96 lines
3.7 KiB
Python
96 lines
3.7 KiB
Python
import pandas as pd
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from sklearn.preprocessing import OneHotEncoder
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from torch.nn import functional
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class Tool:
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def __init__(self) -> None:
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self.__ICG_Training_Root = ""
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self.__Normal_Training_Root = ""
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self.__Comprehensive_Training_Root = ""
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self.__ICG_Test_Data_Root = ""
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self.__Normal_Test_Data_Root = ""
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self.__Comprehensive_Testing_Root = ""
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self.__ICG_Validation_Data_Root = ""
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self.__Normal_Validation_Data_Root = ""
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self.__Comprehensive_Validation_Root = ""
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self.__ICG_ImageGenerator_Data_Root = ""
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self.__Normal_ImageGenerator_Data_Root = ""
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self.__Comprehensive_Generator_Root = ""
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self.Training_Zip = ""
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self.Validation_Zip = ""
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self.Testing_Zip = ""
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self.__Labels = []
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self.__OneHot_Encording = []
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pass
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def Set_Labels(self):
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self.__Labels = ["stomach_cancer_Crop", "Normal_Crop"]
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def Set_Save_Roots(self):
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self.__ICG_Training_Root = "../Dataset/Training/CA_ICG"
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self.__Normal_Training_Root = "../Dataset/Training/CA"
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self.__Comprehensive_Training_Root = "../Dataset/Training/Mixed"
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self.__ICG_Test_Data_Root = "../Dataset/Training/CA_ICG_TestData"
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self.__Normal_Test_Data_Root = "../Dataset/Training/Normal_TestData"
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self.__Comprehensive_Testing_Root = "../Dataset/Training/Comprehensive_TestData"
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self.__ICG_Validation_Data_Root = "../Dataset/Training/CA_ICG_ValidationData"
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self.__Normal_Validation_Data_Root = "../Dataset/Training/Normal_ValidationData"
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self.__Comprehensive_Validation_Root = "../Dataset/Training/Comprehensive_ValidationData"
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self.__ICG_ImageGenerator_Data_Root = "../Dataset/Training/ICG_ImageGenerator"
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self.__Normal_ImageGenerator_Data_Root = "../Dataset/Training/Normal_ImageGenerator"
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self.__Comprehensive_Generator_Root = "../Dataset/Training/Comprehensive_ImageGenerator"
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def Set_OneHotEncording(self, content, Number_Of_Classes):
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OneHot_labels = functional.one_hot(content, Number_Of_Classes)
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return OneHot_labels
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def Set_Zips(self, Datas, Labels, Address_Name):
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if Address_Name == "Training":
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self.Training_Zip = zip(Datas, Labels)
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if Address_Name == "Validation":
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self.Validation_Zip = zip(Datas, Labels)
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if Address_Name == "Testing":
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self.Testing_Zip = zip(Datas, Labels)
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def Get_Data_Label(self):
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'''
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取得所需資料的Labels
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'''
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return self.__Labels
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def Get_Save_Roots(self, choose):
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'''回傳結果為Train, test, validation
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choose = 1 => 取ICG Label
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else => 取Normal Label
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若choose != 1 || choose != 2 => 會回傳四個結果
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'''
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if choose == 1:
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return self.__ICG_Training_Root, self.__ICG_Test_Data_Root, self.__ICG_Validation_Data_Root
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if choose == 2:
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return self.__Normal_Training_Root, self.__Normal_Test_Data_Root, self.__Normal_Validation_Data_Root
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else:
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return self.__Comprehensive_Training_Root, self.__Comprehensive_Testing_Root, self.__Comprehensive_Validation_Root
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def Get_Generator_Save_Roots(self, choose):
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'''回傳結果為Train, test, validation'''
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if choose == 1:
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return self.__ICG_ImageGenerator_Data_Root
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if choose == 2:
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return self.__Normal_ImageGenerator_Data_Root
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else:
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return self.__Comprehensive_Generator_Root
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def Get_OneHot_Encording_Label(self):
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return self.__OneHot_Encording
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def Get_Zip(self):
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return self.Training_Zip, self.Testing_Zip, self.Validation_Zip |