2022-05-27 00:03:24 +02:00
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import copy
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2022-05-22 16:27:36 +02:00
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from enum import Enum
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from typing import List, Tuple
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from mesa import Model
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from mesa.space import MultiGrid
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from mesa.time import RandomActivation
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from AgentBase import AgentBase
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from ForkliftAgent import ForkliftAgent
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from InitialStateFactory import InitialStateFactory
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from ItemDisplayAgent import ItemDisplayAgent
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from PatchAgent import PatchAgent
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from PatchType import PatchType
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from PictureVisualizationAgent import PictureVisualizationAgent
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from data.GameConstants import GameConstants
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from data.Item import Item
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from data.Order import Order
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from data.enum.ItemType import ItemType
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from decision.Action import Action
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from decision.ActionType import ActionType
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from genetic_order.GeneticOrder import GeneticOrder
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from imageClasification.Classificator import image_classification
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from pathfinding.PathfinderOnStates import PathFinderOnStates, PathFinderState
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from tree.DecisionTree import DecisionTree
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from util.PathByEnum import PathByEnum
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from util.PathDefinitions import GridLocation, GridWithWeights
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class Phase(Enum):
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INIT = 1
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ITEM_RECOGNITION = 2
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CLIENT_SORTING = 3
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PLAN_MOVEMENT = 4
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EXECUTION = 5
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class GameModel(Model):
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def __init__(self, width, height, graph: GridWithWeights, items: int, orders: int, classificator,
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item_display_pos: List[GridLocation]):
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# self.num_agents = 5
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self.first = True
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self.item_recognised = False
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self.running = True
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self.grid = MultiGrid(height, width, True)
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self.schedule = RandomActivation(self)
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self.current_item_recognition = None
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self.current_item = None
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self.client_delivery: PatchAgent = None
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self.drop_off: PatchAgent = None
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self.graph = graph
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self.game_constants = GameConstants(
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width,
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height,
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graph.walls,
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graph.puddles
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)
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self.agents = [AgentBase]
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self.forklift_agent = ForkliftAgent(
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self,
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self.game_constants,
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self.client_delivery,
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self.drop_off,
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self.graph
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)
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self.schedule.add(self.forklift_agent)
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self.agents.append(self.forklift_agent)
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self.item_display_agents: List[ItemDisplayAgent] = []
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# INITIALIZATION #
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print("############## INITIALIZATION ##############")
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self.phase = Phase.INIT
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self.initialize_grid(graph, item_display_pos)
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self.orderList: List[Order] = InitialStateFactory.generate_order_list(orders)
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self.fulfilled_orders: List[Order] = []
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self.forklift_agent.fulfilled_orders = self.fulfilled_orders
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self.forklift_agent.set_base(self.drop_off)
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self.classificator = classificator
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print("############## RECOGNISE ITEMS ##############")
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self.phase = Phase.ITEM_RECOGNITION
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self.provided_items = InitialStateFactory.generate_item_list(items)
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self.items_for_recognization = copy.deepcopy(self.provided_items)
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self.recognised_items: List[Item] = []
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self.current_order_delivered_items = self.forklift_agent.current_order_delivered_items
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print("Relocate forklift agent to loading area for item recognition")
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pathFinder = PathFinderOnStates(
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self.game_constants,
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self.drop_off.location,
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PathFinderState(self.forklift_agent.current_position, self.forklift_agent.current_rotation, 0,
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Action(ActionType.NONE), [])
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)
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actions = pathFinder.get_action_list()
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print("PATHFINDING")
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print(actions)
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self.forklift_agent.queue_movement_actions(actions)
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self.current_order = self.forklift_agent.current_order
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def initialize_grid(self, graph: GridWithWeights, item_display_pos):
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print("INITIALIZING GRID")
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# Add the agent to a random grid cell
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x = 5
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y = 5
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self.grid.place_agent(self.forklift_agent, (x, y))
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self.forklift_agent.current_position = (x, y)
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self.picture_visualization = PictureVisualizationAgent(
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self,
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(1, 11),
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)
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self.schedule.add(self.picture_visualization)
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self.grid.place_agent(self.picture_visualization, self.picture_visualization.location)
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self.agents.append(self.picture_visualization)
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self.place_logistics()
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self.place_dividers()
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self.place_walls_agents(graph.walls)
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self.place_puddles(graph.puddles)
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self.place_packing_stations(graph.packingStations)
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self.place_order_items_display(item_display_pos)
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def place_dividers(self):
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for i in range(0, 10):
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for j in range(10, 13):
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agent = PatchAgent(self, (i, j), PatchType.divider)
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self.agents.append(agent)
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self.grid.place_agent(agent, (i, j))
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def place_logistics(self):
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agent = PatchAgent(self, (self.grid.width - 1, int(self.grid.height / 2)), PatchType.pickUp)
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self.schedule.add(agent)
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self.grid.place_agent(agent, agent.location)
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self.agents.append(agent)
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self.client_delivery = agent
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self.forklift_agent.client_delivery = self.client_delivery
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agent = PatchAgent(self, (0, int(self.grid.height / 2)), PatchType.dropOff)
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self.grid.place_agent(agent, agent.location)
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self.agents.append(agent)
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self.drop_off = agent
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self.forklift_agent.drop_off = self.drop_off
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def place_walls_agents(self, walls: List[GridLocation]):
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for w in walls:
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agent = PatchAgent(self, w, PatchType.wall)
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self.agents.append(agent)
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self.grid.place_agent(agent, w)
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def place_puddles(self, puddles: List[GridLocation]):
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for p in puddles:
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agent = PatchAgent(self, p, PatchType.diffTerrain)
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self.agents.append(agent)
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self.grid.place_agent(agent, p)
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def place_packing_stations(self, packing_stations: List[Tuple[PatchType, GridLocation]]):
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for p in packing_stations:
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agent = PatchAgent(self, p[1], p[0])
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self.agents.append(agent)
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self.grid.place_agent(agent, p[1])
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def place_order_items_display(self, item_positions: List[GridLocation]):
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for p in item_positions:
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agent = ItemDisplayAgent(self, p)
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self.item_display_agents.append(agent)
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self.grid.place_agent(agent, p)
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def update_item_display(self):
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self.current_item = self.forklift_agent.current_item
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for i in range(4):
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self.item_display_agents[i].image = None
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if len(self.forklift_agent.current_order_delivered_items) > i:
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self.item_display_agents[i].image = self.forklift_agent.current_order_delivered_items[i].image
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def step(self):
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self.schedule.step()
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self.grid.remove_agent(self.forklift_agent)
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self.grid.place_agent(self.forklift_agent, self.forklift_agent.current_position)
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self.update_item_display()
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if self.phase == Phase.ITEM_RECOGNITION:
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if not self.item_recognised and self.forklift_agent.current_position == self.drop_off.location:
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if len(self.items_for_recognization) == 0:
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print("FINISHED ITEM RECOGNITION")
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self.item_recognised = True
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self.phase = Phase.CLIENT_SORTING
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self.forklift_agent.ready_for_execution = True
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else:
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print("BEGIN ITEM RECOGNITION, left: {}".format(len(self.items_for_recognization)))
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item_to_recognise = self.items_for_recognization.pop()
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self.picture_visualization.img = PathByEnum.get_random_path(item_to_recognise.real_type)
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recognised = self.recognise_item(item_to_recognise)
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self.recognised_items.append(recognised)
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if self.phase == Phase.CLIENT_SORTING:
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orders: [Order] = self.orderList
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tree: DecisionTree = DecisionTree()
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# CLIENT RECOGNITION
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orders_with_prio = tree.get_data_good(orders)
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# print("before:" )
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# for i in range(len(orders_with_prio)):
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# print("ORDER {}, PRIO: {}".format(orders_with_prio[i].id, orders_with_prio[i].priority))
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# GENERICS SORTING
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genericOrder: GeneticOrder = GeneticOrder(orders_with_prio)
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new_orders = genericOrder.get_orders_sorted(orders)
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# print("after:" )
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# for i in range(len(new_orders)):
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# print("ORDER {}, PRIO: {}".format(new_orders[i].id, new_orders[i].priority))
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self.orderList = new_orders
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self.forklift_agent.orderList = self.orderList
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print("FINISHED CLIENT ORDER SORTING")
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self.phase = Phase.EXECUTION
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if self.phase == Phase.EXECUTION:
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self.current_order = self.forklift_agent.current_order
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pass
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# print("Execution")
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def recognise_item(self, item: Item):
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val = image_classification(self.picture_visualization.img, self.classificator)
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print("VAL: {}".format(val))
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if val == ItemType.DOOR:
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item.guessed_type = ItemType.DOOR
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elif val == ItemType.REFRIGERATOR:
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item.guessed_type = ItemType.REFRIGERATOR
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elif val == ItemType.SHELF:
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item.guessed_type = ItemType.SHELF
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return item
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