model_cfgs = {
'cfg_mnet' : {
'name': 'mobilenet0.25',
'min_sizes': [[16, 32], [64, 128], [256, 512]],
'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,
'target_size': 1600,
'nms_threshold': 0.4,
'confidence_threshold':0.5,
'max_size': 2150,
'mean': [104, 117, 123],
'std': [1,1,1],
'pretrain': True,
'return_layers': {'stage1': 1, 'stage2': 2, 'stage3': 3},
'in_channel': 32,
'out_channel': 64
},
'cfg_re50' : {
'name': 'Resnet50',
'min_sizes': [[16, 32], [64, 128], [256, 512]],
'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,
'target_size': 1600,
'nms_threshold': 0.4,
'confidence_threshold':0.5,
'max_size': 2150,
'mean': [104, 117, 123],
'std': [1,1,1],
'pretrain': True,
'return_layers': {'layer2': 1, 'layer3': 2, 'layer4': 3},
'in_channel': 256,
'out_channel': 256
}
}
[docs]def build_configs(name: str):
return model_cfgs[name]
