🔥 Fire Detection with YOLOv5

A simple real-time fire detection system using a custom-trained YOLOv5 model and your system’s webcam.
This program captures video from the webcam, processes it with a trained YOLOv5 model, and highlights detected fire regions in real-time.

📷 Example Output

    Example of YOLOv5 detecting fire in a live webcam feed.

📌 Features

- Uses a custom-trained YOLOv5 model (`yolov5s_best.pt`)
- Real-time webcam image processing
- Annotated frames with detection results
- Fast, live inference

📂 Project Structure

project-folder/
    │
    ├── yolov5_fire_detection.py # Main project code
    ├── yolov5s_best.pt # Trained YOLOv5 model
    └── README.md # Project documentation

⚙️ Requirements

Before running, ensure your Python environment is ready.

Install Dependencies

pip install torch torchvision torchaudio
pip install opencv-python
pip install yolov5
🚀 How to Run
Place your trained model in the MODEL_PATH location.

Run the main script:

bash
  Copy code
  python yolov5_fire_detection.py
  A window will open showing the live webcam feed annotated with detection results.

Press q to exit the program.

🛠 Requirements

Python 3.8+
OpenCV
PyTorch
YOLOv5 trained model

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