decisiontree with network

app.py

@@ -11,10 +11,10 @@ import threading
 import time
 import random
 from classes.data.klient import Klient
-from classes.data.klient import Klient
+from classes.data.klient import KlientCechy
 import xml.etree.ElementTree as ET
 from decisiontree import predict_client
-
+from classes.Jimmy_Neuron.predict_image import predict_image
 
 pygame.init()
 window = pygame.display.set_mode((prefs.WIDTH, prefs.HEIGHT))
@@ -102,9 +102,8 @@ agent = Agent(prefs.SPAWN_POINT[0], prefs.SPAWN_POINT[1], cells)
 klient = Klient(prefs.GRID_SIZE-1, 17,cells)
 target_x, target_y = klientx_target-1, klienty_target
 
-
-
 def watekDlaSciezkiAgenta():
+    assigned = False
     time.sleep(3)
     while True:
         if len(path) > 0:
@@ -119,10 +118,26 @@ def watekDlaSciezkiAgenta():
             elif isinstance(element, tuple):  # Check if it's a tuple indicating movement coordinates
                 x, y = element
                 agent.moveto(x, y)
+                
+        neighbors = agent.get_neighbors(agent.current_cell, agent.cells)
+        for neighbor in neighbors:
+            if neighbor == klient.current_cell:
+                    if not assigned:
+                        random_client_data = random.choice(clients) 
+                        glasses = predict_image(random_client_data.zdjecie)
+                        prediction = predict_client(random_client_data, glasses)
+                        print("\nClient data:")
+                        print(random_client_data)
+                        print("Prediction (Adult):", prediction)
+                        assigned = True
+                        break
+        if assigned:
+            break 
+            
+
         time.sleep(1)
 
 def watekDlaSciezkiKlienta():
-    assigned = False
     time.sleep(3)
     while True:
         if len(path2) > 0:
@@ -138,20 +153,12 @@ def watekDlaSciezkiKlienta():
                 x, y = element2
                 klient.moveto(x, y)
 
-        if not assigned and klient.current_cell == cells[klientx_target][klienty_target]:
+        if klient.current_cell == cells[klientx_target][klienty_target]:
             klient.przyStoliku = True
             klient.stolik = klient.current_cell
-            random_client_data = random.choice(clients) 
-            prediction = predict_client(random_client_data)
-            print("\nClient data:")
-            print(random_client_data)
-            print("Prediction (Adult):", prediction)
-            assigned = True
-        
-        if assigned:
-            break
 
         time.sleep(1)
+        
 
 path2 = klient.bfs2(klientx_target, klienty_target)
 print("Najkrótsza ścieżka:", path2)
@@ -165,6 +172,7 @@ watek = threading.Thread(target=watekDlaSciezkiAgenta)
 watek.daemon = True
 watek.start()
 
+
 running = True
 while running:
     for event in pygame.event.get():

classes/Jimmy_Neuron/predict_image.py

@@ -0,0 +1,36 @@
+import torch
+from torchvision.transforms import Compose, Lambda
+import torchvision.io as io
+
+device = torch.device('cuda') if torch.cuda.is_available() else torch.device('cpu')
+
+hidden_size = 135 * 64
+model = torch.nn.Sequential(
+    torch.nn.Conv2d(3, 6, 5),
+    torch.nn.MaxPool2d(2, 2),
+    torch.nn.Conv2d(6, 16, 5),
+    torch.nn.Flatten(),
+    torch.nn.Linear(53824, hidden_size),
+    torch.nn.ReLU(),
+    torch.nn.Linear(hidden_size, 32 * 32),
+    torch.nn.ReLU(),
+    torch.nn.Linear(32 * 32, 10),
+    torch.nn.LogSoftmax(dim=-1)
+).to(device)
+
+model.load_state_dict(torch.load('model.pt', map_location=device))
+model.eval()
+
+def predict_image(image_path):
+    transform = Compose([Lambda(lambda x: x.float())])
+    image = io.read_image(image_path, mode=io.ImageReadMode.UNCHANGED)
+    image = transform(image)
+    image = image.unsqueeze(0)
+    image = image.to(device)
+    with torch.no_grad():
+        output = model(image)
+        predicted_class = output.argmax(dim=1).item()
+    print(predicted_class)
+
+    return predicted_class
+

classes/agent.py

@@ -275,6 +275,8 @@ class Agent:
         dx = abs(current[0] - target[0])
         dy = abs(current[1] - target[1])
         return dx + dy
+    
+
 
     
     

classes/data/data_initializer.py

@@ -85,8 +85,8 @@ for person in root.findall('person'):
     outfit_element = person.find('Outfit')
     outfit = outfit_element.text if outfit_element is not None else ''
         
-    glasses_element = person.find('Glasses')
-    glasses = glasses_element.text if glasses_element is not None else ''
+    image_element = person.find('Image')
+    image = image_element.text if image_element is not None else ''
         
     tattoo_element = person.find('Tattoo')
     tattoo = tattoo_element.text if tattoo_element is not None else ''
@@ -107,10 +107,10 @@ for person in root.findall('person'):
         'lysienie': balding,
         'broda': beard,
         'ubior': outfit,
-        'okulary': glasses,
         'tatuaz': tattoo,
         'wlosy': hair,
-        'zachowanie': behaviour
+        'zachowanie': behaviour,
+        'zdjecie': image
     }
 
     clients.append(KlientCechy(**person_data))

classes/data/klient.py

@@ -14,7 +14,7 @@ class Klient:
         self.current_cell = cells[x][y]
         self.current_x = x
         self.current_y = y
-        przyStoliku = False
+        self.przyStoliku = False
         self.cells = cells
         self.X = x
         self.Y = y
@@ -183,7 +183,7 @@ class Klient:
     
 
 class KlientCechy:
-    def __init__(self,imie,nazwisko,wiek,ulubiony_posilek,restrykcje_dietowe,zmarszczki, lysienie, broda, ubior, okulary, tatuaz, wlosy, zachowanie):
+    def __init__(self,imie,nazwisko,wiek,ulubiony_posilek,restrykcje_dietowe,zmarszczki, lysienie, broda, ubior, tatuaz, wlosy, zachowanie, zdjecie):
         self.imie = imie
         self.nazwisko = nazwisko
         self.wiek = wiek
@@ -193,7 +193,7 @@ class KlientCechy:
         self.lysienie = lysienie
         self.broda = broda
         self.ubior = ubior
-        self.okulary = okulary
+        self.zdjecie = zdjecie
         self.tatuaz = tatuaz
         self.wlosy = wlosy
         self.zachowanie = zachowanie
@@ -210,4 +210,4 @@ class KlientCechy:
             print("Klient ma juz przypisany stolik.")
 
     def __str__(self):
-        return f"Klient: {self.imie} {self.nazwisko} {self.wiek}, ulubione Danie: {self.ulubiony_posilek}, restrykcje diet: {self.restrykcje_dietowe}. Jego cechy to: zmarszczki: {self.zmarszczki}, lysienie: {self.lysienie}, broda: {self.broda}, ubior: {self.ubior}, okulary: {self.okulary}, tatuaz: {self.tatuaz}, wlosy: {self.wlosy}, zachowanie: {self.zachowanie}"
+        return f"Klient: {self.imie} {self.nazwisko} {self.wiek}, ulubione Danie: {self.ulubiony_posilek}, restrykcje diet: {self.restrykcje_dietowe}. Jego cechy to: zmarszczki: {self.zmarszczki}, lysienie: {self.lysienie}, broda: {self.broda}, ubior: {self.ubior}, tatuaz: {self.tatuaz}, wlosy: {self.wlosy}, zachowanie: {self.zachowanie}"

database/clients.xml

@@ -6,13 +6,14 @@
     <favoriteMeal>Tatar</favoriteMeal>
     <restrictions>Meat</restrictions>
     <Wrinkles>No</Wrinkles>
-    <Balding>Yes</Balding>
-    <Beard>Yes</Beard>
+    <Balding>No</Balding>
+    <Beard>No</Beard>
     <Outfit>Messy</Outfit>
-    <Glasses>No</Glasses>
+    <Glasses>Yes</Glasses>
     <Tattoo>No</Tattoo>
-    <Hair>Color</Hair>
+    <Hair>Natural</Hair>
     <Behaviour>Energetic</Behaviour>
+    <Image>database\\clientsimg\\DavidBowie.png</Image>
   </person>
   <person>
     <name>Kamil</name>
@@ -23,11 +24,12 @@
     <Wrinkles>No</Wrinkles>
     <Balding>No</Balding>
     <Beard>No</Beard>
-    <Outfit>Messy</Outfit>
+    <Outfit>Casual</Outfit>
     <Glasses>No</Glasses>
     <Tattoo>No</Tattoo>
-    <Hair>Color</Hair>
+    <Hair>Natural</Hair>
     <Behaviour>Energetic</Behaviour>
+    <Image>database\\clientsimg\\DavidBowie.png</Image>
   </person>
   <person>
     <name>Jon</name>
@@ -36,14 +38,15 @@
     <favoriteMeal>Grochówka</favoriteMeal>
     <restrictions>Vegan</restrictions>
     <Wrinkles>No</Wrinkles>
-    <Balding>No</Balding>
-    <Beard>No</Beard>
+    <Balding>Yes</Balding>
+    <Beard>Yes</Beard>
     <Outfit>Messy</Outfit>
     <Glasses>No</Glasses>
-    <Tattoo>No</Tattoo>
+    <Tattoo>Yes</Tattoo>
     <Hair>Color</Hair>
-    <Behaviour>Energetic</Behaviour>
-  </person>
+    <Behaviour>Stressed</Behaviour>
+    <Image>database\\clientsimg\\DavidBowie.png</Image>
+</person>
   <person>
     <name>Andrzej</name>
     <surname>Kowalski</surname>
@@ -52,11 +55,12 @@
     <restrictions>Meat</restrictions>
     <Wrinkles>No</Wrinkles>
     <Balding>No</Balding>
-    <Beard>No</Beard>
-    <Outfit>Messy</Outfit>
-    <Glasses>No</Glasses>
+    <Beard>Yes</Beard>
+    <Outfit>Formal</Outfit>
+    <Glasses>Yes</Glasses>
     <Tattoo>No</Tattoo>
-    <Hair>Color</Hair>
-    <Behaviour>Energetic</Behaviour>
+    <Hair>Grey</Hair>
+    <Behaviour>Calm</Behaviour>
+    <Image>database\\clientsimg\\AndrzejKowalski.png</Image>
   </person>
 </people>

decisiontree.py

@@ -64,13 +64,13 @@ dot_data = tree.export_graphviz(clf_en, out_file=None,
     "Behaviour": random.choice(['Energetic', 'Stressed', 'Calm'])
 } """
 
-def predict_client(client_data):
+def predict_client(client_data,glasses):
     new_client = {
     "Wrinkles": client_data.zmarszczki,
     "Balding": client_data.lysienie,
     "Beard": client_data.broda,
     "Outfit": client_data.ubior,
-    "Glasses": client_data.okulary,
+    "Glasses": 'Yes' if glasses == 1 else 'No',
     "Tattoo": client_data.tatuaz,
     "Hair": client_data.wlosy,
     "Behaviour": client_data.zachowanie