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Converter:

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Session is now saved to the model folder.

blur and erode ranges are increased to -400+400

hist-match-bw is now replaced with seamless2 mode.

Added 'ebs' color transfer mode (works only on Windows).

FANSEG model (used in FAN-x mask modes) is retrained with new model configuration
and now produces better precision and less jitter
This commit is contained in:
Colombo 2019-09-07 13:57:42 +04:00
parent 70dada42ea
commit 7ed38a8097
29 changed files with 768 additions and 314 deletions
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13
models/ModelBase.py
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@ -117,9 +117,9 @@ class ModelBase(object):
if ask_batch_size and (self.iter == 0 or ask_override):
default_batch_size = 0 if self.iter == 0 else self.options.get('batch_size',0)
self.options['batch_size'] = max(0, io.input_int("Batch_size (?:help skip:%d) : " % (default_batch_size), default_batch_size, help_message="Larger batch size is better for NN's generalization, but it can cause Out of Memory error. Tune this value for your videocard manually."))
self.batch_size = max(0, io.input_int("Batch_size (?:help skip:%d) : " % (default_batch_size), default_batch_size, help_message="Larger batch size is better for NN's generalization, but it can cause Out of Memory error. Tune this value for your videocard manually."))
else:
self.options['batch_size'] = self.options.get('batch_size', 0)
self.batch_size = self.options.get('batch_size', 0)
if ask_sort_by_yaw:
if (self.iter == 0 or ask_override):
@ -152,7 +152,7 @@ class ModelBase(object):
if self.target_iter == 0 and 'target_iter' in self.options:
self.options.pop('target_iter')
self.batch_size = self.options.get('batch_size',0)
#self.batch_size = self.options.get('batch_size',0)
self.sort_by_yaw = self.options.get('sort_by_yaw',False)
self.random_flip = self.options.get('random_flip',True)
@ -325,14 +325,9 @@ class ModelBase(object):
#overridable
def get_ConverterConfig(self):
#return ConverterConfig() for the model
#return predictor_func, predictor_input_shape, ConverterConfig() for the model
raise NotImplementedError
#overridable
def get_converter(self):
raise NotImplementedError
#return existing or your own converter which derived from base
def get_target_iter(self):
return self.target_iter