|
|
|
|
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cfg_mnet = { |
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'name': 'mobilenet0.25', |
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'min_sizes': [[16, 32], [64, 128], [256, 512]], |
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'steps': [8, 16, 32], |
|
'variance': [0.1, 0.2], |
|
'clip': False, |
|
'loc_weight': 2.0, |
|
'gpu_train': True, |
|
'batch_size': 32, |
|
'ngpu': 1, |
|
'epoch': 250, |
|
'decay1': 190, |
|
'decay2': 220, |
|
'image_size': 640, |
|
'pretrain': False, |
|
'return_layers': {'stage1': 1, 'stage2': 2, 'stage3': 3}, |
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'in_channel': 32, |
|
'out_channel': 64 |
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} |
|
|
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cfg_re50 = { |
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'name': 'Resnet50', |
|
'min_sizes': [[16, 32], [64, 128], [256, 512]], |
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'steps': [8, 16, 32], |
|
'variance': [0.1, 0.2], |
|
'clip': False, |
|
'loc_weight': 2.0, |
|
'gpu_train': True, |
|
'batch_size': 24, |
|
'ngpu': 4, |
|
'epoch': 100, |
|
'decay1': 70, |
|
'decay2': 90, |
|
'image_size': 840, |
|
'pretrain': False, |
|
'return_layers': {'layer2': 1, 'layer3': 2, 'layer4': 3}, |
|
'in_channel': 256, |
|
'out_channel': 256 |
|
} |
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|
|