merge genetic algorithm with main

This commit is contained in:
Wojciech Kubicki 2024-06-09 17:10:52 +02:00
commit 7c1814630a
4 changed files with 128 additions and 43 deletions

3
src/import torch.py Normal file
View File

@ -0,0 +1,3 @@
import torch
x = torch.rand(5, 3)
print(x)

View File

@ -1,8 +1,7 @@
import sys
import pygame import pygame
from field import Field from field import Field
import os import os
from config import TILE_SIZE, TICK_RATE from config import TILE_SIZE, TICK_RATE, FINAL_X, FINAL_Y
if __name__ == "__main__": if __name__ == "__main__":
pygame.init() pygame.init()
@ -14,10 +13,19 @@ if __name__ == "__main__":
field = Field() field = Field()
running = True running = True
while running: while running:
for event in pygame.event.get(): for event in pygame.event.get():
if event.type == pygame.QUIT: if event.type == pygame.QUIT:
running = False running = False
if event.type == pygame.MOUSEBUTTONDOWN:
x, y = pygame.mouse.get_pos()
print(f"Mouse clicked at: ({x}, {y})")
grid_x = x // TILE_SIZE
grid_y = y // TILE_SIZE
field.tractor.set_new_goal((grid_x, grid_y))
field.tractor.update() field.tractor.update()
screen.fill(WHITE) screen.fill(WHITE)

View File

@ -4,6 +4,10 @@ from kb import tractor_kb
import pytholog as pl import pytholog as pl
import random import random
from config import TILE_SIZE, FREE_TILES from config import TILE_SIZE, FREE_TILES
import torch
import torchvision.transforms as transforms
from PIL import Image
class Tile(pygame.sprite.Sprite): class Tile(pygame.sprite.Sprite):
@ -15,6 +19,7 @@ class Tile(pygame.sprite.Sprite):
self.field = field self.field = field
self.set_type(tile_type) self.set_type(tile_type)
print('tile type set as', tile_type)
if self.type == 'water': if self.type == 'water':
self.stage = 'no_plant' self.stage = 'no_plant'
self.water_level = 100 self.water_level = 100
@ -23,6 +28,28 @@ class Tile(pygame.sprite.Sprite):
self.water_level = random.randint(1, 5) * 10 self.water_level = random.randint(1, 5) * 10
else: else:
self.stage = 'planted' self.stage = 'planted'
self.stage = 'planted' # wczesniej to była self.faza = 'posadzono' ale stwierdzilem ze lepiej po angielsku???
classes = [
"bób", "brokuł", "brukselka", "burak", "cebula",
"cukinia", "dynia", "fasola", "groch", "jarmuż",
"kalafior", "kalarepa", "kapusta", "marchew",
"ogórek", "papryka", "pietruszka", "pomidor",
"por", "rzepa", "rzodkiewka", "sałata", "seler",
"szpinak", "ziemniak"]
model = torch.load("veggies_recognition/best_model.pth")
mean = [0.5322, 0.5120, 0.3696]
std = [0.2487, 0.2436, 0.2531]
image_transforms = transforms.Compose([
transforms.Resize((224, 224)),
transforms.ToTensor(),
transforms.Normalize(torch.Tensor(mean),torch.Tensor(std))
])
self.prediction = self.predict(model, image_transforms, self.image_path, classes)
self.rect = self.image.get_rect() self.rect = self.image.get_rect()
self.rect.topleft = (x * TILE_SIZE, y * TILE_SIZE) self.rect.topleft = (x * TILE_SIZE, y * TILE_SIZE)
@ -31,6 +58,15 @@ class Tile(pygame.sprite.Sprite):
def draw(self, surface): def draw(self, surface):
self.tiles.draw(surface) self.tiles.draw(surface)
def get_random_image_from_folder(self):
folder_path = f"veggies_recognition/veggies/testing/{self.type}"
files = [f for f in os.listdir(folder_path) if os.path.isfile(os.path.join(folder_path, f))]
random_file = random.choice(files)
image_path = folder_path + "/" + random_file
return image_path
def set_type(self, type): def set_type(self, type):
self.type = type self.type = type
if self.type == 'grass': if self.type == 'grass':
@ -38,9 +74,30 @@ class Tile(pygame.sprite.Sprite):
elif self.type == 'water': elif self.type == 'water':
image_path = "images/water.png" image_path = "images/water.png"
else: else:
image_path = f"images/vegetables/{self.type}.png" #image_path = f"images/vegetables/{self.type}.png"
image_path = self.get_random_image_from_folder()
if not os.path.exists(image_path): if not os.path.exists(image_path):
image_path = "images/question.jpg" image_path = "images/question.jpg"
self.image_path = image_path
self.image = pygame.image.load(image_path).convert() self.image = pygame.image.load(image_path).convert()
self.image = pygame.transform.scale(self.image, (TILE_SIZE, TILE_SIZE)) self.image = pygame.transform.scale(self.image, (TILE_SIZE, TILE_SIZE))
def predict(self, model, image_transforms, image_path, classes):
model = model.eval()
image = Image.open(image_path)
image = image.convert("RGB")
image = image_transforms(image).float()
image = image.unsqueeze(0)
output = model(image)
_, predicted = torch.max(output.data, 1)
result = classes[predicted.item()]
if result == "ziemniak":
result = 'marchew'
return result

View File

@ -18,30 +18,33 @@ class Tractor(pygame.sprite.Sprite):
def __init__(self, field): def __init__(self, field):
super().__init__ super().__init__
self.field = field self.field = field
self.water = 50
self.image = pygame.image.load('images/tractor/east.png').convert_alpha() self.image = pygame.image.load('images/tractor/east.png').convert_alpha()
self.image = pygame.transform.scale(self.image, (TILE_SIZE, TILE_SIZE)) self.image = pygame.transform.scale(self.image, (TILE_SIZE, TILE_SIZE))
self.rect = self.image.get_rect() self.rect = self.image.get_rect()
self.direction = 'east'
self.direction = STARTING_DIRECTION self.start = (0, 0)
# TODO: enable tractor to start on other tile than (0,0) self.final = (0, 0)
self.start = (START_X, START_Y)
self.final = (FINAL_X, FINAL_Y)
print('destination @', self.final[0], self.final[1]) print('destination @', self.final[0], self.final[1])
self.rect.topleft = (self.start[0] * TILE_SIZE, self.start[1] * TILE_SIZE) self.rect.topleft = (self.start[0] * TILE_SIZE, self.start[1] * TILE_SIZE)
self.water = 50 self.rect.topleft = (self.start[0] * TILE_SIZE, self.start[1] * TILE_SIZE)
self.actions = []
# A-STAR self.action_index = 0
# came_from, total_cost = self.a_star()
# path = self.reconstruct_path(came_from)
# self.actions = self.recreate_actions(path)
# self.action_index = 0
# DECISION TREE: # DECISION TREE:
self.label_encoders = {} self.label_encoders = {}
self.load_decision_tree_model() self.load_decision_tree_model()
def set_new_goal(self, goal):
self.start = self.get_coordinates()
self.final = goal
came_from, total_cost = self.a_star()
path = self.reconstruct_path(came_from)
self.actions = self.recreate_actions(path)
self.action_index = 0
print(f"New goal set to: {self.final}")
def load_decision_tree_model(self): def load_decision_tree_model(self):
data = pd.read_csv('tree.csv') data = pd.read_csv('tree.csv')
@ -67,7 +70,9 @@ class Tractor(pygame.sprite.Sprite):
neighbors.append('grass') neighbors.append('grass')
input_data = { input_data = {
'tile_type': self.get_current_tile().type, #tutaj będzie dostawał informację ze zdjęcia
'tile_type': self.get_current_tile().prediction,
#'tile_type': self.get_current_tile().type,
'water_level': self.get_current_tile().water_level, 'water_level': self.get_current_tile().water_level,
"plant_stage": self.get_current_tile().stage, "plant_stage": self.get_current_tile().stage,
"neighbor_N": neighbors[0], "neighbor_N": neighbors[0],
@ -92,13 +97,11 @@ class Tractor(pygame.sprite.Sprite):
def draw(self, surface): def draw(self, surface):
surface.blit(self.image, self.rect) surface.blit(self.image, self.rect)
def get_coordinates(self): def get_coordinates(self):
x = self.rect.x // TILE_SIZE x = self.rect.x // TILE_SIZE
y = self.rect.y // TILE_SIZE y = self.rect.y // TILE_SIZE
return (x,y) return (x,y)
def move(self): def move(self):
if self.direction == "north" and self.rect.y > 0: if self.direction == "north" and self.rect.y > 0:
self.rect.y -= TILE_SIZE self.rect.y -= TILE_SIZE
@ -161,27 +164,15 @@ class Tractor(pygame.sprite.Sprite):
else: else:
self.move() self.move()
def update(self): def decision_tree(self):
# A STAR:
# if self.action_index == len(self.actions):
# return
# action = self.actions[self.action_index]
# match (action):
# case ('move'):
# self.move()
# case ('left'):
# self.rotate('left')
# case ('right'):
# self.rotate('right')
# DECISION TREE:
action = self.make_decision() action = self.make_decision()
if (self.get_current_tile().type != 'grass' or self.get_current_tile().type == 'water'): action = 'move' if (self.get_current_tile().type != 'grass' or self.get_current_tile().type == 'water'): action = 'nothing'
self.prev_action = action self.prev_action = action
print("Decyzja podjęta przez drzewo decyzyjne: ", action)
match (action): match (action):
case ('move'): case ('nothing'):
pass pass
#self.move_rotating() #self.move_rotating()
case ('harvest'): case ('harvest'):
@ -238,10 +229,37 @@ class Tractor(pygame.sprite.Sprite):
self.get_current_tile().set_type('szpinak') self.get_current_tile().set_type('szpinak')
case ('plant(ziemniak)'): case ('plant(ziemniak)'):
self.get_current_tile().set_type('ziemniak') self.get_current_tile().set_type('ziemniak')
self.move_2()
#self.action_index += 1 def update(self):
print(action) # A STAR:
if self.action_index == len(self.actions):
return return
action = self.actions[self.action_index]
match (action):
case ('move'):
self.move()
case ('left'):
self.rotate('left')
case ('right'):
self.rotate('right')
self.action_index += 1
if self.get_current_tile().type == "grass":
print("Co jest faktycznie: trawa")
elif self.get_current_tile().type == "water":
print("Co jest faktycznie: woda")
else:
print("Rozpoznano: ", self.get_current_tile().prediction)
print("Co jest faktycznie: ", self.get_current_tile().type)
print("\n")
if self.get_coordinates() == self.final:
self.decision_tree()
return
def log_info(self): def log_info(self):
# print on what tile type the tractor is on # print on what tile type the tractor is on
@ -355,13 +373,12 @@ class Tractor(pygame.sprite.Sprite):
if current == self.final: if current == self.final:
break break
# next_node: tuple[int, int]
for next_node in self.neighboring_nodes(coordinates=current): for next_node in self.neighboring_nodes(coordinates=current):
enter_cost = self.cost_of_entering_node(coordinates=next_node) enter_cost = self.cost_of_entering_node(coordinates=next_node)
new_cost: int = cost_so_far[current] + enter_cost new_cost = cost_so_far[current] + enter_cost
if next_node not in cost_so_far or new_cost < cost_so_far[next_node]: if next_node not in cost_so_far or new_cost < cost_so_far[next_node]:
cost_so_far[next_node] = new_cost cost_so_far[next_node] = new_cost
priority = new_cost + self.manhattan_cost(current) priority = new_cost + self.manhattan_cost(next_node)
heapq.heappush(fringe, (priority, next_node)) heapq.heappush(fringe, (priority, next_node))
came_from[next_node] = current came_from[next_node] = current