33 lines
1.1 KiB
Python
33 lines
1.1 KiB
Python
from merge_class.merge import merge
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from Load_process.Loading_Tools import Load_Data_Prepare
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from Load_process.LoadData import Loding_Data_Root
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from Training_Tools.Tools import Tool
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from Read_and_process_image.ReadAndProcess import Read_image_and_Process_image
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from matplotlib import pyplot as plt
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if __name__ == "__main__":
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Merge = merge()
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read = Read_image_and_Process_image()
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tool = Tool()
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Prepare = Load_Data_Prepare()
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tool.Set_Labels()
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tool.Set_Save_Roots()
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Labels = tool.Get_Data_Label()
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Trainig_Root, Testing_Root = tool.Get_Save_Roots(2)
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load = Loding_Data_Root(Labels, Trainig_Root, "")
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Data_Root = load.get_Image_data_roots(Trainig_Root)
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# 將資料做成Dict的資料型態
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Prepare.Set_Final_Dict_Data(Labels, Data_Root, [[], []], 2)
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Final_Dict_Data = Prepare.Get_Final_Data_Dict()
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keys = list(Final_Dict_Data.keys())
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training_data = Merge.merge_all_image_data(Final_Dict_Data[keys[0]], Final_Dict_Data[keys[1]]) # 將訓練資料合併成一個list
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Image = read.Data_Augmentation_Image(training_data)
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plt.imshow(Image[0])
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plt.show()
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