Visible to Intel only — GUID: rkn1661605585336
Ixiasoft
1. Intel® FPGA AI Suite PCIe-based Design Example User Guide
2. About the PCIe* -based Design Example
3. Getting Started with the Intel® FPGA AI Suite PCIe* -based Design Example
4. Building the Intel® 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 Intel® Arria® 10 GX FPGA
A. Intel® FPGA AI Suite PCIe-based Design Example User Guide Archives
B. Intel® 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 Intel FPGA AI Suite
5.3. Compiling the PCIe* -based Example Design
5.4. Programming the FPGA Device ( Intel® Arria® 10)
5.5. Programming the FPGA Device ( Intel Agilex® 7)
5.6. Performing Accelerated Inference with the dla_benchmark Application
5.7. Running the Ported OpenVINO™ Demonstration Applications
Visible to Intel only — GUID: rkn1661605585336
Ixiasoft
5.6.2. Inference on Object Detection Graphs
To enable the accuracy checking routine for object detection graphs, you can use the -enable_object_detection_ap=1 flag.
This flag lets the dla_benchmark calculate the mAP and COCO AP for object detection graphs. Besides, you need to specify the version of the YOLO graph that you provide to the dla_benchmark through the –yolo_version flag. Currently, this routine is known to work with YOLOv3 (graph version is yolo-v3-tf) and TinyYOLOv3 (graph version is yolo-v3-tiny-tf).