Ildaron/Laser_control

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

1601 stars · 185 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

An open-source hardware and software project that uses a camera, deep learning object detection (Darknet/YOLO via OpenCV), and galvanometer-steered laser to detect and neutralize mosquitoes, hornets, weeds, and pests on a Raspberry Pi. It includes documentation for coordinate triangulation, galvanometer setup, and safety warnings about laser hazards.

Use cases

• automatically detect and shoot down mosquitoes with a laser
• build a laser-based weed killer for the garden
• detect and neutralize asian hornets with computer vision
• learn how to aim a galvanometer laser using camera coordinates
• run YOLO object detection on a Raspberry Pi for pest control
• DIY machine vision pest control project

When to choose

• you want a DIY hardware + deep learning project for automated pest or weed control
• you need reference code for camera-to-galvanometer coordinate triangulation
• you want to experiment with YOLO/OpenCV on Raspberry Pi for real-time targeting

When to avoid

• you need a production-ready, safe commercial pest control solution
• you cannot follow laser safety precautions - high-power lasers risk irreversible eye damage
• you need a project with a formal license or polished support

Facets

application · maturity experimental

machine-learning computer-vision image-processing robotics machine-learning computer-vision agriculture hardware python iot laser-control galvanometer pest-control yolo darknet opencv embedded-vision hardware-project automation linux

Member repositories

For agents

markdown · JSON · MCP: product_card(name="Ildaron/Laser_control")