This project is an image resizer application built using artificial intelligence (AI) techniques and implemented in Python. The application allows users to resize images while maintaining the aspect ratio and preserving image quality.

Resizing with AI: The image resizer utilizes state-of-the-art AI algorithms to intelligently resize images. It employs advanced techniques to ensure that the resized images maintain their visual quality and avoid common artifacts such as blurriness or distortion.

Aspect Ratio Preservation: When resizing images, the application automatically maintains the original aspect ratio, preventing images from appearing stretched or distorted. This ensures that the resized images remain visually pleasing and true to the original content.

User-Friendly Interface: The image resizer comes with a user-friendly graphical interface that makes it easy for users to interact with the application. Users can easily select the desired image file, specify the target dimensions, and initiate the resizing process with a simple click.

Batch Processing: The application supports batch processing, allowing users to resize multiple images simultaneously. Users can specify a directory containing multiple images, and the resizer will automatically process each image in the directory, saving the resized versions with the same filenames or a custom naming scheme.

Output Customization: Users have the flexibility to customize the output settings according to their requirements. They can specify the output directory to save the resized images, choose the desired image format (e.g., JPEG, PNG), adjust the compression level, and apply additional post-processing options if needed.

Contributions to this image resizer project are welcome! If you encounter any issues, have ideas for new features, or would like to contribute enhancements, please follow these steps:

Fork the repository and create a new branch for your contribution.

Make the necessary changes and additions in your branch.

Test your changes thoroughly to ensure they work as expected.

Commit your changes and push your branch to your forked repository.

Create a pull request, describing the changes you have made and providing any relevant information or context.