merge genetic algorithm with main
This commit is contained in:
Wojciech Kubicki
commit
7c1814630a
3
src/import torch.py
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3
src/import torch.py
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@ -0,0 +1,3 @@
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import torch
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x = torch.rand(5, 3)
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print(x)
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12
src/main.py
12
src/main.py
@ -1,8 +1,7 @@
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import sys
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import pygame
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from field import Field
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import os
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from config import TILE_SIZE, TICK_RATE
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from config import TILE_SIZE, TICK_RATE, FINAL_X, FINAL_Y
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if __name__ == "__main__":
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pygame.init()
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@ -14,10 +13,19 @@ if __name__ == "__main__":
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field = Field()
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running = True
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while running:
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for event in pygame.event.get():
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if event.type == pygame.QUIT:
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running = False
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if event.type == pygame.MOUSEBUTTONDOWN:
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x, y = pygame.mouse.get_pos()
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print(f"Mouse clicked at: ({x}, {y})")
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grid_x = x // TILE_SIZE
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grid_y = y // TILE_SIZE
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field.tractor.set_new_goal((grid_x, grid_y))
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field.tractor.update()
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screen.fill(WHITE)
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59
src/tile.py
59
src/tile.py
@ -4,6 +4,10 @@ from kb import tractor_kb
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import pytholog as pl
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import random
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from config import TILE_SIZE, FREE_TILES
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import torch
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import torchvision.transforms as transforms
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from PIL import Image
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class Tile(pygame.sprite.Sprite):
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@ -15,6 +19,7 @@ class Tile(pygame.sprite.Sprite):
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self.field = field
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self.set_type(tile_type)
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print('tile type set as', tile_type)
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if self.type == 'water':
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self.stage = 'no_plant'
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self.water_level = 100
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@ -23,13 +28,44 @@ class Tile(pygame.sprite.Sprite):
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self.water_level = random.randint(1, 5) * 10
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else:
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self.stage = 'planted'
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self.stage = 'planted' # wczesniej to była self.faza = 'posadzono' ale stwierdzilem ze lepiej po angielsku???
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classes = [
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"bób", "brokuł", "brukselka", "burak", "cebula",
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"cukinia", "dynia", "fasola", "groch", "jarmuż",
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"kalafior", "kalarepa", "kapusta", "marchew",
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"ogórek", "papryka", "pietruszka", "pomidor",
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"por", "rzepa", "rzodkiewka", "sałata", "seler",
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"szpinak", "ziemniak"]
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model = torch.load("veggies_recognition/best_model.pth")
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mean = [0.5322, 0.5120, 0.3696]
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std = [0.2487, 0.2436, 0.2531]
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image_transforms = transforms.Compose([
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transforms.Resize((224, 224)),
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transforms.ToTensor(),
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transforms.Normalize(torch.Tensor(mean),torch.Tensor(std))
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])
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self.prediction = self.predict(model, image_transforms, self.image_path, classes)
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self.rect = self.image.get_rect()
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self.rect.topleft = (x * TILE_SIZE, y * TILE_SIZE)
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def draw(self, surface):
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self.tiles.draw(surface)
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def get_random_image_from_folder(self):
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folder_path = f"veggies_recognition/veggies/testing/{self.type}"
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files = [f for f in os.listdir(folder_path) if os.path.isfile(os.path.join(folder_path, f))]
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random_file = random.choice(files)
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image_path = folder_path + "/" + random_file
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return image_path
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def set_type(self, type):
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self.type = type
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@ -38,9 +74,30 @@ class Tile(pygame.sprite.Sprite):
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elif self.type == 'water':
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image_path = "images/water.png"
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else:
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image_path = f"images/vegetables/{self.type}.png"
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#image_path = f"images/vegetables/{self.type}.png"
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image_path = self.get_random_image_from_folder()
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if not os.path.exists(image_path):
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image_path = "images/question.jpg"
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self.image_path = image_path
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self.image = pygame.image.load(image_path).convert()
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self.image = pygame.transform.scale(self.image, (TILE_SIZE, TILE_SIZE))
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def predict(self, model, image_transforms, image_path, classes):
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model = model.eval()
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image = Image.open(image_path)
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image = image.convert("RGB")
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image = image_transforms(image).float()
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image = image.unsqueeze(0)
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output = model(image)
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_, predicted = torch.max(output.data, 1)
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result = classes[predicted.item()]
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if result == "ziemniak":
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result = 'marchew'
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return result
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@ -18,30 +18,33 @@ class Tractor(pygame.sprite.Sprite):
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def __init__(self, field):
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super().__init__
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self.field = field
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self.water = 50
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self.image = pygame.image.load('images/tractor/east.png').convert_alpha()
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self.image = pygame.transform.scale(self.image, (TILE_SIZE, TILE_SIZE))
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self.rect = self.image.get_rect()
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self.direction = STARTING_DIRECTION
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# TODO: enable tractor to start on other tile than (0,0)
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self.start = (START_X, START_Y)
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self.final = (FINAL_X, FINAL_Y)
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self.direction = 'east'
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self.start = (0, 0)
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self.final = (0, 0)
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print('destination @', self.final[0], self.final[1])
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self.rect.topleft = (self.start[0] * TILE_SIZE, self.start[1] * TILE_SIZE)
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self.water = 50
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# A-STAR
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# came_from, total_cost = self.a_star()
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# path = self.reconstruct_path(came_from)
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# self.actions = self.recreate_actions(path)
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# self.action_index = 0
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self.rect.topleft = (self.start[0] * TILE_SIZE, self.start[1] * TILE_SIZE)
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self.actions = []
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self.action_index = 0
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# DECISION TREE:
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self.label_encoders = {}
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self.load_decision_tree_model()
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def set_new_goal(self, goal):
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self.start = self.get_coordinates()
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self.final = goal
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came_from, total_cost = self.a_star()
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path = self.reconstruct_path(came_from)
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self.actions = self.recreate_actions(path)
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self.action_index = 0
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print(f"New goal set to: {self.final}")
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def load_decision_tree_model(self):
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data = pd.read_csv('tree.csv')
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@ -67,7 +70,9 @@ class Tractor(pygame.sprite.Sprite):
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neighbors.append('grass')
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input_data = {
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'tile_type': self.get_current_tile().type,
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#tutaj będzie dostawał informację ze zdjęcia
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'tile_type': self.get_current_tile().prediction,
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#'tile_type': self.get_current_tile().type,
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'water_level': self.get_current_tile().water_level,
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"plant_stage": self.get_current_tile().stage,
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"neighbor_N": neighbors[0],
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@ -92,13 +97,11 @@ class Tractor(pygame.sprite.Sprite):
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def draw(self, surface):
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surface.blit(self.image, self.rect)
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def get_coordinates(self):
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x = self.rect.x // TILE_SIZE
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y = self.rect.y // TILE_SIZE
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return (x,y)
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def move(self):
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if self.direction == "north" and self.rect.y > 0:
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self.rect.y -= TILE_SIZE
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@ -160,28 +163,16 @@ class Tractor(pygame.sprite.Sprite):
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self.move()
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else:
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self.move()
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def update(self):
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# A STAR:
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# if self.action_index == len(self.actions):
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# return
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# action = self.actions[self.action_index]
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# match (action):
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# case ('move'):
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# self.move()
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# case ('left'):
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# self.rotate('left')
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# case ('right'):
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# self.rotate('right')
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# DECISION TREE:
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def decision_tree(self):
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action = self.make_decision()
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if (self.get_current_tile().type != 'grass' or self.get_current_tile().type == 'water'): action = 'move'
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if (self.get_current_tile().type != 'grass' or self.get_current_tile().type == 'water'): action = 'nothing'
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self.prev_action = action
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print("Decyzja podjęta przez drzewo decyzyjne: ", action)
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match (action):
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case ('move'):
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case ('nothing'):
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pass
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#self.move_rotating()
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case ('harvest'):
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@ -238,10 +229,37 @@ class Tractor(pygame.sprite.Sprite):
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self.get_current_tile().set_type('szpinak')
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case ('plant(ziemniak)'):
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self.get_current_tile().set_type('ziemniak')
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self.move_2()
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#self.action_index += 1
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print(action)
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def update(self):
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# A STAR:
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if self.action_index == len(self.actions):
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return
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action = self.actions[self.action_index]
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match (action):
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case ('move'):
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self.move()
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case ('left'):
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self.rotate('left')
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case ('right'):
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self.rotate('right')
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self.action_index += 1
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if self.get_current_tile().type == "grass":
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print("Co jest faktycznie: trawa")
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elif self.get_current_tile().type == "water":
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print("Co jest faktycznie: woda")
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else:
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print("Rozpoznano: ", self.get_current_tile().prediction)
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print("Co jest faktycznie: ", self.get_current_tile().type)
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print("\n")
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if self.get_coordinates() == self.final:
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self.decision_tree()
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return
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def log_info(self):
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# print on what tile type the tractor is on
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@ -355,13 +373,12 @@ class Tractor(pygame.sprite.Sprite):
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if current == self.final:
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break
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# next_node: tuple[int, int]
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for next_node in self.neighboring_nodes(coordinates=current):
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enter_cost = self.cost_of_entering_node(coordinates=next_node)
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new_cost: int = cost_so_far[current] + enter_cost
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new_cost = cost_so_far[current] + enter_cost
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if next_node not in cost_so_far or new_cost < cost_so_far[next_node]:
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cost_so_far[next_node] = new_cost
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priority = new_cost + self.manhattan_cost(current)
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priority = new_cost + self.manhattan_cost(next_node)
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heapq.heappush(fringe, (priority, next_node))
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came_from[next_node] = current
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