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bee_track

This explains how to setup a headless pi, how to setup aravis, this project and make it so the project runs on boot with no interaction

Pi setup and connection

This section explains how to setup a blank sd card and Pi5 as a headless Pi you can SSH into

  • Flash OS using Raspbian Imager
  • Unplug and replug into PC
  • Create files in boot partition (bootf) (NOT root/boot): -- touch ssh.txt

-- Create a file wpa_supplicant.conf with the following:

ctrl_interface=DIR=/var/run/wpa_supplicant GROUP=netdev
update_config=1
country=GB

network={
	ssid="WiFi SSID"
	psk="WPA/WPA2 passphrase"
	key_mgmt=WPA-PSK
}

Insert into PI and power on, wait until pi turns up as connected on hotspot

  • Find ip address of Pi : ping raspberrypi.local
  • SSH to pi: ssh pi@IP

Project setup

First create a virtual python environment where all python and pip commands must be run

python3 -m venv bee-venv

Then activate the virtual environment with

source bee-venv/bin/activate

Next we clone this repo

git clone https://github.com/SheffieldMLtracking/bee_track.git

First run aravissetup from the root directory

source bee_track/aravissetup , entering "y" when prompted

This should install any dependencies needed for aravis, clone aravis, setup, build and install it ready to be used.

THEN install python dependencies in the venv (make sure it (bee-venv) is on the left of the bash)

pip install -r bee_track/requirements.txt

This must be done after running aravissetup because some of the python modules rely on some of the installs when installing aravis.

Running Beetrack from command line

Make sure you are in virtual environment where all the installs have occured

source bee-venv/bin/activate

cd bee_track

sudo ifconfig eth0 up 169.254.160.220

Check cameras are working: arv-camera-test-0.10

./startupfast

If something goes wrong use killall python3

Connect to pi with:

http://raspberrypi.local:8000/

If you want to make edits

You will probably want to reinstall with git an editable version

(bee-venv)$ pip uninstall bee_track
(bee-venv)$ cd ~/bee_track
(bee-venv)$ pip install -e .

Running Beetrack on Boot automatically

To run the project on a headless pi with no interaction you must complete the following steps. Bear in mind it takes a good 3-5 miniutes to get up and running every boot.

Edit rc.local by sudo nano /etc/rc.local Add the following line:

su - pi -c /home/pi/bee_track/startup &

Before exit 0

Add the following to /etc/network/interfaces

auto lo
iface lo inet loopback

auto eth0
iface eth0 inet static
address 169.254.160.220

Reboot and the project should run without any interaction

Manual Setup

Python Setup

In root directory of the pi (or create project dir with all files in) git clone https://github.com/lionfish0/bee_track.git

Setup virtual environment python -m venv bee-venv

Activate - (if using SSH terminal to change python env) Make sure all commands are run in the virtual environment from now on source bee-venv/bin/activate

pip install -e bee_track/. sudo apt install libatlas3-base

Aravis setup

git clone https://github.com/AravisProject/aravis.git

sudo apt install cmake

and

sudo apt install libgtk-3-dev libnotify-dev libgstreamer1.0-dev libgstreamer-plugins-base1.0-dev gstreamer1.0-plugins-bad

and

sudo apt-get install gnome-common intltool valac libglib2.0-dev gobject-introspection libgirepository1.0-dev libgtk-3-dev libgnome-desktop-3-dev libcanberra-dev libgdata-dev libdbus-glib-1-dev libgstreamer1.0-dev libupower-glib-dev libxml2-dev

meson setup aravis/

cd aravis

meson build

cd build

meson configure -Dviewer=enabled -Dintrospection=enabled -Dgst-plugin=enabled

sudo ninja install might have to pip install ninja

Beetrack setup

Important installs:

pip install PyGObject rpimotorlib rpi-lgpio psutil spidev requests

pip install scipy
git clone https://github.com/lionfish0/retrodetect.git
cd retrodetect
pip install -e .
git clone https://github.com/lionfish0/QueueBuffer.git
cd QueueBuffer
pip install -e .
pip install libsvm
pip install -U flask-cors
pip install mem_top
pip install flask_compress

Architecture

This is a simplified overview of the different parts of this system and how they communicate.

flowchart LR
user(("Web\nbrowser"))
backend[API\nFlask app\nbee_track/core.py]
frontend[Javascript GUI\nhttp.server\nwebinterface/]
user <--"HTTP 80" --> frontend
frontend <--"HTTP 5000"--> backend
Loading

API architecture

The Flask application has four components which run in separate threads:

  • Cameras
  • Triggers
  • Rotation
  • Tracking

Each thread has a worker process with a configuration message queue.

Usage

TODO

Development

Testing

TODO

Virtual environment

These are instructions for running the API app on a virtual Raspberry Pi machine using dockerpi.

  1. Install Docker
  2. Download the latest stable Raspberry Pi OS Lite image
  3. Decompress the image unxz *.xz
  4. Run a virtual machine (p3 means Rasp. Pi version 3, which is under experimental support)
image_path="./2023-12-11-raspios-bookworm-arm64-lite.img"
docker run -it -v $image_path:/sdcard/filesystem.img lukechilds/dockerpi:vm p3

TODO this doesn't work

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