os.makedirs(model_path)
print((pad("Generating network run folder")))
else:
print((pad("Network run folder already exits")))
exp_cfg_fn = os.path.split(exp_cfg_path)[-1]
env_cfg_fn = os.path.split(env_cfg_path)[-1]
exp, env = move_dataset_to_ssd(env, exp)
exp, env = move_background(env, exp)
dic = {'exp': exp, 'env': env}
model = TrackNet6D(**dic)
early_stop_callback = EarlyStopping(
monitor='avg_val_disparity',
patience=exp.get('early_stopping_cfg', {}).get('patience', 100),
strict=False,
verbose=True,
mode='min',
min_delta=exp.get('early_stopping_cfg', {}).get('min_delta', -0.1))
checkpoint_callback = ModelCheckpoint(
filepath=exp['model_path'] +
'/{epoch}-{avg_val_disparity_float:.4f}',
verbose=True,
monitor="avg_val_disparity",
mode="min",
prefix="",
save_last=True,
save_top_k=10,
)
exp_cfg_fn = os.path.split(exp_cfg_path)[-1]
env_cfg_fn = os.path.split(env_cfg_path)[-1]
print(pad(f'Copy {env_cfg_path} to {model_path}/{exp_cfg_fn}'))
shutil.copy(exp_cfg_path, f'{model_path}/{exp_cfg_fn}')
shutil.copy(env_cfg_path, f'{model_path}/{env_cfg_fn}')
exp, env = move_dataset_to_ssd(env, exp)
exp, env = move_background(env, exp)
dic = {'exp': exp, 'env': env}
model = TrackNet6D(**dic)
early_stop_callback = EarlyStopping(
monitor='avg_val_disparity',
patience=exp.get('early_stopping_cfg', {}).get('patience', 100),
strict=False,
verbose=True,
mode='min',
min_delta=exp.get('early_stopping_cfg', {}).get('min_delta', -0.1))
checkpoint_callback = ModelCheckpoint(
filepath=exp['model_path'] + '/{epoch}-{avg_val_disparity_float:.4f}',
verbose=True,
monitor="avg_val_disparity",
mode="min",
prefix="",
save_last=True,
save_top_k=10,
)
if exp.get('checkpoint_restore', False):