105 lines
3.7 KiB
Python
105 lines
3.7 KiB
Python
import pygame
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import displayControler as dCon
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import random
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import neuralnetwork
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import os
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class Image:
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def __init__(self):
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self.plants_image_dict={}
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self.tractor_image=None
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self.garage_image=None
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self.stone_image=None
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self.gasStation_image=None
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def load_images(self):
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files_plants={
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0:"borowka",
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1:"kukurydza",
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2:"pszenica",
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3:"slonecznik",
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4:"winogrono",
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5:"ziemniak",
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6:"dirt",
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7:"mud",
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8:"road"}
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for index in files_plants:
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if index >= 6:
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plant_image = pygame.image.load("images/" + files_plants[index] + ".jpg")
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else:
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plant_image=pygame.image.load("images/plants/"+files_plants[index]+".jpg")
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plant_image=pygame.transform.scale(plant_image,(dCon.CUBE_SIZE,dCon.CUBE_SIZE))
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self.plants_image_dict[files_plants[index]]=plant_image
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tractor_image=pygame.image.load("images/traktor.png")
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tractor_image=pygame.transform.scale(tractor_image,(dCon.CUBE_SIZE,dCon.CUBE_SIZE))
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garage=pygame.image.load("images/garage.png")
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self.garage_image=pygame.transform.scale(garage,(dCon.CUBE_SIZE,dCon.CUBE_SIZE))
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stone=pygame.image.load("images/stone.png")
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self.stone_image=pygame.transform.scale(stone,(dCon.CUBE_SIZE,dCon.CUBE_SIZE))
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gasStation=pygame.image.load("images/gasStation.png")
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self.gasStation_image=pygame.transform.scale(gasStation,(dCon.CUBE_SIZE,dCon.CUBE_SIZE))
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def return_random_plant(self):
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x=random.randint(0,5) #disabled dirt and mud generation
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keys=list(self.plants_image_dict.keys())
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plant=keys[x]
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return (plant,self.plants_image_dict[plant])
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def return_plant(self,plant_name):
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return (plant_name,self.plants_image_dict[plant_name])
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def return_garage(self):
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return self.garage_image
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def return_stone(self):
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return self.stone_image
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def return_gasStation(self):
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return self.gasStation_image
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# losowanie zdjęcia z testowego datasetu bez powtórzeń
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imagePathList = []
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def getRandomImageFromDataBase():
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label = random.choice(neuralnetwork.labels)
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folderPath = f"dataset/test/{label}"
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files = os.listdir(folderPath)
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random_image = random.choice(files)
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imgPath = os.path.join(folderPath, random_image)
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while imgPath in imagePathList:
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for event in pygame.event.get():
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if event.type == pygame.QUIT:
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quit()
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label = random.choice(neuralnetwork.labels)
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folderPath = f"dataset/test/{label}"
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files = os.listdir(folderPath)
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random_image = random.choice(files)
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imgPath = os.path.join(folderPath, random_image)
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imagePathList.append(imgPath)
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image = pygame.image.load(imgPath)
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image=pygame.transform.scale(image,(dCon.CUBE_SIZE,dCon.CUBE_SIZE))
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return image, label, imgPath
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def getSpedifiedImageFromDatabase(label):
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folderPath = f"dataset/test/{label}"
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files = os.listdir(folderPath)
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random_image = random.choice(files)
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imgPath = os.path.join(folderPath, random_image)
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while imgPath in imagePathList:
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for event in pygame.event.get():
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if event.type == pygame.QUIT:
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quit()
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label = random.choice(neuralnetwork.labels)
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folderPath = f"dataset/test/{label}"
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files = os.listdir(folderPath)
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random_image = random.choice(files)
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imgPath = os.path.join(folderPath, random_image)
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imagePathList.append(imgPath)
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image = pygame.image.load(imgPath)
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image=pygame.transform.scale(image,(dCon.CUBE_SIZE,dCon.CUBE_SIZE))
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return image, label, imgPath
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