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28fe27a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 | # Welcome to the Self_Driven_Vehicle Project!!
# NEAT(NeuroEvolution of Augmenting Topologies) is an evolutionary algorithm that creates artificial neural networks.
# The "config-feedforward.txt" file contains all the hyper-parameters for adjusting Vehicle Behaviour.
#
import pygame
import os
import math
import sys
import random
import neat
screen_width = 1500
screen_height = 800
generation = 0
class Car:
def __init__(self):
self.surface = pygame.image.load("car.png")
self.surface = pygame.transform.scale(self.surface, (100, 100))
self.rotate_surface = self.surface
self.pos = [700, 650]
self.angle = 0
self.speed = 0
self.center = [self.pos[0] + 50, self.pos[1] + 50]
self.radars = []
self.radars_for_draw = []
self.is_alive = True
self.goal = False
self.distance = 0
self.time_spent = 0
def draw(self, screen):
screen.blit(self.rotate_surface, self.pos)
self.draw_radar(screen)
def draw_radar(self, screen):
for r in self.radars:
pos, dist = r
pygame.draw.line(screen, (0, 255, 0), self.center, pos, 1)
pygame.draw.circle(screen, (0, 255, 0), pos, 5)
def check_collision(self, map):
self.is_alive = True
for p in self.four_points:
if map.get_at((int(p[0]), int(p[1]))) == (255, 255, 255, 255):
self.is_alive = False
break
def check_radar(self, degree, map):
len = 0
x = int(self.center[0] + math.cos(math.radians(360 - (self.angle + degree))) * len)
y = int(self.center[1] + math.sin(math.radians(360 - (self.angle + degree))) * len)
while not map.get_at((x, y)) == (255, 255, 255, 255) and len < 300:
len = len + 1
x = int(self.center[0] + math.cos(math.radians(360 - (self.angle + degree))) * len)
y = int(self.center[1] + math.sin(math.radians(360 - (self.angle + degree))) * len)
dist = int(math.sqrt(math.pow(x - self.center[0], 2) + math.pow(y - self.center[1], 2)))
self.radars.append([(x, y), dist])
def update(self, map):
#check speed
self.speed = 15
#check position
self.rotate_surface = self.rot_center(self.surface, self.angle)
self.pos[0] += math.cos(math.radians(360 - self.angle)) * self.speed
if self.pos[0] < 20:
self.pos[0] = 20
elif self.pos[0] > screen_width - 120:
self.pos[0] = screen_width - 120
self.distance += self.speed
self.time_spent += 1
self.pos[1] += math.sin(math.radians(360 - self.angle)) * self.speed
if self.pos[1] < 20:
self.pos[1] = 20
elif self.pos[1] > screen_height - 120:
self.pos[1] = screen_height - 120
# here, we're calculating 4 collision points
self.center = [int(self.pos[0]) + 50, int(self.pos[1]) + 50]
len = 40
left_top = [self.center[0] + math.cos(math.radians(360 - (self.angle + 30))) * len, self.center[1] + math.sin(math.radians(360 - (self.angle + 30))) * len]
right_top = [self.center[0] + math.cos(math.radians(360 - (self.angle + 150))) * len, self.center[1] + math.sin(math.radians(360 - (self.angle + 150))) * len]
left_bottom = [self.center[0] + math.cos(math.radians(360 - (self.angle + 210))) * len, self.center[1] + math.sin(math.radians(360 - (self.angle + 210))) * len]
right_bottom = [self.center[0] + math.cos(math.radians(360 - (self.angle + 330))) * len, self.center[1] + math.sin(math.radians(360 - (self.angle + 330))) * len]
self.four_points = [left_top, right_top, left_bottom, right_bottom]
self.check_collision(map)
self.radars.clear()
for d in range(-90, 120, 45):
self.check_radar(d, map)
def get_data(self):
radars = self.radars
ret = [0, 0, 0, 0, 0]
for i, r in enumerate(radars):
ret[i] = int(r[1] / 30)
return ret
def get_alive(self):
return self.is_alive
def get_reward(self):
return self.distance / 50.0
def rot_center(self, image, angle):
orig_rect = image.get_rect()
rot_image = pygame.transform.rotate(image, angle)
rot_rect = orig_rect.copy()
rot_rect.center = rot_image.get_rect().center
rot_image = rot_image.subsurface(rot_rect).copy()
return rot_image
def run_car(genomes, config):
# Init NEAT
nets = []
cars = []
for id, g in genomes:
net = neat.nn.FeedForwardNetwork.create(g, config)
nets.append(net)
g.fitness = 0
# Init my cars
cars.append(Car())
# Init my game
pygame.init()
screen = pygame.display.set_mode((screen_width, screen_height))
clock = pygame.time.Clock()
generation_font = pygame.font.SysFont("Arial", 70)
font = pygame.font.SysFont("Arial", 30)
map = pygame.image.load('map.png')
# Main loop
global generation
generation += 1
while True:
for event in pygame.event.get():
if event.type == pygame.QUIT:
sys.exit(0)
# Different inputs result in different Vehicle behaviour.
for index, car in enumerate(cars):
output = nets[index].activate(car.get_data())
i = output.index(max(output))
if i == 0:
car.angle += 20
else:
car.angle -= 20
# Update car and fitness
remain_cars = 0
for i, car in enumerate(cars):
if car.get_alive():
remain_cars += 1
car.update(map)
genomes[i][1].fitness += car.get_reward()
# check
if remain_cars == 0:
break
# Drawing
screen.blit(map, (0, 0))
for car in cars:
if car.get_alive():
car.draw(screen)
text = generation_font.render("Generation : " + str(generation), True, (255, 255, 0))
text_rect = text.get_rect()
text_rect.center = (screen_width/2, 100)
screen.blit(text, text_rect)
text = font.render("remain cars : " + str(remain_cars), True, (0, 0, 0))
text_rect = text.get_rect()
text_rect.center = (screen_width/2, 200)
screen.blit(text, text_rect)
pygame.display.flip()
clock.tick(0)
if __name__ == "__main__":
# Set configuration file
config_path = "./config-feedforward.txt"
config = neat.config.Config(neat.DefaultGenome, neat.DefaultReproduction,
neat.DefaultSpeciesSet, neat.DefaultStagnation, config_path)
# Create core evolution algorithm class
p = neat.Population(config)
# Add reporter for fancy statistical result
p.add_reporter(neat.StdOutReporter(True))
stats = neat.StatisticsReporter()
p.add_reporter(stats)
# Run NEAT
p.run(run_car, 1000)
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