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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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import argparse |
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from datetime import datetime |
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TRAIN_DATASET = '/mnt/EncryptedData1/Users/javier/ext_datasets/COMET_dataset/OSLO_COMET_CT/Formatted_128x128x128/train' |
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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('--model', type=str, help='Path to the model file', required=True) |
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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', nargs='+', help='Similarity metric: mse, ncc, ssim', default=['ncc']) |
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parser.add_argument('--segmentation', nargs='+', help='Segmentation loss function: hd, dice', default=['dice']) |
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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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parser.add_argument('--epochs', type=int, help='Max number of epochs', default=1000) |
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parser.add_argument('--name', type=str, default='COMET') |
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parser.add_argument('--uw', type=bool, default=False) |
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parser.add_argument('--freeze', nargs='+', help='What layers to freeze: INPUT, OUTPUT, ENCODER, DECODER, TOP, BOTTOM', default=None) |
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parser.add_argument('--epochs', default=1000) |
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parser.add_argument('--batch', default=16) |
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args = parser.parse_args() |
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print('TRAIN ' + args.dataset) |
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if args.uw: |
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from COMET.COMET_train_UW import launch_train |
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simil = args.similarity |
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segm = args.segmentation |
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output_folder = os.path.join(args.output, '{}_Lsim_{}__Lseg_{}'.format(args.name, '_'.join(simil), '_'.join(segm))) |
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else: |
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from COMET.COMET_train import launch_train |
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simil = args.similarity[0] |
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segm = args.segmentation[0] |
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output_folder = os.path.join(args.output, '{}_Lsim_{}__Lseg_{}'.format(args.name, simil, segm)) |
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output_folder = output_folder + '_' + datetime.now().strftime("%H%M%S-%d%m%Y") |
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if args.freeze is not None: |
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assert all(s in ['INPUT', 'OUTPUT', 'ENCODER', 'DECODER', 'TOP', 'BOTTOM'] for s in args.freeze),\ |
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'Invalid option for "freeze". Expected one or several of: INPUT, OUTPUT, ENCODER, DECODER, TOP, BOTTOM' |
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args.freeze = list(set(args.freeze)) |
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launch_train(dataset_folder=args.dataset, |
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validation_folder=args.validation, |
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output_folder=output_folder, |
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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=simil, |
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segm=segm, |
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max_epochs=args.epochs, |
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model_file=args.model, |
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freeze_layers=args.freeze) |
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