Initial commit: Add .gitignore and README.md

.gitignore

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+# Virtual Environments
+venv/
+.venv/
+env/
+bin/
+lib/
+share/
+Include/
+Lib/
+Scripts/
+pyvenv.cfg
+
+# Python
+__pycache__/
+*.py[cod]
+*$py.class
+*.so
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+
+# IDEs
+.vscode/
+.idea/
+
+# OS
+.DS_Store
+Thumbs.db

README.md

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+# 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.