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from train import Train
from test import Test
from config import DatasetName, ModelArch
from pca_utilities import PCAUtility
if __name__ == '__main__':
'''use the pretrained model'''
tester = Test()
tester.test_model(ds_name=DatasetName.w300,
pretrained_model_path='./pre_trained_models/ACRLoss/mnv2.h5')
'''training model from scratch'''
# pretrain prerequisites
# 1- PCA calculation:
pca_calc = PCAUtility()
pca_calc.create_pca_from_npy(dataset_name=DatasetName.w300,
labels_npy_path='./data/w300/normalized_labels/',
pca_percentages=90)
# Train:
trainer = Train(arch=ModelArch.MNV2,
dataset_name=DatasetName.w300,
save_path='./')
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