For full contest details, please see the 2022 DAC System Design Contest page.
For general questions regarding this contest, please use the Piazza page: piazza.com/dac_2018/winterterm12021/dacsdc2021
- Download the PYNQ 2.7 Ultra96v2 board image from http://www.pynq.io/board.html
- Follow the instructions to image the SD card at https://pynq.readthedocs.io/en/latest/getting_started/pynq_image.html.
- Follow the instructions to setup and connect to the board at https://ultra96-pynq.readthedocs.io/en/latest/getting_started.html.
The get started, users have to run the following command on the Ultra96 board:
cd /home/xilinx/jupyter_notebooks
git clone https://github.com/jgoeders/dac_sdc_2022.git
Remember the user name and password are both xilinx
for super user.
After the above step is completed successfully, you will see a folder dac_sdc_2022
under your
jupyter notebook dashboard. Open the sample_team/dac_sdc.ipynb
notebook for directions on where to begin.
-
sample_team: This folder contains files for a sample team. This includes a .bit and .tcl file that defines the hardware, and a
.ipynb
jupyter notebook, and ahw
folder that is used to create a Vivado project. You should create a new folder for your team, where you will keep all of your files. -
images: All the test images are stored in this folder. Replace the example images in this directory with the full training set.
-
result: The results contain the output xml produced when execution is complete, and contains the runtime, energy usage, and predicted location of each object in each image.