263 lines
9.3 KiB
Python
263 lines
9.3 KiB
Python
from random import randint
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import pygame
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import configparser
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config = configparser.ConfigParser()
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config.read("config.ini")
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from domain.commands.random_cat_move_command import RandomCatMoveCommand
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from domain.commands.vacuum_move_command import VacuumMoveCommand
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from domain.entities.cat import Cat
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from domain.entities.entity import Entity
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from domain.entities.vacuum import Vacuum
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from domain.entities.garbage import Garbage
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from domain.entities.earring import Earring
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from domain.entities.docking_station import Doc_Station
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from domain.world import World
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from view.renderer import Renderer
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from AI_brain.genetic_algorytm import GeneticAlgorytm, Path
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if not config.getboolean("NEURAL_NETWORK", "is_neural_network_off"):
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from AI_brain.image_recognition import VacuumRecognizer
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# from AI_brain.movement import GoAnyDirectionBFS, State
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# from AI_brain.rotate_and_go_bfs import RotateAndGoBFS, State
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from AI_brain.rotate_and_go_aStar import RotateAndGoAStar, State
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class Main:
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def __init__(self):
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tiles_x = 10
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tiles_y = 10
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self.renderer = Renderer(600, 600, tiles_x, tiles_y)
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self.world = generate_world(tiles_x, tiles_y)
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self.commands = []
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self.clock = pygame.time.Clock()
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self.running = True
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self.fps = 60
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def run(self):
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while self.running:
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self.process_input()
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self.update()
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self.renderer.render(self.world)
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self.clock.tick(self.fps)
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pygame.quit()
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def run_robot(self):
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self.renderer.render(self.world)
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if config["AI_BRAIN"]["mode"] == "to_station":
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start_state = State(self.world.vacuum.x, self.world.vacuum.y)
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end_state = State(self.world.doc_station.x, self.world.doc_station.y)
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path_searcher = RotateAndGoAStar(self.world, start_state, end_state)
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if not path_searcher.search():
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print("No solution")
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exit(0)
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print(path_searcher.actions)
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print(path_searcher.cost)
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robot_actions = path_searcher.actions
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elif config["AI_BRAIN"]["mode"] == "full_clean":
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genetic_searcher = GeneticAlgorytm(self.world)
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genetic_searcher.run()
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genetic_searcher.print_top()
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robot_actions = genetic_searcher.best_path.real_path
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else:
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print("Wrong mode")
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exit(0)
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while self.running:
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for event in pygame.event.get():
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if event.type == pygame.QUIT:
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self.running = False
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if len(robot_actions) > 0:
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action_direction = robot_actions.pop(0)
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# self.handle_action1(action_direction)
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self.handle_action2(action_direction)
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self.update()
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self.renderer.render(self.world)
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self.clock.tick(5)
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pygame.quit()
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def handle_action1(self, action):
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if action == "UP":
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self.commands.append(
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VacuumMoveCommand(self.world, self.world.vacuum, (0, -1))
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)
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elif action == "DOWN":
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self.commands.append(
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VacuumMoveCommand(self.world, self.world.vacuum, (0, 1))
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)
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elif action == "LEFT":
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self.commands.append(
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VacuumMoveCommand(self.world, self.world.vacuum, (-1, 0))
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)
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elif action == "RIGHT":
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self.commands.append(
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VacuumMoveCommand(self.world, self.world.vacuum, (1, 0))
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)
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def handle_action2(self, action):
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if action == "GO":
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self.commands.append(
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VacuumMoveCommand(
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self.world, self.world.vacuum, self.world.vacuum.direction
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)
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)
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elif action == "RR":
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self.world.vacuum.direction = (
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-self.world.vacuum.direction[1],
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self.world.vacuum.direction[0],
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)
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elif action == "RL":
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self.world.vacuum.direction = (
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self.world.vacuum.direction[1],
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-self.world.vacuum.direction[0],
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)
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elif action == "DEFAULT_ROTATION":
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self.world.vacuum.direction = (1, 0)
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def process_input(self):
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for event in pygame.event.get():
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if event.type == pygame.QUIT:
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self.running = False
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if event.type == pygame.KEYDOWN:
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if event.key == pygame.K_LEFT:
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self.commands.append(
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VacuumMoveCommand(self.world, self.world.vacuum, (-1, 0))
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)
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if event.key == pygame.K_RIGHT:
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self.commands.append(
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VacuumMoveCommand(self.world, self.world.vacuum, (1, 0))
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)
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if event.key == pygame.K_UP:
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self.commands.append(
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VacuumMoveCommand(self.world, self.world.vacuum, (0, -1))
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)
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if event.key == pygame.K_DOWN:
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self.commands.append(
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VacuumMoveCommand(self.world, self.world.vacuum, (0, 1))
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)
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def update(self):
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if config.getboolean("APP", "cat"):
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self.commands.append(RandomCatMoveCommand(self.world, self.world.cat))
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for command in self.commands:
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command.run()
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self.commands.clear()
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def generate_world(tiles_x: int, tiles_y: int) -> World:
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if config.getboolean("NEURAL_NETWORK", "is_neural_network_off"):
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world = World(tiles_x, tiles_y)
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x, y = config.get("CONSTANT", "RobotStartPosition").split(",")
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x, y = int(x), int(y)
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world.vacuum = Vacuum(x, y)
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x, y = config.get("CONSTANT", "DockStationStartPosition").split(",")
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x, y = int(x), int(y)
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world.doc_station = Doc_Station(x, y)
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if config.getboolean("APP", "cat"):
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world.cat = Cat(7, 8)
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world.add_entity(world.cat)
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world.add_entity(world.doc_station)
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world.add_entity(world.vacuum)
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world.add_entity(Entity(2, 8, "PLANT1"))
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world.add_entity(Entity(4, 1, "PLANT1"))
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world.add_entity(Entity(3, 4, "PLANT2"))
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world.add_entity(Entity(8, 8, "PLANT2"))
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world.add_entity(Entity(9, 3, "PLANT3"))
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numberOfEarrings = config.getint("CONSTANT", "NumberOfEarrings")
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for _ in range(numberOfEarrings):
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temp_x = randint(0, tiles_x - 1)
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temp_y = randint(0, tiles_y - 1)
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while world.is_entity_at(temp_x, temp_y):
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temp_x = randint(0, tiles_x - 1)
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temp_y = randint(0, tiles_y - 1)
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world.add_entity(Earring(temp_x, temp_y))
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for _ in range(config.getint("CONSTANT", "NumberOfBananas")):
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temp_x = randint(0, tiles_x - 1)
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temp_y = randint(0, tiles_y - 1)
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while world.is_entity_at(temp_x, temp_y):
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temp_x = randint(0, tiles_x - 1)
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temp_y = randint(0, tiles_y - 1)
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world.add_entity(Garbage(temp_x, temp_y))
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else:
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def world_adder(x, y, object, style=None):
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print(object)
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if object == "Plant":
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world.add_entity(Entity(x, y, f"PLANT{randint(1, 3)}"))
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if object == "Earings":
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world.add_entity(Earring(x, y))
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if object == "Banana":
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world.add_entity(Garbage(temp_x, temp_y))
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if object == "Cat" and config.getboolean("APP", "cat"):
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world.add_entity(Cat(x, y))
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neural_network = VacuumRecognizer()
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world = World(tiles_x, tiles_y)
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world.vacuum = Vacuum(1, 1)
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world.doc_station = Doc_Station(9, 8)
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if config.getboolean("APP", "cat"):
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world.cat = Cat(7, 8)
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world.add_entity(world.cat)
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for _ in range(config.getint("CONSTANT", "NumberOfPlants")):
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temp_x = randint(0, tiles_x - 1)
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temp_y = randint(0, tiles_y - 1)
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path = VacuumRecognizer.get_random_dir(neural_network, "Plant")
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world_adder(temp_x, temp_y, neural_network.recognize(path))
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for _ in range(config.getint("CONSTANT", "NumberOfEarrings")):
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temp_x = randint(0, tiles_x - 1)
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temp_y = randint(0, tiles_y - 1)
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path = VacuumRecognizer.get_random_dir(neural_network, "Earings")
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world_adder(temp_x, temp_y, neural_network.recognize(path))
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for _ in range(config.getint("CONSTANT", "NumberOfBananas")):
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temp_x = randint(0, tiles_x - 1)
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temp_y = randint(0, tiles_y - 1)
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path = VacuumRecognizer.get_random_dir(neural_network, "Banana")
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world_adder(temp_x, temp_y, neural_network.recognize(path))
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for x in range(world.width):
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for y in range(world.height):
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if world.garbage_at(x, y):
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world.costs[x][y] = 1
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else:
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world.costs[x][y] = 2
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return world
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if __name__ == "__main__":
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app = Main()
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if config["APP"]["movement"] == "human":
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app.run()
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elif config["APP"]["movement"] == "robot":
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app.run_robot()
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