From d2011f8c325f3c0e05b24ad929b049fe2a3dd89d Mon Sep 17 00:00:00 2001 From: iperov Date: Wed, 8 May 2019 09:32:32 +0400 Subject: [PATCH] upd doc --- models/Model_SAE/Model.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/models/Model_SAE/Model.py b/models/Model_SAE/Model.py index 45fb710..2ecc44f 100644 --- a/models/Model_SAE/Model.py +++ b/models/Model_SAE/Model.py @@ -89,7 +89,7 @@ class SAEModel(ModelBase): help_message="Learn to transfer image around face. This can make face more like dst. Enabling this option increases the chance of model collapse."), 0.0, 100.0 ) default_apply_random_ct = False if is_first_run else self.options.get('apply_random_ct', False) - self.options['apply_random_ct'] = io.input_bool ("Apply random color transfer to src faceset? (y/n, ?:help skip:%s) : " % (yn_str[default_apply_random_ct]), default_apply_random_ct, help_message="Increase variativity of src samples by apply RCT color transfer from random dst samples. It is like 'face_style' learning, but more precise color transfer and without risk of model collapse, also it does not require additional GPU resources, but the training time may be longer, due to the src faceset is becoming more diverse.") + self.options['apply_random_ct'] = io.input_bool ("Apply random color transfer to src faceset? (y/n, ?:help skip:%s) : " % (yn_str[default_apply_random_ct]), default_apply_random_ct, help_message="Increase variativity of src samples by apply LCT color transfer from random dst samples. It is like 'face_style' learning, but more precise color transfer and without risk of model collapse, also it does not require additional GPU resources, but the training time may be longer, due to the src faceset is becoming more diverse.") else: self.options['pixel_loss'] = self.options.get('pixel_loss', False) self.options['face_style_power'] = self.options.get('face_style_power', default_face_style_power)