Coprocessor code for 2024
This repository uses Git LFS.
First, install Git LFS:
curl -s https://packagecloud.io/install/repositories/github/git-lfs/script.deb.sh | sudo bash
sudo apt install git-lfs
git lfs install
Next, clone the repo:
git clone https://github.com/titan2022/FRC-2024-Vision
First install the dependencies (as listed below), and build Titan-Processing in ../Titan-Processing
. Then, you can do:
cd src
python3 example-webcam.py
First, please go into the Unity network settings, click "Edit Connections...", and for each network connection, edit the connection and select "General->All users may connect to this network".
Next, go into this directory and run ./autostart-jnano.sh
and reboot. To return to the desktop, run ./no-autostart-jnano.sh
and reboot.
To see the status, run systemctl status titan2022
. To see the full logs, run journalctl -u titan2022 -b
. To follow the logs, run journalctl -u titan2022 -f
. To stop the service, run sudo systemctl stop titan2022
.
On a stock JetPack 4.6.1 / Ubuntu 18.04 installation, run:
wget -qO- https://raw.githubusercontent.com/titan2022/FRC-2024-Vision/main/setup-jnano.sh | bash
First, please have Conda installed on your computer. If it's not installed, please install Miniforge3, which includes Conda and a conda-forge based Python environment. You can install Miniforge3 using the following command:
wget "https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-$(uname)-$(uname -m).sh"
bash Miniforge3-$(uname)-$(uname -m).sh
rm Miniforge3-$(uname)-$(uname -m).sh
Close and reopen your shell, and run:
# Prevent Conda from polluting your environment when you're not working on Conda-managed projects.
conda config --set auto_activate_base false
Now, you can use Conda to install the dependencies.
conda env create -f environment-cpu.yml # or -cuda -intel -jnano
conda activate FRC-2024-Vision
(This might not be necessary) Install a OpenCL implementation.
- If you already have an OpenCL implementation,
conda install ocl-icd-system
- On the Jetson Nano:
- TODO
- On any system with CUDA,
conda install pocl-cuda
- On an Intel GPU,
conda install intel-compute-runtime
If you modify environment.yml
, please run
conda env update -f environment-cpu.yml