diff --git a/ForkliftAgent.py b/ForkliftAgent.py
index 8dee11e..d40448b 100644
--- a/ForkliftAgent.py
+++ b/ForkliftAgent.py
@@ -32,6 +32,7 @@ class ForkliftAgent(AgentBase):
self.current_item = None
self.item_station_completed = False
self.provided_items: List[Item] = []
+ self.ready_for_execution = False
def queue_movement_actions(self, movement_actions: List[Action]):
self.action_queue.extend(movement_actions)
@@ -102,7 +103,7 @@ class ForkliftAgent(AgentBase):
stations = dict(self.graph.packingStations)
if i.real_type == ItemType.SHELF:
packing_station = stations[PatchType.packingA]
- elif i.real_type == ItemType.EGG:
+ elif i.real_type == ItemType.FRIDGE:
packing_station = stations[PatchType.packingB]
elif i.real_type == ItemType.DOOR:
packing_station = stations[PatchType.packingC]
@@ -147,7 +148,7 @@ class ForkliftAgent(AgentBase):
def step(self) -> None:
if len(self.action_queue) > 0:
self.move()
- elif len(self.orderList) > 0:
+ elif self.ready_for_execution and len(self.orderList) > 0:
if (self.current_order is not None and len(self.current_order.items)) == 0:
self.fulfilled_orders.append(self.current_order)
self.current_order = None
diff --git a/GameModel.py b/GameModel.py
index 45999f5..c303fb8 100644
--- a/GameModel.py
+++ b/GameModel.py
@@ -1,3 +1,4 @@
+import copy
from enum import Enum
from typing import List
@@ -14,9 +15,12 @@ from PictureVisualizationAgent import PictureVisualizationAgent
from data.GameConstants import GameConstants
from data.Item import Item
from data.Order import Order
+from data.enum.ItemType import ItemType
from decision.Action import Action
from decision.ActionType import ActionType
+from imageClasification.Classificator import Classificator
from pathfinding.PathfinderOnStates import PathFinderOnStates, PathFinderState
+from util.PathByEnum import PathByEnum
from util.PathDefinitions import GridLocation, GridWithWeights
@@ -30,7 +34,7 @@ class Phase(Enum):
class GameModel(Model):
- def __init__(self, width, height, graph: GridWithWeights):
+ def __init__(self, width, height, graph: GridWithWeights, items: int, orders: int, classificator):
# self.num_agents = 5
self.first = True
self.item_recognised = False
@@ -67,14 +71,16 @@ class GameModel(Model):
print("############## INITIALIZATION ##############")
self.phase = Phase.INIT
self.initialize_grid(graph)
- self.orderList: List[Order] = InitialStateFactory.generate_order_list(3)
+ self.orderList: List[Order] = InitialStateFactory.generate_order_list(orders)
self.fulfilled_orders: List[Order] = []
self.forklift_agent.orderList = self.orderList
self.forklift_agent.fulfilled_orders = self.fulfilled_orders
+ self.classificator = classificator
print("############## RECOGNISE ITEMS ##############")
self.phase = Phase.ITEM_RECOGNITION
- self.provided_items = InitialStateFactory.generate_item_list(3)
+ self.provided_items = InitialStateFactory.generate_item_list(items)
+ self.items_for_recognization = copy.deepcopy(self.provided_items)
self.recognised_items: List[Item] = []
print("Relocate forklift agent to loading area for item recognition")
@@ -115,7 +121,7 @@ class GameModel(Model):
def place_dividers(self):
for i in range(0, 10):
- for j in range(10,13):
+ for j in range(10, 13):
agent = PatchAgent(self, (i, j), PatchType.divider)
self.agents.append(agent)
self.grid.place_agent(agent, (i, j))
@@ -160,14 +166,15 @@ class GameModel(Model):
if self.phase == Phase.ITEM_RECOGNITION:
if not self.item_recognised and self.forklift_agent.current_position == self.drop_off.location:
- if len(self.provided_items) == 0:
+ if len(self.items_for_recognization) == 0:
print("FINISHED ITEM RECOGNITION")
self.item_recognised = True
self.phase = Phase.CLIENT_SORTING
+ self.forklift_agent.ready_for_execution = True
else:
- print("BEGIN ITEM RECOGNITION, left: {}".format(len(self.provided_items)))
- item_to_recognise = self.provided_items.pop()
- self.picture_visualization.img = "item_images/door/drzwi1.jpg"
+ print("BEGIN ITEM RECOGNITION, left: {}".format(len(self.items_for_recognization)))
+ item_to_recognise = self.items_for_recognization.pop()
+ self.picture_visualization.img = PathByEnum.get_random_path(item_to_recognise.real_type)
recognised = self.recognise_item(item_to_recognise)
self.recognised_items.append(recognised)
@@ -182,5 +189,14 @@ class GameModel(Model):
def recognise_item(self, item: Item):
# TODO IMAGE PROCESSING
- item.guessed_type = item.real_type
+ val = self.classificator.image_clasification(self.picture_visualization.img)
+ print("VAL: {}".format(val))
+
+ if val == ItemType.DOOR:
+ item.guessed_type = ItemType.DOOR
+ elif val == ItemType.FRIDGE:
+ item.guessed_type = ItemType.FRIDGE
+ elif val == ItemType.SHELF:
+ item.guessed_type = ItemType.SHELF
+
return item
diff --git a/data/enum/ItemType.py b/data/enum/ItemType.py
index f15e785..54fc4c1 100644
--- a/data/enum/ItemType.py
+++ b/data/enum/ItemType.py
@@ -2,6 +2,6 @@ from enum import Enum
class ItemType(Enum):
- DOOR = 1
- SHELF = 2
- EGG = 3
\ No newline at end of file
+ DOOR = "door"
+ SHELF = "shelf"
+ FRIDGE = "fridge"
\ No newline at end of file
diff --git a/imageClasification/imageClasification.py b/imageClasification/Classificator.py
similarity index 88%
rename from imageClasification/imageClasification.py
rename to imageClasification/Classificator.py
index b8e19b7..4f9d2fd 100644
--- a/imageClasification/imageClasification.py
+++ b/imageClasification/Classificator.py
@@ -9,8 +9,13 @@ from tensorflow.keras import layers
from tensorflow.keras.models import Sequential
-class imageClasification():
- def train_model(data_dir):
+class Classificator():
+
+ def __init__(self, data_dir: str) -> None:
+ super().__init__()
+ self.data = self.train_model(data_dir)
+
+ def train_model(self, data_dir):
batch_size = 32
img_height = 180
img_width = 180
@@ -111,7 +116,7 @@ class imageClasification():
plt.show()
return model, class_names, img_width, img_height
- def image_clasification(image_path, model, class_names):
+ def image_clasification(self,image_path):
# ścieżka do sprawdzanego obrazu
# image_path = "./th-367101945.jpg"
@@ -121,11 +126,11 @@ class imageClasification():
img_array = tf.keras.utils.img_to_array(img)
img_array = tf.expand_dims(img_array, 0) # Create a batch
- predictions = model.predict(img_array)
+ predictions = self.data[0].predict(img_array)
score = tf.nn.softmax(predictions[0])
- # print(
- # "This image most likely belongs to {} with a {:.2f} percent confidence."
- # .format(class_names[np.argmax(score)], 100 * np.max(score))
- # )
- return class_names[np.argmax(score)]
+ print(
+ "This image most likely belongs to {} with a {:.2f} percent confidence."
+ .format(self.data[1][np.argmax(score)], 100 * np.max(score))
+ )
+ return self.data[1][np.argmax(score)]
diff --git a/imageClasification/how_to_use.py b/imageClasification/how_to_use.py
index 225207e..e5e6421 100644
--- a/imageClasification/how_to_use.py
+++ b/imageClasification/how_to_use.py
@@ -1,15 +1,14 @@
-from imageClasification import imageClasification
+from Classificator import Classificator
#Training model
-data = imageClasification.train_model("../SI_InteligentnyWozekWidlowy/imageClasification/images")
-
+data = Classificator.train_model("../SI_InteligentnyWozekWidlowy/imageClasification/images")
#image_path = ścieżka do klasyfikowanego obrazka
#data[0] = model (wytrenowany model
#data[1] = class_names
-image_classified = imageClasification.image_clasification("./th-367101945.jpg",
- data[0],
- data[1])
+image_classified = Classificator.image_clasification("./th-367101945.jpg",
+ data[0],
+ data[1])
print(image_classified)
diff --git a/main.py b/main.py
index 0574917..1991f58 100644
--- a/main.py
+++ b/main.py
@@ -9,11 +9,11 @@ from PatchAgent import PatchAgent
from PatchType import PatchType
from PictureVisualizationAgent import PictureVisualizationAgent
from data.enum.Direction import Direction
+from imageClasification.Classificator import Classificator
from util.PathDefinitions import GridWithWeights
from visualization.DisplayAttributeElement import DisplayAttributeElement
from visualization.DisplayItemListAttribute import DisplayItemListAttributeElement
from visualization.DisplayOrderList import DisplayOrderList
-from visualization.DisplayPictureElement import DisplayPictureElement
colors = [
'blue', 'cyan', 'orange', 'yellow', 'magenta', 'purple', '#103d3e', '#9fc86c',
@@ -88,11 +88,13 @@ if __name__ == '__main__':
ordersText = DisplayOrderList("orderList")
fulfilled_orders = DisplayOrderList("fulfilled_orders")
+ classificator = Classificator("imageClasification/images")
+
server = ModularServer(GameModel,
[grid, readyText, provided_itesm, recognised_items, ordersText,
fulfilled_orders],
"Automatyczny Wózek Widłowy",
- {"width": gridHeight, "height": gridWidth, "graph": diagram}, )
+ dict(width=gridHeight, height=gridWidth, graph=diagram, items=50, orders=3, classificator=classificator))
server.port = 8888
server.launch()
diff --git a/util/PathByEnum.py b/util/PathByEnum.py
index efe2cee..b517494 100644
--- a/util/PathByEnum.py
+++ b/util/PathByEnum.py
@@ -1,14 +1,15 @@
-from random import random
+import random
from data.enum.ItemType import ItemType
class PathByEnum:
- def get_random_path(self, item:ItemType):
+ @staticmethod
+ def get_random_path(item: ItemType):
if item == ItemType.DOOR:
a = str(random.randint(1, 10))
return "item_images/door/drzwi" + a + ".jpg"
- if item == ItemType.EGG:
+ if item == ItemType.FRIDGE:
a = str(random.randint(1, 10))
return "item_images/refrigerator/lodowka" + a + ".jpg"
if item == ItemType.SHELF:
diff --git a/visualization/DisplayItemListAttribute.py b/visualization/DisplayItemListAttribute.py
index 82b2029..9ca1f61 100644
--- a/visualization/DisplayItemListAttribute.py
+++ b/visualization/DisplayItemListAttribute.py
@@ -41,7 +41,7 @@ class DisplayItemListAttributeElement(TextElement):
elif key == ItemType.SHELF:
key_str = "Shelf"
- res += "{}:{}".format(key_str, val)
+ res += "{}:{}".format(key, val)
res += ""
diff --git a/visualization/DisplayOrderList.py b/visualization/DisplayOrderList.py
index 9b06d35..f7b7564 100644
--- a/visualization/DisplayOrderList.py
+++ b/visualization/DisplayOrderList.py
@@ -38,13 +38,13 @@ class DisplayOrderList(TextElement):
key = e
val = itemCounter[key]
- key_str = ""
- if key == ItemType.DOOR:
- key_str = "Door"
- elif key == ItemType.SHELF:
- key_str = "Shelf"
+ # key_str = ""
+ # if key == ItemType.DOOR:
+ # key_str = "Door"
+ # elif key == ItemType.SHELF:
+ # key_str = "Shelf"
- item_str += f"{key_str}:{val}"
+ item_str += f"{str(key)}:{str(val)}"
item_str += ""