1 Overview
2 Software
- 2.1 Development setup
- 2.2 Usage - development
- 2.3 Raspberry Pi setup & usage
- 2.4 Hotspot Detection Configuration
3 Hardware

Overview

The airside system runs on the Raspberry Pi 5 on the drone.

Repository:

GitHub - UWARG/computer-vision-python: Autonomy on airside system

Software

Development setup

Follow the instructions: Autonomy Workflow Software

Install packages:

pip install -r requirements.txt
pip install -r requirements-pytorch.txt
pip install -r modules/common/requirements.txt

Usage - development

Copy the model file (.pt) into the repository.

In config.yaml, update model_path to point to the model file. The latest models can be found in OneDrive Landing Pad Models.

Activate the environment: Autonomy Workflow Software

Enter the commands :

git checkout main
git pull
./setup_project.ps1   OR   source ./setup_project.sh
./venv/Scripts/Activate.ps1   OR   source ./venv/bin/activate
python -m main_2024

If your computer does not have CUDA support (ie for the RPi), add --cpu to force the program to use the CPU:

python -m main_2024 --cpu

Other options are available. See them by using -h .

Raspberry Pi setup & usage

Follow the instructions: Running Airside on the Raspberry Pi 5 - Comp 2025

Hotspot Detection Configuration

To modify the hotspot detection configuration edit the detect_brightspot section in config.yaml :

According to OpenCV reference:

By color. This filter compares the intensity of a binary image at the center of a blob to blobColor. If they differ, the blob is filtered out. Use blob_color = 0 to extract dark blobs and blob_color = 255 to extract light blobs.
By area. Extracted blobs have an area between min_area_pixels (inclusive) and max_area_pixels (exclusive).
By circularity. Extracted blobs have circularity (4∗π∗Area)/(perimeter∗perimeter) between min_circularity (inclusive) and max_circularity (exclusive).
By ratio of the minimum inertia to maximum inertia. Extracted blobs have this ratio between min_inertia_ratio (inclusive) and max_inertia_ratio (exclusive).
By convexity. Extracted blobs have convexity (area / area of blob convex hull) between min_convexity (inclusive) and max_convexity (exclusive)

From https://learnopencv.com/blob-detection-using-opencv-python-c/:

Hardware

Raspberry Pi 5: Raspberry Pi 5

CUDA compability information: CUDA and PyTorch