31 lines
1.4 KiB
Python
31 lines
1.4 KiB
Python
from facelib import get_config
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from facelib import FaceRecognizer
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import argparse
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# python train.py -net mobilefacenet -b 200 -w 4
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if __name__ == '__main__':
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parser = argparse.ArgumentParser(description='for face verification')
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parser.add_argument("-e", "--epochs", help="training epochs", default=20, type=int)
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parser.add_argument("-net", "--net_mode", help="which network, [ir, ir_se, mobilefacenet]",default='ir_se', type=str)
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parser.add_argument("-depth", "--net_depth", help="how many layers [50,100,152]", default=50, type=int)
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parser.add_argument('-lr','--lr',help='learning rate',default=1e-3, type=float)
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parser.add_argument("-b", "--batch_size", help="batch_size", default=96, type=int)
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parser.add_argument("-w", "--num_workers", help="workers number", default=3, type=int)
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parser.add_argument("-d", "--data_mode", help="use which database, [vgg, ms1m, emore, concat]",default='emore', type=str)
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args = parser.parse_args()
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conf = get_config()
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if args.net_mode == 'mobilefacenet':
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conf.use_mobilfacenet = True
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else:
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conf.net_mode = args.net_mode
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conf.net_depth = args.net_depth
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conf.lr = args.lr
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conf.batch_size = args.batch_size
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conf.num_workers = args.num_workers
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conf.data_mode = args.data_mode
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learner = FaceRecognizer(conf)
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learner.train(conf, args.epochs) |