def setup_model(config, prepared, **kwargs):
"""
Create a model
Parameters
----------
config : CfgNode
Model configuration (cf. configs/default_config.py)
prepared : bool
True if the model has been prepared before
kwargs : dict
Extra parameters for the model
Returns
-------
model : nn.Module
Created model
"""
print0(pcolor('Model: %s' % config.name, 'yellow'))
model = load_class(config.name, paths=['packnet_sfm.models',])(
**{**config.loss, **kwargs})
# Add depth network if required
if 'depth_net' in model.network_requirements:
model.add_depth_net(setup_depth_net(config.depth_net, prepared))
# Add pose network if required
if 'pose_net' in model.network_requirements:
model.add_pose_net(setup_pose_net(config.pose_net, prepared))
# If a checkpoint is provided, load pretrained model
if not prepared and config.checkpoint_path is not '':
model = load_network(model, config.checkpoint_path, 'model')
# Return model
return model
def get_default_config(cfg_default):
"""Get default configuration from file"""
config = load_class('get_cfg_defaults',
paths=[cfg_default.replace('/', '.')],
concat=False)()
config.merge_from_list(['default', cfg_default])
return config
def setup_model(config, prepared, **kwargs):
"""
Create a model
Parameters
----------
config : CfgNode
Model configuration (cf. configs/default_config.py)
prepared : bool
True if the model has been prepared before
kwargs : dict
Extra parameters for the model
Returns
-------
model : nn.Module
Created model
"""
print0(pcolor('Model: %s' % config.name, 'yellow'))
# SfmModel, SelfSupModel, VelSupModel loaded
model = load_class(config.name, paths=['packnet_sfm.models',])(
**{**config.loss, **kwargs})
# Add depth network if required
if model.network_requirements['depth_net']:
model.add_depth_net(setup_depth_net(config.depth_net, prepared,
num_scales=config.loss.num_scales,
min_depth=config.params.min_depth,
max_depth=config.params.max_depth,
upsample_depth_maps=config.loss.upsample_depth_maps
))
# Add pose network if required
if model.network_requirements['pose_net']:
model.add_pose_net(
setup_pose_net(config.pose_net,
prepared,
rotation_mode=config.loss.rotation_mode,
**kwargs))
# If a checkpoint is provided, load pretrained model
if not prepared and config.checkpoint_path is not '':
model = load_network(model, config.checkpoint_path, 'model')
# Return model
return model