with the FPGA AI Suite PCIe* -based Design Example
4. Building the FPGA AI Suite Runtime
5. Running the Design Example Demonstration Applications
6. Design Example Components
7. Design Example System Architecture for the Intel PAC with Arria® 10 GX FPGA
A. FPGA AI Suite PCIe-based Design Example User Guide Archives
B. FPGA AI Suite PCIe-based Design Example User Guide Document Revision History

5.6.2.1. The mAP and COCO AP Metrics

Average precision and average recall are averaged over multiple Intersection over Union (IoU) values.

Two metrics are used for accuracy evaluation in the dla_benchmark application. The mean average precision (mAP) is the challenge metric for PASCAL VOC. The mAP value is averaged over all 80 categories using a single IoU threshold of 0.5. The COCO AP is the primary challenge for object detection in the Common Objects in Context contest. The COCO AP value uses 10 IoU thresholds of .50:.05:.95. Averaging over multiple IoUs rewards detectors with better localization.

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