# Palm Oil Fruit Ripeness Recognition Service

A server-side application for identifying the ripeness of palm oil fruits using computer vision.

## Overview

This project provides a recognition service for palm oil fruit ripeness. It is designed to assist in the automation of the harvesting process by providing accurate assessment of fruit maturity.

## Features

- **Ripeness Classification**: Uses advanced image recognition to categorize palm oil fruits (e.g., Unripe, Under-ripe, Ripe, Over-ripe).
- **API Interface**: Built to serve mobile and web clients for real-time recognition.

## Getting Started

### Prerequisites

- Python 3.8+
- Virtual environment (recommended)

### Installation

1. **Clone the repository**:
   ```powershell
   git clone <repository-url>
   cd palm-oil-ai
   ```

2. **Set up virtual environment**:
   ```powershell
   python -m venv venv
   .\venv\Scripts\Activate.ps1
   ```

3. **Install dependencies**:
   ```powershell
   pip install -r requirements.txt
   ```
   *(Note: Ensure requirements.txt is created/updated as the project develops)*

### Running the Server

To start the recognition service:

```powershell
# Assuming a FastAPI/Uvicorn setup (common for such services)
uvicorn main:app --reload
```

## Dataset

This project uses the YOLOv8 dataset format for training and evaluation:
- YOLOv8 Dataset: `oil palm ripeness.v5-roboflow-instant-2--eval-.yolov8`

## License

[License Type] - See LICENSE file for details.