# Denoiser

A powerful and efficient noise reduction tool for audio and image processing.

## Description

Denoiser is a cutting-edge software designed to remove unwanted noise from various types of data, with a focus on audio and image processing. It uses advanced algorithms to separate signal from noise, enhancing the quality of your media files.

## Installation

### Prerequisites

- Python 3.8 or higher
- Required packages: numpy, scipy, pytorch

### Installation Steps

```bash
# Clone the repository
git clone https://github.com/yourusername/denoiser.git

# Navigate to the project directory
cd denoiser

# Install dependencies
pip install -r requirements.txt

# Optional: Install development dependencies
pip install -r requirements-dev.txt
```

## Usage

### Basic Usage

```python
from denoiser import Denoiser

# Initialize the denoiser with default settings
denoiser = Denoiser()

# For audio denoising
clean_audio = denoiser.process_audio("noisy_audio.wav", output_path="clean_audio.wav")

# For image denoising
clean_image = denoiser.process_image("noisy_image.jpg", output_path="clean_image.jpg")
```

### Advanced Configuration

```python
# Configure the denoiser with custom parameters
denoiser = Denoiser(
    algorithm="deep_learning",
    intensity=0.7,
    preserve_details=True,
    use_gpu=True
)

# Process with advanced options
clean_audio = denoiser.process_audio(
    "noisy_audio.wav",
    output_path="clean_audio.wav",
    frequency_range=(20, 20000),
    apply_equalization=True
)
```

## Features

- **Multiple Algorithm Support**: Choose from various denoising algorithms, including traditional filters and deep learning approaches.
- **Cross-Platform**: Works on Windows, macOS, and Linux.
- **GPU Acceleration**: Utilize GPU processing for faster denoising operations.
- **Batch Processing**: Process multiple files at once for efficiency.
- **Customizable Parameters**: Fine-tune the denoising process to suit your specific needs.
- **Preservation Controls**: Balance noise reduction with detail preservation.
- **Format Support**: Handles various audio formats (WAV, MP3, FLAC) and image formats (JPG, PNG, TIFF).

## Contributing

We welcome contributions to the Denoiser project! Here's how you can help:

1. **Fork the Repository**: Create your own fork of the project.
2. **Create a Branch**: Make your changes in a new branch.
3. **Submit a Pull Request**: Once your changes are ready, submit a pull request.
4. **Code Review**: Your changes will be reviewed by the maintainers.
5. **Merge**: After approval, your changes will be merged into the main branch.

### Contribution Guidelines

- Follow the existing code style and conventions.
- Write tests for new features or bug fixes.
- Update documentation to reflect your changes.
- Ensure all tests pass before submitting a pull request.
- Keep pull requests focused on a single topic.

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

## Acknowledgments

- Thanks to all contributors who have helped make this project better.
- Special thanks to the research community for developing the algorithms used in this project.

