diff --git a/tiles.py b/tiles.py
index 49ffaac..ecbca20 100644
--- a/tiles.py
+++ b/tiles.py
@@ -18,7 +18,6 @@ from keras.layers import Dense, Dropout, Activation, Flatten
 from keras.layers import Conv2D, MaxPooling2D
 import math
 
-
 pygame.init()
 
 display = pygame.display.set_mode((640, 640))
@@ -31,6 +30,7 @@ waiterImgR = pygame.image.load("waiterR.png")
 tableImg = pygame.image.load('table.png')
 chairImg = pygame.image.load('chair.png')
 clientImg = pygame.image.load('client.png')
+image = pygame.image.load('test/0.jpg')
 
 class Waiter:
     def __init__(self, loc):
@@ -62,6 +62,7 @@ class Waiter:
     def right(self):
         self.loc[0] += 32
 
+
 class Client:
     def __init__(self, loc):
         self.loc = loc
@@ -69,6 +70,7 @@ class Client:
     def render(self, surface):
         surface.blit(clientImg, (self.loc[0], self.loc[1]))
 
+
 def generate_client():
     loc_for_client = []
     for i in chairs:
@@ -78,6 +80,7 @@ def generate_client():
     client_coordinates = (loc_for_client[loc])
     return client_coordinates
 
+
 class Table:
     def __init__(self, loc, num):
         self.loc = loc
@@ -93,7 +96,8 @@ class Table:
     def get_number_of_chairs(self):
         return self.num_of_chairs
 
-def check_collision_with_table(x,y):
+
+def check_collision_with_table(x, y):
     answer = False
     for i in tables_coordinates:
         if i[0] <= x <= i[0] + 32 and i[1] <= y <= i[1] + 32:
@@ -110,6 +114,7 @@ class Chair:
     def render(self, surface):
         surface.blit(chairImg, (self.loc[0], self.loc[1]))
 
+
 def pos_of_chair(table_cor, k):
     pos = ((table_cor[0], table_cor[1] - 32),
            (table_cor[0], table_cor[1] + 32),
@@ -117,7 +122,8 @@ def pos_of_chair(table_cor, k):
            (table_cor[0] + 32, table_cor[1]))
     return pos[k]
 
-def check_collision_with_chair(x,y):
+
+def check_collision_with_chair(x, y):
     answer = False
     for i in chairs:
         for j in i:
@@ -143,6 +149,7 @@ class Food:
     def get_food(self):
         return self.name, self.price
 
+
 class Menu:
     def __init__(self, card={}):
         self.card = card
@@ -153,6 +160,7 @@ class Menu:
     def add_to_card(self, dish):
         self.card[str(len(self.card) + 1)] = dish
 
+
 class Order(Table):
     def __init__(self, status=False, table=0, dishes=[]):
         self.table = table
@@ -166,6 +174,7 @@ class Order(Table):
     def deliver(self):
         self.status = True
 
+
 class Graph:
     def __init__(self, num_of_nodes, directed=True):
         self.m_num_of_nodes = num_of_nodes
@@ -209,6 +218,7 @@ class Graph:
             path.reverse()
         return path
 
+
 def pathFromTo(start, dest):
     tab2 = [42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57]
     tab4 = [41, 58]
@@ -250,6 +260,7 @@ def pathFromTo(start, dest):
     path = graph.bfs(start, dest)
     return path
 
+
 def numToX(num):
     digits = [int(a) for a in str(num)]
     if num >= 100:
@@ -265,14 +276,17 @@ def numToX(num):
     x = x * 32
     return x
 
+
 def numToY(num):
     y = (math.floor(num / 20)) * 32
     return y
 
+
 def coordsToNum(coords):
     num = ((coords[1] // 32) * 20) + (coords[0] // 32)
     return int(num)
 
+
 def waiterGo(dest):
     print("Path: ", (pathFromTo(coordsToNum(waiter.loc), dest)))
     go = []
@@ -305,6 +319,7 @@ def waiterGo(dest):
             pygame.display.update()
             time.sleep(0.2)
 
+
 def mouseToNum():
     x = pygame.mouse.get_pos()[0]
     y = pygame.mouse.get_pos()[1]
@@ -312,6 +327,7 @@ def mouseToNum():
     squareNum = coordsToNum(cordTab)
     return squareNum
 
+
 class Map:
     def __init__(self):
         self.arr = np.zeros((20, 20))
@@ -326,6 +342,7 @@ class Map:
     def get_arr(self):
         return self.arr.transpose()
 
+
 class Tile():
     def __init__(self, parent=None, loc=None):
         self.parent = parent
@@ -337,6 +354,7 @@ class Tile():
     def __eq__(self, other):
         return self.position == other.position
 
+
 def astar(map, start, end):
     start_tile = Tile(None, start)
     start_tile.g = start_tile.h = start_tile.f = 0
@@ -379,7 +397,8 @@ def astar(map, start, end):
                     skip = True
             if skip is False:
                 child.g = current_tile.g + map[child.position[0]][child.position[1]]
-                child.h = np.absolute(child.position[0] - end_tile.position[0]) + np.absolute(child.position[1] - end_tile.position[1])
+                child.h = np.absolute(child.position[0] - end_tile.position[0]) + np.absolute(
+                    child.position[1] - end_tile.position[1])
                 child.f = child.g + child.h
                 for open_node in open_list:
                     if child == open_node and child.g > open_node.g:
@@ -388,19 +407,20 @@ def astar(map, start, end):
 
 
 def tell_preferences():
-    possibilities = [[30, 40 ,50, None],
-              [True, False, None],
-              [True, False, None],
-              ["high", "low", None],
-              ["tomato", "olives", "feta", None],
-              ["sausage", "pineapple", "mushrooms", "shrimps", "salami", None],
-              [True, False, None]]
+    possibilities = [[30, 40, 50, None],
+                     [True, False, None],
+                     [True, False, None],
+                     ["high", "low", None],
+                     ["tomato", "olives", "feta", None],
+                     ["sausage", "pineapple", "mushrooms", "shrimps", "salami", None],
+                     [True, False, None]]
     choices = []
     for i in possibilities:
         choices.append(random.choice(i))
 
     return choices
 
+
 def evaluate_preferences(preferences):
     data = []
     if preferences[0] == 30:
@@ -499,11 +519,13 @@ def choose_pizza(prefernce):
 
     return ans
 
+
 def append_df_to_excel(df, excel_path):
     df_excel = pd.read_excel(excel_path)
     result = pd.concat([df_excel, df], ignore_index=True)
     result.to_excel(excel_path, index=False)
 
+
 def append_choice(ans, pre, d, df):
     new_row = pre
     new_row.append(list(d.keys())[list(d.values()).index(int(ans))])
@@ -540,15 +562,21 @@ def append_choice(ans, pre, d, df):
     n_df = pd.DataFrame(data, index=[len(df) + 1])
     append_df_to_excel(n_df, "restaurant.xlsx")
 
+
 def get_pizza(number):
     with open("dishes.json") as f:
         data = json.load(f)
     for i in data:
         if i["pos_in_card"] == int(number):
-            food = Food(i['name'], i['pos_in_card'], i['price'], i['spiciness'], i['vege'], i['size'], i['allergens'], i['ingridients'], i['drink_in'])
+            food = Food(i['name'], i['pos_in_card'], i['price'], i['spiciness'], i['vege'], i['size'], i['allergens'],
+                        i['ingridients'], i['drink_in'])
     return food
 
-#network
+
+def display_img(surface, image):
+    surface.blit(image, (120, 120))
+
+
 def create_training_data():
     DATADIR = "Images"
     CATEGORIES = ["yes", "no"]
@@ -575,10 +603,11 @@ def create_training_data():
     y = np.array(y)
 
     print("Training data created!")
-    return X,y
+    return X, y
 
-def learn_neural_network(X,y):
-    X = X/255.0
+
+def learn_neural_network(X, y):
+    X = X / 255.0
 
     model = Sequential()
 
@@ -605,16 +634,19 @@ def learn_neural_network(X,y):
 
     return model
 
+
 def prepare_img(filepath):
     IMG_SIZE = 90
     img_array = cv2.imread(filepath, cv2.IMREAD_GRAYSCALE)
     new_array = cv2.resize(img_array, (IMG_SIZE, IMG_SIZE))
     return new_array.reshape(-1, IMG_SIZE, IMG_SIZE, 1) / 255
 
+
 def predict(model):
     return model.predict([prepare_img('directory')])
 
-def reusult(prediction):
+
+def result(prediction):
     if prediction[0][0] >= 0.5:
         print(math.ceil(prediction[0][0]))
         print('No pepperoni')
@@ -623,16 +655,30 @@ def reusult(prediction):
         print("Pepperoni")
 
 
+#####################neural network##############################
 
+DATADIR = "C:/Datasets/Ingridients"
+CATEGORIES = ["yes", "no"]
+IMG_SIZE = 90
+training_data = []
 
+create_training_data()
+X = []
+y = []
 
+for features, label in training_data:
+    X.append(features)
+    y.append(label)
+X = np.array(X).reshape(-1, IMG_SIZE, IMG_SIZE, 1)
+y = np.array(y)
+"""
+m = learn_neural_network(X, y)
+prediction = m.predict([prepare_img('p1.jpg')])
+print(prediction[0][0])
+result(prediction)
+"""
 
-
-
-
-
-
-
+#######################################################
 
 map = Map()
 waiter = Waiter([32, 32])
@@ -656,8 +702,11 @@ for table in tables:
 
 client = Client(generate_client())
 
+
 def main():
     direction = []
+    first_time = True
+    number = 0
     while True:
 
         clock.tick(10)
@@ -681,6 +730,7 @@ def main():
         for chair_list in chairs:
             for chair in chair_list:
                 chair.render(display)
+
         key = pygame.key.get_pressed()
         left, middle, right = pygame.mouse.get_pressed()
         if middle:
@@ -689,7 +739,9 @@ def main():
             while True:
                 x = pygame.mouse.get_pos()[1]
                 y = pygame.mouse.get_pos()[0]
-                if y > 608 or y < 32 or x > 608 or x < 32 or check_collision_with_table(y,x) or check_collision_with_chair(y, x):
+                if y > 608 or y < 32 or x > 608 or x < 32 or check_collision_with_table(y,
+                                                                                        x) or check_collision_with_chair(
+                        y, x):
                     print("I can't go there")
                     break
                 goal = (x // 32, y // 32)
@@ -715,16 +767,18 @@ def main():
                     break
             print()
             print("Hello Sir, tell me yours preferences")
-            print("Pass: 'budget', 'spiciness', 'vege', 'level_of_hunger', 'allergy', 'favorite_ingridient', 'drink_in'\n")
+            print(
+                "Pass: 'budget', 'spiciness', 'vege', 'level_of_hunger', 'allergy', 'favorite_ingridient', 'drink_in'\n")
             print("Here is my list of preferences")
             ingridients = tell_preferences()
             print(ingridients)
             print()
             pizza = get_pizza(choose_pizza(evaluate_preferences(ingridients)))
             print("Our proposition:")
-            print("Name = {}\nprice = {}\nspiciness = {}\nvege = {}\nsize = {}\nallergens = {}\ningridients = {}\ndrink_in = {}\n"
-                  .format(pizza.name,pizza.price, pizza.spiciness,pizza.vege,pizza.size,pizza.allergens,pizza.ingridients,pizza.drink_in))
-
+            print(
+                "Name = {}\nprice = {}\nspiciness = {}\nvege = {}\nsize = {}\nallergens = {}\ningridients = {}\ndrink_in = {}\n"
+                .format(pizza.name, pizza.price, pizza.spiciness, pizza.vege, pizza.size, pizza.allergens,
+                        pizza.ingridients, pizza.drink_in))
 
         if len(direction) > 0:
             d = direction.pop(0)
@@ -742,6 +796,16 @@ def main():
             pass
         waiter.render(display)
         client.render(display)
+
+        if waiter.loc == [576, 32]:
+            if first_time:
+                number = np.random.randint(20)
+                image = pygame.image.load('test/' + str(number) + '.jpg')
+            first_time = False
+            display_img(display, image)
+        else:
+            first_time = True
+
         pygame.display.update()