diff --git a/Restaurant/Sara/.idea/Sara.iml b/Restaurant/Sara/.idea/Sara.iml
new file mode 100644
index 0000000..f3d7bc9
--- /dev/null
+++ b/Restaurant/Sara/.idea/Sara.iml
@@ -0,0 +1,11 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$" />
+    <orderEntry type="jdk" jdkName="Python 3.7" jdkType="Python SDK" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+  <component name="TestRunnerService">
+    <option name="PROJECT_TEST_RUNNER" value="Unittests" />
+  </component>
+</module>
\ No newline at end of file
diff --git a/Restaurant/Sara/.idea/encodings.xml b/Restaurant/Sara/.idea/encodings.xml
new file mode 100644
index 0000000..15a15b2
--- /dev/null
+++ b/Restaurant/Sara/.idea/encodings.xml
@@ -0,0 +1,4 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="Encoding" addBOMForNewFiles="with NO BOM" />
+</project>
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diff --git a/Restaurant/Sara/.idea/misc.xml b/Restaurant/Sara/.idea/misc.xml
new file mode 100644
index 0000000..8fda991
--- /dev/null
+++ b/Restaurant/Sara/.idea/misc.xml
@@ -0,0 +1,7 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.7" project-jdk-type="Python SDK" />
+  <component name="PyPackaging">
+    <option name="earlyReleasesAsUpgrades" value="true" />
+  </component>
+</project>
\ No newline at end of file
diff --git a/Restaurant/Sara/.idea/modules.xml b/Restaurant/Sara/.idea/modules.xml
new file mode 100644
index 0000000..f756353
--- /dev/null
+++ b/Restaurant/Sara/.idea/modules.xml
@@ -0,0 +1,8 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/Sara.iml" filepath="$PROJECT_DIR$/.idea/Sara.iml" />
+    </modules>
+  </component>
+</project>
\ No newline at end of file
diff --git a/Restaurant/Sara/.idea/workspace.xml b/Restaurant/Sara/.idea/workspace.xml
new file mode 100644
index 0000000..f0b95c1
--- /dev/null
+++ b/Restaurant/Sara/.idea/workspace.xml
@@ -0,0 +1,180 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ChangeListManager">
+    <list default="true" id="725cf93d-c638-4614-9513-b7852343e088" name="Default Changelist" comment="" />
+    <option name="EXCLUDED_CONVERTED_TO_IGNORED" value="true" />
+    <option name="SHOW_DIALOG" value="false" />
+    <option name="HIGHLIGHT_CONFLICTS" value="true" />
+    <option name="HIGHLIGHT_NON_ACTIVE_CHANGELIST" value="false" />
+    <option name="LAST_RESOLUTION" value="IGNORE" />
+  </component>
+  <component name="FileEditorManager">
+    <leaf SIDE_TABS_SIZE_LIMIT_KEY="300">
+      <file pinned="false" current-in-tab="true">
+        <entry file="file://$PROJECT_DIR$/image_classification.py">
+          <provider selected="true" editor-type-id="text-editor">
+            <state relative-caret-position="305">
+              <caret line="78" column="13" selection-start-line="78" selection-start-column="13" selection-end-line="78" selection-end-column="13" />
+              <folding>
+                <element signature="e#0#94#0" expanded="true" />
+              </folding>
+            </state>
+          </provider>
+        </entry>
+      </file>
+    </leaf>
+  </component>
+  <component name="IdeDocumentHistory">
+    <option name="CHANGED_PATHS">
+      <list>
+        <option value="$USER_HOME$/AppData/Local/Programs/Python/Python37/Lib/site-packages/keras/backend/tensorflow_backend.py" />
+        <option value="$PROJECT_DIR$/image_classification.py" />
+      </list>
+    </option>
+  </component>
+  <component name="ProjectFrameBounds" extendedState="7">
+    <option name="x" value="-8" />
+    <option name="y" value="-8" />
+    <option name="width" value="694" />
+    <option name="height" value="735" />
+  </component>
+  <component name="ProjectView">
+    <navigator proportions="" version="1">
+      <foldersAlwaysOnTop value="true" />
+    </navigator>
+    <panes>
+      <pane id="ProjectPane">
+        <subPane>
+          <expand>
+            <path>
+              <item name="Sara" type="b2602c69:ProjectViewProjectNode" />
+              <item name="Sara" type="462c0819:PsiDirectoryNode" />
+            </path>
+          </expand>
+          <select />
+        </subPane>
+      </pane>
+      <pane id="Scope" />
+    </panes>
+  </component>
+  <component name="PropertiesComponent">
+    <property name="last_opened_file_path" value="$PROJECT_DIR$" />
+    <property name="settings.editor.selected.configurable" value="com.jetbrains.python.configuration.PyActiveSdkModuleConfigurable" />
+  </component>
+  <component name="RunDashboard">
+    <option name="ruleStates">
+      <list>
+        <RuleState>
+          <option name="name" value="ConfigurationTypeDashboardGroupingRule" />
+        </RuleState>
+        <RuleState>
+          <option name="name" value="StatusDashboardGroupingRule" />
+        </RuleState>
+      </list>
+    </option>
+  </component>
+  <component name="RunManager">
+    <configuration default="true" type="PythonConfigurationType" factoryName="Python">
+      <module name="Sara" />
+      <option name="INTERPRETER_OPTIONS" value="" />
+      <option name="PARENT_ENVS" value="true" />
+      <envs>
+        <env name="PYTHONUNBUFFERED" value="1" />
+      </envs>
+      <option name="SDK_HOME" value="C:\Users\Sara\AppData\Local\Programs\Python\Python38-32\python.exe" />
+      <option name="WORKING_DIRECTORY" value="" />
+      <option name="IS_MODULE_SDK" value="false" />
+      <option name="ADD_CONTENT_ROOTS" value="true" />
+      <option name="ADD_SOURCE_ROOTS" value="true" />
+      <option name="SCRIPT_NAME" value="" />
+      <option name="PARAMETERS" value="" />
+      <option name="SHOW_COMMAND_LINE" value="false" />
+      <option name="EMULATE_TERMINAL" value="false" />
+      <option name="MODULE_MODE" value="false" />
+      <option name="REDIRECT_INPUT" value="false" />
+      <option name="INPUT_FILE" value="" />
+      <method v="2" />
+    </configuration>
+    <configuration name="image_classification" type="PythonConfigurationType" factoryName="Python" temporary="true">
+      <module name="Sara" />
+      <option name="INTERPRETER_OPTIONS" value="" />
+      <option name="PARENT_ENVS" value="true" />
+      <envs>
+        <env name="PYTHONUNBUFFERED" value="1" />
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+      <option name="SDK_HOME" value="C:\Users\Sara\AppData\Local\Programs\Python\Python38-32\python.exe" />
+      <option name="WORKING_DIRECTORY" value="$PROJECT_DIR$" />
+      <option name="IS_MODULE_SDK" value="true" />
+      <option name="ADD_CONTENT_ROOTS" value="true" />
+      <option name="ADD_SOURCE_ROOTS" value="true" />
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+      <option name="PARAMETERS" value="" />
+      <option name="SHOW_COMMAND_LINE" value="false" />
+      <option name="EMULATE_TERMINAL" value="false" />
+      <option name="MODULE_MODE" value="false" />
+      <option name="REDIRECT_INPUT" value="false" />
+      <option name="INPUT_FILE" value="" />
+      <method v="2" />
+    </configuration>
+    <recent_temporary>
+      <list>
+        <item itemvalue="Python.image_classification" />
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+    </recent_temporary>
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+  <component name="SvnConfiguration">
+    <configuration />
+  </component>
+  <component name="TaskManager">
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+      <option name="number" value="Default" />
+      <option name="presentableId" value="Default" />
+      <updated>1588358263461</updated>
+    </task>
+    <servers />
+  </component>
+  <component name="ToolWindowManager">
+    <frame x="-8" y="-8" width="1382" height="744" extended-state="7" />
+    <editor active="true" />
+    <layout>
+      <window_info content_ui="combo" id="Project" order="0" visible="true" weight="0.102678575" />
+      <window_info id="Structure" order="1" side_tool="true" weight="0.25" />
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+      <window_info anchor="bottom" id="TODO" order="6" />
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diff --git a/Restaurant/Sara/image_classification.py b/Restaurant/Sara/image_classification.py
new file mode 100644
index 0000000..06cbaf2
--- /dev/null
+++ b/Restaurant/Sara/image_classification.py
@@ -0,0 +1,91 @@
+from keras.preprocessing.image import ImageDataGenerator, array_to_img, img_to_array, load_img
+from keras.models import Sequential
+from keras.layers import Conv2D, MaxPooling2D
+from keras.layers import Activation, Dropout, Flatten, Dense
+from keras import backend as K
+import json
+import numpy as np
+import matplotlib.pyplot as plt
+
+img_width, img_height = 256, 256
+
+train_data_dir = 'data/train'
+validation_data_dir = 'data/validation'
+nb_train_samples = 140
+nb_validation_samples = 40
+epochs = 20
+batch_size = 16
+
+if K.image_data_format() == 'channels_first':
+    input_shape = (3, img_width, img_height)
+else:
+    input_shape = (img_width, img_height, 3)
+
+model = Sequential()
+model.add(Conv2D(32, (2, 2), input_shape=input_shape))
+model.add(Activation('relu'))
+model.add(MaxPooling2D(pool_size=(2, 2)))
+
+model.add(Conv2D(32, (2, 2)))
+model.add(Activation('relu'))
+model.add(MaxPooling2D(pool_size=(2, 2)))
+
+model.add(Conv2D(64, (2, 2)))
+model.add(Activation('relu'))
+model.add(MaxPooling2D(pool_size=(2, 2)))
+
+model.add(Flatten())
+model.add(Dense(64))
+model.add(Activation('relu'))
+model.add(Dropout(0.5))
+model.add(Dense(1))
+model.add(Activation('sigmoid'))
+
+model.compile(loss='binary_crossentropy',
+              optimizer='rmsprop',
+              metrics=['accuracy'])
+
+train_datagen = ImageDataGenerator(
+        rotation_range=45,
+        width_shift_range=0.3,
+        height_shift_range=0.3,
+        rescale=1./255,
+        shear_range=0.25,
+        zoom_range=0.1,
+        horizontal_flip=True)
+
+validation_datagen = ImageDataGenerator(rescale=1. / 255)
+
+train_generator = train_datagen.flow_from_directory(
+        train_data_dir,
+        target_size=(img_width, img_height),
+        batch_size=batch_size,
+        class_mode='binary')
+
+validation_generator = validation_datagen.flow_from_directory(
+        validation_data_dir,
+        target_size=(img_width, img_height),
+        batch_size=batch_size,
+        class_mode='binary')
+
+model.fit_generator(
+        train_generator,
+        steps_per_epoch=nb_train_samples // batch_size,
+        epochs=epochs,
+        validation_data=validation_generator,
+        validation_steps=nb_validation_samples // batch_size)
+
+model.save_weights('model_food_dirty.h5')
+results = model.evaluate(train_generator)
+print(results)
+
+'''     test na pojedynczym elemencie
+test_image = load_img('data/train/dirty/dirty016.png', target_size=(img_width, img_height))
+test_image = img_to_array(test_image)
+test_image = test_image.reshape((1,) + test_image.shape)
+
+# 0 -> dirty, 1 -> food
+
+result = model.predict(test_image)
+print(result)
+'''
diff --git a/Restaurant/Sara/model_food_dirty.h5 b/Restaurant/Sara/model_food_dirty.h5
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diff --git a/Restaurant/main.py b/Restaurant/main.py
index da55217..3f7aa39 100644
--- a/Restaurant/main.py
+++ b/Restaurant/main.py
@@ -3,8 +3,14 @@ import random
 import time
 import queue
 import math
-from tkinter import messagebox
+from keras.models import load_model, Sequential, model_from_json
+from keras.preprocessing.image import img_to_array, load_img
+from keras.layers import Conv2D, MaxPooling2D
+from keras.layers import Activation, Dropout, Flatten, Dense
+from keras import backend as K
+from tkinter import messagebox, Label
 import tkinter as tk
+from PIL import Image, ImageTk
 root = tk.Tk()
 root.withdraw()     #ukrycie okna tworzonego przez tkinter
 
@@ -120,17 +126,22 @@ class Dish(object):
 
 
 class Plate(object):
-    def __init__(self, dish):
+    def __init__(self, dish, img):
         self.dishName = dish.dishName
         self.isEmpty = False
         self.preparationTime = dish.preparationTime
         self.eatingTime = dish.eatingTime
         self.price = dish.price
+        self.img = img
 
     def eat(self):
-        time.sleep(self.eatingTime)
+        #time.sleep(self.eatingTime)         psuje program - nie używajcie
         self.isEmpty = True #zjadanie dania jest oznaczeniem talerza jako pusty (metoda będzie wywoływana przez klienta)
 
+    def draw(self):
+        load = Image.open(self.img)
+        load.show()
+
 
 class Kitchen(object):
     def __init__(self, pos):
@@ -170,12 +181,12 @@ class Kitchen(object):
 
 
 class Client(object):
-    def __init__(self, age, sex, budget):
+    def __init__(self, age, sex, budget, table):
         self.age = age
         self.sex = sex
         self.myPlate = None
         self.budget = budget
-        self.myTable = 0            #domyślnie klient nie siedzi przy żadnym stole
+        self.myTable = table            #domyślnie klient nie siedzi przy żadnym stole
 
     def takePlateAndEat(self, plate):
         self.myPlate = plate
@@ -184,6 +195,11 @@ class Client(object):
     def takeASeat(self, table):
         self.myTable = table
 
+    def returnPlate(self):
+        plate = self.myPlate
+        self.myPlate = None
+        return plate
+
 
 class Table(object):
     def __init__(self, pos, capacity):
@@ -390,13 +406,13 @@ class Waiter(object):
 
                 for i in range(self.rotationNumber):
                     redrawWindow(window)
-                    time.sleep(0.5)
+                    time.sleep(0.2)
                 self.rotate = "forward"
                 self.rotationNumber = 0
 
                 self.goForward(movex, movey)
                 redrawWindow(window)
-                time.sleep(0.5)
+                time.sleep(0.2)
 
 
 def drawGrid(width, rows, surface):
@@ -411,6 +427,104 @@ def drawGrid(width, rows, surface):
         pygame.draw.line(surface, (255, 255, 255), (0, y), (width, y))
 
 
+def predictAndShowImg(plate):
+    img_width, img_height = 256, 256
+
+    plate.draw()
+    test_image = load_img(plate.img, target_size=(img_width, img_height))
+    test_image = img_to_array(test_image)
+    test_image = test_image.reshape((1,) + test_image.shape)
+
+    result = img_classify.predict(test_image)
+    print(result)
+    if (result == [1.]):
+        messagebox.showinfo("Rozpoznanie", "Talerz pełny.")
+        return 1
+    else:
+        messagebox.showinfo("Rozpoznanie", "Talerz pusty.")
+        return 0
+
+
+def checkIfEmpty(fullOrEmpty, client):
+    if fullOrEmpty == 1:
+        pass
+    elif fullOrEmpty == 0:
+        client.returnPlate()
+        bot.goByAStar((kitchen.pos[0] - 1, kitchen.pos[1]))
+
+
+def classify(a):
+    if a == 1:
+        dish_1 = Dish("obiad", 40, 20, 15)
+        dish_2 = Dish("deser", 25, 10, 10)
+        dish_3 = Dish("obiad 2", 55, 25, 28)
+
+        plate_1 = Plate(dish_1, "Sara/data/validation/food/food004.png")
+        plate_2 = Plate(dish_2, "Sara/data/validation/food/food002.png")
+        plate_3 = Plate(dish_1, "Sara/data/validation/dirty/dirty001.png")
+        plate_4 = Plate(dish_3, "Sara/data/validation/dirty/dirty009.png")
+
+        client_1 = Client(21, 'f', 45, 1)
+        client_2 = Client(44, 'm', 22, 4)
+        client_3 = Client(27, 'f', 15, 5)
+        client_4 = Client(19, 'm', 32, 8)
+
+        client_1.takePlateAndEat(plate_1)
+        client_2.takePlateAndEat(plate_2)
+        client_3.takePlateAndEat(plate_3)
+        client_4.takePlateAndEat(plate_4)
+
+        '''
+        TRASA + ROZPOZNAWANIE TALERZY
+        '''
+
+        bot.goByAStar((tables[1].pos[0] + 1, tables[1].pos[1]))
+        fullOrEmpty = predictAndShowImg(plate_1)
+        checkIfEmpty(fullOrEmpty, client_1)
+
+        bot.goByAStar((tables[4].pos[0] + 1, tables[4].pos[1]))
+        fullOrEmpty = predictAndShowImg(plate_2)
+        checkIfEmpty(fullOrEmpty, client_2)
+
+        bot.goByAStar((tables[5].pos[0] + 1, tables[5].pos[1]))
+        fullOrEmpty = predictAndShowImg(plate_3)
+        checkIfEmpty(fullOrEmpty, client_3)
+
+        bot.goByAStar((tables[8].pos[0] + 1, tables[8].pos[1]))
+        fullOrEmpty = predictAndShowImg(plate_4)
+        checkIfEmpty(fullOrEmpty, client_4)
+
+        messagebox.showinfo("Informacja końcowa", "Zakończono trasę.")
+
+        pygame.quit()
+        exit()
+    else:
+        pass
+
+
+def text_objects(text, font):
+    textSurface = font.render(text, True, black)
+    return textSurface, textSurface.get_rect()
+
+
+def button(msg, x, y, w, h, ic, ac, action=None):
+    mouse = pygame.mouse.get_pos()
+    click = pygame.mouse.get_pressed()
+
+    if x+w > mouse[0] > x and y+h > mouse[1] > y:
+        pygame.draw.rect(window, ac, (x, y, w, h))
+        if click[0] == 1 and action != None:
+            print("pressed")
+            action(1)
+    else:
+        pygame.draw.rect(window, ic, (x, y, w, h))
+
+    smallText = pygame.font.Font("freesansbold.ttf", 15)
+    textSurf, textRect = text_objects(msg, smallText)
+    textRect.center = ((x+(w/2)), (y+(h/2)))
+    window.blit(textSurf, textRect)
+
+
 def redrawWindow(surface):
     surface.fill(beige)
     bot.draw(surface)
@@ -420,10 +534,14 @@ def redrawWindow(surface):
     for i in range(len(puddles)):
         image = pygame.image.load(r'puddle.png')
         image = pygame.transform.scale(image, (sizeBetween - 1, sizeBetween - 1))
-        surface.blit(image, (puddles[i][0]* sizeBetween + 1, puddles[i][1]* sizeBetween + 1))
+        surface.blit(image, (puddles[i][0] * sizeBetween + 1, puddles[i][1] * sizeBetween + 1))
+
     drawGrid(width, rows, surface)
+    button("Rozpoznawanie talerzy", 0, width + 1, 198, 48, beige, white)
+
     pygame.display.update()
 
+
 def noWalkable(tables, kitchen):
     list = []
     for i in range(len(tables)):
@@ -431,19 +549,56 @@ def noWalkable(tables, kitchen):
     list.append(kitchen.pos)
     return list
 
+
+def makeImgClassificator(model):
+    img_width, img_height = 256, 256
+    if K.image_data_format() == 'channels_first':
+        input_shape = (3, img_width, img_height)
+    else:
+        input_shape = (img_width, img_height, 3)
+
+    model.add(Conv2D(32, (2, 2), input_shape=input_shape))
+    model.add(Activation('relu'))
+    model.add(MaxPooling2D(pool_size=(2, 2)))
+
+    model.add(Conv2D(32, (2, 2)))
+    model.add(Activation('relu'))
+    model.add(MaxPooling2D(pool_size=(2, 2)))
+
+    model.add(Conv2D(64, (2, 2)))
+    model.add(Activation('relu'))
+    model.add(MaxPooling2D(pool_size=(2, 2)))
+
+    model.add(Flatten())
+    model.add(Dense(64))
+    model.add(Activation('relu'))
+    model.add(Dropout(0.5))
+    model.add(Dense(1))
+    model.add(Activation('sigmoid'))
+
+    model.compile(loss='binary_crossentropy',
+                  optimizer='rmsprop',
+                  metrics=['accuracy'])
+
 def main():
-    global width, rows, bot, beige, white, black, sizeBetween, tables, kitchen, cantwalk, puddles, window
+    global width, rows, bot, beige, white, black, sizeBetween, tables, kitchen, cantwalk, puddles, window, clock, \
+        img_classify
     # skróty do kolorów
     beige = (255, 205, 178)
     white = (255, 255, 255)
     black = (0, 0, 0)
 
+    img_classify = Sequential()
+    makeImgClassificator(img_classify)
+    img_classify.load_weights('Sara/model_food_dirty.h5')
+
     width = 600
     rows = 15
     sizeBetween = width // rows     #wielkość pojedynczej kratki
-    window = pygame.display.set_mode((width, width))
-    bot = Waiter((255, 0, 0), (12, 8), 2)
+    window = pygame.display.set_mode((width, width + 50))
 
+    bot = Waiter((255, 0, 0), (12, 8), 2)
+    
     tables = []
     tables.append(Table((0, 3), 1))
     tables.append(Table((0, 6), 1))
@@ -458,8 +613,6 @@ def main():
     tables.append(Table((8, 9), 2))
     tables.append(Table((8, 12), 2))
 
-    flag = True
-    clock = pygame.time.Clock()
     kitchen = Kitchen((13, 1))
 
     cantwalk = noWalkable(tables, kitchen)  # lista pozycji, na ktore bot nie moze wejsc
@@ -472,13 +625,19 @@ def main():
     puddles.append((12, 10))
     puddles.append((1, 4))
 
+    flag = True
+    clock = pygame.time.Clock()
     while flag:
+        for event in pygame.event.get():
+            if event.type == pygame.QUIT:
+                pygame.quit()
+                quit()
+        button("Rozpoznawanie talerzy", 0, width + 1, 198, 48, beige, white, classify)
         redrawWindow(window)
         #bot.moveRandomly()
-        goal = (1, 3)
-        bot.goByAStar(goal)
-        time.sleep(5)
-        flag = False
+        #goal = (1, 3)
+        #bot.goByAStar(goal)
+
 
     pygame.quit()
     exit()