andre1araujo/YOLO-on-PYNQ-Z2
This repository contains all the necessary material to implement a YOLOv3 object detection algorithm on the PYNQ-Z2 FPGA. There is a step-by-step tutorial associated so everyone can do it.
This project helps developers and engineers implement an accelerated object detection system using YOLOv3 on a PYNQ-Z2 FPGA board. You provide an input image, and the system outputs detections (bounding boxes, object classes, and probabilities). This is ideal for embedded systems developers or researchers working with edge AI and custom hardware acceleration for computer vision tasks.
102 stars. No commits in the last 6 months.
Use this if you need to deploy a fast and efficient object detection model on embedded hardware, specifically the PYNQ-Z2, for applications like face detection or PCB defect analysis.
Not ideal if you are looking for a software-only solution or do not have access to or experience with FPGA development and the PYNQ-Z2 board.
Stars
102
Forks
10
Language
C++
License
Apache-2.0
Category
Last pushed
Mar 14, 2025
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