source/NN/neural_network.py

@@ -7,7 +7,6 @@ import matplotlib.pyplot as plt
 from NN.model import *
 from PIL import Image
 import pygame
-from area.constants import GREY
 
 device = torch.device('cuda') if torch.cuda.is_available() else torch.device('cpu')
 
@@ -85,22 +84,16 @@ def load_image(image_path):
     testImage = testImage.unsqueeze(0)
     return testImage
 
-#display the image for prediction next to the field
 def display_image(screen, image_path, position):
     image = pygame.image.load(image_path)
     image = pygame.transform.scale(image, (250, 250))
     screen.blit(image, position)
 
-#display result of the guessed image (text under the image)
 def display_result(screen, position, predicted_class):
     font = pygame.font.Font(None, 30)
     displayed_text = font.render("The predicted image is: "+str(predicted_class), 1, (255,255,255))
     screen.blit(displayed_text, position)
 
-def clear_text_area(win, x, y, width, height, color=GREY):
-    pygame.draw.rect(win, color, (x, y, width, height))
-    pygame.display.update()
-
 def guess_image(model, image_tensor):
     with torch.no_grad():
         testOutput = model(image_tensor)

source/area/tractor.py

@@ -1,6 +1,5 @@
-from NN.neural_network import clear_text_area
 from crop_protection_product import CropProtectionProduct
-from area.constants import TILE_SIZE, DIRECTION_EAST, DIRECTION_SOUTH, DIRECTION_WEST, DIRECTION_NORTH, WIDTH
+from area.constants import TILE_SIZE, DIRECTION_EAST, DIRECTION_SOUTH, DIRECTION_WEST, DIRECTION_NORTH
 from area.field import fieldX, fieldY, tiles
 import pygame
 import time
@@ -39,19 +38,16 @@ class Tractor:
             self.image = pygame.image.load('resources/images/tractor_left.png').convert_alpha()
         
 
-    def work_on_field(self, screen, tile, ground, plant1):
+    def work_on_field(self, tile, ground, plant1):
-        results = []
         if plant1 is None:
             tile.randomizeContent()
             # sprobuj zasadzic cos
             print("Tarctor planted something")
-            results.append("Tarctor planted something")
         elif plant1.growth_level == 100:
             tile.plant = None
             ground.nutrients_level -= 40
             ground.water_level -= 40
             print("Tractor collected something")
-            results.append("Tractor collected something")
         else:
             plant1.try_to_grow(50,50) #mozna dostosowac jeszcze
             ground.nutrients_level -= 11
@@ -65,7 +61,6 @@ class Tractor:
             elif plant1.plant_type == self.spinosad.plant_type:
                 t = "Tractor used Spinosad"
             print(t)
-            results.append(t)
             ground.pest = False
         if ground.weed:
             # traktor pozbywa się chwastow
@@ -76,21 +71,13 @@ class Tractor:
             elif plant1.plant_type == self.metazachlor.plant_type:
                 t = "Tractor used Metazachlor"
             print(t)
-            results.append(t)
             ground.weed = False
         if ground.water_level < plant1.water_requirements:
             ground.water_level += 20
             print("Tractor watered the plant")
-            results.append("Tractor watered the plant")
         if ground.nutrients_level < plant1.nutrients_requirements:
             ground.nutrients_level += 20
             print("Tractor added some nutrients")
-            results.append("Tractor added some nutrients")
-
-        clear_text_area(screen, WIDTH-90, 100, 400, 100)
-        for idx, result in enumerate(results):
-            display_work_results(screen, result, (WIDTH-90, 100 + idx * 30))
-        
 
 
 
@@ -169,13 +156,6 @@ def do_actions(tractor, WIN, move_list):
             tractor.rotate_to_left()
         tractor.draw_tractor(WIN)
         pygame.display.update()
-        time.sleep(0.5)
+        time.sleep(1)
-
-#displays results of the "work_on_field" function next to the field:
-def display_work_results(screen, text, position):
-    font = pygame.font.Font(None, 30)
-    displayed_text = font.render(text, 1, (255,255,255))
-    screen.blit(displayed_text, position)
-    pygame.display.update()
 
 

source/main.py

@@ -5,14 +5,14 @@ import pandas as pd
 import joblib
 from area.constants import WIDTH, HEIGHT, TILE_SIZE
 from area.field import drawWindow
-from area.tractor import Tractor, do_actions, display_work_results
+from area.tractor import Tractor, do_actions
 from area.field import tiles, fieldX, fieldY
 from area.field import get_tile_coordinates, get_tile_index
 from ground import Dirt
 from plant import Plant
 from bfs import graphsearch, Istate, succ
 from astar import a_star
-from NN.neural_network import load_model, load_image, guess_image, display_image, display_result, clear_text_area
+from NN.neural_network import load_model, load_image, guess_image, display_image, display_result
 from PIL import Image
 from genetic import genetic_algorithm
 
@@ -30,25 +30,7 @@ def main():
     window = drawWindow(WIN)
     pygame.display.update()
 
-
+#getting coordinates of our "goal tile":
-
-
-#Tractor initialization:
-    tractor = Tractor(0*TILE_SIZE, 0*TILE_SIZE, 2, None, None)
-    tractor.rect.x += fieldX  
-    tractor.rect.y += fieldY
-    tractor.tractor_start = ((170, 100))
-    istate = Istate(170, 100, 2)  #initial state
-
-
-#main loop:    
-    while run:
-        for event in pygame.event.get():
-            if event.type == pygame.QUIT:
-                run = False       
-        time.sleep(1)
-
-        #getting coordinates of our "goal tile":
     tile_index = get_tile_index()
     tile_x, tile_y = get_tile_coordinates(tile_index)
     if tile_x is not None and tile_y is not None:
@@ -63,20 +45,34 @@ def main():
     pygame.display.flip()
 
 
-        tractor.tractor_end = ((tile_x, tile_y))
+#graphsearch activation:
-        goaltest = []    #final state (consists of x and y because direction doesnt matter)   
+    istate = Istate(170, 100, 2)  #initial state
-        goaltest.append(tile_x)
-        goaltest.append(tile_y)
-        goaltest[0] = tile_x
-        goaltest[1]=tile_y        
 
-        #moves = (graphsearch(istate, succ, goaltest, tractor))     #<-------BFS
+    goaltest = []                 
+    goaltest.append(tile_x)       #final state (consists of x and y because direction doesnt matter)
+    goaltest.append(tile_y)
+
+    tractor = Tractor(0*TILE_SIZE, 0*TILE_SIZE, 2, None, None)
+    tractor.rect.x += fieldX  
+    tractor.rect.y += fieldY 
+    tractor.tractor_start = ((istate.get_x(), istate.get_y()))
+    #tractor.tractor_start = ((istate.get_x(), istate.get_y(), istate.get_direction))
+    tractor.tractor_end = ((goaltest[0], goaltest[1]))
+
+    #moves = (graphsearch(istate, succ, goaltest, tractor))
     moves = (a_star(istate, succ, goaltest, tractor))
     print(moves)
 
 
 
-        # movement based on route-planning:
+#main loop:    
+    while run:
+        for event in pygame.event.get():
+            if event.type == pygame.QUIT:
+                run = False       
+        time.sleep(1)
+
+        # movement based on route-planning (test):
 
         tractor.draw_tractor(WIN)
         time.sleep(1)
@@ -93,7 +89,6 @@ def main():
         image_tensor = load_image(image_path)
         prediction = guess_image(load_model(), image_tensor)
         
-        clear_text_area(WIN, WIDTH - 50, 600, 400, 50)
         display_result(WIN, (WIDTH - 50 , 600), prediction)      #display text under the photo
         pygame.display.update()
         print(f"The predicted image is: {prediction}")
@@ -107,8 +102,7 @@ def main():
         #getting the name and type of the recognized plant:
         p1.update_name(prediction)
 
-        
+        #decission tree test:
-#decission tree test:
         if d1.pest:
             pe = 1
         else:
@@ -137,71 +131,19 @@ def main():
                     t3 = True
                     t4 = False
 
-        weather_n = random.randint(1, 4)
-        if weather_n == 1:
-            h1 = True
-            h2 = False
-            h3 = False
-            h4 = False
-        else:
-            h1 = False
-            if weather_n == 2:
-                h2 = True
-                h3 = False
-                h4 = False
-            else:
-                h2 = False
-                if weather_n == 3:
-                    h3 = True
-                    h4 = False
-                else:
-                    h3 = False
-                    h4 = True   
-
-        season_n = random.randint(1,4)
-        if season_n == 1:
-            s1 = True
-            s2 = False
-            s3 = False
-            s4 = False
-            temp_n = random.randint(0,22)
-        else:
-            s1 = False
-            if season_n == 2:
-                s2 = True
-                s3 = False
-                s4 = False
-                temp_n = random.randint(0,22)
-            else:
-                s2 = False
-                if season_n == 3:
-                    s3 = True
-                    s4 = False
-                    temp_n = random.randint(20,39)
-                else:
-                    s3 = False
-                    s4 = True
-                    temp_n = random.randint(-20, 10)
-        
-        anomaly_n = random.randint(1, 10)
-        if anomaly_n == 1:
-            a1 = True
-        else:
-            a1 = False
         dane = {
-                'anomalies': [a1],
+            'anomalies': [True],
-                'temp': [temp_n],
+            'temp': [17],
             'water': [d1.water_level],
             'nutri': [d1.nutrients_level],
             'pests': [pe],
             'weeds': [we],
             'ripeness': [p1.growth_level],
-                'season_autumn': [s1], 'season_spring': [s2], 'season_summer': [s3], 'season_winter': [s4],
+            'season_autumn': [True], 'season_spring': [False], 'season_summer': [False], 'season_winter': [False],
-                'weather_heavyCloudy': [h1], 'weather_partCloudy': [h2], 'weather_precipitation': [h3],
+            'weather_heavyCloudy': [False], 'weather_partCloudy': [False], 'weather_precipitation': [False],
-                'weather_sunny': [h4],
+            'weather_sunny': [True],
             'type_cereal': [t1], 'type_fruit': [t2], 'type_none': [t3], 'type_vegetable': [t4]
         }
-        
         df = pd.DataFrame(dane)
         df.to_csv('model_data.csv', index=False)
 
@@ -212,11 +154,8 @@ def main():
 
         #work on field:
         if predykcje == 'work':
-            tractor.work_on_field(WIN, goalTile, d1, p1)
+            tractor.work_on_field(goalTile, d1, p1)
-    
+        time.sleep(50)
-        #update the initial state for the next target:
-        istate = Istate(tile_x, tile_y, tractor.direction)
-        time.sleep(2)
         print("\n")