360° Panorama Processor

Welcome to the 360° Panorama Processor! This project is designed to help you process 360-degree panoramic images, allowing for various transformations, analyses, and enhancements to be applied to your panoramic content.

Table of Contents

Features Installation Usage Examples Contributing License Contact

Features

Stitching: Seamlessly stitch multiple images into a single 360-degree panorama. Enhancement: Improve the quality and clarity of your panoramas with advanced filters. Projection: Convert panoramic images into different projection types (e.g., equirectangular, stereographic). Analysis: Analyze panoramic images for features and metrics. Export: Save processed panoramas in various formats and resolutions.

Installation

To run the 360° Panorama Processor, you need to have Python installed on your system along with a few libraries.

Clone the repository:

bash git clone https://github.com/yourusername/360-panorama-processor.git
cd 360-panorama-processor
Install the required dependencies using pip:

bash pip install -r requirements.txt
Ensure you have the dependencies installed:

OpenCV NumPy Scikit-image Matplotlib (optional, for visualization)

Usage

Here is a basic example of how to use the processor:

python from panorama_processor import PanoramaProcessor

Initialize the processor

processor = PanoramaProcessor()

Load your images

images = ['image1.jpg', 'image2.jpg', ...]

Stitch the images

panorama = processor.stitch(images)

Enhance the panorama

enhanced_panorama = processor.enhance(panorama)

Save the result

processor.save(enhanced_panorama, 'output_panorama.jpg')

Examples

Check out the examples directory for more comprehensive examples demonstrating various use cases of the 360° Panorama Processor.

Contributing

We welcome contributions from the community! If you'd like to contribute, please follow these steps:

Fork the repository. Create a new branch (git checkout -b feature/YourFeatureName). Make your changes. Commit your changes (git commit -am 'Add a feature'). Push to the branch (git push origin feature/YourFeatureName). Create a new Pull Request. Please ensure your code adheres to our coding standards and includes appropriate test coverage for new features.

License

This project is licensed under the MIT License. See the LICENSE file for more information.

Contact

If you have any questions or feedback, feel free to open an issue or contact the project maintainer at your-email@example.com.