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config.py
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config.py
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# # Soft Gated Skip Connections
config = {
# architecture in ['SGSC', 'SHG'] for SoftGatedSkipConnections and StackedHourGlass
'architecture': 'SGSC',
'inference': {
'nstack': 4,
'inp_dim': 144,
'oup_dim': 16,
'num_parts': 16,
'checkpoint_path': 'checkpoints/SGSC_model_weights.tar',
'presentation_dir' : 'presentation/',
},
'train': {
'epochs': 200,
'batchsize': 24,
'input_res': 256,
'output_res': 64,
'learning_rate': 1e-3,
'decay_epochs': [75, 100, 150],
'start_learning_rate': 2.5e-4,
'end_learning_rate': 1e-5,
},
}
# # Stacked Hourglass Network
# config = {
# # architecture in ['SGSC', 'SHG'] for SoftGatedSkipConnections and StackedHourGlass
# 'architecture': 'SHG',
# 'inference': {
# 'nstack': 8,
# 'inp_dim': 256, # channels 256
# 'oup_dim': 16,
# 'num_parts': 16,
# 'checkpoint_path': 'checkpoints/SHG_model_weights.tar',
# 'presentation_dir' : '/presentation',
# },
# 'train': {
# 'epochs': 200,
# 'batchsize': 24,
# 'input_res': 256,
# 'output_res': 64,
# 'learning_rate': 1e-3,
# 'decay_epochs': [75, 100, 150],
# 'start_learning_rate': 2.5e-4,
# 'end_learning_rate': 1e-5,
# },
# }