Genetic_Algorithm

This program uses a genetic algorithm to replicate a target image with triangles. The genetic operations include a fitness function, crossover, asexual reproduction, and mutations. The idea was inspired by the following blog:

Genetic Programming: Evolution of Mona Lisa

Dependencies

Python 3

If you do not have the pip installer, you will need to install it. Type this command in the terminal:

python get-pip.py

In your terminal, use the package manager pip install Pillow.

pip install Pillow

Usage

Run the program by typing in the terminal in the following format:

# "population size" and "num of triangles" should be an integer. "crossover rate", "mutation rate", and
# "mutation amount" must be decimals between 0 and 1.
py main.py [target image] [population size] [num of triangles] [crossover rate] [mutation rate] [mutation amount]

# For example, type this to replicate an image by the name "mona_lisa.jpg" with a population size of 20,
# 100 triangles, a crossover rate of 0.1, mutation rate of 0.7, and a mutation amount of 0.1.
py main.py mona_lisa.jpg 20 100 0.1 0.7 0.1

Parameters

• Target Image: The image that will be replicated.
• Population Size: Number of individuals in a generation.
• Number of Triangles: The number of triangles present in an individual/image.
• Crossover Rate: Percentage of individuals that reproduce sexually or asexually (The closer to 1, the more reproduced sexually).
• Mutation Rate: Percentage of how many individuals get mutated.
• Mutation Amount: Percentage of how many triangles in an individual get mutated.

Results

The replicated images will be saved in the newly created "generated_images" directory. It will save an image in every 20 iterations.