This repository contains code for a 2D diffusion model applied to an image. The diffusion model is implemented using the finite difference method and the scipy.ndimage library in Python.
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
You need to have the following libraries installed in order to run the code:
numpyscipymatplotlib
You can install these libraries using the following command:
pip install numpy scipy matplotlib
To run the code, simply run the following command in the terminal:
python diffusion_model.py
This will apply the diffusion model to an input image and plot the original and diffused images for comparison.
You can change the input image by replacing the input_image.jpg file with your own image.
You can also modify the diffusion parameters by changing the alpha and n_iterations arguments in the diffuse_image function. The alpha argument is the diffusion coefficient, which controls the amount of diffusion, and the n_iterations argument is the number of iterations, which controls the duration of the diffusion process.
This code serves as a simple example of how to apply a 2D diffusion model to an image using the finite difference method and the scipy.ndimage library in Python. Feel free to use and modify the code as you see fit.