diff --git a/.gitignore b/.gitignore
index 8b29db5..0abd250 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,2 +1,5 @@
 __pycache__/
-.idea/
\ No newline at end of file
+.idea/
+tree.png
+dataset/
+dataset.zip
\ No newline at end of file
diff --git a/App.py b/App.py
index 090d36d..591e937 100644
--- a/App.py
+++ b/App.py
@@ -9,17 +9,19 @@ import Osprzet
 import Ui
 import BFS
 import AStar
-import random
+import neuralnetwork
 
 
 bfs1_flag=False
 bfs2_flag=False #Change this lines to show different bfs implementation
 bfs3_flag=False
 Astar = False
-Astar2 = True
+Astar2 = False
 if bfs3_flag or Astar or Astar2:
    Pole.stoneFlag = True
-
+TreeFlag=False
+nnFlag=True
+newModel=False
 
 pygame.init()
 show_console=True
@@ -30,7 +32,7 @@ image_loader=Image.Image()
 image_loader.load_images()
 goalTreasure = AStar.getRandomGoalTreasure() # nie wiem czy to najlepsze miejsce, obecnie pole zawiera pole gasStation, które służy do renderowania odpowiedniego zdjęcia
 pole=Pole.Pole(screen,image_loader, goalTreasure)
-pole.draw_grid() #musi byc tutaj wywołane ponieważ inicjalizuje sloty do slownika
+pole.draw_grid(nnFlag) #musi byc tutaj wywołane ponieważ inicjalizuje sloty do slownika
 ui=Ui.Ui(screen)
 #Tractor creation
 traktor_slot = pole.get_slot_from_cord((0, 0))
@@ -41,13 +43,13 @@ def init_demo(): #Demo purpose
     old_info=""
     traktor.draw_tractor()
     time.sleep(2)
-    pole.randomize_colors()
+    pole.randomize_colors(nnFlag)
     traktor.draw_tractor()
     start_flag=True
     while True:
         clock.tick(FPS)
         if(start_flag):
-            ui.render_text_to_console(string_to_print="Przejazd inicjalizujacy- traktor sprawdza poziom nawodnienia")
+            #ui.render_text_to_console(string_to_print="Przejazd inicjalizujacy- traktor sprawdza poziom nawodnienia")
             if not bfs1_flag:
                 time.sleep(2)
             else:
@@ -56,7 +58,7 @@ def init_demo(): #Demo purpose
             clock.tick(20)
             ui.clear_console()
             clock.tick(20)
-            ui.render_text_to_console("Obliczanie sciezki przy uzyciu BFS")
+            #ui.render_text_to_console("Obliczanie sciezki przy uzyciu BFS")
             for event in pygame.event.get():
                 if event.type == pygame.QUIT:
                     quit()
@@ -64,7 +66,7 @@ def init_demo(): #Demo purpose
                 bfsRoot1 = BFS.BFS1({"x": 0, "y": 0, "direction": "E", "hydradeIndex": traktor.slot_hydrate_dict}) 
                 #displayControler: NUM_X: 6, NUM_Y: 3 (klasyczne) CHANGE THIS BY HAND
                 bfsRoot1.reverse()
-                print_to_console("Traktor porusza sie obliczona sciezka BFS")
+                #print_to_console("Traktor porusza sie obliczona sciezka BFS")
                 traktor.move_by_root(bfsRoot1, pole, [traktor.irrigateSlot])
             if(bfs2_flag):
                 bfsRoot2 = [[{'x': 2, 'y': 2, 'direction': 'N', 'hydradeIndex': {(0, 0): -1, (1, 0): 1, (2, 0): 1, (3, 0): 1, (4, 0): 1, (5, 0): 1, (6, 0): 1, (7, 0): 1, (8, 0): 1, (9, 0): 1, (0, 1): 1, (1, 1): 1, (2, 1): 0, (3, 1): 1, (4, 1): 1, (5, 1): 1, (6, 1): 1, (7, 1): 1, (8, 1): 1, (9, 1): 1, (0, 2): 1, (1, 2): 1, (2, 2): 1, (3, 2): 1, (4, 2): 1, (5, 2): 1, (6, 2): 1, (7, 2): 1, (8, 2): 1, (9, 2): 1, (0, 3): 1, (1, 3): 1, (2, 3): 1, (3, 3): 1, (4, 3): 1, (5, 3): 1, (6, 3): 1, (7, 3): 1, (8, 3): 1, (9, 3): 1, (0, 4): 1, (1, 4): 1, (2, 4): 1, (3, 4): 1, (4, 4): 1, (5, 4): 1, (6, 4): 1, (7, 4): 1, (8, 4): 1, (9, 4): 1}}, 'forward'], [{'x': 2, 'y': 2, 'direction': 'E', 'hydradeIndex': {(0, 0): -1, (1, 0): 1, (2, 0): 1, (3, 0): 1, (4, 0): 1, (5, 0): 1, (6, 0): 1, (7, 0): 1, (8, 0): 1, (9, 0): 1, (0, 1): 1, (1, 1): 1, (2, 1): 0, (3, 1): 1, (4, 1): 1, (5, 1): 1, (6, 1): 1, (7, 1): 1, (8, 1): 1, (9, 1): 1, (0, 2): 1, (1, 2): 1, (2, 2): 1, (3, 2): 1, (4, 2): 1, (5, 2): 1, (6, 2): 1, (7, 2): 1, (8, 2): 1, (9, 2): 1, (0, 3): 1, (1, 3): 1, (2, 3): 1, (3, 3): 1, (4, 3): 1, (5, 3): 1, (6, 3): 1, (7, 3): 1, (8, 3): 1, (9, 3): 1, (0, 4): 1, (1, 4): 1, (2, 4): 1, (3, 4): 1, (4, 4): 1, (5, 4): 1, (6, 4): 1, (7, 4): 1, (8, 4): 1, (9, 4): 1}}, 'left'], [{'x': 1, 'y': 2, 'direction': 'E', 'hydradeIndex': {(0, 0): -1, (1, 0): 1, (2, 0): 1, (3, 0): 1, (4, 0): 1, (5, 0): 1, (6, 0): 1, (7, 0): 1, (8, 0): 1, (9, 0): 1, (0, 1): 1, (1, 1): 1, (2, 1): 0, (3, 1): 1, (4, 1): 1, (5, 1): 1, (6, 1): 1, (7, 1): 1, (8, 1): 1, (9, 1): 1, (0, 2): 1, (1, 2): 1, (2, 2): 0, (3, 2): 1, (4, 2): 1, (5, 2): 1, (6, 2): 1, (7, 2): 1, (8, 2): 1, (9, 2): 1, (0, 3): 1, (1, 3): 1, (2, 3): 1, (3, 3): 1, (4, 3): 1, (5, 3): 1, (6, 3): 1, (7, 3): 1, (8, 3): 1, (9, 3): 1, (0, 4): 1, (1, 4): 1, (2, 4): 1, (3, 4): 1, (4, 4): 1, (5, 4): 1, (6, 4): 1, (7, 4): 1, (8, 4): 1, (9, 4): 1}}, 'forward'], [{'x': 0, 'y': 2, 'direction': 'E', 'hydradeIndex': {(0, 0): -1, (1, 0): 1, (2, 0): 1, (3, 0): 1, (4, 0): 1, (5, 0): 1, (6, 0): 1, (7, 0): 1, (8, 0): 1, (9, 0): 1, (0, 1): 1, (1, 1): 1, (2, 1): 0, (3, 1): 1, (4, 1): 1, (5, 1): 1, (6, 1): 1, (7, 1): 1, (8, 1): 1, (9, 1): 1, (0, 2): 1, (1, 2): 1, (2, 2): 0, (3, 2): 1, (4, 2): 1, (5, 2): 1, (6, 2): 1, (7, 2): 1, (8, 2): 1, (9, 2): 1, (0, 3): 1, (1, 3): 1, (2, 3): 1, (3, 3): 1, (4, 3): 1, (5, 3): 1, (6, 3): 1, (7, 3): 1, (8, 3): 1, (9, 3): 1, (0, 4): 1, (1, 4): 1, (2, 4): 1, (3, 4): 1, (4, 4): 1, (5, 4): 1, (6, 4): 1, (7, 4): 1, (8, 4): 1, (9, 4): 1}}, 'forward'], [{'x': 0, 'y': 2, 'direction': 'N', 'hydradeIndex': {(0, 0): -1, (1, 0): 1, (2, 0): 1, (3, 0): 1, (4, 0): 1, (5, 0): 1, (6, 0): 1, (7, 0): 1, (8, 0): 1, (9, 0): 1, (0, 1): 1, (1, 1): 1, (2, 1): 0, (3, 1): 1, (4, 1): 1, (5, 1): 1, (6, 1): 1, (7, 1): 1, (8, 1): 1, (9, 1): 1, (0, 2): 1, (1, 2): 1, (2, 2): 0, (3, 2): 1, (4, 2): 1, (5, 2): 1, (6, 2): 1, (7, 2): 1, (8, 2): 1, (9, 2): 1, (0, 3): 1, (1, 3): 1, (2, 3): 1, (3, 3): 1, (4, 3): 1, (5, 3): 1, (6, 3): 1, (7, 3): 1, (8, 3): 1, (9, 3): 1, (0, 4): 1, (1, 4): 1, (2, 4): 1, (3, 4): 1, (4, 4): 1, (5, 4): 1, (6, 4): 1, (7, 4): 1, (8, 4): 1, (9, 4): 1}}, 'right'], [{'x': 0, 'y': 3, 'direction': 'N', 'hydradeIndex': {(0, 0): -1, (1, 0): 1, (2, 0): 1, (3, 0): 1, (4, 0): 1, (5, 0): 1, (6, 0): 1, (7, 0): 1, (8, 0): 1, (9, 0): 1, (0, 1): 1, (1, 1): 1, (2, 1): 0, (3, 1): 1, (4, 1): 1, (5, 1): 1, (6, 1): 1, (7, 1): 1, (8, 1): 1, (9, 1): 1, (0, 2): 0, (1, 2): 1, (2, 2): 0, (3, 2): 1, (4, 2): 1, (5, 2): 1, (6, 2): 1, (7, 2): 1, (8, 2): 1, (9, 2): 1, (0, 3): 1, (1, 3): 1, (2, 3): 1, (3, 3): 1, (4, 3): 1, (5, 3): 1, (6, 3): 1, (7, 3): 1, (8, 3): 1, (9, 3): 1, (0, 4): 1, (1, 4): 1, (2, 4): 1, (3, 4): 1, (4, 4): 1, (5, 4): 1, (6, 4): 1, (7, 4): 1, (8, 4): 1, (9, 4): 1}}, 'forward'], [{'x': 0, 'y': 3, 'direction': 'W', 'hydradeIndex': {(0, 0): -1, (1, 0): 1, (2, 0): 1, (3, 0): 1, (4, 0): 1, (5, 0): 1, (6, 0): 1, (7, 0): 1, (8, 0): 1, (9, 0): 1, (0, 1): 1, (1, 1): 1, (2, 1): 0, (3, 1): 1, (4, 1): 1, (5, 1): 1, (6, 1): 1, (7, 1): 1, (8, 1): 1, (9, 1): 1, (0, 2): 0, (1, 2): 1, (2, 2): 0, (3, 2): 1, (4, 2): 1, (5, 2): 1, (6, 2): 1, (7, 2): 1, (8, 2): 1, (9, 2): 1, (0, 3): 1, (1, 3): 1, (2, 3): 1, (3, 3): 1, (4, 3): 1, (5, 3): 1, (6, 3): 1, (7, 3): 1, (8, 3): 1, (9, 3): 1, (0, 4): 1, (1, 4): 1, (2, 4): 1, (3, 4): 1, (4, 4): 1, (5, 4): 1, (6, 4): 1, (7, 4): 1, (8, 4): 1, (9, 4): 1}}, 'right'], [{'x': 1, 'y': 3, 'direction': 'W', 'hydradeIndex': {(0, 0): -1, (1, 0): 1, (2, 0): 1, (3, 0): 1, (4, 0): 1, (5, 0): 1, (6, 0): 1, (7, 0): 1, (8, 0): 1, (9, 0): 1, (0, 1): 1, (1, 1): 1, (2, 1): 0, (3, 1): 1, (4, 1): 1, (5, 1): 1, (6, 1): 1, (7, 1): 1, (8, 1): 1, (9, 1): 1, (0, 2): 0, (1, 2): 1, (2, 2): 0, (3, 2): 1, (4, 2): 1, (5, 2): 1, (6, 2): 1, (7, 2): 1, (8, 2): 1, (9, 2): 1, (0, 3): 1, (1, 3): 1, (2, 3): 1, (3, 3): 1, (4, 3): 1, (5, 3): 1, (6, 3): 1, (7, 3): 1, (8, 3): 1, (9, 3): 1, (0, 4): 1, (1, 4): 1, (2, 4): 1, (3, 4): 1, (4, 4): 1, (5, 4): 1, (6, 4): 1, (7, 4): 1, (8, 4): 1, (9, 4): 1}}, 'forward'], [{'x': 2, 'y': 3, 'direction': 'W', 'hydradeIndex': {(0, 0): -1, (1, 0): 1, (2, 0): 1, (3, 0): 1, (4, 0): 1, (5, 0): 1, (6, 0): 1, (7, 0): 1, (8, 0): 1, (9, 0): 1, (0, 1): 1, (1, 1): 1, (2, 1): 0, (3, 1): 1, (4, 1): 1, (5, 1): 1, (6, 1): 1, (7, 1): 1, (8, 1): 1, (9, 1): 1, (0, 2): 0, (1, 2): 1, (2, 2): 0, (3, 2): 1, (4, 2): 1, (5, 2): 1, (6, 2): 1, (7, 2): 1, (8, 2): 1, (9, 2): 1, (0, 3): 1, (1, 3): 0, (2, 3): 1, (3, 3): 1, (4, 3): 1, (5, 3): 1, (6, 3): 1, (7, 3): 1, (8, 3): 1, (9, 3): 1, (0, 4): 1, (1, 4): 1, (2, 4): 1, (3, 4): 1, (4, 4): 1, (5, 4): 1, (6, 4): 1, (7, 4): 1, (8, 4): 1, (9, 4): 1}}, 'forward'], [{'x': 3, 'y': 3, 'direction': 'W', 'hydradeIndex': {(0, 0): -1, (1, 0): 1, (2, 0): 1, (3, 0): 1, (4, 0): 1, (5, 0): 1, (6, 0): 1, (7, 0): 1, (8, 0): 1, (9, 0): 1, (0, 1): 1, (1, 1): 1, (2, 1): 0, (3, 1): 1, (4, 1): 1, (5, 1): 1, (6, 1): 1, (7, 1): 1, (8, 1): 1, (9, 1): 1, (0, 2): 0, (1, 2): 1, (2, 2): 0, (3, 2): 1, (4, 2): 1, (5, 2): 1, (6, 2): 1, (7, 2): 1, (8, 2): 1, (9, 2): 1, (0, 3): 1, (1, 3): 0, (2, 3): 0, (3, 3): 1, (4, 3): 1, (5, 3): 1, (6, 3): 1, (7, 3): 1, (8, 3): 1, (9, 3): 1, (0, 4): 1, (1, 4): 1, (2, 4): 1, (3, 4): 1, (4, 4): 1, (5, 4): 1, (6, 4): 1, (7, 4): 1, (8, 4): 1, (9, 4): 1}}, 'forward'], [{'x': 4, 'y': 3, 'direction': 'W', 'hydradeIndex': {(0, 0): -1, (1, 0): 1, (2, 0): 1, (3, 0): 1, (4, 0): 1, (5, 0): 1, (6, 0): 1, (7, 0): 1, (8, 0): 1, (9, 0): 1, (0, 1): 1, (1, 1): 1, (2, 1): 0, (3, 1): 1, (4, 1): 1, (5, 1): 1, (6, 1): 1, (7, 1): 1, (8, 1): 1, (9, 1): 1, (0, 2): 0, (1, 2): 1, (2, 2): 0, (3, 2): 1, (4, 2): 1, (5, 2): 1, (6, 2): 1, (7, 2): 1, (8, 2): 1, (9, 2): 1, (0, 3): 1, (1, 3): 0, (2, 3): 0, (3, 3): 0, (4, 3): 1, (5, 3): 1, (6, 3): 1, (7, 3): 1, (8, 3): 1, (9, 3): 1, (0, 4): 1, (1, 4): 1, (2, 4): 1, (3, 4): 1, (4, 4): 1, (5, 4): 1, (6, 4): 1, (7, 4): 1, (8, 4): 1, (9, 4): 1}}, 'forward'], [{'x': 4, 'y': 3, 'direction': 'S', 'hydradeIndex': {(0, 0): -1, (1, 0): 1, (2, 0): 1, (3, 0): 1, (4, 0): 1, (5, 0): 1, (6, 0): 1, (7, 0): 1, (8, 0): 1, (9, 0): 1, (0, 1): 1, (1, 1): 1, (2, 1): 0, (3, 1): 1, (4, 1): 1, (5, 1): 1, (6, 1): 1, (7, 1): 1, (8, 1): 1, (9, 1): 1, (0, 2): 0, (1, 2): 1, (2, 2): 0, (3, 2): 1, (4, 2): 1, (5, 2): 1, (6, 2): 1, (7, 2): 1, (8, 2): 1, (9, 2): 1, (0, 3): 1, (1, 3): 0, (2, 3): 0, (3, 3): 0, (4, 3): 1, (5, 3): 1, (6, 3): 1, (7, 3): 1, (8, 3): 1, (9, 3): 1, (0, 4): 1, (1, 4): 1, (2, 4): 1, (3, 4): 1, (4, 4): 1, (5, 4): 1, (6, 4): 1, (7, 4): 1, (8, 4): 1, (9, 4): 1}}, 'right'], [{'x': 4, 'y': 2, 'direction': 'S', 'hydradeIndex': {(0, 0): -1, (1, 0): 1, (2, 0): 1, (3, 0): 1, (4, 0): 1, (5, 0): 1, (6, 0): 1, (7, 0): 1, (8, 0): 1, (9, 0): 1, (0, 1): 1, (1, 1): 1, (2, 1): 0, (3, 1): 1, (4, 1): 1, (5, 1): 1, (6, 1): 1, (7, 1): 1, (8, 1): 1, (9, 1): 1, (0, 2): 0, (1, 2): 1, (2, 2): 0, (3, 2): 1, (4, 2): 1, (5, 2): 1, (6, 2): 1, (7, 2): 1, (8, 2): 1, (9, 2): 1, (0, 3): 1, (1, 3): 0, (2, 3): 0, (3, 3): 0, (4, 3): 0, (5, 3): 1, (6, 3): 1, (7, 3): 1, (8, 3): 1, (9, 3): 1, (0, 4): 1, (1, 4): 1, (2, 4): 1, (3, 4): 1, (4, 4): 1, (5, 4): 1, (6, 4): 1, (7, 4): 1, (8, 4): 1, (9, 4): 1}}, 'forward'], [{'x': 4, 'y': 1, 'direction': 'S', 'hydradeIndex': {(0, 0): -1, (1, 0): 1, (2, 0): 1, (3, 0): 1, (4, 0): 1, (5, 0): 1, (6, 0): 1, (7, 0): 1, (8, 0): 1, (9, 0): 1, (0, 1): 1, (1, 1): 1, (2, 1): 0, (3, 1): 1, (4, 1): 1, (5, 1): 1, (6, 1): 1, (7, 1): 1, (8, 1): 1, (9, 1): 1, (0, 2): 0, (1, 2): 1, (2, 2): 0, (3, 2): 1, (4, 2): 0, (5, 2): 1, (6, 2): 1, (7, 2): 1, (8, 2): 1, (9, 2): 1, (0, 3): 1, (1, 3): 0, (2, 3): 0, (3, 3): 0, (4, 3): 0, (5, 3): 1, (6, 3): 1, (7, 3): 1, (8, 3): 1, (9, 3): 1, (0, 4): 1, (1, 4): 1, (2, 4): 1, (3, 4): 1, (4, 4): 1, (5, 4): 1, (6, 4): 1, (7, 4): 1, (8, 4): 1, (9, 4): 1}}, 'forward'], [{'x': 4, 'y': 0, 'direction': 'S', 'hydradeIndex': {(0, 0): -1, (1, 0): 1, (2, 0): 1, (3, 0): 1, (4, 0): 1, (5, 0): 1, (6, 0): 1, (7, 0): 1, (8, 0): 1, (9, 0): 1, (0, 1): 1, (1, 1): 1, (2, 1): 0, (3, 1): 1, (4, 1): 0, (5, 1): 1, (6, 1): 1, (7, 1): 1, (8, 1): 1, (9, 1): 1, (0, 2): 0, (1, 2): 1, (2, 2): 0, (3, 2): 1, (4, 2): 0, (5, 2): 1, (6, 2): 1, (7, 2): 1, (8, 2): 1, (9, 2): 1, (0, 3): 1, (1, 3): 0, (2, 3): 0, (3, 3): 0, (4, 3): 0, (5, 3): 1, (6, 3): 1, (7, 3): 1, (8, 3): 1, (9, 3): 1, (0, 4): 1, (1, 4): 1, (2, 4): 1, (3, 4): 1, (4, 4): 1, (5, 4): 1, (6, 4): 1, (7, 4): 1, (8, 4): 1, (9, 4): 1}}, 'forward'], [{'x': 4, 'y': 0, 'direction': 'E', 'hydradeIndex': {(0, 0): -1, (1, 0): 1, (2, 0): 1, (3, 0): 1, (4, 0): 1, (5, 0): 1, (6, 0): 1, (7, 0): 1, (8, 0): 1, (9, 0): 1, (0, 1): 1, (1, 1): 1, (2, 1): 0, (3, 1): 1, (4, 1): 0, (5, 1): 1, (6, 1): 1, (7, 1): 1, (8, 1): 1, (9, 1): 1, (0, 2): 0, (1, 2): 1, (2, 2): 0, (3, 2): 1, (4, 2): 0, (5, 2): 1, (6, 2): 1, (7, 2): 1, (8, 2): 1, (9, 2): 1, (0, 3): 1, (1, 3): 0, (2, 3): 0, (3, 3): 0, (4, 3): 0, (5, 3): 1, (6, 3): 1, (7, 3): 1, (8, 3): 1, (9, 3): 1, (0, 4): 1, (1, 4): 1, (2, 4): 1, (3, 4): 1, (4, 4): 1, (5, 4): 1, (6, 4): 1, (7, 4): 1, (8, 4): 1, (9, 4): 1}}, 'right'], [{'x': 3, 'y': 0, 'direction': 'E', 'hydradeIndex': {(0, 0): -1, (1, 0): 1, (2, 0): 1, (3, 0): 1, (4, 0): 0, (5, 0): 1, (6, 0): 1, (7, 0): 1, (8, 0): 1, (9, 0): 1, (0, 1): 1, (1, 1): 1, (2, 1): 0, (3, 1): 1, (4, 1): 0, (5, 1): 1, (6, 1): 1, (7, 1): 1, (8, 1): 1, (9, 1): 1, (0, 2): 0, (1, 2): 1, (2, 2): 0, (3, 2): 1, (4, 2): 0, (5, 2): 1, (6, 2): 1, (7, 2): 1, (8, 2): 1, (9, 2): 1, (0, 3): 1, (1, 3): 0, (2, 3): 0, (3, 3): 0, (4, 3): 0, (5, 3): 1, (6, 3): 1, (7, 3): 1, (8, 3): 1, (9, 3): 1, (0, 4): 1, (1, 4): 1, (2, 4): 1, (3, 4): 1, (4, 4): 1, (5, 4): 1, (6, 4): 1, (7, 4): 1, (8, 4): 1, (9, 4): 1}}, 'forward'], [{'x': 2, 'y': 0, 'direction': 'E', 'hydradeIndex': {(0, 0): -1, (1, 0): 1, (2, 0): 1, (3, 0): 0, (4, 0): 0, (5, 0): 1, (6, 0): 1, (7, 0): 1, (8, 0): 1, (9, 0): 1, (0, 1): 1, (1, 1): 1, (2, 1): 0, (3, 1): 1, (4, 1): 0, (5, 1): 1, (6, 1): 1, (7, 1): 1, (8, 1): 1, (9, 1): 1, (0, 2): 0, (1, 2): 1, (2, 2): 0, (3, 2): 1, (4, 2): 0, (5, 2): 1, (6, 2): 1, (7, 2): 1, (8, 2): 1, (9, 2): 1, (0, 3): 1, (1, 3): 0, (2, 3): 0, (3, 3): 0, (4, 3): 0, (5, 3): 1, (6, 3): 1, (7, 3): 1, (8, 3): 1, (9, 3): 1, (0, 4): 1, (1, 4): 1, (2, 4): 1, (3, 4): 1, (4, 4): 1, (5, 4): 1, (6, 4): 1, (7, 4): 1, (8, 4): 1, (9, 4): 1}}, 'forward'], [{'x': 1, 'y': 0, 'direction': 'E', 'hydradeIndex': {(0, 0): -1, (1, 0): 1, (2, 0): 0, (3, 0): 0, (4, 0): 0, (5, 0): 1, (6, 0): 1, (7, 0): 1, (8, 0): 1, (9, 0): 1, (0, 1): 1, (1, 1): 1, (2, 1): 0, (3, 1): 1, (4, 1): 0, (5, 1): 1, (6, 1): 1, (7, 1): 1, (8, 1): 1, (9, 1): 1, (0, 2): 0, (1, 2): 1, (2, 2): 0, (3, 2): 1, (4, 2): 0, (5, 2): 1, (6, 2): 1, (7, 2): 1, (8, 2): 1, (9, 2): 1, (0, 3): 1, (1, 3): 0, (2, 3): 0, (3, 3): 0, (4, 3): 0, (5, 3): 1, (6, 3): 1, (7, 3): 1, (8, 3): 1, (9, 3): 1, (0, 4): 1, (1, 4): 1, (2, 4): 1, (3, 4): 1, (4, 4): 1, (5, 4): 1, (6, 4): 1, (7, 4): 1, (8, 4): 1, (9, 4): 1}}, 'forward'], [{'x': 0, 'y': 0, 'direction': 'E', 'hydradeIndex': {(0, 0): -1, (1, 0): 0, (2, 0): 0, (3, 0): 0, (4, 0): 0, (5, 0): 1, (6, 0): 1, (7, 0): 1, (8, 0): 1, (9, 0): 1, (0, 1): 1, (1, 1): 1, (2, 1): 0, (3, 1): 1, (4, 1): 0, (5, 1): 1, (6, 1): 1, (7, 1): 1, (8, 1): 1, (9, 1): 1, (0, 2): 0, (1, 2): 1, (2, 2): 0, (3, 2): 1, (4, 2): 0, (5, 2): 1, (6, 2): 1, (7, 2): 1, (8, 2): 1, (9, 2): 1, (0, 3): 1, (1, 3): 0, (2, 3): 0, (3, 3): 0, (4, 3): 0, (5, 3): 1, (6, 3): 1, (7, 3): 1, (8, 3): 1, (9, 3): 1, (0, 4): 1, (1, 4): 1, (2, 4): 1, (3, 4): 1, (4, 4): 1, (5, 4): 1, (6, 4): 1, (7, 4): 1, (8, 4): 1, (9, 4): 1}}, 'forward']] 
@@ -114,7 +116,23 @@ def init_demo(): #Demo purpose
                 else:
                     print_to_console("Nie można znaleźć ścieżki A*")  # Wyświetl komunikat, jeśli nie znaleziono ścieżki
            
-
+            if(TreeFlag):
+                traktor.move_forward(pole)
+                traktor.tree_move(pole)
+            if(nnFlag):
+                global model
+                if (newModel):
+                    print_to_console("uczenie sieci neuronowej")
+                    model = neuralnetwork.trainNewModel()
+                    neuralnetwork.saveModel(model, 'model.pth')
+                    print_to_console("sieć nuronowa nauczona")
+                    print('model został wygenerowany')
+                else:
+                    model = neuralnetwork.loadModel('model.pth')
+                    print_to_console("model został załądowny")
+                testset = neuralnetwork.getDataset(False)
+                print(neuralnetwork.accuracy(model, testset))
+                traktor.snake_move_predict_plant(pole, model)
             start_flag=False
         # demo_move()
         old_info=get_info(old_info)
diff --git a/Climate.py b/Climate.py
new file mode 100644
index 0000000..aa376db
--- /dev/null
+++ b/Climate.py
@@ -0,0 +1,49 @@
+#THESE DICTIONARIES ARE USED FOR DISPLAY AND FOR DOCUMENTATION PURPOSES
+
+seasons={
+            0:"zima",
+            1:"wiosna",
+            2:"lato",
+            3:"jesien"}
+
+time={
+            0:"rano",
+            1:"poludnie",
+            2:"wieczor", 
+            3:"noc"}
+
+rain={
+    0:"brak",
+    1:"lekki deszcz",
+    2:"normalny deszcz",
+    3:"ulewa"
+}
+
+temperature={
+                0:"bardzo zimno",
+                1:"zimno",
+                2:"przecietnie",
+                3:"cieplo",
+                4:"upal",}
+
+def getNextSeason(season):
+    if(season==3):
+        return 0
+    else:
+        return season+1
+    
+def getNextTime(currentTime):
+    if(currentTime==3):
+        return 0
+    else:
+        return currentTime+1
+    
+def getAmount(type):
+    if(type=="seasons"):
+        return len(seasons)
+    if(type=="rain"):
+        return len(rain)
+    if(type=="time"):
+        return len(time)
+    if(type=="temperature"):
+        return len(temperature)
\ No newline at end of file
diff --git a/Condition.py b/Condition.py
new file mode 100644
index 0000000..52594ac
--- /dev/null
+++ b/Condition.py
@@ -0,0 +1,47 @@
+import random
+import Climate
+import Ui
+
+class Condition:
+    def __init__(self):
+        self.season=self.setRandomSeason()
+        self.currentTime=self.setRandomTime()
+        self.rain=self.setRandomRain()
+        self.temperature=self.setRandomRain()
+        self.clock=0
+
+    def setRandomSeason(self):
+        return self.randomizer(Climate.getAmount("seasons"))
+        
+    def setRandomTime(self):
+        return self.randomizer(Climate.getAmount("time"))
+    
+    def setRandomRain(self):
+        return self.randomizer(Climate.getAmount("rain"))
+
+    def setRandomTemperature(self):
+        return self.randomizer(Climate.getAmount("temperature"))
+
+    def randomizer(self,max):
+        return random.randint(0,max-1)
+    
+    def cycle(self):
+        if(self.clock==11):
+            self.currentTime=0
+            self.rain=self.setRandomRain()
+            self.temperature=self.setRandomTemperature()
+            self.season=Climate.getNextSeason(self.season)
+            self.clock=0
+            return
+        else:
+            self.currentTime=Climate.getNextTime(self.currentTime)
+            self.rain=self.setRandomRain()
+            self.temperature=self.setRandomTemperature()
+            self.clock=self.clock+1
+
+    def return_condition(self):
+        return [self.temperature,self.rain,self.season,self.currentTime]
+
+
+    def getCondition(self):
+        return ([Climate.temperature[self.temperature],Climate.rain[self.rain],Climate.seasons[self.season],Climate.time[self.currentTime]])
diff --git a/Data/dataTree.csv b/Data/dataTree.csv
new file mode 100644
index 0000000..84bc040
--- /dev/null
+++ b/Data/dataTree.csv
@@ -0,0 +1,9219 @@
+plant_water_level,growth,disease,fertility,tractor_water_level,temperature,rain,season,current_time,action
+80,20,0,90,40,2,0,1,0,0
+50,20,0,90,80,2,0,1,0,1
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diff --git a/Data/dataTree2.csv b/Data/dataTree2.csv
new file mode 100644
index 0000000..2745730
--- /dev/null
+++ b/Data/dataTree2.csv
@@ -0,0 +1,248 @@
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+14,2,0,92,9,2,1,3,0,1
+1,6,0,5,10,4,3,1,3,0
+2,7,0,4,20,4,3,2,2,0
+3,4,0,11,30,4,3,3,1,0
+4,5,0,43,5,2,3,1,2,0
+5,6,0,9,17,2,3,2,1,0
+6,2,0,98,18,4,3,3,1,0
+7,11,0,54,19,4,3,0,2,0
+8,20,0,43,22,4,3,1,1,0
+9,30,0,65,43,4,3,2,3,0
+10,60,0,87,50,1,3,3,3,0
+11,80,0,63,76,1,3,0,2,0
+12,95,0,75,32,1,3,1,1,0
+13,76,0,30,43,2,3,2,0,0
+14,2,0,92,9,2,3,3,0,0
diff --git a/Drzewo.py b/Drzewo.py
new file mode 100644
index 0000000..71b82c6
--- /dev/null
+++ b/Drzewo.py
@@ -0,0 +1,29 @@
+from sklearn import tree as skltree
+import pandas,os
+import matplotlib.pyplot as plt
+
+atributes=['plant_water_level','growth','disease','fertility','tractor_water_level','temperature','rain','season','current_time'] #Columns in CSV file has to be in the same order
+class Drzewo:
+    def __init__(self):
+        self.tree=self.treeLearn()
+
+    def treeLearn(self):
+        csvdata=pandas.read_csv('Data/dataTree.csv')
+        #csvdata = pandas.read_csv('Data/dataTree2.csv')
+        x=csvdata[atributes]
+        decision=csvdata['action']
+        self.tree=skltree.DecisionTreeClassifier()
+        self.tree=self.tree.fit(x.values,decision)
+
+    def plotTree(self):
+        plt.figure(figsize=(20,30))
+        skltree.plot_tree(self.tree,filled=True,feature_names=atributes)
+        plt.title("Drzewo decyzyjne wytrenowane na przygotowanych danych: ")
+        plt.savefig('tree.png')
+        #plt.show()
+    def makeDecision(self,values):
+        action=self.tree.predict([values]) #0- nie podlewac, 1-podlewac
+        if(action==[0]):
+            return "Nie"
+        if(action==[1]):
+            return "Tak"
\ No newline at end of file
diff --git a/Image.py b/Image.py
index 3a8557d..90fefca 100644
--- a/Image.py
+++ b/Image.py
@@ -1,6 +1,8 @@
 import pygame
 import displayControler as dCon
 import random
+import neuralnetwork
+import os
 
 class Image:
     def __init__(self):
@@ -37,7 +39,7 @@ class Image:
         self.gasStation_image=pygame.transform.scale(gasStation,(dCon.CUBE_SIZE,dCon.CUBE_SIZE))
 
     def return_random_plant(self):
-        x=random.randint(0,7)
+        x=random.randint(0,5) #disabled dirt and mud generation
         keys=list(self.plants_image_dict.keys())
         plant=keys[x]
         return (plant,self.plants_image_dict[plant])
@@ -53,3 +55,28 @@ class Image:
     
     def return_gasStation(self):
         return self.gasStation_image
+
+# losowanie zdjęcia z testowego datasetu bez powtórzeń
+imagePathList = []
+def getRandomImageFromDataBase():
+    label = random.choice(neuralnetwork.labels)
+    folderPath = f"dataset/test/{label}"
+    files = os.listdir(folderPath)
+    random_image = random.choice(files)
+    imgPath = os.path.join(folderPath, random_image)
+
+    while imgPath in imagePathList:
+        for event in pygame.event.get():
+            if event.type == pygame.QUIT:
+                quit()
+        label = random.choice(neuralnetwork.labels)
+        folderPath = f"dataset/test/{label}"
+        files = os.listdir(folderPath)
+        random_image = random.choice(files)
+        imgPath = os.path.join(folderPath, random_image)
+
+    imagePathList.append(imgPath)
+
+    image = pygame.image.load(imgPath)
+    image=pygame.transform.scale(image,(dCon.CUBE_SIZE,dCon.CUBE_SIZE))
+    return image, label, imgPath
diff --git a/Pole.py b/Pole.py
index f0e5b8b..f8e6aa3 100644
--- a/Pole.py
+++ b/Pole.py
@@ -6,6 +6,8 @@ import time
 import Ui
 import math
 import random
+import neuralnetwork
+import Image
 
 stoneList = [(3,3), (3,4), (3,5), (3,6), (4,6), (5,6), (6,6), (7,6), (8,6), (9,6), (10,6), (11,6), (12,6), (13,6), (14,6), (15,6), (16,6), (16,7), (16,8), (16,9)]
 stoneFlag = False
@@ -30,7 +32,7 @@ class Pole:
         return self.slot_dict
 
     #Draw grid and tractor (new one)
-    def draw_grid(self):
+    def draw_grid(self, nn=False):
         for x in range(0,dCon.NUM_X): #Draw all cubes in X axis
             for y in range(0,dCon.NUM_Y): #Draw all cubes in Y axis
                 new_slot=Slot.Slot(x,y,Colors.BROWN,self.screen,self.image_loader) #Creation of empty slot 
@@ -44,19 +46,22 @@ class Pole:
             for i in stoneList:
                 st=self.slot_dict[i]
                 st.set_stone_image()
-        if self.gasStation[0] != -1:
-            st=self.slot_dict[self.gasStation]
-            st.set_gasStation_image()
+            if self.gasStation[0] != -1:
+                st=self.slot_dict[self.gasStation]
+                st.set_gasStation_image()
     
-    def randomize_colors(self):
+    def randomize_colors(self, nn = False):
         pygame.display.update()
         time.sleep(3)
         #self.ui.render_text("Randomizing Crops")
         for coordinates in self.slot_dict:
-            if(coordinates==(0,0) or coordinates in stoneList or coordinates == self.gasStation):
+            if(stoneFlag):
+                if( coordinates in stoneList or coordinates == self.gasStation ):
+                    continue
+            if(coordinates==(0,0)):
                 continue
             else:
-                self.slot_dict[coordinates].set_random_plant()
+                self.slot_dict[coordinates].set_random_plant(nn)
 
     def change_color_of_slot(self,coordinates,color): #Coordinates must be tuple (x,y) (left top slot has cord (0,0) ), color has to be from defined in Colors.py or custom in RGB value (R,G,B)
         self.get_slot_from_cord(coordinates).color_change(color)
diff --git a/Roslina.py b/Roslina.py
index 103fd03..133c8bd 100644
--- a/Roslina.py
+++ b/Roslina.py
@@ -110,8 +110,14 @@ class Roslina:
     def return_stan(self):
         return self.stan
     
+    def return_stan_for_tree(self):
+        return self.stan.return_stan_for_tree()
+    
     def get_hydrate_stats(self):
         return self.stan.return_hydrate()
     
     def report_status(self):
-        return f"Nazwa rosliny: {self.nazwa} "+self.stan.report_all()
\ No newline at end of file
+        return f"Nazwa rosliny: {self.nazwa} "+self.stan.report_all()
+    
+    def return_status_tree(self):
+        return self.stan.return_stan_for_tree()
\ No newline at end of file
diff --git a/Slot.py b/Slot.py
index a29b815..69a971a 100644
--- a/Slot.py
+++ b/Slot.py
@@ -16,14 +16,20 @@ class Slot:
         self.field=pygame.Rect(self.x_axis*dCon.CUBE_SIZE,self.y_axis*dCon.CUBE_SIZE,dCon.CUBE_SIZE,dCon.CUBE_SIZE)
         self.image_loader=image_loader
         self.garage_image=None
+        self.label = None
+        self.imagePath = None
 
     def draw(self):
         pygame.draw.rect(self.screen,Colors.BROWN,self.field,0) #Draw field
         pygame.draw.rect(self.screen,Colors.BLACK,self.field,BORDER_THICKNESS) #Draw border
         pygame.display.update()
     
-    def redraw_image(self):
-        self.mark_visited()
+    def redraw_image(self, destroy = True):
+        if destroy:
+            self.mark_visited()
+        else:
+            self.screen.blit(self.plant_image, (self.x_axis * dCon.CUBE_SIZE, self.y_axis * dCon.CUBE_SIZE))
+            pygame.draw.rect(self.screen, Colors.BLACK, self.field, BORDER_THICKNESS)
 
     def mark_visited(self):
         plant,self.plant_image=self.image_loader.return_plant('road')
@@ -34,9 +40,14 @@ class Slot:
         self.plant=color
         self.draw()
 
-    def set_random_plant(self):
-        (plant_name,self.plant_image)=self.random_plant()
-        self.plant=Roslina.Roslina(plant_name)
+    def set_random_plant(self, nn=False):
+        if not nn:
+            (plant_name,self.plant_image)=self.random_plant()
+            self.plant=Roslina.Roslina(plant_name)
+        else:
+            self.plant_image, self.label, self.imagePath = self.random_plant_dataset()
+            # print(self.plant_image)
+            self.plant=Roslina.Roslina(self.label)
         self.set_image()
 
     def set_image(self):
@@ -62,6 +73,8 @@ class Slot:
 
     def random_plant(self): #Probably will not be used later only for demo purpouse
         return self.image_loader.return_random_plant()
+    def random_plant_dataset(self):
+        return Image.getRandomImageFromDataBase()
     
     def return_plant(self):
         return self.plant
@@ -82,4 +95,6 @@ class Slot:
             self.plant.stan.nawodnienie=random.randint(61,100)
         elif(index==-1):
             pass
-    
\ No newline at end of file
+    
+    def return_stan_for_tree(self):
+        return self.plant.return_stan_for_tree()
\ No newline at end of file
diff --git a/Stan.py b/Stan.py
index 59594c0..ce3e733 100644
--- a/Stan.py
+++ b/Stan.py
@@ -5,7 +5,7 @@ class Stan:
     nawodnienie = None #[int] 0-100 (0-60: trzeba podlać), spada w zaleznosci od rosliny: aktualizowane bedzie "w tle"
     zyznosc = None #[int] 0-100 (0-60: trzeba użyźnić), spada w zaleznosci od rosliny: aktualizowane bedzie "w tle"
     wzrost = None #[int] 0-100 (75-100: scinanie), wzrasta w zaleznosci od rosliny: aktualizowane bedzie "w tle"
-    choroba = None #[string] brak, grzyb, bakteria, pasożyt
+    choroba = None #[int] brak-0,choroba-1
     akcja = None #[Akcja]
     koszt = None #[int] 0-15, im więcej tym trudniej wjechać
 
@@ -24,7 +24,7 @@ class Stan:
         self.nawodnienie=random.randint(0,100)
         self.zyznosc=random.randint(0,100)
         self.wzrost=random.randint(0,100)
-        self.choroba=random.choice(["brak","grzyb","bakteria","pasozyt"])
+        self.choroba=random.randint(0,1)
 
     def checkStan(self):
         # sprawdza stan rośliny i podejmuje akcje jeśli potrzebna
@@ -47,6 +47,20 @@ class Stan:
         
     def return_hydrate(self):
         return self.nawodnienie
+    
+
+    def return_disease(self):
+        return self.choroba   
+    
+    def return_disease_as_string(self):
+        if(self.choroba==0):
+            return "Zdrowa"
+        if(self.choroba==1):
+            return "Chora"       
         
+    def return_stan_for_tree(self):
+        return [self.nawodnienie,self.wzrost,self.choroba,self.zyznosc]
+    
     def report_all(self):
-        return f"Nawodnienie: {self.nawodnienie} Zyznosc: {self.zyznosc} Wzrost: {self.wzrost} Choroba: {self.choroba} Koszt wejścia: {self.koszt}"
\ No newline at end of file
+        return f"Nawodnienie: {self.nawodnienie} Zyznosc: {self.zyznosc} Wzrost: {self.wzrost} Choroba: {self.return_disease_as_string()}"
+    
diff --git a/Tractor.py b/Tractor.py
index c9707df..b135b08 100644
--- a/Tractor.py
+++ b/Tractor.py
@@ -7,6 +7,16 @@ import displayControler as dCon
 import Slot
 import Osprzet
 import Node
+import Condition
+import Drzewo
+import neuralnetwork as nn
+
+condition=Condition.Condition()
+drzewo=Drzewo.Drzewo()
+
+format_string = "{:<25}{:<25}{:<25}{:<10}{:<10}{:<10}{:<25}{:<15}{:<20}{:<10}{:<15}"
+format_string_nn="{:<10}{:<20}{:<20}{:<15}{:<20}"
+
 
 tab = [-1, 0, 0, 0, 0, 1, 1, 1, 1, 1,
        1, 1, 1, 1, 1, 0, 1, 0, 1, 1,
@@ -39,7 +49,7 @@ class Tractor:
         self.clock=clock
         self.slot_hydrate_dict={}
         self.bfs2_flag=bfs2_flag
-
+        self.waterLevel=random.randint(0,100)
 
     def draw_tractor(self):
         self.screen.blit(self.current_tractor_image, (self.slot.x_axis * dCon.CUBE_SIZE, self.slot.y_axis * dCon.CUBE_SIZE))
@@ -57,6 +67,24 @@ class Tractor:
         self.current_tractor_image = self.tractor_images[self.direction]
         self.draw_tractor()
 
+    def tree_move(self, pole):
+        drzewo.treeLearn()
+        drzewo.plotTree()
+        self.snake_move_irrigation(pole, drzewo)
+    
+    def get_attributes(self): 
+        slot_attributes=self.slot.return_stan_for_tree()
+        climate_attributes=condition.return_condition()
+        attributes=[]
+        attributes=attributes+slot_attributes+[self.waterLevel]+climate_attributes
+        return attributes
+    
+    def get_attributes_for_print(self):
+        slot_attributes=self.slot.return_plant().return_status_tree()
+        climate_attributes=condition.getCondition()
+        slot_attributes=slot_attributes+[self.waterLevel]
+        return slot_attributes+climate_attributes
+
     def turn_right(self):
         # zmiana kierunku w prawo
         direction_map = {
@@ -69,7 +97,7 @@ class Tractor:
         self.current_tractor_image = self.tractor_images[self.direction]
         self.draw_tractor()
 
-    def move_forward(self, pole):
+    def move_forward(self, pole, destroy = True):
         next_slot_coordinates = None
         if self.direction == Tractor.DIRECTION_EAST:
             next_slot_coordinates = (self.slot.x_axis + 1, self.slot.y_axis)
@@ -85,12 +113,13 @@ class Tractor:
             self.current_tractor_image = self.tractor_images[self.direction]
 
         # sprawdzenie czy następny slot jest dobry
-        self.do_move_if_valid(pole,next_slot_coordinates)
+        self.do_move_if_valid(pole,next_slot_coordinates, destroy)
+        self.clock.tick(10)
 
-    def do_move_if_valid(self,pole, next_slot_coordinates):
+    def do_move_if_valid(self,pole, next_slot_coordinates, destroy = True):
         if next_slot_coordinates and pole.is_valid_move(next_slot_coordinates):
             next_slot = pole.get_slot_from_cord(next_slot_coordinates)
-            self.slot.redraw_image()
+            self.slot.redraw_image(destroy)
             self.slot = next_slot
             self.draw_tractor()
             return True
@@ -136,6 +165,63 @@ class Tractor:
                         self.snake_move(pole,x,y)
 
 
+    def snake_move_irrigation(self, pole, drzewo):
+        headers=['Wspolrzedne','Czy podlac','Poziom nawodnienia','Wzrost','Choroba','Zyznosc','Poziom wody w traktorze','Temperatura','Opady','Pora Roku','Aktualny czas']
+        print(format_string.format(*headers))
+        initPos = (self.slot.x_axis, self.slot.y_axis)
+        counter = 0
+        for i in range(initPos[1], dCon.NUM_Y):
+            for j in range(initPos[0], dCon.NUM_X):
+                attributes=self.get_attributes()
+                decision = drzewo.makeDecision(attributes)
+                self.pretty_print_tree([str("({:02d}, {:02d})").format(self.slot.x_axis, self.slot.y_axis),decision,*self.get_attributes_for_print()])
+                if decision == "Tak":
+                    self.slot.irrigatePlant()
+                    counter += 1
+                condition.cycle()
+                pygame.time.delay(50)
+                self.waterLevel=random.randint(0,100)
+                #condition.getCondition()
+                self.move_forward(pole, False)
+            if i % 2 == 0 and i != dCon.NUM_Y - 1:
+                self.turn_right()
+                self.move_forward(pole, False)
+                self.turn_right()
+            elif i != dCon.NUM_Y - 1:
+                self.turn_left()
+                self.move_forward(pole, False)
+                self.turn_left()
+        print("podlanych slotów: ", str(counter))
+
+    def snake_move_predict_plant(self, pole, model):
+        headers=['Coords','Real plant','Predicted plant','Result','Fertilizer']
+        print(format_string_nn.format(*headers))
+        initPos = (self.slot.x_axis, self.slot.y_axis)
+        count = 0
+        for i in range(initPos[1], dCon.NUM_Y):
+            for j in range(initPos[0], dCon.NUM_X):
+                for event in pygame.event.get():
+                    if event.type == pygame.QUIT:
+                        quit()
+                if self.slot.imagePath != None:
+                    predictedLabel = nn.predictLabel(self.slot.imagePath, model)
+
+                    #print(str("Coords: ({:02d}, {:02d})").format(self.slot.x_axis, self.slot.y_axis), "real:", self.slot.label, "predicted:", predictedLabel, "correct" if (self.slot.label == predictedLabel) else "incorrect", 'nawożę za pomocą:', nn.fertilizer[predictedLabel])
+                    print(format_string_nn.format(f"{self.slot.x_axis,self.slot.y_axis}",self.slot.label,predictedLabel,"correct" if (self.slot.label == predictedLabel) else "incorrect",nn.fertilizer[predictedLabel]))
+                    if self.slot.label != predictedLabel:
+                        self.slot.mark_visited()
+                        count += 1
+                self.move_forward(pole, False)
+            if i % 2 == 0 and i != dCon.NUM_Y - 1:
+                self.turn_right()
+                self.move_forward(pole, False)
+                self.turn_right()
+            elif i != dCon.NUM_Y - 1:
+                self.turn_left()
+                self.move_forward(pole, False)
+                self.turn_left()
+        print(f"Dobrze nawiezionych roślin: {20*12-count}, źle nawiezionych roślin: {count}")
+
     def snake_move(self,pole,x,y):
         next_slot_coordinates=(x,y)
         if(self.do_move_if_valid(pole,next_slot_coordinates)):
@@ -180,9 +266,11 @@ class Tractor:
                 print("- Typ:", akcja.typ)
         else:
             print("Brak akcji przypisanych do tego sprzętu.")
+
+    def pretty_print_tree(self,attributes):
+        print(format_string.format(*attributes))
     def irrigateSlot(self):
         try:
             self.slot.irrigatePlant()
         except:
             pass
-
diff --git a/main.py b/main.py
index b78b3f2..843c2d9 100644
--- a/main.py
+++ b/main.py
@@ -1,3 +1,3 @@
 import App
 
-App.init(demo=True)#DEMO=TRUE WILL INIT DEMO MODE WITH RANDOM COLOR GEN
\ No newline at end of file
+App.init(demo=True)#DEMO=TRUE WILL INIT DEMO MODE WITH RANDOM COLOR GEN
diff --git a/model_2_crops.pth b/model_2_crops.pth
new file mode 100644
index 0000000..6954cc1
Binary files /dev/null and b/model_2_crops.pth differ
diff --git a/model_500_hidden.pth b/model_500_hidden.pth
new file mode 100644
index 0000000..30627b5
Binary files /dev/null and b/model_500_hidden.pth differ
diff --git a/neuralnetwork.py b/neuralnetwork.py
new file mode 100644
index 0000000..568abaf
--- /dev/null
+++ b/neuralnetwork.py
@@ -0,0 +1,114 @@
+import torch
+import torch.nn as nn
+from torch.utils.data import DataLoader
+from torchvision import datasets
+from torchvision.transforms import Compose, Lambda, ToTensor
+import torchvision.transforms as transforms
+import matplotlib.pyplot as plt
+from PIL import Image
+import random
+
+imageSize = (128, 128)
+labels = ['carrot','corn', 'potato', 'tomato'] # musi być w kolejności alfabetycznej 
+fertilizer = {labels[0]: 'kompost', labels[1]: 'saletra amonowa', labels[2]: 'superfosfat', labels[3]:'obornik kurzy'}
+#labels = ['corn','tomato'] #uncomment this two lines for 2 crops only
+#fertilizer = {labels[0]: 'kompost', labels[1]: 'saletra amonowa'}
+torch.manual_seed(42)
+
+#device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+device = torch.device("cpu")
+# device = torch.device("mps") if torch.backends.mps.is_available() else torch.device('cpu')
+# print(device)
+
+def getTransformation():
+    transform=transforms.Compose([
+        transforms.ToTensor(),
+        transforms.Normalize(mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5]),
+        transforms.Resize(imageSize),
+        Lambda(lambda x: x.flatten())])
+    return transform
+
+def getDataset(train=True):
+    transform = getTransformation()
+    if (train):
+        trainset = datasets.ImageFolder(root='dataset/train', transform=transform)
+        return trainset
+    else:
+        testset = datasets.ImageFolder(root='dataset/test', transform=transform)
+        return testset
+
+
+def train(model, dataset, n_iter=100, batch_size=256):
+    optimizer = torch.optim.SGD(model.parameters(), lr=0.01)
+    criterion = nn.NLLLoss()
+    dl = DataLoader(dataset, batch_size=batch_size)
+    model.train()
+    for epoch in range(n_iter):
+        for images, targets in dl:
+            optimizer.zero_grad()
+            out = model(images.to(device))
+            loss = criterion(out, targets.to(device))
+            loss.backward()
+            optimizer.step()
+        if epoch % 10 == 0:
+            print('epoch: %3d loss: %.4f' % (epoch, loss))
+    return model
+
+def accuracy(model, dataset):
+    model.eval()
+    correct = sum([(model(images.to(device)).argmax(dim=1) == targets.to(device)).sum()
+    for images, targets in DataLoader(dataset, batch_size=256)])
+    return correct.float() / len(dataset)
+
+def getModel():
+    hidden_size = 500
+    model = nn.Sequential(
+        nn.Linear(imageSize[0] * imageSize[1] * 3, hidden_size),
+        nn.ReLU(),
+        nn.Linear(hidden_size, len(labels)),
+        nn.LogSoftmax(dim=-1)
+        ).to(device)
+    return model
+    
+def saveModel(model, path):
+    print("Saving model")
+    torch.save(model.state_dict(), path)
+
+def loadModel(path):
+    print("Loading model")
+    model = getModel()
+    model.load_state_dict(torch.load(path))
+    return model
+
+def trainNewModel(n_iter=100, batch_size=256):
+    trainset = getDataset(True)
+    model = getModel()
+    model = train(model, trainset)
+    return model
+
+def predictLabel(imagePath, model):
+    image = Image.open(imagePath).convert("RGB")
+    image = preprocess_image(image)
+    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+    model.to(device)
+    with torch.no_grad():
+        model.eval()  # Ustawienie modelu w tryb ewaluacji
+        output = model(image)
+
+    # Znalezienie indeksu klasy o największej wartości prawdopodobieństwa
+    predicted_class = torch.argmax(output).item()
+    return labels[predicted_class]
+
+    # Znalezienie indeksu klasy o największej wartości prawdopodobieństwa
+    predicted_class = torch.argmax(output).item()
+    return labels[predicted_class]
+
+
+def preprocess_image(image):
+    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+    transform = getTransformation()
+    image = transform(image).unsqueeze(0)  # Add batch dimension
+    image = image.to(device)  # Move the image tensor to the same device as the model
+    return image
+
+
diff --git a/readme.txt b/readme.txt
new file mode 100644
index 0000000..1cbea52
--- /dev/null
+++ b/readme.txt
@@ -0,0 +1,7 @@
+Required packages:
+    pygame,matplotlib,sklearn,pandas
+    How to install:
+        pip install pygame
+        pip install matplotlib
+        pip install scikit-learn
+        pip install pandas
\ No newline at end of file
diff --git a/testModels/modelCPUdataset2.pth b/testModels/modelCPUdataset2.pth
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diff --git a/testModels/modelCPUdataset2_500.pth b/testModels/modelCPUdataset2_500.pth
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index 0000000..e9aa218
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diff --git a/testModels/modelMPS.pth b/testModels/modelMPS.pth
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diff --git a/testModels/modelMPS650.pth b/testModels/modelMPS650.pth
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diff --git a/testModels/modelMPS_AL.pth b/testModels/modelMPS_AL.pth
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diff --git a/treeData.py b/treeData.py
new file mode 100644
index 0000000..11b3b7c
--- /dev/null
+++ b/treeData.py
@@ -0,0 +1,87 @@
+tab = []
+def iter(odp, i):
+    if i == 0:
+        j = ""
+        for k in range(0, 101, 28):
+            odp += f"{k},"
+            odp = iter(odp, i + 1)
+            j = str(k)
+            odp = odp[:-(len(j) + 1)]
+        return odp
+    if i == 1:
+        j = ""
+        for k in range(0, 101, 28):
+            odp += f"{k},"
+            odp = iter(odp, i + 1)
+            j = str(k)
+            odp = odp[:-(len(j) + 1)]
+        return odp
+    if i == 2:
+        j = ""
+        for k in range(2):
+            odp += f"{k},"
+            odp = iter(odp, i + 1)
+            j = str(k)
+            odp = odp[:-(len(j) + 1)]
+        return odp
+    if i == 3:
+        j = ""
+        for k in range(0, 101, 34):
+            odp += f"{k},"
+            odp = iter(odp, i + 1)
+            j = str(k)
+            odp = odp[:-(len(j) + 1)]
+        return odp
+    if i == 4:
+        j = ""
+        for k in range(0, 101, 40):
+            odp += f"{k},"
+            odp = iter(odp, i + 1)
+            j = str(k)
+            odp = odp[:-(len(j) + 1)]
+        return odp
+    if i == 5:
+        j = ""
+        for k in range(0, 4, 2):
+            odp += f"{k},"
+            odp = iter(odp, i + 1)
+            j = str(k)
+            odp = odp[:-(len(j) + 1)]
+        return odp
+    if i == 6:
+        j = ""
+        for k in range(0, 4, 2):
+            odp += f"{k},"
+            odp = iter(odp, i + 1)
+            j = str(k)
+            odp = odp[:-(len(j) + 1)]
+        return odp
+    if i == 7:
+        j = ""
+        for k in range(0, 4, 2):
+            odp += f"{k},"
+            odp = iter(odp, i + 1)
+            j = str(k)
+            odp = odp[:-(len(j) + 1)]
+        return odp
+    if i == 8:
+        j=""
+        for k in range(4):
+            odp += f"{k},"
+            odp = iter(odp, i + 1)
+            j = str(k)
+            odp = odp[:-(len(j) + 1)]
+        return odp
+    if i == 9:
+        global licznik
+        x = odp.split(",")
+        if (int(x[0]) > 60 or int(x[1]) > 90 or int(x[2]) == 1 or int(x[3]) > 70 or int(x[4]) <= 10 or int(x[5]) == 0 or int(x[5]) == 4 or int(x[6]) == 2 or int(x[6]) == 3 or int(x[7]) == 0 or int(x[8]) == 1):
+            odp += "0"
+        else:
+            odp += "1"
+        print(odp)
+        tab.append(odp)
+        licznik += 1
+        return odp[:-1]
+
+iter("", 0)