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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 Agilex™ 7 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
5.1. 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 ( Agilex™ 7)
5.5. Performing Accelerated Inference with the dla_benchmark Application
5.6. Running the Ported OpenVINO™ Demonstration Applications
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5.5.2.1. 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.