DeepFaceLab/models/ConverterBase.py
iperov 7b70e7eec1 added new model U-net Face Morpher.
removed AVATAR - useless model was just for demo
removed MIAEF128 - use UFM insted
removed LIAEF128YAW - use model option sort by yaw on start for any model
All models now ask some options on start.
Session options (such as target epoch, batch_size, write_preview_history etc) can be overrided by special command arg.
Converter now always ask options and no more support to define options via command line.
fix bug when ConverterMasked always used not predicted mask.
SampleGenerator now always generate samples with replicated border, exclude mask samples.
refactorings
2019-01-02 17:26:12 +04:00

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1.3 KiB
Python

import copy
'''
You can implement your own Converter, check example ConverterMasked.py
'''
class ConverterBase(object):
MODE_FACE = 0
MODE_IMAGE = 1
MODE_IMAGE_WITH_LANDMARKS = 2
#overridable
def __init__(self, predictor):
self.predictor = predictor
#overridable
def get_mode(self):
#MODE_FACE calls convert_face
#MODE_IMAGE calls convert_image without landmarks
#MODE_IMAGE_WITH_LANDMARKS calls convert_image with landmarks
return ConverterBase.MODE_FACE
#overridable
def convert_face (self, img_bgr, img_face_landmarks, debug):
#return float32 image
#if debug , return tuple ( images of any size and channels, ...)
return image
#overridable
def convert_image (self, img_bgr, img_landmarks, debug):
#img_landmarks not None, if input image is png with embedded data
#return float32 image
#if debug , return tuple ( images of any size and channels, ...)
return image
#overridable
def dummy_predict(self):
#do dummy predict here
pass
def copy(self):
return copy.copy(self)
def copy_and_set_predictor(self, predictor):
result = self.copy()
result.predictor = predictor
return result