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/config.py
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| a | b/config.py | ||
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| 1 | import os |
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| 2 | |||
| 3 | from numpy.core.numeric import False_ |
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| 4 | |||
| 5 | class Config(object): |
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| 6 | """ Wrapper class for various (hyper)parameters. """ |
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| 7 | def __init__(self): |
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| 8 | self.arch = 'mymodel_fold1' |
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| 9 | # training settings |
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| 10 | self.epochs = 150 |
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| 11 | self.learning_rate = 0.00001 |
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| 12 | self.gpu = 0 |
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| 13 | self.evaluate = False # test or train |
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| 14 | self.resume = False |
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| 15 | self.num_classes = 3 |
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| 16 | self.in_dim = 3 |
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| 17 | self.out_dim = 1 |
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| 18 | self.lr_type = 'SGDR' |
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| 19 | self.milestones = [80, 160, 240] |
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| 20 | self.sgdr_t = 50 |
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| 21 | self.weight_seg1 = 1 |
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| 22 | self.weight_seg2 = 0.5 |
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| 23 | self.weight_con = 0.1 |
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| 24 | self.weight_im = 0.9 |
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| 25 | self.weight_kd = 0.5 |
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| 26 | self.weight_edge = 0.5 |
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| 27 | self.batch_size = 8 |
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| 28 | |||
| 29 | # cross validation settings |
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| 30 | self.fold = 1 |
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| 31 | self.fold_num = 5 |
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| 32 | |||
| 33 | self.training_fold_index = [] |
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| 34 | for i in range(self.fold_num + 1): |
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| 35 | if i != self.fold and i != 0: |
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| 36 | self.training_fold_index.append(i) |
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| 37 | |||
| 38 | self.test_fold_index = [self.fold] |
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| 39 | |||
| 40 | # paths |
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| 41 | self.maskPath1 = './data/row_image/' # 对比实验所用数据集 |
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| 42 | self.csvPath = './dataprocess/split_csv/' # fold_csv |
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| 43 | self.maskPath2 = './data/mid_image/' |
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| 44 | self.midPath = './data/mid_image_npy/' |
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| 45 | self.lungPath = './data/lung_image/' |
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| 46 | self.mediaPath = './data/media_image/' |
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| 47 | self.figurePath = './result/figure/' |
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| 48 | |||
| 49 |