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detect and classify insects on a raspberry pi

Project description

bugcam - Raspberry Pi Insect Detection

CLI for running insect detection on Raspberry Pi with Hailo AI HAT+.

Requirements

Hardware

  • Raspberry Pi: Raspberry Pi 5 (required - Pi 4 not supported due to PCIe requirement)
  • RAM: 8GB recommended
  • Storage: 32GB microSD minimum (64GB recommended for multiple models)
  • AI Accelerator: Raspberry Pi AI HAT+ with Hailo-8L (13 TOPS) or Hailo-8 (26 TOPS)
  • Camera: Any official Raspberry Pi camera (Camera Module 3 recommended, High Quality Camera also supported)
  • Cooling: Active Cooler required (thermal management essential under AI workload)
  • Power Supply: Official 27W USB-C power supply recommended

Software

  • OS: Raspberry Pi OS Bookworm 64-bit (latest version)
  • Kernel: 6.6.31 or newer (run sudo apt full-upgrade if needed)
  • PCIe: Gen 3 enabled via raspi-config (required for optimal performance)

Quick Start

# 1. Install system dependencies
sudo apt update && sudo apt install hailo-all

# 2. Install bugcam
pipx install bugcam

# 3. Download detection model
bugcam models download yolov8m

# 4. Run detection
bugcam preview

Commands

bugcam setup

Initialize bugcam by installing dependencies and downloading hailo-rpi5-examples.

bugcam setup

bugcam preview

Run live camera preview with detection overlay.

bugcam preview [--model yolov8m]

bugcam detect

Run continuous detection and save results.

bugcam detect start [--output detections.jsonl] [--duration 30] [--quiet]

Output format (JSONL):

{"timestamp": "2025-12-14T10:30:45", "class": "insect", "confidence": 0.92, "bbox": [100, 200, 150, 250]}

bugcam doctor

Run system diagnostics to check dependencies, hardware, and configuration.

bugcam doctor

bugcam check

Test hardware connections before running detection.

bugcam check all      # Run all checks
bugcam check hailo    # Test Hailo AI accelerator
bugcam check camera   # Test camera connection
bugcam check sensor   # Test I2C sensors

Checks performed:

Check What it tests How
hailo Hailo AI accelerator is detected Runs hailortcli scan
camera RPi camera is accessible Imports picamera2 and initializes
sensor I2C sensors are connected Scans I2C bus for known addresses (SCD30, SCD40, BME280)

bugcam models

Manage detection models.

# Download a model (yolov8s or yolov8m)
bugcam models download yolov8m

# List installed models
bugcam models list

# Show model details
bugcam models info yolov8m

bugcam autostart

Manage systemd service for automatic detection on boot.

bugcam autostart enable
bugcam autostart disable
bugcam autostart status
bugcam autostart logs [--follow]

Environment Variables

Optional configuration:

  • HAILO_EXAMPLES_PATH - Custom path for hailo-rpi5-examples (default: ~/hailo-rpi5-examples)
  • XDG_CACHE_HOME - Custom cache directory location (default: ~/.cache)

Monitoring

# Hailo hardware monitoring
hailortcli monitor

# System temperature
vcgencmd measure_temp

# Service logs
bugcam autostart logs --follow

Troubleshooting

# Run diagnostics
bugcam doctor

# Verify system readiness
bugcam check

# Command not found after install
pipx ensurepath  # then close and reopen terminal

# Camera not detected
rpicam-hello
sudo raspi-config  # Enable camera in Interface Options

# Hailo driver issues
sudo apt install --reinstall hailo-all
hailortcli scan

# Service logs
bugcam autostart logs

Development

git clone https://github.com/MIT-Senseable-City-Lab/sensing-garden.git
cd sensing-garden
poetry install
poetry run pytest tests/ -v
poetry run bugcam --help

License

MIT

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