## Installation Guide

### Environment Setup
1. **Create a new Conda environment** with Python version 3.11.9.

2. **Install PyTorch** with CUDA 12.4 support. Ensure the installed PyTorch version is 2.4.0 with the appropriate CUDA configuration.

3. **Install Ultralytics** using `pip install -U ultralytics`.

### Repository Structure
The project repository contains three main folders:
- **yolov5**: Contains training and inference Jupyter notebooks for YOLOv5.
- **yolov8**: Contains training and inference Jupyter notebooks for YOLOv8.
- **yolov9**: Contains training and inference Jupyter notebooks for YOLOv9.

Each folder includes:
- Training notebooks
- Inference notebooks
- Sample images from our dataset for testing.

### Running the Code
To train or run inference, open the respective Jupyter notebooks in each folder and execute the provided cells.
