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from train import Train |
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from test import Test |
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from configuration import DatasetName, ModelArch |
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from pca_utility import PCAUtility |
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if __name__ == '__main__': |
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'''use the pretrained model''' |
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tester = Test() |
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tester.test_model(ds_name=DatasetName.w300, |
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pretrained_model_path='./pre_trained_models/ASMNet/ASM_loss/ASMNet_300W_ASMLoss.h5') |
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'''training model from scratch''' |
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pca_calc = PCAUtility() |
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pca_calc.create_pca_from_npy(dataset_name=DatasetName.w300, |
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labels_npy_path='./data/w300/normalized_labels/', |
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pca_percentages=90) |
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trainer = Train(arch=ModelArch.ASMNet, |
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dataset_name=DatasetName.w300, |
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save_path='./', |
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asm_accuracy=90) |
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