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import os, sys |
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currentdir = os.path.dirname(os.path.realpath(__file__)) |
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parentdir = os.path.dirname(currentdir) |
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sys.path.append(parentdir) |
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from Brain_study.Train_Baseline import launch_train |
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import argparse |
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TRAIN_DATASET = '/mnt/EncryptedData1/Users/javier/ext_datasets/IXI_dataset/T1/training' |
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err = list() |
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if __name__ == '__main__': |
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parser = argparse.ArgumentParser() |
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parser.add_argument('--dataset', type=str, help='Location of the training data', default=TRAIN_DATASET) |
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parser.add_argument('--validation', type=str, help='Location of the validation data', default=None) |
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parser.add_argument('--similarity', type=str, help='Similarity metric: mse, ncc, ssim') |
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parser.add_argument('--output', type=str, help='Output directory', default=TRAIN_DATASET) |
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parser.add_argument('--gpu', type=str, help='GPU number', default='0') |
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parser.add_argument('--lr', type=float, help='Learning rate', default=1e-4) |
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parser.add_argument('--rw', type=float, help='Regularization weigh', default=5e-3) |
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args = parser.parse_args() |
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print('TRAIN ' + args.dataset) |
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launch_train(dataset_folder=args.dataset, |
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validation_folder=args.validation, |
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output_folder=os.path.join(args.output, 'BASELINE_L_{}__MET_mse_ncc_ssim'.format(args.similarity)), |
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gpu_num=args.gpu, |
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lr=args.lr, |
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rw=args.rw, |
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simil=args.similarity) |
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