.idea/Traktor AI.iml

@@ -4,7 +4,7 @@
     <content url="file://$MODULE_DIR$">
       <excludeFolder url="file://$MODULE_DIR$/venv" />
     </content>
-    <orderEntry type="jdk" jdkName="Python 3.10 (Traktor)" jdkType="Python SDK" />
+    <orderEntry type="inheritedJdk" />
     <orderEntry type="sourceFolder" forTests="false" />
   </component>
 </module>

.idea/misc.xml

@@ -0,0 +1,4 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.9" project-jdk-type="Python SDK" />
+</project>

source/NN/neural_network.py

@@ -7,6 +7,7 @@ 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')
 
@@ -84,16 +85,22 @@ 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/field.py

@@ -6,6 +6,9 @@ from area.constants import WIDTH,FIELD_WIDTH,TILE_SIZE,GREY,ROWS,COLS
 from tile import Tile
 from ground import Dirt
 
+from genetic import genetic_algorithm
+import os
+
 tiles = []
 
 fieldX = (WIDTH-FIELD_WIDTH)/2
@@ -20,7 +23,7 @@ def positionFieldElements():
         t.y += fieldY
 
 
-def createTiles():
+''' def createTiles():
     for y in range(0, COLS):
         for x in range(0, ROWS):
             tile = Tile(x*TILE_SIZE, y*TILE_SIZE)
@@ -30,8 +33,47 @@ def createTiles():
             tile.randomizeContent()
             tiles.append(tile)
     positionFieldElements()
+    return tiles '''
+
+def createTiles():
+    best = genetic_algorithm(50, 20, 0.7, 10)
+
+    for y in range(COLS):
+        for x in range (ROWS):
+            tile = Tile(x * TILE_SIZE, y * TILE_SIZE)
+            dirt = Dirt(random.randint(1, 100), random.randint(1, 100))
+            dirt.pests_and_weeds()
+
+            crop = best[y][x]
+            if crop == 'apple':
+                tile.image = "resources/images/sampling.png"
+                photo_path = random.choice(os.listdir("resources/images/plant_photos/apples"))
+                tile.photo = os.path.join("resources/images/plant_photos/apples", photo_path)
+            elif crop == 'cauliflower':
+                tile.image = "resources/images/sampling.png"
+                photo_path = random.choice(os.listdir("resources/images/plant_photos/cauliflowers"))
+                tile.photo = os.path.join("resources/images/plant_photos/cauliflowers", photo_path)
+            elif crop == 'radish':
+                tile.image = "resources/images/sampling.png"
+                photo_path = random.choice(os.listdir("resources/images/plant_photos/radishes"))
+                tile.photo = os.path.join("resources/images/plant_photos/radishes", photo_path)
+            elif crop == 'wheat':
+                tile.image = "resources/images/sampling.png"
+                photo_path = random.choice(os.listdir("resources/images/plant_photos/wheats"))
+                tile.photo = os.path.join("resources/images/plant_photos/wheats", photo_path)
+            elif crop == 'rock_dirt':
+                tile.image = "resources/images/rock_dirt.png"
+                dirt.set_ocstacle(True)
+            else:
+                tile.image = "resources/images/dirt.png"
+                tile.ground = "resources/images/background.jpg"
+
+            tile.ground = dirt
+            tiles.append(tile)
+    positionFieldElements()
     return tiles
 
+
 def createField(win):
     createTiles()
     for t in tiles:

source/area/tractor.py

@@ -1,5 +1,6 @@
+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
+from area.constants import TILE_SIZE, DIRECTION_EAST, DIRECTION_SOUTH, DIRECTION_WEST, DIRECTION_NORTH, WIDTH
 from area.field import fieldX, fieldY, tiles
 import pygame
 import time
@@ -38,16 +39,19 @@ class Tractor:
             self.image = pygame.image.load('resources/images/tractor_left.png').convert_alpha()
         
 
-    def work_on_field(self, tile, ground, plant1):
+    def work_on_field(self, screen, 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
@@ -61,6 +65,7 @@ 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
@@ -71,13 +76,21 @@ 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))
+        
 
 
 
@@ -135,27 +148,58 @@ class Tractor:
 
 
     def draw_tractor(self, win):
-
         imageTractor = pygame.transform.scale(self.image, (TILE_SIZE, TILE_SIZE))
         win.blit(imageTractor, (self.rect.x, self.rect.y))
         pygame.display.flip()
         
+     
+    def store_tile_image(self, tile):
+        return pygame.image.load(tile.image).convert_alpha()
+
+    def restore_tile_image(self, screen, tile):
+        image = pygame.image.load(tile.image).convert_alpha()
+        image = pygame.transform.scale(image, (TILE_SIZE, TILE_SIZE))
+        screen.blit(image, (tile.x, tile.y))
+        pygame.display.update()
+
+
+
 #translates move_list generated by bfs into the actual movement:
 def do_actions(tractor, WIN, move_list):
-    trail = pygame.image.load("resources/images/background.jpg").convert_alpha()
-    trail = pygame.transform.scale(trail, (TILE_SIZE, TILE_SIZE))
+    # trail = pygame.image.load("resources/images/background.jpg").convert_alpha()
+    # trail = pygame.transform.scale(trail, (TILE_SIZE, TILE_SIZE))
+    tile_images = {}
+    for tile in tiles:
+        tile_images[(tile.x, tile.y)] = tractor.store_tile_image(tile)
     
     pygame.display.update()
     for move in move_list:
-        WIN.blit(trail, (tractor.rect.x, tractor.rect.y, TILE_SIZE, TILE_SIZE))
+        # WIN.blit(trail, (tractor.rect.x, tractor.rect.y, TILE_SIZE, TILE_SIZE))
+        current_tile = None
+        for tile in tiles:
+            if tile.x == tractor.rect.x and tile.y == tractor.rect.y:
+                current_tile = tile
+                break
+        if current_tile:
+            tractor.restore_tile_image(WIN, current_tile)
+
         if move == "move":
             tractor.move()            
         elif move == "rotate_right":
             tractor.rotate_to_right()
         elif move == "rotate_left":
             tractor.rotate_to_left()
+
         tractor.draw_tractor(WIN)
         pygame.display.update()
-        time.sleep(1)
+        time.sleep(0.35)
+
+
+#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/astar.py

@@ -79,6 +79,8 @@ def goal_test(elem, goalstate):
 def tile_cost(tile):
     if tile.image == "resources/images/sampling.png":
         return 100
+    if tile.image == "resources/images/rock_dirt.png":
+        return 500
     else:
         return 1
 
@@ -89,7 +91,7 @@ def heuristic(current_x, current_y, end_x, end_y):
 # actions(string): move, rotate_to_left, rotate_to_right
 
 # main search function:
-def a_star(istate, succ, goaltest, tractor):
+def a_star(istate, succ_astar, goaltest):
     fringe = []
     explored = set()
     node = Node(0, istate.get_x(), istate.get_y(), istate.get_direction(), None, None, 0)
@@ -107,7 +109,7 @@ def a_star(istate, succ, goaltest, tractor):
 
         explored.add(elem)
 
-        for (action, state) in succ(temp, tractor):
+        for (action, state) in succ_astar(temp):
             fringe_tuple = []
             explored_tuple = []
 

source/bfs.py

@@ -159,6 +159,42 @@ def succ(elem, tractor):
     return actions_states
  
  
+ #its the copy of successor function for A* only - tractor can ride through stones if there is no other way:
+def succ_astar(elem):
+    actions_states = []
+    temp = copy.copy(elem.get_direction())
+    
+    if temp == 1:
+        temp = 4
+    else:
+        temp -= 1
+    actions_states.append(("rotate_left", (elem.get_x(), elem.get_y(), temp)))
+
+    temp = copy.copy(elem.get_direction())   
+    if temp == 4:
+        temp = 1
+    else:
+        temp += 1
+    actions_states.append(("rotate_right", (elem.get_x(), elem.get_y(), temp)))
+   
+    temp_move_east = elem.get_x() + TILE_SIZE
+    temp_move_west = elem.get_x() - TILE_SIZE
+    temp_move_north = elem.get_y() - TILE_SIZE
+    temp_move_south = elem.get_y() + TILE_SIZE
+
+    if Tractor.can_it_move_node(elem) == "move east":
+         actions_states.append(("move", (temp_move_east, elem.get_y(), elem.get_direction())))
+
+    elif Tractor.can_it_move_node(elem) == "move west":
+         actions_states.append(("move", (temp_move_west, elem.get_y(), elem.get_direction())))
+
+    elif Tractor.can_it_move_node(elem) == "move north":
+         actions_states.append(("move", (elem.get_x(), temp_move_north, elem.get_direction())))
+
+    elif Tractor.can_it_move_node(elem) == "move south":
+         actions_states.append(("move", (elem.get_x(), temp_move_south, elem.get_direction())))
+
+    return actions_states
 
 #returns list of actions      
 def get_moves(elem):

source/genetic.py

@@ -0,0 +1,98 @@
+import random
+
+def make_population(population_s, field_s):
+    population = []
+    crops = ['apple', 'cauliflower', 'radish', 'wheat', 'rock_dirt', 'dirt']
+
+    for _ in range(population_s):
+        i = []
+        for _ in range(field_s):
+            row = random.choices(crops, k=field_s)
+            i.append(row)
+        population.append(i)
+    return population
+
+def calculate_fitness(individual):
+    cost = 0
+    for i in range(len(individual)):
+        for j in range(len(individual[i])):
+            crop = individual[i][j]
+            neighbors = [
+                individual[x][y]
+                for x in range(max(0, i-1), min(len(individual), i+2))
+                for y in range(max(0, j-1), min(len(individual), j+2))
+                if (x,y) != (i,j)
+            ]
+            for n in neighbors:
+                if crop == 'wheat' and n == 'apple':
+                    cost += 2
+                elif crop == 'cauliflower' and n == 'radish':
+                    cost += 4
+
+    fitness = 1/(1+cost)
+    return fitness
+
+def select_parents(population, fitnesses):
+    fitnesses_sum = sum(fitnesses)
+    selection_parts = [fitness / fitnesses_sum for fitness in fitnesses]
+    parents = random.choices(population, weights=selection_parts, k=2)
+    return parents
+
+def crossover(parent_1, parent_2):
+    crossover_point = random.randint(1, (len(parent_1)-1))
+    child_1 = parent_1[:crossover_point] + parent_2[crossover_point:]
+    child_2 = parent_2[:crossover_point] + parent_1[crossover_point:]
+    return child_1, child_2
+
+def mutation(individual, chance):
+    crops = ['apple', 'cauliflower', 'radish', 'wheat', 'rock_dirt', 'dirt']
+    if random.random() < chance:
+        row = random.randint(0, len(individual) - 1)
+        column = random.randint(0, len(individual[0]) - 1)
+        individual[row][column] = random.choice(crops)
+    return individual
+
+def genetic_algorithm(population_s, field_s, chance, limit):
+    population = make_population(population_s, field_s)
+
+    best_fitness = 0
+    count = 0
+
+    while best_fitness < 1:
+        fitnesses = [calculate_fitness(individual) for individual in population]
+        new_population = []
+
+        for _ in range(population_s // 2):
+            parent_1, parent_2 = select_parents(population, fitnesses)
+
+            p1c = calculate_fitness(parent_1)
+            p2c = calculate_fitness(parent_2)
+            print("p1c: ",p1c,"\np2c: ",p2c)
+
+            child_1, child_2 = crossover(parent_1, parent_2)
+            child_1 = mutation(child_1, chance)
+            child_2 = mutation(child_2, chance)
+            new_population.append(child_1)
+            new_population.append(child_2)
+
+        combined_population = population + new_population
+        combined_population = sorted(combined_population, key=calculate_fitness, reverse=True)
+
+        population = combined_population[:population_s]
+
+        current_best_fitness = calculate_fitness(population[0])
+        if current_best_fitness > best_fitness:
+            best_fitness = current_best_fitness
+            count = 0
+        else:
+            count += 1
+
+        if count >= limit:
+            break
+
+    best_child = max(population, key=calculate_fitness)
+
+    bsf = calculate_fitness(best_child)
+    print("bsf: ", bsf)
+
+    return best_child

source/ground.py

@@ -20,7 +20,10 @@ class Dirt:
         elif i == 4:
             self.weed = True
             self.pest = True
-        elif i == 5:
-            self.obstacle = True
+        '''elif i == 5:
+            self.obstacle = True'''
+
+    def set_ocstacle(self, obstacle_status):
+        self.obstacle = obstacle_status
 
 # add init, getters,setters

source/main.py

@@ -5,15 +5,18 @@ 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
+from area.tractor import Tractor, do_actions, display_work_results
 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 bfs import graphsearch, Istate, succ_astar, succ
 from astar import a_star
-from NN.neural_network import load_model, load_image, guess_image, display_image, display_result
-from PIL import  Image
+from NN.neural_network import load_model, load_image, guess_image, display_image, display_result, clear_text_area
+from PIL import Image
+from genetic import genetic_algorithm
+
+from area.field import createTiles
 
 pygame.init()
 WIN_WIDTH = WIDTH + 300
@@ -26,39 +29,13 @@ def main():
     window = drawWindow(WIN)
     pygame.display.update()
 
-#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:
-        print(f"Coordinates of tile {tile_index} are: ({tile_x}, {tile_y})")
-    else: print("Such tile does not exist")
-
-    #mark the goal tile:
-    tiles[tile_index].image = "resources/images/sampling_goal.png"
-    image = pygame.image.load(tiles[tile_index].image).convert()
-    image = pygame.transform.scale(image, (TILE_SIZE, TILE_SIZE))
-    WIN.blit(image, (tiles[tile_index].x, tiles[tile_index].y))
-    pygame.display.flip()
-
-
-#graphsearch activation:
-    istate = Istate(170, 100, 2)  #initial state
-
-    goaltest = []                 
-    goaltest.append(tile_x)       #final state (consists of x and y because direction doesnt matter)
-    goaltest.append(tile_y)
 
+#Tractor initialization:
     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)
-
+    tractor.tractor_start = ((170, 100))
+    istate = Istate(170, 100, 2)  #initial state
 
 
 #main loop:    
@@ -68,8 +45,34 @@ def main():
                 run = False       
         time.sleep(1)
 
-        # movement based on route-planning (test):
+        #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:
+            print(f"Coordinates of tile {tile_index} are: ({tile_x}, {tile_y})")
+        else: print("Such tile does not exist")
 
+        #mark the goal tile:
+        tiles[tile_index].image = "resources/images/sampling_goal.png"
+        image = pygame.image.load(tiles[tile_index].image).convert()
+        image = pygame.transform.scale(image, (TILE_SIZE, TILE_SIZE))
+        WIN.blit(image, (tiles[tile_index].x, tiles[tile_index].y))
+        pygame.display.flip()
+
+
+        tractor.tractor_end = ((tile_x, tile_y))
+        goaltest = []    #final state (consists of x and y because direction doesnt matter)   
+        goaltest.append(tile_x)
+        goaltest.append(tile_y)
+        goaltest[0] = tile_x
+        goaltest[1]=tile_y        
+       
+        #moves = (graphsearch(istate, succ, goaltest, tractor))     #<-------BFS
+        moves = (a_star(istate, succ_astar, goaltest))
+        print(moves)
+
+
+        # movement based on route-planning:
         tractor.draw_tractor(WIN)
         time.sleep(1)
         if moves != False:
@@ -85,6 +88,7 @@ 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}")
@@ -98,7 +102,8 @@ 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:
@@ -127,19 +132,71 @@ 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': [True],
-            'temp': [17],
-            'water': [d1.water_level],
-            'nutri': [d1.nutrients_level],
-            'pests': [pe],
-            'weeds': [we],
-            'ripeness': [p1.growth_level],
-            'season_autumn': [True], 'season_spring': [False], 'season_summer': [False], 'season_winter': [False],
-            'weather_heavyCloudy': [False], 'weather_partCloudy': [False], 'weather_precipitation': [False],
-            'weather_sunny': [True],
-            'type_cereal': [t1], 'type_fruit': [t2], 'type_none': [t3], 'type_vegetable': [t4]
+                'anomalies': [a1],
+                'temp': [temp_n],
+                '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],
+                'weather_heavyCloudy': [h1], 'weather_partCloudy': [h2], 'weather_precipitation': [h3],
+                'weather_sunny': [h4],
+                'type_cereal': [t1], 'type_fruit': [t2], 'type_none': [t3], 'type_vegetable': [t4]
         }
+        
         df = pd.DataFrame(dane)
         df.to_csv('model_data.csv', index=False)
 
@@ -150,8 +207,20 @@ def main():
 
         #work on field:
         if predykcje == 'work':
-            tractor.work_on_field(goalTile, d1, p1)
-        time.sleep(50)
+            tractor.work_on_field(WIN, goalTile, d1, p1)
+
+        #update the initial state for the next target:
+        istate = Istate(tile_x, tile_y, tractor.direction)
+
+        #old goalTile is displayed with a black border - to show that it was an old target:
+        tiles[tile_index].image = "resources/images/sampling_old_goal.png"
+        image = pygame.image.load(tiles[tile_index].image).convert()
+        image = pygame.transform.scale(image, (TILE_SIZE, TILE_SIZE))
+        WIN.blit(image, (tiles[tile_index].x, tiles[tile_index].y))
+        pygame.display.flip()
+        tractor.draw_tractor(WIN)
+
+        time.sleep(2)
         print("\n")
 
 

source/model_data.csv

@@ -1,2 +1,2 @@
 anomalies,temp,water,nutri,pests,weeds,ripeness,season_autumn,season_spring,season_summer,season_winter,weather_heavyCloudy,weather_partCloudy,weather_precipitation,weather_sunny,type_cereal,type_fruit,type_none,type_vegetable
-True,17,32,2,0,0,54,True,False,False,False,False,False,False,True,True,False,False,False
+True,17,72,73,0,0,60,True,False,False,False,False,False,False,True,False,True,False,False