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SAE: added option 'Pretrain the model?',

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Pretrain the model with large amount of various faces. This technique may help to train the fake with overly different face shapes and light conditions of src/dst data. Face will be look more like a morphed. To reduce the morph effect, some model files will be initialized but not be updated after pretrain: LIAE: inter_AB.h5 DF: both decoders.h5. The longer you pretrain the model the more morphed face will look. After that, save and run the training again.
This commit is contained in:
iperov 2019-05-01 19:55:27 +04:00
parent 659aa5705a
commit 2a8dd788dc
8 changed files with 78 additions and 44 deletions
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2
mainscripts/Trainer.py
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@ -19,6 +19,7 @@ def trainerThread (s2c, c2s, args, device_args):
training_data_src_path = Path( args.get('training_data_src_dir', '') )
training_data_dst_path = Path( args.get('training_data_dst_dir', '') )
pretraining_data_path = Path( args.get('pretraining_data_dir', '') )
model_path = Path( args.get('model_path', '') )
model_name = args.get('model_name', '')
save_interval_min = 15
@ -40,6 +41,7 @@ def trainerThread (s2c, c2s, args, device_args):
model_path,
training_data_src_path=training_data_src_path,
training_data_dst_path=training_data_dst_path,
pretraining_data_path=pretraining_data_path,
debug=debug,
device_args=device_args)