Automated Gastropod Species Classification Using Deep Learning

📖 Project Overview

This project automates the taxonomic classification of marine gastropods using deep learning. Powered by the Ultralytics YOLO algorithm, the system performs real-time video classification and instance segmentation to identify 23 distinct species accurately. To enable real-world inferencing, the model is deployed as an Edge AI solution on a Raspberry Pi 4 Model B equipped with a Raspberry Pi Camera Module v2.

✨ Key Features

• Integrates a Deep Learning model designed for gastropod classification and instance segmentation.
• Fully optimized for edge deployment on a Raspberry Pi 4 Model B with a Raspberry Pi Camera Module v2.
• Performs live, on-device inferencing for immediate specimen identification without the need for cloud computing.
• Achieves highly robust spatial accuracy, achieving an overall mAP@50-95 of 92%–94%.

🚀 Deployment Guide

This guide outlines step-by-step procedures for setting up the YOLOv8-based gastropod classification environment. The system is designed for Edge AI deployment on a Raspberry Pi 4 Model B.

1. System Requirements

• Hardware
  • Raspberry Pi 4 Model B (4GB or 8GB recommended)
  • MicroSD (32GB+)
  • Camera Module (for live detection)
• Operating System
  • Raspberry Pi OS (64-bit)

  sudo apt update && sudo apt upgrade -y

2. Install System Dependencies

   sudo apt update
   sudo apt install -y \
   python3-venv python3-pip git \
   libatlas-base-dev libjpeg-dev zlib1g-dev \
   libopenblas-dev libblas-dev liblapack-dev \
   gfortran

3. Clone the Repository.

   git clone https://github.com/ejramirez525/automated-gastropod-species-classification-using-deep-learning.git
   cd automated-gastropod-species-classification-using-deep-learning

4. Create Virtual Environment.

   python3 -m venv yolov8-env
   source yolov8-env/bin/activate
   pip install --upgrade pip

5. Project Files Needed.
   • Make sure you have:

   ScientificName.pt
   Gastropod_Classification.py
   

   • Example structure:

   models\ScientificName.pt
   Gastropod_Classification.py
   requirements.txt
   

6. Install the required dependencies.

   pip install -r requirements.txt

7. Pi Camera Setup.
   • Enable camera interface:

   sudo raspi-config
   

   • Go to: Interface Options → Camera → Enable
   • Install camera library:

   pip install picamera2

8. Running the Application.

   python Gastropod_Classification.py

🏆 Research Output

Best in Thesis 🏅
Department of Computer Studies Research Exhibit 2024

Official Research Tarpaulin presented at the Department of Computer Studies, NEMSU Cantilan Research Exhibit.

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