Merge pull request 'genetic_algorithm' (#7) from genetic_algorithm into master

Reviewed-on: #7
This commit is contained in:
s481894 2024-06-10 11:47:15 +02:00
commit 912a7a5eae
48 changed files with 367 additions and 64 deletions

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@ -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>

4
.idea/misc.xml Normal file
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@ -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>

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@ -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)

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@ -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:

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@ -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()

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@ -91,7 +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)
@ -109,7 +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 = []

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@ -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):

98
source/genetic.py Normal file
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@ -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

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@ -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

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@ -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 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
@ -26,6 +29,22 @@ def main():
window = drawWindow(WIN)
pygame.display.update()
#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)
@ -41,35 +60,19 @@ def main():
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)
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
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))
#moves = (graphsearch(istate, succ, goaltest, tractor)) #<-------BFS
moves = (a_star(istate, succ_astar, goaltest))
print(moves)
#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):
# 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}")
@ -98,6 +102,7 @@ def main():
#getting the name and type of the recognized plant:
p1.update_name(prediction)
#decission tree test:
if d1.pest:
pe = 1
@ -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],
'anomalies': [a1],
'temp': [temp_n],
'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],
'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")

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@ -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

1 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
2 True 17 32 72 2 73 0 0 54 60 True False False False False False False True True False False True False False

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