mirror of
https://github.com/iperov/DeepFaceLab.git
synced 2025-07-07 05:22:06 -07:00
76ca79216e
Removed the wait at first launch for most graphics cards. Increased speed of training by 10-20%, but you have to retrain all models from scratch. SAEHD: added option 'use float16' Experimental option. Reduces the model size by half. Increases the speed of training. Decreases the accuracy of the model. The model may collapse or not train. Model may not learn the mask in large resolutions. true_face_training option is replaced by "True face power". 0.0000 .. 1.0 Experimental option. Discriminates the result face to be more like the src face. Higher value - stronger discrimination. Comparison - https://i.imgur.com/czScS9q.png
104 lines
No EOL
2.6 KiB
Python
104 lines
No EOL
2.6 KiB
Python
import numpy as np
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import cv2
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class IEPolysPoints:
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def __init__(self, IEPolys_parent, type):
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self.parent = IEPolys_parent
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self.type = type
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self.points = np.empty( (0,2), dtype=np.int32 )
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self.n_max = self.n = 0
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def add(self,x,y):
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self.points = np.append(self.points[0:self.n], [ (x,y) ], axis=0)
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self.n_max = self.n = self.n + 1
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self.parent.dirty = True
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def n_dec(self):
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self.n = max(0, self.n-1)
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self.parent.dirty = True
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return self.n
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def n_inc(self):
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self.n = min(len(self.points), self.n+1)
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self.parent.dirty = True
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return self.n
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def n_clip(self):
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self.points = self.points[0:self.n]
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self.n_max = self.n
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def cur_point(self):
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return self.points[self.n-1]
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def points_to_n(self):
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return self.points[0:self.n]
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def set_points(self, points):
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self.points = np.array(points)
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self.n_max = self.n = len(points)
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self.parent.dirty = True
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class IEPolys:
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def __init__(self):
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self.list = []
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self.n_max = self.n = 0
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self.dirty = True
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def add(self, type):
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self.list = self.list[0:self.n]
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self.list.append ( IEPolysPoints(self, type) )
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self.n_max = self.n = self.n + 1
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self.dirty = True
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def n_dec(self):
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self.n = max(0, self.n-1)
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self.dirty = True
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return self.n
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def n_inc(self):
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self.n = min(len(self.list), self.n+1)
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self.dirty = True
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return self.n
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def n_list(self):
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return self.list[self.n-1]
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def n_clip(self):
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self.list = self.list[0:self.n]
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self.n_max = self.n
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if self.n > 0:
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self.list[-1].n_clip()
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def __iter__(self):
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for n in range(self.n):
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yield self.list[n]
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def switch_dirty(self):
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d = self.dirty
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self.dirty = False
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return d
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def overlay_mask(self, mask):
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h,w,c = mask.shape
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white = (1,)*c
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black = (0,)*c
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for n in range(self.n):
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poly = self.list[n]
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if poly.n > 0:
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cv2.fillPoly(mask, [poly.points_to_n()], white if poly.type == 1 else black )
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def dump(self):
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result = []
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for n in range(self.n):
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l = self.list[n]
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result += [ (l.type, l.points_to_n().tolist() ) ]
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return result
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@staticmethod
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def load(ie_polys=None):
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obj = IEPolys()
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if ie_polys is not None and isinstance(ie_polys, list):
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for (type, points) in ie_polys:
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obj.add(type)
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obj.n_list().set_points(points)
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return obj |