Participant Info


  • Registration (The contest is open to both industry and academia.)

Target Platform

The 2023 contest will use the Kria KV260 Vision AI Starter Kit and the Jetson Nano Developer Kit.

GPU Platform

The base design framework is provided here: This repository is a work in progress and should be available by late March

FPGA Platform

You should use the Ubuntu 22.04 PYNQ PYNQ image, available at

The base design framework, with additional setup instructions, is provided here:

Training Dataset

Link to download training dataset:

The training dataset contains:

  • 10000 training images in the JPEGImages directory:
    • Some extra images with _1 suffix are included such as 00009_1.jpg, which are simply mirror images of the base image and can be ignored.
    • The images have varied size, with the following distribution of sizes:
      • 1920x1080: 4962 images
      • 1280x720: 4552 images
      • 1920x1088: 404 images
      • 1920x1072: 82 images
  • Labelled object types and locations in the label directory. For example, JPEGImages/00001.jpg will have an associated label/00001.json file describe object types and locations in the image.
  • Object types:
Type Name Example Identifying Data
1 Motor Vehicle Bounding Box
2 Non-motorized Vehicle Bounding Box
3 Pedestrian Bounding Box
4 Red Traffic Light Bounding Box
5 Yellow Traffic Light Bounding Box
6 Green Traffic Light Bounding Box
7 Off Traffic Light Bounding Box

Test Dataset

The hidden test dataset contains 6000 images. The images have varied size, with the following distribution of sizes:

  • 1920x1080: 3788 images
  • 1280x720: 1932 images
  • 1920x1088: 243 images
  • 1920x1072: 37 images

Other Info

Frequently Asked Questions

Previous Contest Winning Designs

Note: These are designs for the FPGA contest, and were for a different image detection problem/dataset than this year.

Q&A Platform

See Slack link on sidebar.