AI_PROJECT/Image.py

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