Image Reconstruction with Genetic Algorithm

This project implements a genetic algorithm for image reconstruction. The goal is to evolve a population of random images to resemble a target image.

Requirements

To run this project, you need to have the following libraries installed:

• NumPy
• Matplotlib
• PIL (Python Imaging Library)

Usage

1. Clone the repository to your local machine.
2. Place the target image you want to reconstruct in the same directory as the script.
3. Open the script file image_reconstruction.py.
4. Adjust the genetic algorithm parameters if needed:
   • population_size: The size of the population (default: 100).
   • generations: The number of generations to evolve the population (default: 5000).
   • mutation_rate: The probability of mutation for each individual (default: 0.5).
5. In the main() function, specify the path to the target image by updating the image_path parameter in the load_image() function call.
6. Save the script file.
7. Run the script using a Python interpreter: python image_reconstruction.py.
8. The script will generate the reconstructed image and save it as reconstructed_image.jpg in the same directory.
9. The original and reconstructed images will be displayed side by side in a matplotlib window.

Examples

Here are some examples of reconstructed images using this algorithm: