DeepFaceLab/core/imagelib/text.py
Colombo 76ca79216e Upgraded to TF version 1.13.2
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
2020-01-25 21:58:19 +04:00

65 lines
2.0 KiB
Python

import localization
import numpy as np
from PIL import Image, ImageDraw, ImageFont
pil_fonts = {}
def _get_pil_font (font, size):
global pil_fonts
try:
font_str_id = '%s_%d' % (font, size)
if font_str_id not in pil_fonts.keys():
pil_fonts[font_str_id] = ImageFont.truetype(font + ".ttf", size=size, encoding="unic")
pil_font = pil_fonts[font_str_id]
return pil_font
except:
return ImageFont.load_default()
def get_text_image( shape, text, color=(1,1,1), border=0.2, font=None):
h,w,c = shape
try:
pil_font = _get_pil_font( localization.get_default_ttf_font_name() , h-2)
canvas = Image.new('RGB', (w,h) , (0,0,0) )
draw = ImageDraw.Draw(canvas)
offset = ( 0, 0)
draw.text(offset, text, font=pil_font, fill=tuple((np.array(color)*255).astype(np.int)) )
result = np.asarray(canvas) / 255
if c > 3:
result = np.concatenate ( (result, np.ones ((h,w,c-3)) ), axis=-1 )
elif c < 3:
result = result[...,0:c]
return result
except:
return np.zeros ( (h,w,c) )
def draw_text( image, rect, text, color=(1,1,1), border=0.2, font=None):
h,w,c = image.shape
l,t,r,b = rect
l = np.clip (l, 0, w-1)
r = np.clip (r, 0, w-1)
t = np.clip (t, 0, h-1)
b = np.clip (b, 0, h-1)
image[t:b, l:r] += get_text_image ( (b-t,r-l,c) , text, color, border, font )
def draw_text_lines (image, rect, text_lines, color=(1,1,1), border=0.2, font=None):
text_lines_len = len(text_lines)
if text_lines_len == 0:
return
l,t,r,b = rect
h = b-t
h_per_line = h // text_lines_len
for i in range(0, text_lines_len):
draw_text (image, (l, i*h_per_line, r, (i+1)*h_per_line), text_lines[i], color, border, font)
def get_draw_text_lines ( image, rect, text_lines, color=(1,1,1), border=0.2, font=None):
image = np.zeros ( image.shape, dtype=np.float )
draw_text_lines ( image, rect, text_lines, color, border, font)
return image