43 lines
1.3 KiB
Python
43 lines
1.3 KiB
Python
import random
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from Global_variables import Global_variables as G_var
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from Package import Package
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from Package_types import Package_types
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from decision_tree.Decision_tree import DecisionTree
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import glob2
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from neural_network.NeuralNetwork import NeuralNetwork
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class Packages_spawner:
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def __init__(self, window,enviroment_2d):
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self.window = window
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self.enviroment_2d = enviroment_2d
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def read_photo_and_determine_marking(self): # USING NEURAL NETWORK
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image = self.get_marking_photo()
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net = NeuralNetwork()
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marking = net.use_neural_net(image)
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if marking == "fragile":
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type = Package_types.fragile
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elif marking == "priority":
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type = Package_types.priority
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return type
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def spawn_package(self):
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package_x = random.randrange(22, 26)
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package_y = random.randrange(1, 13)
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# package_type = random.choice(list(Package_types))
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package_type = self.read_photo_and_determine_marking()
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new_package = Package(self.window, package_x, package_y, package_type)
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self.enviroment_2d[package_x][package_y] = new_package
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def get_marking_photo(self):
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file_path_type = ["resources/markings/*.png"]
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images = glob2.glob(random.choice(file_path_type))
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random_image = random.choice(images)
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return random_image
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