camera.py

import cv2
from picamera.array import PiRGBArray
from picamera import PiCamera
import time

# Initialize the camera
camera = PiCamera()
camera.resolution = (640, 480)
camera.framerate = 30
rawCapture = PiRGBArray(camera, size=(640, 480))

# Allow the camera to warm up
time.sleep(0.1)

# Loop over the frames from the camera
for frame in camera.capture_continuous(rawCapture, format="bgr", use_video_port=True):
    # Grab the raw NumPy array representing the image
    image = frame.array

    # Display the image on the screen
    cv2.imshow("Frame", image)
    key = cv2.waitKey(1) & 0xFF

    # Clear the stream for the next frame
    rawCapture.truncate(0)

    # If the 'q' key was pressed, break from the loop
    if key == ord("q"):
        break

# Cleanup
cv2.destroyAllWindows()

neat.py

import neat

# Define the fitness function for the NEAT algorithm
def eval_genomes(genomes, config):
    for genome_id, genome in genomes:
        # Create a neural network from the genome
        net = neat.nn.FeedForwardNetwork.create(genome, config)

        # Run some example inputs through the network
        output = net.activate((0, 0))

        # Evaluate the fitness of the network based on its output
        fitness = output[0]

        # Update the genome's fitness score
        genome.fitness = fitness

# Load the NEAT configuration file
config = neat.Config(neat.DefaultGenome, neat.DefaultReproduction, neat.DefaultSpeciesSet, neat.DefaultStagnation, 'neat_config.txt')

# Create the NEAT population and evolve it for 10 generations
pop = neat.Population(config)
pop.add_reporter(neat.StdOutReporter(True))
pop.add_reporter(neat.StatisticsReporter())
winner = pop.run(eval_genomes, 10)

# Save the winning network to a file
with open('winner_network.txt', 'w') as f:
    f.write(str(winner))

# Load the winning network from the file and use it to make predictions
with open('winner_network.txt', 'r') as f:
    genome = f.read()
    net = neat.nn.FeedForwardNetwork.create(genome, config)
    output = net.activate((1, 1))
    print(output)