fc7e96b182b21f5be42d5060b4cc04b1c2e517067a0c471c97505b29f93f45e5
Browse files- .gitattributes +9 -0
- ebsynth_utility/__pycache__/stage8.cpython-310.pyc +0 -0
- ebsynth_utility/calculator.py +237 -0
- ebsynth_utility/ebsynth_utility.py +185 -0
- ebsynth_utility/imgs/clipseg.png +0 -0
- ebsynth_utility/imgs/controlnet_0.png +0 -0
- ebsynth_utility/imgs/controlnet_1.png +0 -0
- ebsynth_utility/imgs/controlnet_option_in_ebsynthutil.png +0 -0
- ebsynth_utility/imgs/controlnet_setting.png +0 -0
- ebsynth_utility/imgs/sample1.mp4 +3 -0
- ebsynth_utility/imgs/sample2.mp4 +3 -0
- ebsynth_utility/imgs/sample3.mp4 +3 -0
- ebsynth_utility/imgs/sample4.mp4 +3 -0
- ebsynth_utility/imgs/sample5.mp4 +3 -0
- ebsynth_utility/imgs/sample6.mp4 +3 -0
- ebsynth_utility/imgs/sample_anyaheh.mp4 +3 -0
- ebsynth_utility/imgs/sample_autotag.mp4 +3 -0
- ebsynth_utility/imgs/sample_clipseg.mp4 +3 -0
- ebsynth_utility/install.py +24 -0
- ebsynth_utility/sample/add_token.txt +54 -0
- ebsynth_utility/sample/blacklist.txt +10 -0
- ebsynth_utility/scripts/__pycache__/custom_script.cpython-310.pyc +0 -0
- ebsynth_utility/scripts/__pycache__/ui.cpython-310.pyc +0 -0
- ebsynth_utility/scripts/custom_script.py +1012 -0
- ebsynth_utility/scripts/ui.py +199 -0
- ebsynth_utility/stage1.py +258 -0
- ebsynth_utility/stage2.py +173 -0
- ebsynth_utility/stage3_5.py +178 -0
- ebsynth_utility/stage5.py +279 -0
- ebsynth_utility/stage7.py +234 -0
- ebsynth_utility/stage8.py +146 -0
- ebsynth_utility/style.css +39 -0
- microsoftexcel-controlnet/__pycache__/preload.cpython-310.pyc +0 -0
- microsoftexcel-controlnet/annotator/__pycache__/util.cpython-310.pyc +0 -0
.gitattributes
CHANGED
@@ -55,3 +55,12 @@ SD-CN-Animation/examples/gold_1.gif filter=lfs diff=lfs merge=lfs -text
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SD-CN-Animation/examples/macaroni_1.gif filter=lfs diff=lfs merge=lfs -text
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SD-CN-Animation/examples/tree_2.gif filter=lfs diff=lfs merge=lfs -text
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SD-CN-Animation/examples/tree_2.mp4 filter=lfs diff=lfs merge=lfs -text
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SD-CN-Animation/examples/macaroni_1.gif filter=lfs diff=lfs merge=lfs -text
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SD-CN-Animation/examples/tree_2.gif filter=lfs diff=lfs merge=lfs -text
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SD-CN-Animation/examples/tree_2.mp4 filter=lfs diff=lfs merge=lfs -text
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ebsynth_utility/imgs/sample1.mp4 filter=lfs diff=lfs merge=lfs -text
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ebsynth_utility/imgs/sample2.mp4 filter=lfs diff=lfs merge=lfs -text
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ebsynth_utility/imgs/sample3.mp4 filter=lfs diff=lfs merge=lfs -text
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ebsynth_utility/imgs/sample4.mp4 filter=lfs diff=lfs merge=lfs -text
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ebsynth_utility/imgs/sample5.mp4 filter=lfs diff=lfs merge=lfs -text
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ebsynth_utility/imgs/sample6.mp4 filter=lfs diff=lfs merge=lfs -text
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ebsynth_utility/imgs/sample_anyaheh.mp4 filter=lfs diff=lfs merge=lfs -text
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ebsynth_utility/imgs/sample_autotag.mp4 filter=lfs diff=lfs merge=lfs -text
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ebsynth_utility/imgs/sample_clipseg.mp4 filter=lfs diff=lfs merge=lfs -text
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ebsynth_utility/__pycache__/stage8.cpython-310.pyc
ADDED
Binary file (3.97 kB). View file
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ebsynth_utility/calculator.py
ADDED
@@ -0,0 +1,237 @@
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1 |
+
# https://www.mycompiler.io/view/3TFZagC
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3 |
+
class ParseError(Exception):
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def __init__(self, pos, msg, *args):
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self.pos = pos
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+
self.msg = msg
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7 |
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self.args = args
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8 |
+
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9 |
+
def __str__(self):
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10 |
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return '%s at position %s' % (self.msg % self.args, self.pos)
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+
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12 |
+
class Parser:
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13 |
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def __init__(self):
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14 |
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self.cache = {}
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15 |
+
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16 |
+
def parse(self, text):
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17 |
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self.text = text
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18 |
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self.pos = -1
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19 |
+
self.len = len(text) - 1
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20 |
+
rv = self.start()
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21 |
+
self.assert_end()
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22 |
+
return rv
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23 |
+
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24 |
+
def assert_end(self):
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25 |
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if self.pos < self.len:
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26 |
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raise ParseError(
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self.pos + 1,
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28 |
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'Expected end of string but got %s',
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29 |
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self.text[self.pos + 1]
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30 |
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)
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31 |
+
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32 |
+
def eat_whitespace(self):
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33 |
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while self.pos < self.len and self.text[self.pos + 1] in " \f\v\r\t\n":
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34 |
+
self.pos += 1
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35 |
+
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36 |
+
def split_char_ranges(self, chars):
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37 |
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try:
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38 |
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return self.cache[chars]
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39 |
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except KeyError:
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40 |
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pass
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41 |
+
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42 |
+
rv = []
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43 |
+
index = 0
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44 |
+
length = len(chars)
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45 |
+
|
46 |
+
while index < length:
|
47 |
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if index + 2 < length and chars[index + 1] == '-':
|
48 |
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if chars[index] >= chars[index + 2]:
|
49 |
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raise ValueError('Bad character range')
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50 |
+
|
51 |
+
rv.append(chars[index:index + 3])
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52 |
+
index += 3
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53 |
+
else:
|
54 |
+
rv.append(chars[index])
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55 |
+
index += 1
|
56 |
+
|
57 |
+
self.cache[chars] = rv
|
58 |
+
return rv
|
59 |
+
|
60 |
+
def char(self, chars=None):
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61 |
+
if self.pos >= self.len:
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62 |
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raise ParseError(
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63 |
+
self.pos + 1,
|
64 |
+
'Expected %s but got end of string',
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65 |
+
'character' if chars is None else '[%s]' % chars
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66 |
+
)
|
67 |
+
|
68 |
+
next_char = self.text[self.pos + 1]
|
69 |
+
if chars == None:
|
70 |
+
self.pos += 1
|
71 |
+
return next_char
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72 |
+
|
73 |
+
for char_range in self.split_char_ranges(chars):
|
74 |
+
if len(char_range) == 1:
|
75 |
+
if next_char == char_range:
|
76 |
+
self.pos += 1
|
77 |
+
return next_char
|
78 |
+
elif char_range[0] <= next_char <= char_range[2]:
|
79 |
+
self.pos += 1
|
80 |
+
return next_char
|
81 |
+
|
82 |
+
raise ParseError(
|
83 |
+
self.pos + 1,
|
84 |
+
'Expected %s but got %s',
|
85 |
+
'character' if chars is None else '[%s]' % chars,
|
86 |
+
next_char
|
87 |
+
)
|
88 |
+
|
89 |
+
def keyword(self, *keywords):
|
90 |
+
self.eat_whitespace()
|
91 |
+
if self.pos >= self.len:
|
92 |
+
raise ParseError(
|
93 |
+
self.pos + 1,
|
94 |
+
'Expected %s but got end of string',
|
95 |
+
','.join(keywords)
|
96 |
+
)
|
97 |
+
|
98 |
+
for keyword in keywords:
|
99 |
+
low = self.pos + 1
|
100 |
+
high = low + len(keyword)
|
101 |
+
|
102 |
+
if self.text[low:high] == keyword:
|
103 |
+
self.pos += len(keyword)
|
104 |
+
self.eat_whitespace()
|
105 |
+
return keyword
|
106 |
+
|
107 |
+
raise ParseError(
|
108 |
+
self.pos + 1,
|
109 |
+
'Expected %s but got %s',
|
110 |
+
','.join(keywords),
|
111 |
+
self.text[self.pos + 1],
|
112 |
+
)
|
113 |
+
|
114 |
+
def match(self, *rules):
|
115 |
+
self.eat_whitespace()
|
116 |
+
last_error_pos = -1
|
117 |
+
last_exception = None
|
118 |
+
last_error_rules = []
|
119 |
+
|
120 |
+
for rule in rules:
|
121 |
+
initial_pos = self.pos
|
122 |
+
try:
|
123 |
+
rv = getattr(self, rule)()
|
124 |
+
self.eat_whitespace()
|
125 |
+
return rv
|
126 |
+
except ParseError as e:
|
127 |
+
self.pos = initial_pos
|
128 |
+
|
129 |
+
if e.pos > last_error_pos:
|
130 |
+
last_exception = e
|
131 |
+
last_error_pos = e.pos
|
132 |
+
last_error_rules.clear()
|
133 |
+
last_error_rules.append(rule)
|
134 |
+
elif e.pos == last_error_pos:
|
135 |
+
last_error_rules.append(rule)
|
136 |
+
|
137 |
+
if len(last_error_rules) == 1:
|
138 |
+
raise last_exception
|
139 |
+
else:
|
140 |
+
raise ParseError(
|
141 |
+
last_error_pos,
|
142 |
+
'Expected %s but got %s',
|
143 |
+
','.join(last_error_rules),
|
144 |
+
self.text[last_error_pos]
|
145 |
+
)
|
146 |
+
|
147 |
+
def maybe_char(self, chars=None):
|
148 |
+
try:
|
149 |
+
return self.char(chars)
|
150 |
+
except ParseError:
|
151 |
+
return None
|
152 |
+
|
153 |
+
def maybe_match(self, *rules):
|
154 |
+
try:
|
155 |
+
return self.match(*rules)
|
156 |
+
except ParseError:
|
157 |
+
return None
|
158 |
+
|
159 |
+
def maybe_keyword(self, *keywords):
|
160 |
+
try:
|
161 |
+
return self.keyword(*keywords)
|
162 |
+
except ParseError:
|
163 |
+
return None
|
164 |
+
|
165 |
+
class CalcParser(Parser):
|
166 |
+
def start(self):
|
167 |
+
return self.expression()
|
168 |
+
|
169 |
+
def expression(self):
|
170 |
+
rv = self.match('term')
|
171 |
+
while True:
|
172 |
+
op = self.maybe_keyword('+', '-')
|
173 |
+
if op is None:
|
174 |
+
break
|
175 |
+
|
176 |
+
term = self.match('term')
|
177 |
+
if op == '+':
|
178 |
+
rv += term
|
179 |
+
else:
|
180 |
+
rv -= term
|
181 |
+
|
182 |
+
return rv
|
183 |
+
|
184 |
+
def term(self):
|
185 |
+
rv = self.match('factor')
|
186 |
+
while True:
|
187 |
+
op = self.maybe_keyword('*', '/')
|
188 |
+
if op is None:
|
189 |
+
break
|
190 |
+
|
191 |
+
term = self.match('factor')
|
192 |
+
if op == '*':
|
193 |
+
rv *= term
|
194 |
+
else:
|
195 |
+
rv /= term
|
196 |
+
|
197 |
+
return rv
|
198 |
+
|
199 |
+
def factor(self):
|
200 |
+
if self.maybe_keyword('('):
|
201 |
+
rv = self.match('expression')
|
202 |
+
self.keyword(')')
|
203 |
+
|
204 |
+
return rv
|
205 |
+
|
206 |
+
return self.match('number')
|
207 |
+
|
208 |
+
def number(self):
|
209 |
+
chars = []
|
210 |
+
|
211 |
+
sign = self.maybe_keyword('+', '-')
|
212 |
+
if sign is not None:
|
213 |
+
chars.append(sign)
|
214 |
+
|
215 |
+
chars.append(self.char('0-9'))
|
216 |
+
|
217 |
+
while True:
|
218 |
+
char = self.maybe_char('0-9')
|
219 |
+
if char is None:
|
220 |
+
break
|
221 |
+
|
222 |
+
chars.append(char)
|
223 |
+
|
224 |
+
if self.maybe_char('.'):
|
225 |
+
chars.append('.')
|
226 |
+
chars.append(self.char('0-9'))
|
227 |
+
|
228 |
+
while True:
|
229 |
+
char = self.maybe_char('0-9')
|
230 |
+
if char is None:
|
231 |
+
break
|
232 |
+
|
233 |
+
chars.append(char)
|
234 |
+
|
235 |
+
rv = float(''.join(chars))
|
236 |
+
return rv
|
237 |
+
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ebsynth_utility/ebsynth_utility.py
ADDED
@@ -0,0 +1,185 @@
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|
1 |
+
import os
|
2 |
+
|
3 |
+
from modules.ui import plaintext_to_html
|
4 |
+
|
5 |
+
import cv2
|
6 |
+
import glob
|
7 |
+
from PIL import Image
|
8 |
+
|
9 |
+
from extensions.ebsynth_utility.stage1 import ebsynth_utility_stage1,ebsynth_utility_stage1_invert
|
10 |
+
from extensions.ebsynth_utility.stage2 import ebsynth_utility_stage2
|
11 |
+
from extensions.ebsynth_utility.stage5 import ebsynth_utility_stage5
|
12 |
+
from extensions.ebsynth_utility.stage7 import ebsynth_utility_stage7
|
13 |
+
from extensions.ebsynth_utility.stage8 import ebsynth_utility_stage8
|
14 |
+
from extensions.ebsynth_utility.stage3_5 import ebsynth_utility_stage3_5
|
15 |
+
|
16 |
+
|
17 |
+
def x_ceiling(value, step):
|
18 |
+
return -(-value // step) * step
|
19 |
+
|
20 |
+
def dump_dict(string, d:dict):
|
21 |
+
for key in d.keys():
|
22 |
+
string += ( key + " : " + str(d[key]) + "\n")
|
23 |
+
return string
|
24 |
+
|
25 |
+
class debug_string:
|
26 |
+
txt = ""
|
27 |
+
def print(self, comment):
|
28 |
+
print(comment)
|
29 |
+
self.txt += comment + '\n'
|
30 |
+
def to_string(self):
|
31 |
+
return self.txt
|
32 |
+
|
33 |
+
def ebsynth_utility_process(stage_index: int, project_dir:str, original_movie_path:str, frame_width:int, frame_height:int, st1_masking_method_index:int, st1_mask_threshold:float, tb_use_fast_mode:bool, tb_use_jit:bool, clipseg_mask_prompt:str, clipseg_exclude_prompt:str, clipseg_mask_threshold:int, clipseg_mask_blur_size:int, clipseg_mask_blur_size2:int, key_min_gap:int, key_max_gap:int, key_th:float, key_add_last_frame:bool, color_matcher_method:str, st3_5_use_mask:bool, st3_5_use_mask_ref:bool, st3_5_use_mask_org:bool, color_matcher_ref_type:int, color_matcher_ref_image:Image, blend_rate:float, export_type:str, bg_src:str, bg_type:str, mask_blur_size:int, mask_threshold:float, fg_transparency:float, mask_mode:str):
|
34 |
+
args = locals()
|
35 |
+
info = ""
|
36 |
+
info = dump_dict(info, args)
|
37 |
+
dbg = debug_string()
|
38 |
+
|
39 |
+
|
40 |
+
def process_end(dbg, info):
|
41 |
+
return plaintext_to_html(dbg.to_string()), plaintext_to_html(info)
|
42 |
+
|
43 |
+
|
44 |
+
if not os.path.isdir(project_dir):
|
45 |
+
dbg.print("{0} project_dir not found".format(project_dir))
|
46 |
+
return process_end( dbg, info )
|
47 |
+
|
48 |
+
if not os.path.isfile(original_movie_path):
|
49 |
+
dbg.print("{0} original_movie_path not found".format(original_movie_path))
|
50 |
+
return process_end( dbg, info )
|
51 |
+
|
52 |
+
is_invert_mask = False
|
53 |
+
if mask_mode == "Invert":
|
54 |
+
is_invert_mask = True
|
55 |
+
|
56 |
+
frame_path = os.path.join(project_dir , "video_frame")
|
57 |
+
frame_mask_path = os.path.join(project_dir, "video_mask")
|
58 |
+
|
59 |
+
if is_invert_mask:
|
60 |
+
inv_path = os.path.join(project_dir, "inv")
|
61 |
+
os.makedirs(inv_path, exist_ok=True)
|
62 |
+
|
63 |
+
org_key_path = os.path.join(inv_path, "video_key")
|
64 |
+
img2img_key_path = os.path.join(inv_path, "img2img_key")
|
65 |
+
img2img_upscale_key_path = os.path.join(inv_path, "img2img_upscale_key")
|
66 |
+
else:
|
67 |
+
org_key_path = os.path.join(project_dir, "video_key")
|
68 |
+
img2img_key_path = os.path.join(project_dir, "img2img_key")
|
69 |
+
img2img_upscale_key_path = os.path.join(project_dir, "img2img_upscale_key")
|
70 |
+
|
71 |
+
if mask_mode == "None":
|
72 |
+
frame_mask_path = ""
|
73 |
+
|
74 |
+
|
75 |
+
project_args = [project_dir, original_movie_path, frame_path, frame_mask_path, org_key_path, img2img_key_path, img2img_upscale_key_path]
|
76 |
+
|
77 |
+
|
78 |
+
if stage_index == 0:
|
79 |
+
ebsynth_utility_stage1(dbg, project_args, frame_width, frame_height, st1_masking_method_index, st1_mask_threshold, tb_use_fast_mode, tb_use_jit, clipseg_mask_prompt, clipseg_exclude_prompt, clipseg_mask_threshold, clipseg_mask_blur_size, clipseg_mask_blur_size2, is_invert_mask)
|
80 |
+
if is_invert_mask:
|
81 |
+
inv_mask_path = os.path.join(inv_path, "inv_video_mask")
|
82 |
+
ebsynth_utility_stage1_invert(dbg, frame_mask_path, inv_mask_path)
|
83 |
+
|
84 |
+
elif stage_index == 1:
|
85 |
+
ebsynth_utility_stage2(dbg, project_args, key_min_gap, key_max_gap, key_th, key_add_last_frame, is_invert_mask)
|
86 |
+
elif stage_index == 2:
|
87 |
+
|
88 |
+
sample_image = glob.glob( os.path.join(frame_path , "*.png" ) )[0]
|
89 |
+
img_height, img_width, _ = cv2.imread(sample_image).shape
|
90 |
+
if img_width < img_height:
|
91 |
+
re_w = 512
|
92 |
+
re_h = int(x_ceiling( (512 / img_width) * img_height , 64))
|
93 |
+
else:
|
94 |
+
re_w = int(x_ceiling( (512 / img_height) * img_width , 64))
|
95 |
+
re_h = 512
|
96 |
+
img_width = re_w
|
97 |
+
img_height = re_h
|
98 |
+
|
99 |
+
dbg.print("stage 3")
|
100 |
+
dbg.print("")
|
101 |
+
dbg.print("!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!")
|
102 |
+
dbg.print("1. Go to img2img tab")
|
103 |
+
dbg.print("2. Select [ebsynth utility] in the script combo box")
|
104 |
+
dbg.print("3. Fill in the \"Project directory\" field with [" + project_dir + "]" )
|
105 |
+
dbg.print("4. Select in the \"Mask Mode(Override img2img Mask mode)\" field with [" + ("Invert" if is_invert_mask else "Normal") + "]" )
|
106 |
+
dbg.print("5. I recommend to fill in the \"Width\" field with [" + str(img_width) + "]" )
|
107 |
+
dbg.print("6. I recommend to fill in the \"Height\" field with [" + str(img_height) + "]" )
|
108 |
+
dbg.print("7. I recommend to fill in the \"Denoising strength\" field with lower than 0.35" )
|
109 |
+
dbg.print(" (When using controlnet together, you can put in large values (even 1.0 is possible).)")
|
110 |
+
dbg.print("8. Fill in the remaining configuration fields of img2img. No image and mask settings are required.")
|
111 |
+
dbg.print("9. Drop any image onto the img2img main screen. This is necessary to avoid errors, but does not affect the results of img2img.")
|
112 |
+
dbg.print("10. Generate")
|
113 |
+
dbg.print("(Images are output to [" + img2img_key_path + "])")
|
114 |
+
dbg.print("!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!")
|
115 |
+
return process_end( dbg, "" )
|
116 |
+
|
117 |
+
elif stage_index == 3:
|
118 |
+
ebsynth_utility_stage3_5(dbg, project_args, color_matcher_method, st3_5_use_mask, st3_5_use_mask_ref, st3_5_use_mask_org, color_matcher_ref_type, color_matcher_ref_image)
|
119 |
+
|
120 |
+
elif stage_index == 4:
|
121 |
+
sample_image = glob.glob( os.path.join(frame_path , "*.png" ) )[0]
|
122 |
+
img_height, img_width, _ = cv2.imread(sample_image).shape
|
123 |
+
|
124 |
+
sample_img2img_key = glob.glob( os.path.join(img2img_key_path , "*.png" ) )[0]
|
125 |
+
img_height_key, img_width_key, _ = cv2.imread(sample_img2img_key).shape
|
126 |
+
|
127 |
+
if is_invert_mask:
|
128 |
+
project_dir = inv_path
|
129 |
+
|
130 |
+
dbg.print("stage 4")
|
131 |
+
dbg.print("")
|
132 |
+
|
133 |
+
if img_height == img_height_key and img_width == img_width_key:
|
134 |
+
dbg.print("!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!")
|
135 |
+
dbg.print("!! The size of frame and img2img_key matched.")
|
136 |
+
dbg.print("!! You can skip this stage.")
|
137 |
+
|
138 |
+
dbg.print("!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!")
|
139 |
+
dbg.print("0. Enable the following item")
|
140 |
+
dbg.print("Settings ->")
|
141 |
+
dbg.print(" Saving images/grids ->")
|
142 |
+
dbg.print(" Use original name for output filename during batch process in extras tab")
|
143 |
+
dbg.print("!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!")
|
144 |
+
dbg.print("1. If \"img2img_upscale_key\" directory already exists in the %s, delete it manually before executing."%(project_dir))
|
145 |
+
dbg.print("2. Go to Extras tab")
|
146 |
+
dbg.print("3. Go to Batch from Directory tab")
|
147 |
+
dbg.print("4. Fill in the \"Input directory\" field with [" + img2img_key_path + "]" )
|
148 |
+
dbg.print("5. Fill in the \"Output directory\" field with [" + img2img_upscale_key_path + "]" )
|
149 |
+
dbg.print("6. Go to Scale to tab")
|
150 |
+
dbg.print("7. Fill in the \"Width\" field with [" + str(img_width) + "]" )
|
151 |
+
dbg.print("8. Fill in the \"Height\" field with [" + str(img_height) + "]" )
|
152 |
+
dbg.print("9. Fill in the remaining configuration fields of Upscaler.")
|
153 |
+
dbg.print("10. Generate")
|
154 |
+
dbg.print("!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!")
|
155 |
+
return process_end( dbg, "" )
|
156 |
+
elif stage_index == 5:
|
157 |
+
ebsynth_utility_stage5(dbg, project_args, is_invert_mask)
|
158 |
+
elif stage_index == 6:
|
159 |
+
|
160 |
+
if is_invert_mask:
|
161 |
+
project_dir = inv_path
|
162 |
+
|
163 |
+
dbg.print("stage 6")
|
164 |
+
dbg.print("")
|
165 |
+
dbg.print("!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!")
|
166 |
+
dbg.print("Running ebsynth.(on your self)")
|
167 |
+
dbg.print("Open the generated .ebs under %s and press [Run All] button."%(project_dir))
|
168 |
+
dbg.print("If ""out-*"" directory already exists in the %s, delete it manually before executing."%(project_dir))
|
169 |
+
dbg.print("If multiple .ebs files are generated, run them all.")
|
170 |
+
dbg.print("(I recommend associating the .ebs file with EbSynth.exe.)")
|
171 |
+
dbg.print("!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!")
|
172 |
+
return process_end( dbg, "" )
|
173 |
+
elif stage_index == 7:
|
174 |
+
ebsynth_utility_stage7(dbg, project_args, blend_rate, export_type, is_invert_mask)
|
175 |
+
elif stage_index == 8:
|
176 |
+
if mask_mode != "Normal":
|
177 |
+
dbg.print("!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!")
|
178 |
+
dbg.print("Please reset [configuration]->[etc]->[Mask Mode] to Normal.")
|
179 |
+
dbg.print("!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!")
|
180 |
+
return process_end( dbg, "" )
|
181 |
+
ebsynth_utility_stage8(dbg, project_args, bg_src, bg_type, mask_blur_size, mask_threshold, fg_transparency, export_type)
|
182 |
+
else:
|
183 |
+
pass
|
184 |
+
|
185 |
+
return process_end( dbg, info )
|
ebsynth_utility/imgs/clipseg.png
ADDED
![]() |
ebsynth_utility/imgs/controlnet_0.png
ADDED
![]() |
ebsynth_utility/imgs/controlnet_1.png
ADDED
![]() |
ebsynth_utility/imgs/controlnet_option_in_ebsynthutil.png
ADDED
![]() |
ebsynth_utility/imgs/controlnet_setting.png
ADDED
![]() |
ebsynth_utility/imgs/sample1.mp4
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:9c5458eea82a691a584af26f51d1db728092069a3409c6f9eb2dd14fd2b71173
|
3 |
+
size 4824162
|
ebsynth_utility/imgs/sample2.mp4
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:537b8331b74d8ea49ee580aed138d460735ef897ab31ca694031d7a56d99ff72
|
3 |
+
size 2920523
|
ebsynth_utility/imgs/sample3.mp4
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:c49739c2ef1f2ecaf14453f463e46b1a05de1688ce22b50200563a03b1758ddf
|
3 |
+
size 5161880
|
ebsynth_utility/imgs/sample4.mp4
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:62ed25263b6e5328a49460714c0b6e6ac46759921c87c91850f749f5bf068cfa
|
3 |
+
size 5617838
|
ebsynth_utility/imgs/sample5.mp4
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:4e429cfef8b3ed7829ce3219895fcfdbbe94e1494a2e4dcd87988e03509c8d50
|
3 |
+
size 4190467
|
ebsynth_utility/imgs/sample6.mp4
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:fb9a9ea8662ef1b7fc7151b987006eef8dd3598e320242bd87a2838ac8733df6
|
3 |
+
size 6890883
|
ebsynth_utility/imgs/sample_anyaheh.mp4
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:4de4e9b9758cefe28c430f909da9dfc086e5b3510e9d0aa7becab7b4be355447
|
3 |
+
size 12159686
|
ebsynth_utility/imgs/sample_autotag.mp4
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:4e904d68fc0fd9ac09ce153a9d54e9f1ce9f8db7cf5e96109c496f7e64924c92
|
3 |
+
size 7058129
|
ebsynth_utility/imgs/sample_clipseg.mp4
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:17701c5c3a376d3c4cf8ce0acfb991033830d56670ca3178eedd6e671e096af3
|
3 |
+
size 10249706
|
ebsynth_utility/install.py
ADDED
@@ -0,0 +1,24 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
import launch
|
2 |
+
|
3 |
+
def update_transparent_background():
|
4 |
+
from importlib.metadata import version as meta_version
|
5 |
+
from packaging import version
|
6 |
+
v = meta_version("transparent-background")
|
7 |
+
print("current transparent-background " + v)
|
8 |
+
if version.parse(v) < version.parse('1.2.3'):
|
9 |
+
launch.run_pip("install -U transparent-background", "update transparent-background version for Ebsynth Utility")
|
10 |
+
|
11 |
+
if not launch.is_installed("transparent_background"):
|
12 |
+
launch.run_pip("install transparent-background", "requirements for Ebsynth Utility")
|
13 |
+
|
14 |
+
update_transparent_background()
|
15 |
+
|
16 |
+
if not launch.is_installed("IPython"):
|
17 |
+
launch.run_pip("install ipython", "requirements for Ebsynth Utility")
|
18 |
+
|
19 |
+
if not launch.is_installed("seaborn"):
|
20 |
+
launch.run_pip("install ""seaborn>=0.11.0""", "requirements for Ebsynth Utility")
|
21 |
+
|
22 |
+
if not launch.is_installed("color_matcher"):
|
23 |
+
launch.run_pip("install color-matcher", "requirements for Ebsynth Utility")
|
24 |
+
|
ebsynth_utility/sample/add_token.txt
ADDED
@@ -0,0 +1,54 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
[
|
2 |
+
{
|
3 |
+
"target":"smile",
|
4 |
+
"min_score":0.5,
|
5 |
+
"token": ["lottalewds_v0", "1.2"],
|
6 |
+
"type":"lora"
|
7 |
+
},
|
8 |
+
{
|
9 |
+
"target":"smile",
|
10 |
+
"min_score":0.5,
|
11 |
+
"token": ["anyahehface", "score*1.2"],
|
12 |
+
"type":"normal"
|
13 |
+
},
|
14 |
+
{
|
15 |
+
"target":"smile",
|
16 |
+
"min_score":0.5,
|
17 |
+
"token": ["wicked smug", "score*1.2"],
|
18 |
+
"type":"normal"
|
19 |
+
},
|
20 |
+
{
|
21 |
+
"target":"smile",
|
22 |
+
"min_score":0.5,
|
23 |
+
"token": ["half closed eyes", "0.2 + score*0.3"],
|
24 |
+
"type":"normal"
|
25 |
+
},
|
26 |
+
|
27 |
+
|
28 |
+
|
29 |
+
{
|
30 |
+
"target":"test_token",
|
31 |
+
"min_score":0.8,
|
32 |
+
"token": ["lora_name_A", "0.5"],
|
33 |
+
"type":"lora"
|
34 |
+
},
|
35 |
+
{
|
36 |
+
"target":"test_token",
|
37 |
+
"min_score":0.5,
|
38 |
+
"token": ["bbbb", "score - 0.1"],
|
39 |
+
"type":"normal"
|
40 |
+
},
|
41 |
+
{
|
42 |
+
"target":"test_token2",
|
43 |
+
"min_score":0.8,
|
44 |
+
"token": ["hypernet_name_A", "score"],
|
45 |
+
"type":"hypernet"
|
46 |
+
},
|
47 |
+
{
|
48 |
+
"target":"test_token3",
|
49 |
+
"min_score":0.0,
|
50 |
+
"token": ["dddd", "score"],
|
51 |
+
"type":"normal"
|
52 |
+
}
|
53 |
+
]
|
54 |
+
|
ebsynth_utility/sample/blacklist.txt
ADDED
@@ -0,0 +1,10 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
motion_blur
|
2 |
+
blurry
|
3 |
+
realistic
|
4 |
+
depth_of_field
|
5 |
+
mountain
|
6 |
+
tree
|
7 |
+
water
|
8 |
+
underwater
|
9 |
+
tongue
|
10 |
+
tongue_out
|
ebsynth_utility/scripts/__pycache__/custom_script.cpython-310.pyc
ADDED
Binary file (25.8 kB). View file
|
|
ebsynth_utility/scripts/__pycache__/ui.cpython-310.pyc
ADDED
Binary file (10.2 kB). View file
|
|
ebsynth_utility/scripts/custom_script.py
ADDED
@@ -0,0 +1,1012 @@
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|
|
|
1 |
+
import modules.scripts as scripts
|
2 |
+
import gradio as gr
|
3 |
+
import os
|
4 |
+
import torch
|
5 |
+
import random
|
6 |
+
import time
|
7 |
+
import pprint
|
8 |
+
import shutil
|
9 |
+
|
10 |
+
from modules.processing import process_images,Processed
|
11 |
+
from modules.paths import models_path
|
12 |
+
from modules.textual_inversion import autocrop
|
13 |
+
import modules.images
|
14 |
+
from modules import shared,deepbooru,masking
|
15 |
+
import cv2
|
16 |
+
import copy
|
17 |
+
import numpy as np
|
18 |
+
from PIL import Image,ImageOps
|
19 |
+
import glob
|
20 |
+
import requests
|
21 |
+
import json
|
22 |
+
import re
|
23 |
+
from extensions.ebsynth_utility.calculator import CalcParser,ParseError
|
24 |
+
|
25 |
+
def get_my_dir():
|
26 |
+
if os.path.isdir("extensions/ebsynth_utility"):
|
27 |
+
return "extensions/ebsynth_utility"
|
28 |
+
return scripts.basedir()
|
29 |
+
|
30 |
+
def x_ceiling(value, step):
|
31 |
+
return -(-value // step) * step
|
32 |
+
|
33 |
+
def remove_pngs_in_dir(path):
|
34 |
+
if not os.path.isdir(path):
|
35 |
+
return
|
36 |
+
pngs = glob.glob( os.path.join(path, "*.png") )
|
37 |
+
for png in pngs:
|
38 |
+
os.remove(png)
|
39 |
+
|
40 |
+
def resize_img(img, w, h):
|
41 |
+
if img.shape[0] + img.shape[1] < h + w:
|
42 |
+
interpolation = interpolation=cv2.INTER_CUBIC
|
43 |
+
else:
|
44 |
+
interpolation = interpolation=cv2.INTER_AREA
|
45 |
+
|
46 |
+
return cv2.resize(img, (w, h), interpolation=interpolation)
|
47 |
+
|
48 |
+
def download_and_cache_models(dirname):
|
49 |
+
download_url = 'https://github.com/zymk9/yolov5_anime/blob/8b50add22dbd8224904221be3173390f56046794/weights/yolov5s_anime.pt?raw=true'
|
50 |
+
model_file_name = 'yolov5s_anime.pt'
|
51 |
+
|
52 |
+
if not os.path.exists(dirname):
|
53 |
+
os.makedirs(dirname)
|
54 |
+
|
55 |
+
cache_file = os.path.join(dirname, model_file_name)
|
56 |
+
if not os.path.exists(cache_file):
|
57 |
+
print(f"downloading face detection model from '{download_url}' to '{cache_file}'")
|
58 |
+
response = requests.get(download_url)
|
59 |
+
with open(cache_file, "wb") as f:
|
60 |
+
f.write(response.content)
|
61 |
+
|
62 |
+
if os.path.exists(cache_file):
|
63 |
+
return cache_file
|
64 |
+
return None
|
65 |
+
|
66 |
+
class Script(scripts.Script):
|
67 |
+
anime_face_detector = None
|
68 |
+
face_detector = None
|
69 |
+
face_merge_mask_filename = "face_crop_img2img_mask.png"
|
70 |
+
face_merge_mask_image = None
|
71 |
+
prompts_dir = ""
|
72 |
+
calc_parser = None
|
73 |
+
is_invert_mask = False
|
74 |
+
controlnet_weight = 0.5
|
75 |
+
controlnet_weight_for_face = 0.5
|
76 |
+
add_tag_replace_underscore = False
|
77 |
+
|
78 |
+
|
79 |
+
# The title of the script. This is what will be displayed in the dropdown menu.
|
80 |
+
def title(self):
|
81 |
+
return "ebsynth utility"
|
82 |
+
|
83 |
+
# Determines when the script should be shown in the dropdown menu via the
|
84 |
+
# returned value. As an example:
|
85 |
+
# is_img2img is True if the current tab is img2img, and False if it is txt2img.
|
86 |
+
# Thus, return is_img2img to only show the script on the img2img tab.
|
87 |
+
|
88 |
+
def show(self, is_img2img):
|
89 |
+
return is_img2img
|
90 |
+
|
91 |
+
# How the script's is displayed in the UI. See https://gradio.app/docs/#components
|
92 |
+
# for the different UI components you can use and how to create them.
|
93 |
+
# Most UI components can return a value, such as a boolean for a checkbox.
|
94 |
+
# The returned values are passed to the run method as parameters.
|
95 |
+
|
96 |
+
def ui(self, is_img2img):
|
97 |
+
with gr.Column(variant='panel'):
|
98 |
+
with gr.Column():
|
99 |
+
project_dir = gr.Textbox(label='Project directory', lines=1)
|
100 |
+
generation_test = gr.Checkbox(False, label="Generation TEST!!(Ignore Project directory and use the image and mask specified in the main UI)")
|
101 |
+
|
102 |
+
with gr.Accordion("Mask option"):
|
103 |
+
mask_mode = gr.Dropdown(choices=["Normal","Invert","None","Don't Override"], value="Normal" ,label="Mask Mode(Override img2img Mask mode)")
|
104 |
+
inpaint_area = gr.Dropdown(choices=["Whole picture","Only masked","Don't Override"], type = "index", value="Only masked" ,label="Inpaint Area(Override img2img Inpaint area)")
|
105 |
+
use_depth = gr.Checkbox(True, label="Use Depth Map If exists in /video_key_depth")
|
106 |
+
gr.HTML(value="<p style='margin-bottom: 0.7em'>\
|
107 |
+
See \
|
108 |
+
<font color=\"blue\"><a href=\"https://github.com/thygate/stable-diffusion-webui-depthmap-script\">[here]</a></font> for depth map.\
|
109 |
+
</p>")
|
110 |
+
|
111 |
+
with gr.Accordion("ControlNet option"):
|
112 |
+
controlnet_weight = gr.Slider(minimum=0.0, maximum=2.0, step=0.01, value=0.5, label="Control Net Weight")
|
113 |
+
controlnet_weight_for_face = gr.Slider(minimum=0.0, maximum=2.0, step=0.01, value=0.5, label="Control Net Weight For Face")
|
114 |
+
use_preprocess_img = gr.Checkbox(True, label="Use Preprocess image If exists in /controlnet_preprocess")
|
115 |
+
gr.HTML(value="<p style='margin-bottom: 0.7em'>\
|
116 |
+
Please enable the following settings to use controlnet from this script.<br>\
|
117 |
+
<font color=\"red\">\
|
118 |
+
Settings->ControlNet->Allow other script to control this extension\
|
119 |
+
</font>\
|
120 |
+
</p>")
|
121 |
+
|
122 |
+
with gr.Accordion("Loopback option"):
|
123 |
+
img2img_repeat_count = gr.Slider(minimum=1, maximum=30, step=1, value=1, label="Img2Img Repeat Count (Loop Back)")
|
124 |
+
inc_seed = gr.Slider(minimum=0, maximum=9999999, step=1, value=1, label="Add N to seed when repeating ")
|
125 |
+
|
126 |
+
with gr.Accordion("Auto Tagging option"):
|
127 |
+
auto_tag_mode = gr.Dropdown(choices=["None","DeepDanbooru","CLIP"], value="None" ,label="Auto Tagging")
|
128 |
+
add_tag_to_head = gr.Checkbox(False, label="Add additional prompts to the head")
|
129 |
+
add_tag_replace_underscore = gr.Checkbox(False, label="Replace '_' with ' '(Does not affect the function to add tokens using add_token.txt.)")
|
130 |
+
gr.HTML(value="<p style='margin-bottom: 0.7em'>\
|
131 |
+
The results are stored in timestamp_prompts.txt.<br>\
|
132 |
+
If you want to use the same tagging results the next time you run img2img, rename the file to prompts.txt<br>\
|
133 |
+
Recommend enabling the following settings.<br>\
|
134 |
+
<font color=\"red\">\
|
135 |
+
Settings->Interrogate Option->Interrogate: include ranks of model tags matches in results\
|
136 |
+
</font>\
|
137 |
+
</p>")
|
138 |
+
|
139 |
+
with gr.Accordion("Face Crop option"):
|
140 |
+
is_facecrop = gr.Checkbox(False, label="use Face Crop img2img")
|
141 |
+
|
142 |
+
with gr.Row():
|
143 |
+
face_detection_method = gr.Dropdown(choices=["YuNet","Yolov5_anime"], value="YuNet" ,label="Face Detection Method")
|
144 |
+
gr.HTML(value="<p style='margin-bottom: 0.7em'>\
|
145 |
+
If loading of the Yolov5_anime model fails, check\
|
146 |
+
<font color=\"blue\"><a href=\"https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/2235\">[this]</a></font> solution.\
|
147 |
+
</p>")
|
148 |
+
face_crop_resolution = gr.Slider(minimum=128, maximum=2048, step=1, value=512, label="Face Crop Resolution")
|
149 |
+
max_crop_size = gr.Slider(minimum=0, maximum=2048, step=1, value=1024, label="Max Crop Size")
|
150 |
+
face_denoising_strength = gr.Slider(minimum=0.00, maximum=1.00, step=0.01, value=0.5, label="Face Denoising Strength")
|
151 |
+
face_area_magnification = gr.Slider(minimum=1.00, maximum=10.00, step=0.01, value=1.5, label="Face Area Magnification ")
|
152 |
+
disable_facecrop_lpbk_last_time = gr.Checkbox(False, label="Disable at the last loopback time")
|
153 |
+
|
154 |
+
with gr.Column():
|
155 |
+
enable_face_prompt = gr.Checkbox(False, label="Enable Face Prompt")
|
156 |
+
face_prompt = gr.Textbox(label="Face Prompt", show_label=False, lines=2,
|
157 |
+
placeholder="Prompt for Face",
|
158 |
+
value = "face close up,"
|
159 |
+
)
|
160 |
+
|
161 |
+
return [project_dir, generation_test, mask_mode, inpaint_area, use_depth, img2img_repeat_count, inc_seed, auto_tag_mode, add_tag_to_head, add_tag_replace_underscore, is_facecrop, face_detection_method, face_crop_resolution, max_crop_size, face_denoising_strength, face_area_magnification, enable_face_prompt, face_prompt, controlnet_weight, controlnet_weight_for_face, disable_facecrop_lpbk_last_time,use_preprocess_img]
|
162 |
+
|
163 |
+
|
164 |
+
def detect_face_from_img(self, img_array):
|
165 |
+
if not self.face_detector:
|
166 |
+
dnn_model_path = autocrop.download_and_cache_models(os.path.join(models_path, "opencv"))
|
167 |
+
self.face_detector = cv2.FaceDetectorYN.create(dnn_model_path, "", (0, 0))
|
168 |
+
|
169 |
+
self.face_detector.setInputSize((img_array.shape[1], img_array.shape[0]))
|
170 |
+
_, result = self.face_detector.detect(img_array)
|
171 |
+
return result
|
172 |
+
|
173 |
+
def detect_anime_face_from_img(self, img_array):
|
174 |
+
import sys
|
175 |
+
|
176 |
+
if not self.anime_face_detector:
|
177 |
+
if 'models' in sys.modules:
|
178 |
+
del sys.modules['models']
|
179 |
+
|
180 |
+
anime_model_path = download_and_cache_models(os.path.join(models_path, "yolov5_anime"))
|
181 |
+
|
182 |
+
if not os.path.isfile(anime_model_path):
|
183 |
+
print( "WARNING!! " + anime_model_path + " not found.")
|
184 |
+
print( "use YuNet instead.")
|
185 |
+
return self.detect_face_from_img(img_array)
|
186 |
+
|
187 |
+
self.anime_face_detector = torch.hub.load('ultralytics/yolov5', 'custom', path=anime_model_path)
|
188 |
+
|
189 |
+
# warmup
|
190 |
+
test = np.zeros([512,512,3],dtype=np.uint8)
|
191 |
+
_ = self.anime_face_detector(test)
|
192 |
+
|
193 |
+
result = self.anime_face_detector(img_array)
|
194 |
+
#models.common.Detections
|
195 |
+
faces = []
|
196 |
+
for x_c, y_c, w, h, _, _ in result.xywh[0].tolist():
|
197 |
+
faces.append( [ x_c - w/2 , y_c - h/2, w, h ] )
|
198 |
+
|
199 |
+
return faces
|
200 |
+
|
201 |
+
def detect_face(self, img, mask, face_detection_method, max_crop_size):
|
202 |
+
img_array = np.array(img)
|
203 |
+
|
204 |
+
# image without alpha
|
205 |
+
if img_array.shape[2] == 4:
|
206 |
+
img_array = img_array[:,:,:3]
|
207 |
+
|
208 |
+
if mask is not None:
|
209 |
+
if self.is_invert_mask:
|
210 |
+
mask = ImageOps.invert(mask)
|
211 |
+
mask_array = np.array(mask)/255
|
212 |
+
if mask_array.ndim == 2:
|
213 |
+
mask_array = mask_array[:, :, np.newaxis]
|
214 |
+
|
215 |
+
if mask_array.shape[2] == 4:
|
216 |
+
mask_array = mask_array[:,:,:3]
|
217 |
+
|
218 |
+
img_array = mask_array * img_array
|
219 |
+
img_array = img_array.astype(np.uint8)
|
220 |
+
|
221 |
+
if face_detection_method == "YuNet":
|
222 |
+
faces = self.detect_face_from_img(img_array)
|
223 |
+
elif face_detection_method == "Yolov5_anime":
|
224 |
+
faces = self.detect_anime_face_from_img(img_array)
|
225 |
+
else:
|
226 |
+
faces = self.detect_face_from_img(img_array)
|
227 |
+
|
228 |
+
if faces is None or len(faces) == 0:
|
229 |
+
return []
|
230 |
+
|
231 |
+
face_coords = []
|
232 |
+
for face in faces:
|
233 |
+
x = int(face[0])
|
234 |
+
y = int(face[1])
|
235 |
+
w = int(face[2])
|
236 |
+
h = int(face[3])
|
237 |
+
if max(w,h) > max_crop_size:
|
238 |
+
print("ignore big face")
|
239 |
+
continue
|
240 |
+
if w == 0 or h == 0:
|
241 |
+
print("ignore w,h = 0 face")
|
242 |
+
continue
|
243 |
+
|
244 |
+
face_coords.append( [ x/img_array.shape[1],y/img_array.shape[0],w/img_array.shape[1],h/img_array.shape[0]] )
|
245 |
+
|
246 |
+
return face_coords
|
247 |
+
|
248 |
+
def get_mask(self):
|
249 |
+
def create_mask( output, x_rate, y_rate, k_size ):
|
250 |
+
img = np.zeros((512, 512, 3))
|
251 |
+
img = cv2.ellipse(img, ((256, 256), (int(512 * x_rate), int(512 * y_rate)), 0), (255, 255, 255), thickness=-1)
|
252 |
+
img = cv2.GaussianBlur(img, (k_size, k_size), 0)
|
253 |
+
cv2.imwrite(output, img)
|
254 |
+
|
255 |
+
if self.face_merge_mask_image is None:
|
256 |
+
mask_file_path = os.path.join( get_my_dir() , self.face_merge_mask_filename)
|
257 |
+
if not os.path.isfile(mask_file_path):
|
258 |
+
create_mask( mask_file_path, 0.9, 0.9, 91)
|
259 |
+
|
260 |
+
m = cv2.imread( mask_file_path )[:,:,0]
|
261 |
+
m = m[:, :, np.newaxis]
|
262 |
+
self.face_merge_mask_image = m / 255
|
263 |
+
|
264 |
+
return self.face_merge_mask_image
|
265 |
+
|
266 |
+
def face_img_crop(self, img, face_coords,face_area_magnification):
|
267 |
+
img_array = np.array(img)
|
268 |
+
face_imgs =[]
|
269 |
+
new_coords = []
|
270 |
+
|
271 |
+
for face in face_coords:
|
272 |
+
x = int(face[0] * img_array.shape[1])
|
273 |
+
y = int(face[1] * img_array.shape[0])
|
274 |
+
w = int(face[2] * img_array.shape[1])
|
275 |
+
h = int(face[3] * img_array.shape[0])
|
276 |
+
print([x,y,w,h])
|
277 |
+
|
278 |
+
cx = x + int(w/2)
|
279 |
+
cy = y + int(h/2)
|
280 |
+
|
281 |
+
x = cx - int(w*face_area_magnification / 2)
|
282 |
+
x = x if x > 0 else 0
|
283 |
+
w = cx + int(w*face_area_magnification / 2) - x
|
284 |
+
w = w if x+w < img.width else img.width - x
|
285 |
+
|
286 |
+
y = cy - int(h*face_area_magnification / 2)
|
287 |
+
y = y if y > 0 else 0
|
288 |
+
h = cy + int(h*face_area_magnification / 2) - y
|
289 |
+
h = h if y+h < img.height else img.height - y
|
290 |
+
|
291 |
+
print([x,y,w,h])
|
292 |
+
|
293 |
+
face_imgs.append( img_array[y: y+h, x: x+w] )
|
294 |
+
new_coords.append( [x,y,w,h] )
|
295 |
+
|
296 |
+
resized = []
|
297 |
+
for face_img in face_imgs:
|
298 |
+
if face_img.shape[1] < face_img.shape[0]:
|
299 |
+
re_w = self.face_crop_resolution
|
300 |
+
re_h = int(x_ceiling( (self.face_crop_resolution / face_img.shape[1]) * face_img.shape[0] , 64))
|
301 |
+
else:
|
302 |
+
re_w = int(x_ceiling( (self.face_crop_resolution / face_img.shape[0]) * face_img.shape[1] , 64))
|
303 |
+
re_h = self.face_crop_resolution
|
304 |
+
|
305 |
+
face_img = resize_img(face_img, re_w, re_h)
|
306 |
+
resized.append( Image.fromarray(face_img))
|
307 |
+
|
308 |
+
return resized, new_coords
|
309 |
+
|
310 |
+
def face_crop_img2img(self, p, face_coords, face_denoising_strength, face_area_magnification, enable_face_prompt, face_prompt, controlnet_input_img, controlnet_input_face_imgs, preprocess_img_exist):
|
311 |
+
|
312 |
+
def merge_face(img, face_img, face_coord, base_img_size, mask):
|
313 |
+
x_rate = img.width / base_img_size[0]
|
314 |
+
y_rate = img.height / base_img_size[1]
|
315 |
+
|
316 |
+
img_array = np.array(img)
|
317 |
+
x = int(face_coord[0] * x_rate)
|
318 |
+
y = int(face_coord[1] * y_rate)
|
319 |
+
w = int(face_coord[2] * x_rate)
|
320 |
+
h = int(face_coord[3] * y_rate)
|
321 |
+
|
322 |
+
face_array = np.array(face_img)
|
323 |
+
face_array = resize_img(face_array, w, h)
|
324 |
+
mask = resize_img(mask, w, h)
|
325 |
+
if mask.ndim == 2:
|
326 |
+
mask = mask[:, :, np.newaxis]
|
327 |
+
|
328 |
+
bg = img_array[y: y+h, x: x+w]
|
329 |
+
img_array[y: y+h, x: x+w] = mask * face_array + (1-mask)*bg
|
330 |
+
|
331 |
+
return Image.fromarray(img_array)
|
332 |
+
|
333 |
+
base_img = p.init_images[0]
|
334 |
+
|
335 |
+
base_img_size = (base_img.width, base_img.height)
|
336 |
+
|
337 |
+
if face_coords is None or len(face_coords) == 0:
|
338 |
+
print("no face detected")
|
339 |
+
return process_images(p)
|
340 |
+
|
341 |
+
print(face_coords)
|
342 |
+
face_imgs, new_coords = self.face_img_crop(base_img, face_coords, face_area_magnification)
|
343 |
+
|
344 |
+
if not face_imgs:
|
345 |
+
return process_images(p)
|
346 |
+
|
347 |
+
face_p = copy.copy(p)
|
348 |
+
|
349 |
+
### img2img base img
|
350 |
+
proc = self.process_images(p, controlnet_input_img, self.controlnet_weight, preprocess_img_exist)
|
351 |
+
print(proc.seed)
|
352 |
+
|
353 |
+
### img2img for each face
|
354 |
+
face_img2img_results = []
|
355 |
+
|
356 |
+
for face, coord, controlnet_input_face in zip(face_imgs, new_coords, controlnet_input_face_imgs):
|
357 |
+
# cv2.imwrite("scripts/face.png", np.array(face)[:, :, ::-1])
|
358 |
+
face_p.init_images = [face]
|
359 |
+
face_p.width = face.width
|
360 |
+
face_p.height = face.height
|
361 |
+
face_p.denoising_strength = face_denoising_strength
|
362 |
+
|
363 |
+
if enable_face_prompt:
|
364 |
+
face_p.prompt = face_prompt
|
365 |
+
else:
|
366 |
+
face_p.prompt = "close-up face ," + face_p.prompt
|
367 |
+
|
368 |
+
if p.image_mask is not None:
|
369 |
+
x,y,w,h = coord
|
370 |
+
cropped_face_mask = Image.fromarray(np.array(p.image_mask)[y: y+h, x: x+w])
|
371 |
+
face_p.image_mask = modules.images.resize_image(0, cropped_face_mask, face.width, face.height)
|
372 |
+
|
373 |
+
face_proc = self.process_images(face_p, controlnet_input_face, self.controlnet_weight_for_face, preprocess_img_exist)
|
374 |
+
print(face_proc.seed)
|
375 |
+
|
376 |
+
face_img2img_results.append((face_proc.images[0], coord))
|
377 |
+
|
378 |
+
### merge faces
|
379 |
+
bg = proc.images[0]
|
380 |
+
mask = self.get_mask()
|
381 |
+
|
382 |
+
for face_img, coord in face_img2img_results:
|
383 |
+
bg = merge_face(bg, face_img, coord, base_img_size, mask)
|
384 |
+
|
385 |
+
proc.images[0] = bg
|
386 |
+
|
387 |
+
return proc
|
388 |
+
|
389 |
+
def get_depth_map(self, mask, depth_path ,img_basename, is_invert_mask):
|
390 |
+
depth_img_path = os.path.join( depth_path , img_basename )
|
391 |
+
|
392 |
+
depth = None
|
393 |
+
|
394 |
+
if os.path.isfile( depth_img_path ):
|
395 |
+
depth = Image.open(depth_img_path)
|
396 |
+
else:
|
397 |
+
# try 00001-0000.png
|
398 |
+
os.path.splitext(img_basename)[0]
|
399 |
+
depth_img_path = os.path.join( depth_path , os.path.splitext(img_basename)[0] + "-0000.png" )
|
400 |
+
if os.path.isfile( depth_img_path ):
|
401 |
+
depth = Image.open(depth_img_path)
|
402 |
+
|
403 |
+
if depth:
|
404 |
+
if mask:
|
405 |
+
mask_array = np.array(mask)
|
406 |
+
depth_array = np.array(depth)
|
407 |
+
|
408 |
+
if is_invert_mask == False:
|
409 |
+
depth_array[mask_array[:,:,0] == 0] = 0
|
410 |
+
else:
|
411 |
+
depth_array[mask_array[:,:,0] != 0] = 0
|
412 |
+
|
413 |
+
depth = Image.fromarray(depth_array)
|
414 |
+
|
415 |
+
tmp_path = os.path.join( depth_path , "tmp" )
|
416 |
+
os.makedirs(tmp_path, exist_ok=True)
|
417 |
+
tmp_path = os.path.join( tmp_path , img_basename )
|
418 |
+
depth_array = depth_array.astype(np.uint16)
|
419 |
+
cv2.imwrite(tmp_path, depth_array)
|
420 |
+
|
421 |
+
mask = depth
|
422 |
+
|
423 |
+
return depth!=None, mask
|
424 |
+
|
425 |
+
### auto tagging
|
426 |
+
debug_count = 0
|
427 |
+
|
428 |
+
def get_masked_image(self, image, mask_image):
|
429 |
+
|
430 |
+
if mask_image == None:
|
431 |
+
return image.convert("RGB")
|
432 |
+
|
433 |
+
mask = mask_image.convert('L')
|
434 |
+
if self.is_invert_mask:
|
435 |
+
mask = ImageOps.invert(mask)
|
436 |
+
crop_region = masking.get_crop_region(np.array(mask), 0)
|
437 |
+
# crop_region = masking.expand_crop_region(crop_region, self.width, self.height, mask.width, mask.height)
|
438 |
+
# x1, y1, x2, y2 = crop_region
|
439 |
+
image = image.crop(crop_region).convert("RGB")
|
440 |
+
mask = mask.crop(crop_region)
|
441 |
+
|
442 |
+
base_img = Image.new("RGB", image.size, (255, 190, 200))
|
443 |
+
|
444 |
+
image = Image.composite( image, base_img, mask )
|
445 |
+
|
446 |
+
# image.save("scripts/get_masked_image_test_"+ str(self.debug_count) + ".png")
|
447 |
+
# self.debug_count += 1
|
448 |
+
|
449 |
+
return image
|
450 |
+
|
451 |
+
def interrogate_deepdanbooru(self, imgs, masks):
|
452 |
+
prompts_dict = {}
|
453 |
+
cause_err = False
|
454 |
+
|
455 |
+
try:
|
456 |
+
deepbooru.model.start()
|
457 |
+
|
458 |
+
for img,mask in zip(imgs,masks):
|
459 |
+
key = os.path.basename(img)
|
460 |
+
print(key + " interrogate deepdanbooru")
|
461 |
+
|
462 |
+
image = Image.open(img)
|
463 |
+
mask_image = Image.open(mask) if mask else None
|
464 |
+
image = self.get_masked_image(image, mask_image)
|
465 |
+
|
466 |
+
prompt = deepbooru.model.tag_multi(image)
|
467 |
+
|
468 |
+
prompts_dict[key] = prompt
|
469 |
+
except Exception as e:
|
470 |
+
import traceback
|
471 |
+
traceback.print_exc()
|
472 |
+
print(e)
|
473 |
+
cause_err = True
|
474 |
+
finally:
|
475 |
+
deepbooru.model.stop()
|
476 |
+
if cause_err:
|
477 |
+
print("Exception occurred during auto-tagging(deepdanbooru)")
|
478 |
+
return Processed()
|
479 |
+
|
480 |
+
return prompts_dict
|
481 |
+
|
482 |
+
|
483 |
+
def interrogate_clip(self, imgs, masks):
|
484 |
+
from modules import devices, shared, lowvram, paths
|
485 |
+
import importlib
|
486 |
+
import models
|
487 |
+
|
488 |
+
caption_list = []
|
489 |
+
prompts_dict = {}
|
490 |
+
cause_err = False
|
491 |
+
|
492 |
+
try:
|
493 |
+
if shared.cmd_opts.lowvram or shared.cmd_opts.medvram:
|
494 |
+
lowvram.send_everything_to_cpu()
|
495 |
+
devices.torch_gc()
|
496 |
+
|
497 |
+
with paths.Prioritize("BLIP"):
|
498 |
+
importlib.reload(models)
|
499 |
+
shared.interrogator.load()
|
500 |
+
|
501 |
+
for img,mask in zip(imgs,masks):
|
502 |
+
key = os.path.basename(img)
|
503 |
+
print(key + " generate caption")
|
504 |
+
|
505 |
+
image = Image.open(img)
|
506 |
+
mask_image = Image.open(mask) if mask else None
|
507 |
+
image = self.get_masked_image(image, mask_image)
|
508 |
+
|
509 |
+
caption = shared.interrogator.generate_caption(image)
|
510 |
+
caption_list.append(caption)
|
511 |
+
|
512 |
+
shared.interrogator.send_blip_to_ram()
|
513 |
+
devices.torch_gc()
|
514 |
+
|
515 |
+
for img,mask,caption in zip(imgs,masks,caption_list):
|
516 |
+
key = os.path.basename(img)
|
517 |
+
print(key + " interrogate clip")
|
518 |
+
|
519 |
+
image = Image.open(img)
|
520 |
+
mask_image = Image.open(mask) if mask else None
|
521 |
+
image = self.get_masked_image(image, mask_image)
|
522 |
+
|
523 |
+
clip_image = shared.interrogator.clip_preprocess(image).unsqueeze(0).type(shared.interrogator.dtype).to(devices.device_interrogate)
|
524 |
+
|
525 |
+
res = ""
|
526 |
+
|
527 |
+
with torch.no_grad(), devices.autocast():
|
528 |
+
image_features = shared.interrogator.clip_model.encode_image(clip_image).type(shared.interrogator.dtype)
|
529 |
+
image_features /= image_features.norm(dim=-1, keepdim=True)
|
530 |
+
|
531 |
+
for name, topn, items in shared.interrogator.categories():
|
532 |
+
matches = shared.interrogator.rank(image_features, items, top_count=topn)
|
533 |
+
for match, score in matches:
|
534 |
+
if shared.opts.interrogate_return_ranks:
|
535 |
+
res += f", ({match}:{score/100:.3f})"
|
536 |
+
else:
|
537 |
+
res += ", " + match
|
538 |
+
|
539 |
+
prompts_dict[key] = (caption + res)
|
540 |
+
|
541 |
+
except Exception as e:
|
542 |
+
import traceback
|
543 |
+
traceback.print_exc()
|
544 |
+
print(e)
|
545 |
+
cause_err = True
|
546 |
+
finally:
|
547 |
+
shared.interrogator.unload()
|
548 |
+
if cause_err:
|
549 |
+
print("Exception occurred during auto-tagging(blip/clip)")
|
550 |
+
return Processed()
|
551 |
+
|
552 |
+
return prompts_dict
|
553 |
+
|
554 |
+
|
555 |
+
def remove_reserved_token(self, token_list):
|
556 |
+
reserved_list = ["pink_background","simple_background","pink","pink_theme"]
|
557 |
+
|
558 |
+
result_list = []
|
559 |
+
|
560 |
+
head_token = token_list[0]
|
561 |
+
|
562 |
+
if head_token[2] == "normal":
|
563 |
+
head_token_str = head_token[0].replace('pink background', '')
|
564 |
+
token_list[0] = (head_token_str, head_token[1], head_token[2])
|
565 |
+
|
566 |
+
for token in token_list:
|
567 |
+
if token[0] in reserved_list:
|
568 |
+
continue
|
569 |
+
result_list.append(token)
|
570 |
+
|
571 |
+
return result_list
|
572 |
+
|
573 |
+
def remove_blacklisted_token(self, token_list):
|
574 |
+
black_list_path = os.path.join(self.prompts_dir, "blacklist.txt")
|
575 |
+
if not os.path.isfile(black_list_path):
|
576 |
+
print(black_list_path + " not found.")
|
577 |
+
return token_list
|
578 |
+
|
579 |
+
with open(black_list_path) as f:
|
580 |
+
black_list = [s.strip() for s in f.readlines()]
|
581 |
+
|
582 |
+
result_list = []
|
583 |
+
|
584 |
+
for token in token_list:
|
585 |
+
if token[0] in black_list:
|
586 |
+
continue
|
587 |
+
result_list.append(token)
|
588 |
+
|
589 |
+
token_list = result_list
|
590 |
+
|
591 |
+
return token_list
|
592 |
+
|
593 |
+
def add_token(self, token_list):
|
594 |
+
add_list_path = os.path.join(self.prompts_dir, "add_token.txt")
|
595 |
+
if not os.path.isfile(add_list_path):
|
596 |
+
print(add_list_path + " not found.")
|
597 |
+
|
598 |
+
if self.add_tag_replace_underscore:
|
599 |
+
token_list = [ (x[0].replace("_"," "), x[1], x[2]) for x in token_list ]
|
600 |
+
|
601 |
+
return token_list
|
602 |
+
|
603 |
+
if not self.calc_parser:
|
604 |
+
self.calc_parser = CalcParser()
|
605 |
+
|
606 |
+
with open(add_list_path) as f:
|
607 |
+
add_list = json.load(f)
|
608 |
+
'''
|
609 |
+
[
|
610 |
+
{
|
611 |
+
"target":"test_token",
|
612 |
+
"min_score":0.8,
|
613 |
+
"token": ["lora_name_A", "0.5"],
|
614 |
+
"type":"lora"
|
615 |
+
},
|
616 |
+
{
|
617 |
+
"target":"test_token",
|
618 |
+
"min_score":0.5,
|
619 |
+
"token": ["bbbb", "score - 0.1"],
|
620 |
+
"type":"normal"
|
621 |
+
},
|
622 |
+
{
|
623 |
+
"target":"test_token2",
|
624 |
+
"min_score":0.8,
|
625 |
+
"token": ["hypernet_name_A", "score"],
|
626 |
+
"type":"hypernet"
|
627 |
+
},
|
628 |
+
{
|
629 |
+
"target":"test_token3",
|
630 |
+
"min_score":0.0,
|
631 |
+
"token": ["dddd", "score"],
|
632 |
+
"type":"normal"
|
633 |
+
}
|
634 |
+
]
|
635 |
+
'''
|
636 |
+
result_list = []
|
637 |
+
|
638 |
+
for token in token_list:
|
639 |
+
for add_item in add_list:
|
640 |
+
if token[0] == add_item["target"]:
|
641 |
+
if token[1] > add_item["min_score"]:
|
642 |
+
# hit
|
643 |
+
formula = str(add_item["token"][1])
|
644 |
+
formula = formula.replace("score",str(token[1]))
|
645 |
+
print('Input: %s' % str(add_item["token"][1]))
|
646 |
+
|
647 |
+
try:
|
648 |
+
score = self.calc_parser.parse(formula)
|
649 |
+
score = round(score, 3)
|
650 |
+
except (ParseError, ZeroDivisionError) as e:
|
651 |
+
print('Input: %s' % str(add_item["token"][1]))
|
652 |
+
print('Error: %s' % e)
|
653 |
+
print("ignore this token")
|
654 |
+
continue
|
655 |
+
|
656 |
+
print("score = " + str(score))
|
657 |
+
result_list.append( ( add_item["token"][0], score, add_item["type"] ) )
|
658 |
+
|
659 |
+
if self.add_tag_replace_underscore:
|
660 |
+
token_list = [ (x[0].replace("_"," "), x[1], x[2]) for x in token_list ]
|
661 |
+
|
662 |
+
token_list = token_list + result_list
|
663 |
+
|
664 |
+
return token_list
|
665 |
+
|
666 |
+
def create_prompts_dict(self, imgs, masks, auto_tag_mode):
|
667 |
+
prompts_dict = {}
|
668 |
+
|
669 |
+
if auto_tag_mode == "DeepDanbooru":
|
670 |
+
raw_dict = self.interrogate_deepdanbooru(imgs, masks)
|
671 |
+
elif auto_tag_mode == "CLIP":
|
672 |
+
raw_dict = self.interrogate_clip(imgs, masks)
|
673 |
+
|
674 |
+
repatter = re.compile(r'\((.+)\:([0-9\.]+)\)')
|
675 |
+
|
676 |
+
for key, value_str in raw_dict.items():
|
677 |
+
value_list = [x.strip() for x in value_str.split(',')]
|
678 |
+
|
679 |
+
value = []
|
680 |
+
for v in value_list:
|
681 |
+
m = repatter.fullmatch(v)
|
682 |
+
if m:
|
683 |
+
value.append((m.group(1), float(m.group(2)), "normal"))
|
684 |
+
else:
|
685 |
+
value.append((v, 1, "no_score"))
|
686 |
+
|
687 |
+
# print(value)
|
688 |
+
value = self.remove_reserved_token(value)
|
689 |
+
# print(value)
|
690 |
+
value = self.remove_blacklisted_token(value)
|
691 |
+
# print(value)
|
692 |
+
value = self.add_token(value)
|
693 |
+
# print(value)
|
694 |
+
|
695 |
+
def create_token_str(x):
|
696 |
+
print(x)
|
697 |
+
if x[2] == "no_score":
|
698 |
+
return x[0]
|
699 |
+
elif x[2] == "lora":
|
700 |
+
return "<lora:" + x[0] + ":" + str(x[1]) + ">"
|
701 |
+
elif x[2] == "hypernet":
|
702 |
+
return "<hypernet:" + x[0] + ":" + str(x[1]) + ">"
|
703 |
+
else:
|
704 |
+
return "(" + x[0] + ":" + str(x[1]) + ")"
|
705 |
+
|
706 |
+
value_list = [create_token_str(x) for x in value]
|
707 |
+
value = ",".join(value_list)
|
708 |
+
|
709 |
+
prompts_dict[key] = value
|
710 |
+
|
711 |
+
return prompts_dict
|
712 |
+
|
713 |
+
def load_prompts_dict(self, imgs, default_token):
|
714 |
+
prompts_path = os.path.join(self.prompts_dir, "prompts.txt")
|
715 |
+
if not os.path.isfile(prompts_path):
|
716 |
+
print(prompts_path + " not found.")
|
717 |
+
return {}
|
718 |
+
|
719 |
+
prompts_dict = {}
|
720 |
+
|
721 |
+
print(prompts_path + " found!!")
|
722 |
+
print("skip auto tagging.")
|
723 |
+
|
724 |
+
with open(prompts_path) as f:
|
725 |
+
raw_dict = json.load(f)
|
726 |
+
prev_value = default_token
|
727 |
+
for img in imgs:
|
728 |
+
key = os.path.basename(img)
|
729 |
+
|
730 |
+
if key in raw_dict:
|
731 |
+
prompts_dict[key] = raw_dict[key]
|
732 |
+
prev_value = raw_dict[key]
|
733 |
+
else:
|
734 |
+
prompts_dict[key] = prev_value
|
735 |
+
|
736 |
+
return prompts_dict
|
737 |
+
|
738 |
+
def process_images(self, p, input_img, controlnet_weight, input_img_is_preprocessed):
|
739 |
+
p.control_net_input_image = input_img
|
740 |
+
p.control_net_weight = controlnet_weight
|
741 |
+
if input_img_is_preprocessed:
|
742 |
+
p.control_net_module = "none"
|
743 |
+
return process_images(p)
|
744 |
+
|
745 |
+
# This is where the additional processing is implemented. The parameters include
|
746 |
+
# self, the model object "p" (a StableDiffusionProcessing class, see
|
747 |
+
# processing.py), and the parameters returned by the ui method.
|
748 |
+
# Custom functions can be defined here, and additional libraries can be imported
|
749 |
+
# to be used in processing. The return value should be a Processed object, which is
|
750 |
+
# what is returned by the process_images method.
|
751 |
+
def run(self, p, project_dir, generation_test, mask_mode, inpaint_area, use_depth, img2img_repeat_count, inc_seed, auto_tag_mode, add_tag_to_head, add_tag_replace_underscore, is_facecrop, face_detection_method, face_crop_resolution, max_crop_size, face_denoising_strength, face_area_magnification, enable_face_prompt, face_prompt, controlnet_weight, controlnet_weight_for_face, disable_facecrop_lpbk_last_time, use_preprocess_img):
|
752 |
+
args = locals()
|
753 |
+
|
754 |
+
if generation_test:
|
755 |
+
print("generation_test")
|
756 |
+
test_proj_dir = os.path.join( get_my_dir() , "generation_test_proj")
|
757 |
+
os.makedirs(test_proj_dir, exist_ok=True)
|
758 |
+
test_video_key_path = os.path.join( test_proj_dir , "video_key")
|
759 |
+
os.makedirs(test_video_key_path, exist_ok=True)
|
760 |
+
test_video_mask_path = os.path.join( test_proj_dir , "video_mask")
|
761 |
+
os.makedirs(test_video_mask_path, exist_ok=True)
|
762 |
+
|
763 |
+
controlnet_input_path = os.path.join(test_proj_dir, "controlnet_input")
|
764 |
+
if os.path.isdir(controlnet_input_path):
|
765 |
+
shutil.rmtree(controlnet_input_path)
|
766 |
+
|
767 |
+
remove_pngs_in_dir(test_video_key_path)
|
768 |
+
remove_pngs_in_dir(test_video_mask_path)
|
769 |
+
|
770 |
+
test_base_img = p.init_images[0]
|
771 |
+
test_mask = p.image_mask
|
772 |
+
|
773 |
+
if test_base_img:
|
774 |
+
test_base_img.save( os.path.join( test_video_key_path , "00001.png") )
|
775 |
+
if test_mask:
|
776 |
+
test_mask.save( os.path.join( test_video_mask_path , "00001.png") )
|
777 |
+
|
778 |
+
project_dir = test_proj_dir
|
779 |
+
else:
|
780 |
+
if not os.path.isdir(project_dir):
|
781 |
+
print("project_dir not found")
|
782 |
+
return Processed()
|
783 |
+
|
784 |
+
self.controlnet_weight = controlnet_weight
|
785 |
+
self.controlnet_weight_for_face = controlnet_weight_for_face
|
786 |
+
|
787 |
+
self.add_tag_replace_underscore = add_tag_replace_underscore
|
788 |
+
self.face_crop_resolution = face_crop_resolution
|
789 |
+
|
790 |
+
if p.seed == -1:
|
791 |
+
p.seed = int(random.randrange(4294967294))
|
792 |
+
|
793 |
+
if mask_mode == "Normal":
|
794 |
+
p.inpainting_mask_invert = 0
|
795 |
+
elif mask_mode == "Invert":
|
796 |
+
p.inpainting_mask_invert = 1
|
797 |
+
|
798 |
+
if inpaint_area in (0,1): #"Whole picture","Only masked"
|
799 |
+
p.inpaint_full_res = inpaint_area
|
800 |
+
|
801 |
+
is_invert_mask = False
|
802 |
+
if mask_mode == "Invert":
|
803 |
+
is_invert_mask = True
|
804 |
+
|
805 |
+
inv_path = os.path.join(project_dir, "inv")
|
806 |
+
if not os.path.isdir(inv_path):
|
807 |
+
print("project_dir/inv not found")
|
808 |
+
return Processed()
|
809 |
+
|
810 |
+
org_key_path = os.path.join(inv_path, "video_key")
|
811 |
+
img2img_key_path = os.path.join(inv_path, "img2img_key")
|
812 |
+
depth_path = os.path.join(inv_path, "video_key_depth")
|
813 |
+
|
814 |
+
preprocess_path = os.path.join(inv_path, "controlnet_preprocess")
|
815 |
+
|
816 |
+
controlnet_input_path = os.path.join(inv_path, "controlnet_input")
|
817 |
+
|
818 |
+
self.prompts_dir = inv_path
|
819 |
+
self.is_invert_mask = True
|
820 |
+
else:
|
821 |
+
org_key_path = os.path.join(project_dir, "video_key")
|
822 |
+
img2img_key_path = os.path.join(project_dir, "img2img_key")
|
823 |
+
depth_path = os.path.join(project_dir, "video_key_depth")
|
824 |
+
|
825 |
+
preprocess_path = os.path.join(project_dir, "controlnet_preprocess")
|
826 |
+
|
827 |
+
controlnet_input_path = os.path.join(project_dir, "controlnet_input")
|
828 |
+
|
829 |
+
self.prompts_dir = project_dir
|
830 |
+
self.is_invert_mask = False
|
831 |
+
|
832 |
+
frame_mask_path = os.path.join(project_dir, "video_mask")
|
833 |
+
|
834 |
+
if not use_depth:
|
835 |
+
depth_path = None
|
836 |
+
|
837 |
+
if not os.path.isdir(org_key_path):
|
838 |
+
print(org_key_path + " not found")
|
839 |
+
print("Generate key frames first." if is_invert_mask == False else \
|
840 |
+
"Generate key frames first.(with [Ebsynth Utility] Tab -> [configuration] -> [etc]-> [Mask Mode] = Invert setting)")
|
841 |
+
return Processed()
|
842 |
+
|
843 |
+
if not os.path.isdir(controlnet_input_path):
|
844 |
+
print(controlnet_input_path + " not found")
|
845 |
+
print("copy {0} -> {1}".format(org_key_path,controlnet_input_path))
|
846 |
+
|
847 |
+
os.makedirs(controlnet_input_path, exist_ok=True)
|
848 |
+
|
849 |
+
imgs = glob.glob( os.path.join(org_key_path ,"*.png") )
|
850 |
+
for img in imgs:
|
851 |
+
img_basename = os.path.basename(img)
|
852 |
+
shutil.copy( img , os.path.join(controlnet_input_path, img_basename) )
|
853 |
+
|
854 |
+
remove_pngs_in_dir(img2img_key_path)
|
855 |
+
os.makedirs(img2img_key_path, exist_ok=True)
|
856 |
+
|
857 |
+
|
858 |
+
def get_mask_of_img(img):
|
859 |
+
img_basename = os.path.basename(img)
|
860 |
+
|
861 |
+
if mask_mode != "None":
|
862 |
+
mask_path = os.path.join( frame_mask_path , img_basename )
|
863 |
+
if os.path.isfile( mask_path ):
|
864 |
+
return mask_path
|
865 |
+
return ""
|
866 |
+
|
867 |
+
def get_pair_of_img(img, target_dir):
|
868 |
+
img_basename = os.path.basename(img)
|
869 |
+
|
870 |
+
pair_path = os.path.join( target_dir , img_basename )
|
871 |
+
if os.path.isfile( pair_path ):
|
872 |
+
return pair_path
|
873 |
+
print("!!! pair of "+ img + " not in " + target_dir)
|
874 |
+
return ""
|
875 |
+
|
876 |
+
def get_controlnet_input_img(img):
|
877 |
+
pair_img = get_pair_of_img(img, controlnet_input_path)
|
878 |
+
if not pair_img:
|
879 |
+
pair_img = get_pair_of_img(img, org_key_path)
|
880 |
+
return pair_img
|
881 |
+
|
882 |
+
imgs = glob.glob( os.path.join(org_key_path ,"*.png") )
|
883 |
+
masks = [ get_mask_of_img(i) for i in imgs ]
|
884 |
+
controlnet_input_imgs = [ get_controlnet_input_img(i) for i in imgs ]
|
885 |
+
|
886 |
+
for mask in masks:
|
887 |
+
m = cv2.imread(mask) if mask else None
|
888 |
+
if m is not None:
|
889 |
+
if m.max() == 0:
|
890 |
+
print("{0} blank mask found".format(mask))
|
891 |
+
if m.ndim == 2:
|
892 |
+
m[0,0] = 255
|
893 |
+
else:
|
894 |
+
m = m[:,:,:3]
|
895 |
+
m[0,0,0:3] = 255
|
896 |
+
cv2.imwrite(mask, m)
|
897 |
+
|
898 |
+
######################
|
899 |
+
# face crop
|
900 |
+
face_coords_dict={}
|
901 |
+
for img,mask in zip(imgs,masks):
|
902 |
+
face_detected = False
|
903 |
+
if is_facecrop:
|
904 |
+
image = Image.open(img)
|
905 |
+
mask_image = Image.open(mask) if mask else None
|
906 |
+
face_coords = self.detect_face(image, mask_image, face_detection_method, max_crop_size)
|
907 |
+
if face_coords is None or len(face_coords) == 0:
|
908 |
+
print("no face detected")
|
909 |
+
else:
|
910 |
+
print("face detected")
|
911 |
+
face_detected = True
|
912 |
+
|
913 |
+
key = os.path.basename(img)
|
914 |
+
face_coords_dict[key] = face_coords if face_detected else []
|
915 |
+
|
916 |
+
with open( os.path.join( project_dir if is_invert_mask == False else inv_path,"faces.txt" ), "w") as f:
|
917 |
+
f.write(json.dumps(face_coords_dict,indent=4))
|
918 |
+
|
919 |
+
######################
|
920 |
+
# prompts
|
921 |
+
prompts_dict = self.load_prompts_dict(imgs, p.prompt)
|
922 |
+
|
923 |
+
if not prompts_dict:
|
924 |
+
if auto_tag_mode != "None":
|
925 |
+
prompts_dict = self.create_prompts_dict(imgs, masks, auto_tag_mode)
|
926 |
+
|
927 |
+
for key, value in prompts_dict.items():
|
928 |
+
prompts_dict[key] = (value + "," + p.prompt) if add_tag_to_head else (p.prompt + "," + value)
|
929 |
+
|
930 |
+
else:
|
931 |
+
for img in imgs:
|
932 |
+
key = os.path.basename(img)
|
933 |
+
prompts_dict[key] = p.prompt
|
934 |
+
|
935 |
+
with open( os.path.join( project_dir if is_invert_mask == False else inv_path, time.strftime("%Y%m%d-%H%M%S_") + "prompts.txt" ), "w") as f:
|
936 |
+
f.write(json.dumps(prompts_dict,indent=4))
|
937 |
+
|
938 |
+
|
939 |
+
######################
|
940 |
+
# img2img
|
941 |
+
for img, mask, controlnet_input_img, face_coords, prompts in zip(imgs, masks, controlnet_input_imgs, face_coords_dict.values(), prompts_dict.values()):
|
942 |
+
|
943 |
+
# Generation cancelled.
|
944 |
+
if shared.state.interrupted:
|
945 |
+
print("Generation cancelled.")
|
946 |
+
break
|
947 |
+
|
948 |
+
image = Image.open(img)
|
949 |
+
mask_image = Image.open(mask) if mask else None
|
950 |
+
|
951 |
+
img_basename = os.path.basename(img)
|
952 |
+
|
953 |
+
_p = copy.copy(p)
|
954 |
+
|
955 |
+
_p.init_images=[image]
|
956 |
+
_p.image_mask = mask_image
|
957 |
+
_p.prompt = prompts
|
958 |
+
resized_mask = None
|
959 |
+
|
960 |
+
repeat_count = img2img_repeat_count
|
961 |
+
|
962 |
+
if mask_mode != "None" or use_depth:
|
963 |
+
if use_depth:
|
964 |
+
depth_found, _p.image_mask = self.get_depth_map( mask_image, depth_path ,img_basename, is_invert_mask )
|
965 |
+
mask_image = _p.image_mask
|
966 |
+
if depth_found:
|
967 |
+
_p.inpainting_mask_invert = 0
|
968 |
+
|
969 |
+
preprocess_img_exist = False
|
970 |
+
controlnet_input_base_img = Image.open(controlnet_input_img) if controlnet_input_img else None
|
971 |
+
|
972 |
+
if use_preprocess_img:
|
973 |
+
preprocess_img = os.path.join(preprocess_path, img_basename)
|
974 |
+
if os.path.isfile( preprocess_img ):
|
975 |
+
controlnet_input_base_img = Image.open(preprocess_img)
|
976 |
+
preprocess_img_exist = True
|
977 |
+
|
978 |
+
if face_coords:
|
979 |
+
controlnet_input_face_imgs, _ = self.face_img_crop(controlnet_input_base_img, face_coords, face_area_magnification)
|
980 |
+
|
981 |
+
while repeat_count > 0:
|
982 |
+
|
983 |
+
if disable_facecrop_lpbk_last_time:
|
984 |
+
if img2img_repeat_count > 1:
|
985 |
+
if repeat_count == 1:
|
986 |
+
face_coords = None
|
987 |
+
|
988 |
+
if face_coords:
|
989 |
+
proc = self.face_crop_img2img(_p, face_coords, face_denoising_strength, face_area_magnification, enable_face_prompt, face_prompt, controlnet_input_base_img, controlnet_input_face_imgs, preprocess_img_exist)
|
990 |
+
else:
|
991 |
+
proc = self.process_images(_p, controlnet_input_base_img, self.controlnet_weight, preprocess_img_exist)
|
992 |
+
print(proc.seed)
|
993 |
+
|
994 |
+
repeat_count -= 1
|
995 |
+
|
996 |
+
if repeat_count > 0:
|
997 |
+
_p.init_images=[proc.images[0]]
|
998 |
+
|
999 |
+
if mask_image is not None and resized_mask is None:
|
1000 |
+
resized_mask = resize_img(np.array(mask_image) , proc.images[0].width, proc.images[0].height)
|
1001 |
+
resized_mask = Image.fromarray(resized_mask)
|
1002 |
+
_p.image_mask = resized_mask
|
1003 |
+
_p.seed += inc_seed
|
1004 |
+
|
1005 |
+
proc.images[0].save( os.path.join( img2img_key_path , img_basename ) )
|
1006 |
+
|
1007 |
+
with open( os.path.join( project_dir if is_invert_mask == False else inv_path,"param.txt" ), "w") as f:
|
1008 |
+
f.write(pprint.pformat(proc.info))
|
1009 |
+
with open( os.path.join( project_dir if is_invert_mask == False else inv_path ,"args.txt" ), "w") as f:
|
1010 |
+
f.write(pprint.pformat(args))
|
1011 |
+
|
1012 |
+
return proc
|
ebsynth_utility/scripts/ui.py
ADDED
@@ -0,0 +1,199 @@
|
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|
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|
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|
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
|
2 |
+
import gradio as gr
|
3 |
+
|
4 |
+
from ebsynth_utility import ebsynth_utility_process
|
5 |
+
from modules import script_callbacks
|
6 |
+
from modules.call_queue import wrap_gradio_gpu_call
|
7 |
+
|
8 |
+
def on_ui_tabs():
|
9 |
+
|
10 |
+
with gr.Blocks(analytics_enabled=False) as ebs_interface:
|
11 |
+
with gr.Row().style(equal_height=False):
|
12 |
+
with gr.Column(variant='panel'):
|
13 |
+
|
14 |
+
with gr.Row():
|
15 |
+
with gr.Tabs(elem_id="ebs_settings"):
|
16 |
+
with gr.TabItem('project setting', elem_id='ebs_project_setting'):
|
17 |
+
project_dir = gr.Textbox(label='Project directory', lines=1)
|
18 |
+
original_movie_path = gr.Textbox(label='Original Movie Path', lines=1)
|
19 |
+
|
20 |
+
org_video = gr.Video(interactive=True, mirror_webcam=False)
|
21 |
+
def fn_upload_org_video(video):
|
22 |
+
return video
|
23 |
+
org_video.upload(fn_upload_org_video, org_video, original_movie_path)
|
24 |
+
gr.HTML(value="<p style='margin-bottom: 1.2em'>\
|
25 |
+
If you have trouble entering the video path manually, you can also use drag and drop.For large videos, please enter the path manually. \
|
26 |
+
</p>")
|
27 |
+
|
28 |
+
with gr.TabItem('configuration', elem_id='ebs_configuration'):
|
29 |
+
with gr.Tabs(elem_id="ebs_configuration_tab"):
|
30 |
+
with gr.TabItem(label="stage 1",elem_id='ebs_configuration_tab1'):
|
31 |
+
with gr.Row():
|
32 |
+
frame_width = gr.Number(value=-1, label="Frame Width", precision=0, interactive=True)
|
33 |
+
frame_height = gr.Number(value=-1, label="Frame Height", precision=0, interactive=True)
|
34 |
+
gr.HTML(value="<p style='margin-bottom: 1.2em'>\
|
35 |
+
-1 means that it is calculated automatically. If both are -1, the size will be the same as the source size. \
|
36 |
+
</p>")
|
37 |
+
|
38 |
+
st1_masking_method_index = gr.Radio(label='Masking Method', choices=["transparent-background","clipseg","transparent-background AND clipseg"], value="transparent-background", type="index")
|
39 |
+
|
40 |
+
with gr.Accordion(label="transparent-background options"):
|
41 |
+
st1_mask_threshold = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Mask Threshold', value=0.0)
|
42 |
+
|
43 |
+
# https://pypi.org/project/transparent-background/
|
44 |
+
gr.HTML(value="<p style='margin-bottom: 0.7em'>\
|
45 |
+
configuration for \
|
46 |
+
<font color=\"blue\"><a href=\"https://pypi.org/project/transparent-background\">[transparent-background]</a></font>\
|
47 |
+
</p>")
|
48 |
+
tb_use_fast_mode = gr.Checkbox(label="Use Fast Mode(It will be faster, but the quality of the mask will be lower.)", value=False)
|
49 |
+
tb_use_jit = gr.Checkbox(label="Use Jit", value=False)
|
50 |
+
|
51 |
+
with gr.Accordion(label="clipseg options"):
|
52 |
+
clipseg_mask_prompt = gr.Textbox(label='Mask Target (e.g., girl, cats)', lines=1)
|
53 |
+
clipseg_exclude_prompt = gr.Textbox(label='Exclude Target (e.g., finger, book)', lines=1)
|
54 |
+
clipseg_mask_threshold = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Mask Threshold', value=0.4)
|
55 |
+
clipseg_mask_blur_size = gr.Slider(minimum=0, maximum=150, step=1, label='Mask Blur Kernel Size(MedianBlur)', value=11)
|
56 |
+
clipseg_mask_blur_size2 = gr.Slider(minimum=0, maximum=150, step=1, label='Mask Blur Kernel Size(GaussianBlur)', value=11)
|
57 |
+
|
58 |
+
with gr.TabItem(label="stage 2", elem_id='ebs_configuration_tab2'):
|
59 |
+
key_min_gap = gr.Slider(minimum=0, maximum=500, step=1, label='Minimum keyframe gap', value=10)
|
60 |
+
key_max_gap = gr.Slider(minimum=0, maximum=1000, step=1, label='Maximum keyframe gap', value=300)
|
61 |
+
key_th = gr.Slider(minimum=0.0, maximum=100.0, step=0.1, label='Threshold of delta frame edge', value=8.5)
|
62 |
+
key_add_last_frame = gr.Checkbox(label="Add last frame to keyframes", value=True)
|
63 |
+
|
64 |
+
with gr.TabItem(label="stage 3.5", elem_id='ebs_configuration_tab3_5'):
|
65 |
+
gr.HTML(value="<p style='margin-bottom: 0.7em'>\
|
66 |
+
<font color=\"blue\"><a href=\"https://github.com/hahnec/color-matcher\">[color-matcher]</a></font>\
|
67 |
+
</p>")
|
68 |
+
|
69 |
+
color_matcher_method = gr.Radio(label='Color Transfer Method', choices=['default', 'hm', 'reinhard', 'mvgd', 'mkl', 'hm-mvgd-hm', 'hm-mkl-hm'], value="hm-mkl-hm", type="value")
|
70 |
+
color_matcher_ref_type = gr.Radio(label='Color Matcher Ref Image Type', choices=['original video frame', 'first frame of img2img result'], value="original video frame", type="index")
|
71 |
+
gr.HTML(value="<p style='margin-bottom: 0.7em'>\
|
72 |
+
<font color=\"red\">If an image is specified below, it will be used with highest priority.</font>\
|
73 |
+
</p>")
|
74 |
+
color_matcher_ref_image = gr.Image(label="Color Matcher Ref Image", source='upload', mirror_webcam=False, type='pil')
|
75 |
+
st3_5_use_mask = gr.Checkbox(label="Apply mask to the result", value=True)
|
76 |
+
st3_5_use_mask_ref = gr.Checkbox(label="Apply mask to the Ref Image", value=False)
|
77 |
+
st3_5_use_mask_org = gr.Checkbox(label="Apply mask to original image", value=False)
|
78 |
+
#st3_5_number_of_itr = gr.Slider(minimum=1, maximum=10, step=1, label='Number of iterations', value=1)
|
79 |
+
|
80 |
+
with gr.TabItem(label="stage 7", elem_id='ebs_configuration_tab7'):
|
81 |
+
blend_rate = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Crossfade blend rate', value=1.0)
|
82 |
+
export_type = gr.Dropdown(choices=["mp4","webm","gif","rawvideo"], value="mp4" ,label="Export type")
|
83 |
+
|
84 |
+
with gr.TabItem(label="stage 8", elem_id='ebs_configuration_tab8'):
|
85 |
+
bg_src = gr.Textbox(label='Background source(mp4 or directory containing images)', lines=1)
|
86 |
+
bg_type = gr.Dropdown(choices=["Fit video length","Loop"], value="Fit video length" ,label="Background type")
|
87 |
+
mask_blur_size = gr.Slider(minimum=0, maximum=150, step=1, label='Mask Blur Kernel Size', value=5)
|
88 |
+
mask_threshold = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Mask Threshold', value=0.0)
|
89 |
+
#is_transparent = gr.Checkbox(label="Is Transparent", value=True, visible = False)
|
90 |
+
fg_transparency = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Foreground Transparency', value=0.0)
|
91 |
+
|
92 |
+
with gr.TabItem(label="etc", elem_id='ebs_configuration_tab_etc'):
|
93 |
+
mask_mode = gr.Dropdown(choices=["Normal","Invert","None"], value="Normal" ,label="Mask Mode")
|
94 |
+
|
95 |
+
with gr.Column(variant='panel'):
|
96 |
+
with gr.Column(scale=1):
|
97 |
+
with gr.Group():
|
98 |
+
debug_info = gr.HTML(elem_id="ebs_info_area", value=".")
|
99 |
+
|
100 |
+
with gr.Column(scale=2):
|
101 |
+
stage_index = gr.Radio(label='Process Stage', choices=["stage 1","stage 2","stage 3","stage 3.5","stage 4","stage 5","stage 6","stage 7","stage 8"], value="stage 1", type="index")
|
102 |
+
gr.HTML(value="<p style='margin-bottom: 0.7em'>\
|
103 |
+
The process of creating a video can be divided into the following stages.<br>\
|
104 |
+
(Stage 3, 4, and 6 only show a guide and do nothing actual processing.)<br><br>\
|
105 |
+
<b>stage 1</b> <br>\
|
106 |
+
Extract frames from the original video. <br>\
|
107 |
+
Generate a mask image. <br><br>\
|
108 |
+
<b>stage 2</b> <br>\
|
109 |
+
Select keyframes to be given to ebsynth.<br><br>\
|
110 |
+
<b>stage 3</b> <br>\
|
111 |
+
img2img keyframes.<br><br>\
|
112 |
+
<b>stage 3.5</b> <br>\
|
113 |
+
(this is optional. Perform color correction on the img2img results and expect flickering to decrease. Or, you can simply change the color tone from the generated result.)<br><br>\
|
114 |
+
<b>stage 4</b> <br>\
|
115 |
+
and upscale to the size of the original video.<br><br>\
|
116 |
+
<b>stage 5</b> <br>\
|
117 |
+
Rename keyframes.<br>\
|
118 |
+
Generate .ebs file.(ebsynth project file)<br><br>\
|
119 |
+
<b>stage 6</b> <br>\
|
120 |
+
Running ebsynth.(on your self)<br>\
|
121 |
+
Open the generated .ebs under project directory and press [Run All] button. <br>\
|
122 |
+
If ""out-*"" directory already exists in the Project directory, delete it manually before executing.<br>\
|
123 |
+
If multiple .ebs files are generated, run them all.<br><br>\
|
124 |
+
<b>stage 7</b> <br>\
|
125 |
+
Concatenate each frame while crossfading.<br>\
|
126 |
+
Composite audio files extracted from the original video onto the concatenated video.<br><br>\
|
127 |
+
<b>stage 8</b> <br>\
|
128 |
+
This is an extra stage.<br>\
|
129 |
+
You can put any image or images or video you like in the background.<br>\
|
130 |
+
You can specify in this field -> [Ebsynth Utility]->[configuration]->[stage 8]->[Background source]<br>\
|
131 |
+
If you have already created a background video in Invert Mask Mode([Ebsynth Utility]->[configuration]->[etc]->[Mask Mode]),<br>\
|
132 |
+
You can specify \"path_to_project_dir/inv/crossfade_tmp\".<br>\
|
133 |
+
</p>")
|
134 |
+
|
135 |
+
with gr.Row():
|
136 |
+
generate_btn = gr.Button('Generate', elem_id="ebs_generate_btn", variant='primary')
|
137 |
+
|
138 |
+
with gr.Group():
|
139 |
+
html_info = gr.HTML()
|
140 |
+
|
141 |
+
|
142 |
+
ebs_args = dict(
|
143 |
+
fn=wrap_gradio_gpu_call(ebsynth_utility_process),
|
144 |
+
inputs=[
|
145 |
+
stage_index,
|
146 |
+
|
147 |
+
project_dir,
|
148 |
+
original_movie_path,
|
149 |
+
|
150 |
+
frame_width,
|
151 |
+
frame_height,
|
152 |
+
st1_masking_method_index,
|
153 |
+
st1_mask_threshold,
|
154 |
+
tb_use_fast_mode,
|
155 |
+
tb_use_jit,
|
156 |
+
clipseg_mask_prompt,
|
157 |
+
clipseg_exclude_prompt,
|
158 |
+
clipseg_mask_threshold,
|
159 |
+
clipseg_mask_blur_size,
|
160 |
+
clipseg_mask_blur_size2,
|
161 |
+
|
162 |
+
key_min_gap,
|
163 |
+
key_max_gap,
|
164 |
+
key_th,
|
165 |
+
key_add_last_frame,
|
166 |
+
|
167 |
+
color_matcher_method,
|
168 |
+
st3_5_use_mask,
|
169 |
+
st3_5_use_mask_ref,
|
170 |
+
st3_5_use_mask_org,
|
171 |
+
color_matcher_ref_type,
|
172 |
+
color_matcher_ref_image,
|
173 |
+
|
174 |
+
blend_rate,
|
175 |
+
export_type,
|
176 |
+
|
177 |
+
bg_src,
|
178 |
+
bg_type,
|
179 |
+
mask_blur_size,
|
180 |
+
mask_threshold,
|
181 |
+
fg_transparency,
|
182 |
+
|
183 |
+
mask_mode,
|
184 |
+
|
185 |
+
],
|
186 |
+
outputs=[
|
187 |
+
debug_info,
|
188 |
+
html_info,
|
189 |
+
],
|
190 |
+
show_progress=False,
|
191 |
+
)
|
192 |
+
generate_btn.click(**ebs_args)
|
193 |
+
|
194 |
+
return (ebs_interface, "Ebsynth Utility", "ebs_interface"),
|
195 |
+
|
196 |
+
|
197 |
+
|
198 |
+
script_callbacks.on_ui_tabs(on_ui_tabs)
|
199 |
+
|
ebsynth_utility/stage1.py
ADDED
@@ -0,0 +1,258 @@
|
|
|
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|
|
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|
|
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|
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|
|
|
|
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
import os
|
2 |
+
import subprocess
|
3 |
+
import glob
|
4 |
+
import cv2
|
5 |
+
import re
|
6 |
+
|
7 |
+
from transformers import AutoProcessor, CLIPSegForImageSegmentation
|
8 |
+
from PIL import Image
|
9 |
+
import torch
|
10 |
+
import numpy as np
|
11 |
+
|
12 |
+
|
13 |
+
def resize_img(img, w, h):
|
14 |
+
if img.shape[0] + img.shape[1] < h + w:
|
15 |
+
interpolation = interpolation=cv2.INTER_CUBIC
|
16 |
+
else:
|
17 |
+
interpolation = interpolation=cv2.INTER_AREA
|
18 |
+
|
19 |
+
return cv2.resize(img, (w, h), interpolation=interpolation)
|
20 |
+
|
21 |
+
def resize_all_img(path, frame_width, frame_height):
|
22 |
+
if not os.path.isdir(path):
|
23 |
+
return
|
24 |
+
|
25 |
+
pngs = glob.glob( os.path.join(path, "*.png") )
|
26 |
+
img = cv2.imread(pngs[0])
|
27 |
+
org_h,org_w = img.shape[0],img.shape[1]
|
28 |
+
|
29 |
+
if frame_width == -1 and frame_height == -1:
|
30 |
+
return
|
31 |
+
elif frame_width == -1 and frame_height != -1:
|
32 |
+
frame_width = int(frame_height * org_w / org_h)
|
33 |
+
elif frame_width != -1 and frame_height == -1:
|
34 |
+
frame_height = int(frame_width * org_h / org_w)
|
35 |
+
else:
|
36 |
+
pass
|
37 |
+
print("({0},{1}) resize to ({2},{3})".format(org_w, org_h, frame_width, frame_height))
|
38 |
+
|
39 |
+
for png in pngs:
|
40 |
+
img = cv2.imread(png)
|
41 |
+
img = resize_img(img, frame_width, frame_height)
|
42 |
+
cv2.imwrite(png, img)
|
43 |
+
|
44 |
+
def remove_pngs_in_dir(path):
|
45 |
+
if not os.path.isdir(path):
|
46 |
+
return
|
47 |
+
|
48 |
+
pngs = glob.glob( os.path.join(path, "*.png") )
|
49 |
+
for png in pngs:
|
50 |
+
os.remove(png)
|
51 |
+
|
52 |
+
def create_and_mask(mask_dir1, mask_dir2, output_dir):
|
53 |
+
masks = glob.glob( os.path.join(mask_dir1, "*.png") )
|
54 |
+
|
55 |
+
for mask1 in masks:
|
56 |
+
base_name = os.path.basename(mask1)
|
57 |
+
print("combine {0}".format(base_name))
|
58 |
+
|
59 |
+
mask2 = os.path.join(mask_dir2, base_name)
|
60 |
+
if not os.path.isfile(mask2):
|
61 |
+
print("{0} not found!!! -> skip".format(mask2))
|
62 |
+
continue
|
63 |
+
|
64 |
+
img_1 = cv2.imread(mask1)
|
65 |
+
img_2 = cv2.imread(mask2)
|
66 |
+
img_1 = np.minimum(img_1,img_2)
|
67 |
+
|
68 |
+
out_path = os.path.join(output_dir, base_name)
|
69 |
+
cv2.imwrite(out_path, img_1)
|
70 |
+
|
71 |
+
|
72 |
+
def create_mask_clipseg(input_dir, output_dir, clipseg_mask_prompt, clipseg_exclude_prompt, clipseg_mask_threshold, mask_blur_size, mask_blur_size2):
|
73 |
+
from modules import devices
|
74 |
+
|
75 |
+
devices.torch_gc()
|
76 |
+
|
77 |
+
device = devices.get_optimal_device_name()
|
78 |
+
|
79 |
+
processor = AutoProcessor.from_pretrained("CIDAS/clipseg-rd64-refined")
|
80 |
+
model = CLIPSegForImageSegmentation.from_pretrained("CIDAS/clipseg-rd64-refined")
|
81 |
+
model.to(device)
|
82 |
+
|
83 |
+
imgs = glob.glob( os.path.join(input_dir, "*.png") )
|
84 |
+
texts = [x.strip() for x in clipseg_mask_prompt.split(',')]
|
85 |
+
exclude_texts = [x.strip() for x in clipseg_exclude_prompt.split(',')] if clipseg_exclude_prompt else None
|
86 |
+
|
87 |
+
if exclude_texts:
|
88 |
+
all_texts = texts + exclude_texts
|
89 |
+
else:
|
90 |
+
all_texts = texts
|
91 |
+
|
92 |
+
|
93 |
+
for img_count,img in enumerate(imgs):
|
94 |
+
image = Image.open(img)
|
95 |
+
base_name = os.path.basename(img)
|
96 |
+
|
97 |
+
inputs = processor(text=all_texts, images=[image] * len(all_texts), padding="max_length", return_tensors="pt")
|
98 |
+
inputs = inputs.to(device)
|
99 |
+
|
100 |
+
with torch.no_grad(), devices.autocast():
|
101 |
+
outputs = model(**inputs)
|
102 |
+
|
103 |
+
if len(all_texts) == 1:
|
104 |
+
preds = outputs.logits.unsqueeze(0)
|
105 |
+
else:
|
106 |
+
preds = outputs.logits
|
107 |
+
|
108 |
+
mask_img = None
|
109 |
+
|
110 |
+
for i in range(len(all_texts)):
|
111 |
+
x = torch.sigmoid(preds[i])
|
112 |
+
x = x.to('cpu').detach().numpy()
|
113 |
+
|
114 |
+
# x[x < clipseg_mask_threshold] = 0
|
115 |
+
x = x > clipseg_mask_threshold
|
116 |
+
|
117 |
+
if i < len(texts):
|
118 |
+
if mask_img is None:
|
119 |
+
mask_img = x
|
120 |
+
else:
|
121 |
+
mask_img = np.maximum(mask_img,x)
|
122 |
+
else:
|
123 |
+
mask_img[x > 0] = 0
|
124 |
+
|
125 |
+
mask_img = mask_img*255
|
126 |
+
mask_img = mask_img.astype(np.uint8)
|
127 |
+
|
128 |
+
if mask_blur_size > 0:
|
129 |
+
mask_blur_size = mask_blur_size//2 * 2 + 1
|
130 |
+
mask_img = cv2.medianBlur(mask_img, mask_blur_size)
|
131 |
+
|
132 |
+
if mask_blur_size2 > 0:
|
133 |
+
mask_blur_size2 = mask_blur_size2//2 * 2 + 1
|
134 |
+
mask_img = cv2.GaussianBlur(mask_img, (mask_blur_size2, mask_blur_size2), 0)
|
135 |
+
|
136 |
+
mask_img = resize_img(mask_img, image.width, image.height)
|
137 |
+
|
138 |
+
mask_img = cv2.cvtColor(mask_img, cv2.COLOR_GRAY2RGB)
|
139 |
+
save_path = os.path.join(output_dir, base_name)
|
140 |
+
cv2.imwrite(save_path, mask_img)
|
141 |
+
|
142 |
+
print("{0} / {1}".format( img_count+1,len(imgs) ))
|
143 |
+
|
144 |
+
devices.torch_gc()
|
145 |
+
|
146 |
+
|
147 |
+
def create_mask_transparent_background(input_dir, output_dir, tb_use_fast_mode, tb_use_jit, st1_mask_threshold):
|
148 |
+
fast_str = " --fast" if tb_use_fast_mode else ""
|
149 |
+
jit_str = " --jit" if tb_use_jit else ""
|
150 |
+
venv = "venv"
|
151 |
+
if 'VIRTUAL_ENV' in os.environ:
|
152 |
+
venv = os.environ['VIRTUAL_ENV']
|
153 |
+
bin_path = os.path.join(venv, "Scripts")
|
154 |
+
bin_path = os.path.join(bin_path, "transparent-background")
|
155 |
+
|
156 |
+
if os.path.isfile(bin_path) or os.path.isfile(bin_path + ".exe"):
|
157 |
+
subprocess.call(bin_path + " --source " + input_dir + " --dest " + output_dir + " --type map" + fast_str + jit_str, shell=True)
|
158 |
+
else:
|
159 |
+
subprocess.call("transparent-background --source " + input_dir + " --dest " + output_dir + " --type map" + fast_str + jit_str, shell=True)
|
160 |
+
|
161 |
+
mask_imgs = glob.glob( os.path.join(output_dir, "*.png") )
|
162 |
+
|
163 |
+
for m in mask_imgs:
|
164 |
+
img = cv2.imread(m)
|
165 |
+
img[img < int( 255 * st1_mask_threshold )] = 0
|
166 |
+
cv2.imwrite(m, img)
|
167 |
+
|
168 |
+
p = re.compile(r'([0-9]+)_[a-z]*\.png')
|
169 |
+
|
170 |
+
for mask in mask_imgs:
|
171 |
+
base_name = os.path.basename(mask)
|
172 |
+
m = p.fullmatch(base_name)
|
173 |
+
if m:
|
174 |
+
os.rename(mask, os.path.join(output_dir, m.group(1) + ".png"))
|
175 |
+
|
176 |
+
def ebsynth_utility_stage1(dbg, project_args, frame_width, frame_height, st1_masking_method_index, st1_mask_threshold, tb_use_fast_mode, tb_use_jit, clipseg_mask_prompt, clipseg_exclude_prompt, clipseg_mask_threshold, clipseg_mask_blur_size, clipseg_mask_blur_size2, is_invert_mask):
|
177 |
+
dbg.print("stage1")
|
178 |
+
dbg.print("")
|
179 |
+
|
180 |
+
if st1_masking_method_index == 1 and (not clipseg_mask_prompt):
|
181 |
+
dbg.print("Error: clipseg_mask_prompt is Empty")
|
182 |
+
return
|
183 |
+
|
184 |
+
project_dir, original_movie_path, frame_path, frame_mask_path, _, _, _ = project_args
|
185 |
+
|
186 |
+
if is_invert_mask:
|
187 |
+
if os.path.isdir( frame_path ) and os.path.isdir( frame_mask_path ):
|
188 |
+
dbg.print("Skip as it appears that the frame and normal masks have already been generated.")
|
189 |
+
return
|
190 |
+
|
191 |
+
# remove_pngs_in_dir(frame_path)
|
192 |
+
|
193 |
+
if frame_mask_path:
|
194 |
+
remove_pngs_in_dir(frame_mask_path)
|
195 |
+
|
196 |
+
if frame_mask_path:
|
197 |
+
os.makedirs(frame_mask_path, exist_ok=True)
|
198 |
+
|
199 |
+
if os.path.isdir( frame_path ):
|
200 |
+
dbg.print("Skip frame extraction")
|
201 |
+
else:
|
202 |
+
os.makedirs(frame_path, exist_ok=True)
|
203 |
+
|
204 |
+
png_path = os.path.join(frame_path , "%05d.png")
|
205 |
+
# ffmpeg.exe -ss 00:00:00 -y -i %1 -qscale 0 -f image2 -c:v png "%05d.png"
|
206 |
+
subprocess.call("ffmpeg -ss 00:00:00 -y -i " + original_movie_path + " -qscale 0 -f image2 -c:v png " + png_path, shell=True)
|
207 |
+
|
208 |
+
dbg.print("frame extracted")
|
209 |
+
|
210 |
+
frame_width = max(frame_width,-1)
|
211 |
+
frame_height = max(frame_height,-1)
|
212 |
+
|
213 |
+
if frame_width != -1 or frame_height != -1:
|
214 |
+
resize_all_img(frame_path, frame_width, frame_height)
|
215 |
+
|
216 |
+
if frame_mask_path:
|
217 |
+
if st1_masking_method_index == 0:
|
218 |
+
create_mask_transparent_background(frame_path, frame_mask_path, tb_use_fast_mode, tb_use_jit, st1_mask_threshold)
|
219 |
+
elif st1_masking_method_index == 1:
|
220 |
+
create_mask_clipseg(frame_path, frame_mask_path, clipseg_mask_prompt, clipseg_exclude_prompt, clipseg_mask_threshold, clipseg_mask_blur_size, clipseg_mask_blur_size2)
|
221 |
+
elif st1_masking_method_index == 2:
|
222 |
+
tb_tmp_path = os.path.join(project_dir , "tb_mask_tmp")
|
223 |
+
if not os.path.isdir( tb_tmp_path ):
|
224 |
+
os.makedirs(tb_tmp_path, exist_ok=True)
|
225 |
+
create_mask_transparent_background(frame_path, tb_tmp_path, tb_use_fast_mode, tb_use_jit, st1_mask_threshold)
|
226 |
+
create_mask_clipseg(frame_path, frame_mask_path, clipseg_mask_prompt, clipseg_exclude_prompt, clipseg_mask_threshold, clipseg_mask_blur_size, clipseg_mask_blur_size2)
|
227 |
+
create_and_mask(tb_tmp_path,frame_mask_path,frame_mask_path)
|
228 |
+
|
229 |
+
|
230 |
+
dbg.print("mask created")
|
231 |
+
|
232 |
+
dbg.print("")
|
233 |
+
dbg.print("completed.")
|
234 |
+
|
235 |
+
|
236 |
+
def ebsynth_utility_stage1_invert(dbg, frame_mask_path, inv_mask_path):
|
237 |
+
dbg.print("stage 1 create_invert_mask")
|
238 |
+
dbg.print("")
|
239 |
+
|
240 |
+
if not os.path.isdir( frame_mask_path ):
|
241 |
+
dbg.print( frame_mask_path + " not found")
|
242 |
+
dbg.print("Normal masks must be generated previously.")
|
243 |
+
dbg.print("Do stage 1 with [Ebsynth Utility] Tab -> [configuration] -> [etc]-> [Mask Mode] = Normal setting first")
|
244 |
+
return
|
245 |
+
|
246 |
+
os.makedirs(inv_mask_path, exist_ok=True)
|
247 |
+
|
248 |
+
mask_imgs = glob.glob( os.path.join(frame_mask_path, "*.png") )
|
249 |
+
|
250 |
+
for m in mask_imgs:
|
251 |
+
img = cv2.imread(m)
|
252 |
+
inv = cv2.bitwise_not(img)
|
253 |
+
|
254 |
+
base_name = os.path.basename(m)
|
255 |
+
cv2.imwrite(os.path.join(inv_mask_path,base_name), inv)
|
256 |
+
|
257 |
+
dbg.print("")
|
258 |
+
dbg.print("completed.")
|
ebsynth_utility/stage2.py
ADDED
@@ -0,0 +1,173 @@
|
|
|
|
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|
|
|
|
|
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|
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|
|
|
|
|
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|
|
|
|
|
|
|
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|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
import cv2
|
2 |
+
import os
|
3 |
+
import glob
|
4 |
+
import shutil
|
5 |
+
import numpy as np
|
6 |
+
import math
|
7 |
+
|
8 |
+
#---------------------------------
|
9 |
+
# Copied from PySceneDetect
|
10 |
+
def mean_pixel_distance(left: np.ndarray, right: np.ndarray) -> float:
|
11 |
+
"""Return the mean average distance in pixel values between `left` and `right`.
|
12 |
+
Both `left and `right` should be 2 dimensional 8-bit images of the same shape.
|
13 |
+
"""
|
14 |
+
assert len(left.shape) == 2 and len(right.shape) == 2
|
15 |
+
assert left.shape == right.shape
|
16 |
+
num_pixels: float = float(left.shape[0] * left.shape[1])
|
17 |
+
return (np.sum(np.abs(left.astype(np.int32) - right.astype(np.int32))) / num_pixels)
|
18 |
+
|
19 |
+
|
20 |
+
def estimated_kernel_size(frame_width: int, frame_height: int) -> int:
|
21 |
+
"""Estimate kernel size based on video resolution."""
|
22 |
+
size: int = 4 + round(math.sqrt(frame_width * frame_height) / 192)
|
23 |
+
if size % 2 == 0:
|
24 |
+
size += 1
|
25 |
+
return size
|
26 |
+
|
27 |
+
_kernel = None
|
28 |
+
|
29 |
+
def _detect_edges(lum: np.ndarray) -> np.ndarray:
|
30 |
+
global _kernel
|
31 |
+
"""Detect edges using the luma channel of a frame.
|
32 |
+
Arguments:
|
33 |
+
lum: 2D 8-bit image representing the luma channel of a frame.
|
34 |
+
Returns:
|
35 |
+
2D 8-bit image of the same size as the input, where pixels with values of 255
|
36 |
+
represent edges, and all other pixels are 0.
|
37 |
+
"""
|
38 |
+
# Initialize kernel.
|
39 |
+
if _kernel is None:
|
40 |
+
kernel_size = estimated_kernel_size(lum.shape[1], lum.shape[0])
|
41 |
+
_kernel = np.ones((kernel_size, kernel_size), np.uint8)
|
42 |
+
|
43 |
+
# Estimate levels for thresholding.
|
44 |
+
sigma: float = 1.0 / 3.0
|
45 |
+
median = np.median(lum)
|
46 |
+
low = int(max(0, (1.0 - sigma) * median))
|
47 |
+
high = int(min(255, (1.0 + sigma) * median))
|
48 |
+
|
49 |
+
# Calculate edges using Canny algorithm, and reduce noise by dilating the edges.
|
50 |
+
# This increases edge overlap leading to improved robustness against noise and slow
|
51 |
+
# camera movement. Note that very large kernel sizes can negatively affect accuracy.
|
52 |
+
edges = cv2.Canny(lum, low, high)
|
53 |
+
return cv2.dilate(edges, _kernel)
|
54 |
+
|
55 |
+
#---------------------------------
|
56 |
+
|
57 |
+
def detect_edges(img_path, mask_path, is_invert_mask):
|
58 |
+
im = cv2.imread(img_path)
|
59 |
+
if mask_path:
|
60 |
+
mask = cv2.imread(mask_path)[:,:,0]
|
61 |
+
mask = mask[:, :, np.newaxis]
|
62 |
+
im = im * ( (mask == 0) if is_invert_mask else (mask > 0) )
|
63 |
+
# im = im * (mask/255)
|
64 |
+
# im = im.astype(np.uint8)
|
65 |
+
# cv2.imwrite( os.path.join( os.path.dirname(mask_path) , "tmp.png" ) , im)
|
66 |
+
|
67 |
+
hue, sat, lum = cv2.split(cv2.cvtColor( im , cv2.COLOR_BGR2HSV))
|
68 |
+
return _detect_edges(lum)
|
69 |
+
|
70 |
+
def get_mask_path_of_img(img_path, mask_dir):
|
71 |
+
img_basename = os.path.basename(img_path)
|
72 |
+
mask_path = os.path.join( mask_dir , img_basename )
|
73 |
+
return mask_path if os.path.isfile( mask_path ) else None
|
74 |
+
|
75 |
+
def analyze_key_frames(png_dir, mask_dir, th, min_gap, max_gap, add_last_frame, is_invert_mask):
|
76 |
+
keys = []
|
77 |
+
|
78 |
+
frames = sorted(glob.glob( os.path.join(png_dir, "[0-9]*.png") ))
|
79 |
+
|
80 |
+
key_frame = frames[0]
|
81 |
+
keys.append( int(os.path.splitext(os.path.basename(key_frame))[0]) )
|
82 |
+
key_edges = detect_edges( key_frame, get_mask_path_of_img( key_frame, mask_dir ), is_invert_mask )
|
83 |
+
gap = 0
|
84 |
+
|
85 |
+
for frame in frames:
|
86 |
+
gap += 1
|
87 |
+
if gap < min_gap:
|
88 |
+
continue
|
89 |
+
|
90 |
+
edges = detect_edges( frame, get_mask_path_of_img( frame, mask_dir ), is_invert_mask )
|
91 |
+
|
92 |
+
delta = mean_pixel_distance( edges, key_edges )
|
93 |
+
|
94 |
+
_th = th * (max_gap - gap)/max_gap
|
95 |
+
|
96 |
+
if _th < delta:
|
97 |
+
basename_without_ext = os.path.splitext(os.path.basename(frame))[0]
|
98 |
+
keys.append( int(basename_without_ext) )
|
99 |
+
key_frame = frame
|
100 |
+
key_edges = edges
|
101 |
+
gap = 0
|
102 |
+
|
103 |
+
if add_last_frame:
|
104 |
+
basename_without_ext = os.path.splitext(os.path.basename(frames[-1]))[0]
|
105 |
+
last_frame = int(basename_without_ext)
|
106 |
+
if not last_frame in keys:
|
107 |
+
keys.append( last_frame )
|
108 |
+
|
109 |
+
return keys
|
110 |
+
|
111 |
+
def remove_pngs_in_dir(path):
|
112 |
+
if not os.path.isdir(path):
|
113 |
+
return
|
114 |
+
|
115 |
+
pngs = glob.glob( os.path.join(path, "*.png") )
|
116 |
+
for png in pngs:
|
117 |
+
os.remove(png)
|
118 |
+
|
119 |
+
def ebsynth_utility_stage2(dbg, project_args, key_min_gap, key_max_gap, key_th, key_add_last_frame, is_invert_mask):
|
120 |
+
dbg.print("stage2")
|
121 |
+
dbg.print("")
|
122 |
+
|
123 |
+
_, original_movie_path, frame_path, frame_mask_path, org_key_path, _, _ = project_args
|
124 |
+
|
125 |
+
remove_pngs_in_dir(org_key_path)
|
126 |
+
os.makedirs(org_key_path, exist_ok=True)
|
127 |
+
|
128 |
+
fps = 30
|
129 |
+
clip = cv2.VideoCapture(original_movie_path)
|
130 |
+
if clip:
|
131 |
+
fps = clip.get(cv2.CAP_PROP_FPS)
|
132 |
+
clip.release()
|
133 |
+
|
134 |
+
if key_min_gap == -1:
|
135 |
+
key_min_gap = int(10 * fps/30)
|
136 |
+
else:
|
137 |
+
key_min_gap = max(1, key_min_gap)
|
138 |
+
key_min_gap = int(key_min_gap * fps/30)
|
139 |
+
|
140 |
+
if key_max_gap == -1:
|
141 |
+
key_max_gap = int(300 * fps/30)
|
142 |
+
else:
|
143 |
+
key_max_gap = max(10, key_max_gap)
|
144 |
+
key_max_gap = int(key_max_gap * fps/30)
|
145 |
+
|
146 |
+
key_min_gap,key_max_gap = (key_min_gap,key_max_gap) if key_min_gap < key_max_gap else (key_max_gap,key_min_gap)
|
147 |
+
|
148 |
+
dbg.print("fps: {}".format(fps))
|
149 |
+
dbg.print("key_min_gap: {}".format(key_min_gap))
|
150 |
+
dbg.print("key_max_gap: {}".format(key_max_gap))
|
151 |
+
dbg.print("key_th: {}".format(key_th))
|
152 |
+
|
153 |
+
keys = analyze_key_frames(frame_path, frame_mask_path, key_th, key_min_gap, key_max_gap, key_add_last_frame, is_invert_mask)
|
154 |
+
|
155 |
+
dbg.print("keys : " + str(keys))
|
156 |
+
|
157 |
+
for k in keys:
|
158 |
+
filename = str(k).zfill(5) + ".png"
|
159 |
+
shutil.copy( os.path.join( frame_path , filename) , os.path.join(org_key_path, filename) )
|
160 |
+
|
161 |
+
|
162 |
+
dbg.print("")
|
163 |
+
dbg.print("Keyframes are output to [" + org_key_path + "]")
|
164 |
+
dbg.print("")
|
165 |
+
dbg.print("[Ebsynth Utility]->[configuration]->[stage 2]->[Threshold of delta frame edge]")
|
166 |
+
dbg.print("The smaller this value, the narrower the keyframe spacing, and if set to 0, the keyframes will be equally spaced at the value of [Minimum keyframe gap].")
|
167 |
+
dbg.print("")
|
168 |
+
dbg.print("If you do not like the selection, you can modify it manually.")
|
169 |
+
dbg.print("(Delete keyframe, or Add keyframe from ["+frame_path+"])")
|
170 |
+
|
171 |
+
dbg.print("")
|
172 |
+
dbg.print("completed.")
|
173 |
+
|
ebsynth_utility/stage3_5.py
ADDED
@@ -0,0 +1,178 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
|
|
|
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|
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|
|
|
|
|
|
|
|
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|
|
|
|
|
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|
|
|
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|
|
|
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|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
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|
|
|
|
|
|
|
|
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|
|
|
|
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|
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|
|
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|
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|
|
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|
|
|
|
|
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|
|
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|
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|
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|
|
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|
|
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|
|
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|
|
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|
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|
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|
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|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
import cv2
|
2 |
+
import os
|
3 |
+
import glob
|
4 |
+
import shutil
|
5 |
+
import numpy as np
|
6 |
+
from PIL import Image
|
7 |
+
|
8 |
+
from color_matcher import ColorMatcher
|
9 |
+
from color_matcher.normalizer import Normalizer
|
10 |
+
|
11 |
+
def resize_img(img, w, h):
|
12 |
+
if img.shape[0] + img.shape[1] < h + w:
|
13 |
+
interpolation = interpolation=cv2.INTER_CUBIC
|
14 |
+
else:
|
15 |
+
interpolation = interpolation=cv2.INTER_AREA
|
16 |
+
|
17 |
+
return cv2.resize(img, (w, h), interpolation=interpolation)
|
18 |
+
|
19 |
+
def get_pair_of_img(img_path, target_dir):
|
20 |
+
img_basename = os.path.basename(img_path)
|
21 |
+
target_path = os.path.join( target_dir , img_basename )
|
22 |
+
return target_path if os.path.isfile( target_path ) else None
|
23 |
+
|
24 |
+
def remove_pngs_in_dir(path):
|
25 |
+
if not os.path.isdir(path):
|
26 |
+
return
|
27 |
+
|
28 |
+
pngs = glob.glob( os.path.join(path, "*.png") )
|
29 |
+
for png in pngs:
|
30 |
+
os.remove(png)
|
31 |
+
|
32 |
+
def get_pair_of_img(img, target_dir):
|
33 |
+
img_basename = os.path.basename(img)
|
34 |
+
|
35 |
+
pair_path = os.path.join( target_dir , img_basename )
|
36 |
+
if os.path.isfile( pair_path ):
|
37 |
+
return pair_path
|
38 |
+
print("!!! pair of "+ img + " not in " + target_dir)
|
39 |
+
return ""
|
40 |
+
|
41 |
+
def get_mask_array(mask_path):
|
42 |
+
if not mask_path:
|
43 |
+
return None
|
44 |
+
mask_array = np.asarray(Image.open( mask_path ))
|
45 |
+
if mask_array.ndim == 2:
|
46 |
+
mask_array = mask_array[:, :, np.newaxis]
|
47 |
+
mask_array = mask_array[:,:,:1]
|
48 |
+
mask_array = mask_array/255
|
49 |
+
return mask_array
|
50 |
+
|
51 |
+
def color_match(imgs, ref_image, color_matcher_method, dst_path):
|
52 |
+
cm = ColorMatcher(method=color_matcher_method)
|
53 |
+
|
54 |
+
i = 0
|
55 |
+
total = len(imgs)
|
56 |
+
|
57 |
+
for fname in imgs:
|
58 |
+
|
59 |
+
img_src = Image.open(fname)
|
60 |
+
img_src = Normalizer(np.asarray(img_src)).type_norm()
|
61 |
+
|
62 |
+
img_src = cm.transfer(src=img_src, ref=ref_image, method=color_matcher_method)
|
63 |
+
|
64 |
+
img_src = Normalizer(img_src).uint8_norm()
|
65 |
+
Image.fromarray(img_src).save(os.path.join(dst_path, os.path.basename(fname)))
|
66 |
+
|
67 |
+
i += 1
|
68 |
+
print("{0}/{1}".format(i, total))
|
69 |
+
|
70 |
+
imgs = sorted( glob.glob( os.path.join(dst_path, "*.png") ) )
|
71 |
+
|
72 |
+
|
73 |
+
def ebsynth_utility_stage3_5(dbg, project_args, color_matcher_method, st3_5_use_mask, st3_5_use_mask_ref, st3_5_use_mask_org, color_matcher_ref_type, color_matcher_ref_image):
|
74 |
+
dbg.print("stage3.5")
|
75 |
+
dbg.print("")
|
76 |
+
|
77 |
+
_, _, frame_path, frame_mask_path, org_key_path, img2img_key_path, _ = project_args
|
78 |
+
|
79 |
+
backup_path = os.path.join( os.path.join( img2img_key_path, "..") , "st3_5_backup_img2img_key")
|
80 |
+
backup_path = os.path.normpath(backup_path)
|
81 |
+
|
82 |
+
if not os.path.isdir( backup_path ):
|
83 |
+
dbg.print("{0} not found -> create backup.".format(backup_path))
|
84 |
+
os.makedirs(backup_path, exist_ok=True)
|
85 |
+
|
86 |
+
imgs = glob.glob( os.path.join(img2img_key_path, "*.png") )
|
87 |
+
|
88 |
+
for img in imgs:
|
89 |
+
img_basename = os.path.basename(img)
|
90 |
+
pair_path = os.path.join( backup_path , img_basename )
|
91 |
+
shutil.copy( img , pair_path)
|
92 |
+
|
93 |
+
else:
|
94 |
+
dbg.print("{0} found -> Treat the images here as originals.".format(backup_path))
|
95 |
+
|
96 |
+
org_imgs = sorted( glob.glob( os.path.join(backup_path, "*.png") ) )
|
97 |
+
head_of_keyframe = org_imgs[0]
|
98 |
+
|
99 |
+
# open ref img
|
100 |
+
ref_image = color_matcher_ref_image
|
101 |
+
if not ref_image:
|
102 |
+
dbg.print("color_matcher_ref_image not set")
|
103 |
+
|
104 |
+
if color_matcher_ref_type == 0:
|
105 |
+
#'original video frame'
|
106 |
+
dbg.print("select -> original video frame")
|
107 |
+
ref_image = Image.open( get_pair_of_img(head_of_keyframe, frame_path) )
|
108 |
+
else:
|
109 |
+
#'first frame of img2img result'
|
110 |
+
dbg.print("select -> first frame of img2img result")
|
111 |
+
ref_image = Image.open( get_pair_of_img(head_of_keyframe, backup_path) )
|
112 |
+
|
113 |
+
ref_image = np.asarray(ref_image)
|
114 |
+
|
115 |
+
if st3_5_use_mask_ref:
|
116 |
+
mask = get_pair_of_img(head_of_keyframe, frame_mask_path)
|
117 |
+
if mask:
|
118 |
+
mask_array = get_mask_array( mask )
|
119 |
+
ref_image = ref_image * mask_array
|
120 |
+
ref_image = ref_image.astype(np.uint8)
|
121 |
+
|
122 |
+
else:
|
123 |
+
dbg.print("select -> color_matcher_ref_image")
|
124 |
+
ref_image = np.asarray(ref_image)
|
125 |
+
|
126 |
+
|
127 |
+
if color_matcher_method in ('mvgd', 'hm-mvgd-hm'):
|
128 |
+
sample_img = Image.open(head_of_keyframe)
|
129 |
+
ref_image = resize_img( ref_image, sample_img.width, sample_img.height )
|
130 |
+
|
131 |
+
ref_image = Normalizer(ref_image).type_norm()
|
132 |
+
|
133 |
+
|
134 |
+
if st3_5_use_mask_org:
|
135 |
+
tmp_path = os.path.join( os.path.join( img2img_key_path, "..") , "st3_5_tmp")
|
136 |
+
tmp_path = os.path.normpath(tmp_path)
|
137 |
+
dbg.print("create {0} for masked original image".format(tmp_path))
|
138 |
+
|
139 |
+
remove_pngs_in_dir(tmp_path)
|
140 |
+
os.makedirs(tmp_path, exist_ok=True)
|
141 |
+
|
142 |
+
for org_img in org_imgs:
|
143 |
+
image_basename = os.path.basename(org_img)
|
144 |
+
|
145 |
+
org_image = np.asarray(Image.open(org_img))
|
146 |
+
|
147 |
+
mask = get_pair_of_img(org_img, frame_mask_path)
|
148 |
+
if mask:
|
149 |
+
mask_array = get_mask_array( mask )
|
150 |
+
org_image = org_image * mask_array
|
151 |
+
org_image = org_image.astype(np.uint8)
|
152 |
+
|
153 |
+
Image.fromarray(org_image).save( os.path.join( tmp_path, image_basename ) )
|
154 |
+
|
155 |
+
org_imgs = sorted( glob.glob( os.path.join(tmp_path, "*.png") ) )
|
156 |
+
|
157 |
+
|
158 |
+
color_match(org_imgs, ref_image, color_matcher_method, img2img_key_path)
|
159 |
+
|
160 |
+
|
161 |
+
if st3_5_use_mask or st3_5_use_mask_org:
|
162 |
+
imgs = sorted( glob.glob( os.path.join(img2img_key_path, "*.png") ) )
|
163 |
+
for img in imgs:
|
164 |
+
mask = get_pair_of_img(img, frame_mask_path)
|
165 |
+
if mask:
|
166 |
+
mask_array = get_mask_array( mask )
|
167 |
+
bg = get_pair_of_img(img, frame_path)
|
168 |
+
bg_image = np.asarray(Image.open( bg ))
|
169 |
+
fg_image = np.asarray(Image.open( img ))
|
170 |
+
|
171 |
+
final_img = fg_image * mask_array + bg_image * (1-mask_array)
|
172 |
+
final_img = final_img.astype(np.uint8)
|
173 |
+
|
174 |
+
Image.fromarray(final_img).save(img)
|
175 |
+
|
176 |
+
dbg.print("")
|
177 |
+
dbg.print("completed.")
|
178 |
+
|
ebsynth_utility/stage5.py
ADDED
@@ -0,0 +1,279 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
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|
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|
|
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|
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|
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|
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|
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|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
import cv2
|
2 |
+
import re
|
3 |
+
import os
|
4 |
+
import glob
|
5 |
+
import time
|
6 |
+
|
7 |
+
from sys import byteorder
|
8 |
+
import binascii
|
9 |
+
import numpy as np
|
10 |
+
|
11 |
+
SYNTHS_PER_PROJECT = 15
|
12 |
+
|
13 |
+
def to_float_bytes(f):
|
14 |
+
if byteorder == 'little':
|
15 |
+
return np.array([ float(f) ], dtype='<f4').tobytes()
|
16 |
+
else:
|
17 |
+
return np.array([ float(f) ], dtype='>f4').tobytes()
|
18 |
+
|
19 |
+
def path2framenum(path):
|
20 |
+
return int( os.path.splitext(os.path.basename( path ))[0] )
|
21 |
+
|
22 |
+
def search_key_dir(key_dir):
|
23 |
+
frames = glob.glob( os.path.join(key_dir ,"[0-9]*.png"), recursive=False)
|
24 |
+
|
25 |
+
frames = sorted(frames)
|
26 |
+
|
27 |
+
basename = os.path.splitext(os.path.basename( frames[0] ))[0]
|
28 |
+
|
29 |
+
key_list = [ path2framenum(key) for key in frames ]
|
30 |
+
|
31 |
+
print("digits = " + str(len(basename)))
|
32 |
+
print("keys = " + str(key_list))
|
33 |
+
|
34 |
+
return len(basename), key_list
|
35 |
+
|
36 |
+
|
37 |
+
def search_video_dir(video_dir):
|
38 |
+
frames = glob.glob( os.path.join(video_dir, "[0-9]*.png"), recursive=False)
|
39 |
+
|
40 |
+
frames = sorted(frames)
|
41 |
+
|
42 |
+
first = path2framenum( frames[0] )
|
43 |
+
last = path2framenum( frames[-1] )
|
44 |
+
|
45 |
+
return first, last
|
46 |
+
|
47 |
+
def export_project( project, proj_filename ):
|
48 |
+
|
49 |
+
proj_path = os.path.join( project["proj_dir"] , proj_filename + ".ebs")
|
50 |
+
|
51 |
+
with open(proj_path, 'wb') as f:
|
52 |
+
# header
|
53 |
+
f.write( binascii.unhexlify('45') )
|
54 |
+
f.write( binascii.unhexlify('42') )
|
55 |
+
f.write( binascii.unhexlify('53') )
|
56 |
+
f.write( binascii.unhexlify('30') )
|
57 |
+
f.write( binascii.unhexlify('35') )
|
58 |
+
f.write( binascii.unhexlify('00') )
|
59 |
+
|
60 |
+
# video
|
61 |
+
f.write( len( project["video_dir"] + project["file_name"]).to_bytes(4, byteorder) )
|
62 |
+
f.write( (project["video_dir"] + project["file_name"]).encode() )
|
63 |
+
|
64 |
+
# mask
|
65 |
+
if project["mask_dir"]:
|
66 |
+
f.write( len( project["mask_dir"] + project["file_name"]).to_bytes(4, byteorder) )
|
67 |
+
f.write( (project["mask_dir"] + project["file_name"]).encode() )
|
68 |
+
else:
|
69 |
+
f.write( int(0).to_bytes(4, byteorder) )
|
70 |
+
|
71 |
+
# key
|
72 |
+
f.write( len( project["key_dir"] + project["file_name"]).to_bytes(4, byteorder) )
|
73 |
+
f.write( (project["key_dir"] + project["file_name"]).encode() )
|
74 |
+
|
75 |
+
# mask on flag
|
76 |
+
if project["mask_dir"]:
|
77 |
+
f.write( int(1).to_bytes(1, byteorder) )
|
78 |
+
else:
|
79 |
+
f.write( int(0).to_bytes(1, byteorder) )
|
80 |
+
|
81 |
+
|
82 |
+
# keyframe weight
|
83 |
+
f.write( to_float_bytes( project["key_weight"] ) )
|
84 |
+
|
85 |
+
# video weight
|
86 |
+
f.write( to_float_bytes( project["video_weight"] ) )
|
87 |
+
|
88 |
+
# mask weight
|
89 |
+
f.write( to_float_bytes( project["mask_weight"] ) )
|
90 |
+
|
91 |
+
# mapping
|
92 |
+
f.write( to_float_bytes( project["adv_mapping"] ) )
|
93 |
+
|
94 |
+
# de-flicker
|
95 |
+
f.write( to_float_bytes( project["adv_de-flicker"] ) )
|
96 |
+
|
97 |
+
# diversity
|
98 |
+
f.write( to_float_bytes( project["adv_diversity"] ) )
|
99 |
+
|
100 |
+
|
101 |
+
# num of synths
|
102 |
+
f.write( len( project["synth_list"] ).to_bytes(4, byteorder) )
|
103 |
+
|
104 |
+
# synth
|
105 |
+
for synth in project["synth_list"]:
|
106 |
+
# key frame
|
107 |
+
f.write( int( synth["key"] ).to_bytes(4, byteorder) )
|
108 |
+
# is start frame exist
|
109 |
+
f.write( int(1).to_bytes(1, byteorder) )
|
110 |
+
# is end frame exist
|
111 |
+
f.write( int(1).to_bytes(1, byteorder) )
|
112 |
+
# start frame
|
113 |
+
f.write( int( synth["prev_key"] ).to_bytes(4, byteorder) )
|
114 |
+
# end frame
|
115 |
+
f.write( int( synth["next_key"] ).to_bytes(4, byteorder) )
|
116 |
+
|
117 |
+
# out path
|
118 |
+
path = "out-" + str(synth["key"]).zfill( project["number_of_digits"] ) + project["file_name"]
|
119 |
+
f.write( len(path).to_bytes(4, byteorder) )
|
120 |
+
f.write( path.encode() )
|
121 |
+
|
122 |
+
# ?
|
123 |
+
f.write( binascii.unhexlify('56') )
|
124 |
+
f.write( binascii.unhexlify('30') )
|
125 |
+
f.write( binascii.unhexlify('32') )
|
126 |
+
f.write( binascii.unhexlify('00') )
|
127 |
+
|
128 |
+
# synthesis detail
|
129 |
+
f.write( int( project["adv_detail"] ).to_bytes(1, byteorder) )
|
130 |
+
|
131 |
+
# padding
|
132 |
+
f.write( binascii.unhexlify('00') )
|
133 |
+
f.write( binascii.unhexlify('00') )
|
134 |
+
f.write( binascii.unhexlify('00') )
|
135 |
+
|
136 |
+
# use gpu
|
137 |
+
f.write( int( project["adv_gpu"] ).to_bytes(1, byteorder) )
|
138 |
+
|
139 |
+
# ?
|
140 |
+
f.write( binascii.unhexlify('00') )
|
141 |
+
f.write( binascii.unhexlify('00') )
|
142 |
+
f.write( binascii.unhexlify('F0') )
|
143 |
+
f.write( binascii.unhexlify('41') )
|
144 |
+
f.write( binascii.unhexlify('C0') )
|
145 |
+
f.write( binascii.unhexlify('02') )
|
146 |
+
f.write( binascii.unhexlify('00') )
|
147 |
+
f.write( binascii.unhexlify('00') )
|
148 |
+
|
149 |
+
|
150 |
+
def rename_keys(key_dir):
|
151 |
+
imgs = glob.glob(os.path.join(key_dir, "*.png"), recursive=False)
|
152 |
+
|
153 |
+
if not imgs:
|
154 |
+
print('no files in %s' % key_dir)
|
155 |
+
return
|
156 |
+
|
157 |
+
p = re.compile(r'([0-9]+).*\.png')
|
158 |
+
|
159 |
+
for img in imgs:
|
160 |
+
|
161 |
+
filename = os.path.basename(img)
|
162 |
+
|
163 |
+
m = p.fullmatch(filename)
|
164 |
+
|
165 |
+
if m:
|
166 |
+
f = m.group(1) + ".png"
|
167 |
+
dirname = os.path.dirname(img)
|
168 |
+
os.rename(img, os.path.join(dirname, f))
|
169 |
+
|
170 |
+
def ebsynth_utility_stage5(dbg, project_args, is_invert_mask):
|
171 |
+
dbg.print("stage5")
|
172 |
+
dbg.print("")
|
173 |
+
|
174 |
+
project_dir, _, frame_path, frame_mask_path, _, img2img_key_path, img2img_upscale_key_path = project_args
|
175 |
+
|
176 |
+
if not os.path.isdir(project_dir):
|
177 |
+
dbg.print('project_dir : no such dir %s' % project_dir)
|
178 |
+
return
|
179 |
+
if not os.path.isdir(frame_path):
|
180 |
+
dbg.print('frame_path : no such dir %s' % frame_path)
|
181 |
+
return
|
182 |
+
|
183 |
+
no_upscale = False
|
184 |
+
|
185 |
+
if not os.path.isdir(img2img_upscale_key_path):
|
186 |
+
dbg.print('img2img_upscale_key_path : no such dir %s' % img2img_upscale_key_path)
|
187 |
+
if not os.path.isdir(img2img_key_path):
|
188 |
+
return
|
189 |
+
|
190 |
+
sample_img2img_key = glob.glob( os.path.join(img2img_key_path , "*.png" ) )[0]
|
191 |
+
img_height1, img_width1, _ = cv2.imread(sample_img2img_key).shape
|
192 |
+
sample_frame = glob.glob( os.path.join(frame_path , "*.png" ) )[0]
|
193 |
+
img_height2, img_width2, _ = cv2.imread(sample_frame).shape
|
194 |
+
|
195 |
+
if img_height1 != img_height2 or img_width1 != img_width2:
|
196 |
+
return
|
197 |
+
|
198 |
+
dbg.print('The size of frame and img2img_key matched. use %s instead' % img2img_key_path)
|
199 |
+
img2img_upscale_key_path = img2img_key_path
|
200 |
+
no_upscale = True
|
201 |
+
|
202 |
+
else:
|
203 |
+
rename_keys(img2img_upscale_key_path)
|
204 |
+
|
205 |
+
number_of_digits, keys = search_key_dir( img2img_upscale_key_path )
|
206 |
+
|
207 |
+
if number_of_digits == -1:
|
208 |
+
dbg.print('no key frame')
|
209 |
+
return
|
210 |
+
|
211 |
+
first_frame, last_frame = search_video_dir( frame_path )
|
212 |
+
|
213 |
+
### add next key
|
214 |
+
synth_list = []
|
215 |
+
next_key = last_frame
|
216 |
+
|
217 |
+
for key in keys[::-1]:
|
218 |
+
synth_list.append( { "next_key": next_key })
|
219 |
+
next_key = key
|
220 |
+
|
221 |
+
synth_list = synth_list[::-1]
|
222 |
+
prev_key = first_frame
|
223 |
+
|
224 |
+
### add key / prev key
|
225 |
+
for i, key in enumerate(keys):
|
226 |
+
synth_list[i]["key"] = key
|
227 |
+
synth_list[i]["prev_key"] = prev_key
|
228 |
+
prev_key = key
|
229 |
+
|
230 |
+
project = {
|
231 |
+
"proj_dir" : project_dir if is_invert_mask == False else os.path.join(project_dir, "inv"),
|
232 |
+
"file_name" : "/[" + "#" * number_of_digits + "].png",
|
233 |
+
"number_of_digits" : number_of_digits,
|
234 |
+
|
235 |
+
"key_dir" : "img2img_upscale_key" if no_upscale == False else "img2img_key",
|
236 |
+
"video_dir" : "video_frame" if is_invert_mask == False else "../video_frame",
|
237 |
+
"mask_dir" : "video_mask" if is_invert_mask == False else "inv_video_mask",
|
238 |
+
"key_weight" : 1.0,
|
239 |
+
"video_weight" : 4.0,
|
240 |
+
"mask_weight" : 1.0,
|
241 |
+
"adv_mapping" : 10.0,
|
242 |
+
"adv_de-flicker" : 1.0,
|
243 |
+
"adv_diversity" : 3500.0,
|
244 |
+
"adv_detail" : 1, # high
|
245 |
+
"adv_gpu" : 1, # use gpu
|
246 |
+
}
|
247 |
+
|
248 |
+
if not frame_mask_path:
|
249 |
+
# no mask
|
250 |
+
project["mask_dir"] = ""
|
251 |
+
|
252 |
+
proj_base_name = time.strftime("%Y%m%d-%H%M%S")
|
253 |
+
if is_invert_mask:
|
254 |
+
proj_base_name = "inv_" + proj_base_name
|
255 |
+
|
256 |
+
tmp=[]
|
257 |
+
proj_index = 0
|
258 |
+
for i, synth in enumerate(synth_list):
|
259 |
+
tmp.append(synth)
|
260 |
+
if (i % SYNTHS_PER_PROJECT == SYNTHS_PER_PROJECT-1):
|
261 |
+
project["synth_list"] = tmp
|
262 |
+
proj_file_name = proj_base_name + "_" + str(proj_index).zfill(5)
|
263 |
+
export_project( project, proj_file_name )
|
264 |
+
proj_index += 1
|
265 |
+
tmp = []
|
266 |
+
dbg.print("exported : " + proj_file_name + ".ebs" )
|
267 |
+
|
268 |
+
if tmp:
|
269 |
+
project["synth_list"] = tmp
|
270 |
+
proj_file_name = proj_base_name + "_" + str(proj_index).zfill(5)
|
271 |
+
export_project( project, proj_file_name )
|
272 |
+
proj_index += 1
|
273 |
+
dbg.print("exported : " + proj_file_name + ".ebs" )
|
274 |
+
|
275 |
+
dbg.print("")
|
276 |
+
dbg.print("completed.")
|
277 |
+
|
278 |
+
|
279 |
+
|
ebsynth_utility/stage7.py
ADDED
@@ -0,0 +1,234 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
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|
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|
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|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
import os
|
2 |
+
import re
|
3 |
+
import subprocess
|
4 |
+
import glob
|
5 |
+
import shutil
|
6 |
+
import time
|
7 |
+
import cv2
|
8 |
+
import numpy as np
|
9 |
+
|
10 |
+
|
11 |
+
def clamp(n, smallest, largest):
|
12 |
+
return sorted([smallest, n, largest])[1]
|
13 |
+
|
14 |
+
|
15 |
+
def create_movie_from_frames( dir, start, end, number_of_digits, fps, output_path, export_type):
|
16 |
+
def get_export_str(export_type):
|
17 |
+
if export_type == "mp4":
|
18 |
+
return " -vcodec libx264 -pix_fmt yuv420p "
|
19 |
+
elif export_type == "webm":
|
20 |
+
# return " -vcodec vp9 -crf 10 -b:v 0 "
|
21 |
+
return " -crf 40 -b:v 0 -threads 4 "
|
22 |
+
elif export_type == "gif":
|
23 |
+
return " "
|
24 |
+
elif export_type == "rawvideo":
|
25 |
+
return " -vcodec rawvideo -pix_fmt bgr24 "
|
26 |
+
|
27 |
+
vframes = end - start + 1
|
28 |
+
path = os.path.join(dir , '%0' + str(number_of_digits) + 'd.png')
|
29 |
+
|
30 |
+
# ffmpeg -r 10 -start_number n -i snapshot_%03d.png -vframes 50 example.gif
|
31 |
+
subprocess.call("ffmpeg -framerate " + str(fps) + " -r " + str(fps) +
|
32 |
+
" -start_number " + str(start) +
|
33 |
+
" -i " + path +
|
34 |
+
" -vframes " + str( vframes ) +
|
35 |
+
get_export_str(export_type) +
|
36 |
+
output_path, shell=True)
|
37 |
+
|
38 |
+
|
39 |
+
def search_out_dirs(proj_dir, blend_rate):
|
40 |
+
### create out_dirs
|
41 |
+
p = re.compile(r'.*[\\\/]out\-([0-9]+)[\\\/]')
|
42 |
+
|
43 |
+
number_of_digits = -1
|
44 |
+
|
45 |
+
out_dirs=[]
|
46 |
+
for d in glob.glob( os.path.join(proj_dir ,"out-*/"), recursive=False):
|
47 |
+
m = p.fullmatch(d)
|
48 |
+
if m:
|
49 |
+
if number_of_digits == -1:
|
50 |
+
number_of_digits = len(m.group(1))
|
51 |
+
out_dirs.append({ 'keyframe':int(m.group(1)), 'path':d })
|
52 |
+
|
53 |
+
out_dirs = sorted(out_dirs, key=lambda x: x['keyframe'], reverse=True)
|
54 |
+
|
55 |
+
print(number_of_digits)
|
56 |
+
|
57 |
+
prev_key = -1
|
58 |
+
for out_d in out_dirs:
|
59 |
+
out_d['next_keyframe'] = prev_key
|
60 |
+
prev_key = out_d['keyframe']
|
61 |
+
|
62 |
+
out_dirs = sorted(out_dirs, key=lambda x: x['keyframe'])
|
63 |
+
|
64 |
+
|
65 |
+
### search start/end frame
|
66 |
+
prev_key = 0
|
67 |
+
for out_d in out_dirs:
|
68 |
+
imgs = sorted(glob.glob( os.path.join( out_d['path'], '[0-9]'*number_of_digits + '.png') ))
|
69 |
+
|
70 |
+
first_img = imgs[0]
|
71 |
+
print(first_img)
|
72 |
+
basename_without_ext = os.path.splitext(os.path.basename(first_img))[0]
|
73 |
+
blend_timing = (prev_key - out_d['keyframe'])*blend_rate + out_d['keyframe']
|
74 |
+
blend_timing = round(blend_timing)
|
75 |
+
start_frame = max( blend_timing, int(basename_without_ext) )
|
76 |
+
out_d['startframe'] = start_frame
|
77 |
+
|
78 |
+
last_img = imgs[-1]
|
79 |
+
print(last_img)
|
80 |
+
basename_without_ext = os.path.splitext(os.path.basename(last_img))[0]
|
81 |
+
end_frame = min( out_d['next_keyframe'], int(basename_without_ext) )
|
82 |
+
if end_frame == -1:
|
83 |
+
end_frame = int(basename_without_ext)
|
84 |
+
out_d['endframe'] = end_frame
|
85 |
+
prev_key = out_d['keyframe']
|
86 |
+
|
87 |
+
return number_of_digits, out_dirs
|
88 |
+
|
89 |
+
def get_ext(export_type):
|
90 |
+
if export_type in ("mp4","webm","gif"):
|
91 |
+
return "." + export_type
|
92 |
+
else:
|
93 |
+
return ".avi"
|
94 |
+
|
95 |
+
def trying_to_add_audio(original_movie_path, no_snd_movie_path, output_path, tmp_dir ):
|
96 |
+
if os.path.isfile(original_movie_path):
|
97 |
+
sound_path = os.path.join(tmp_dir , 'sound.mp4')
|
98 |
+
subprocess.call("ffmpeg -i " + original_movie_path + " -vn -acodec copy " + sound_path, shell=True)
|
99 |
+
|
100 |
+
if os.path.isfile(sound_path):
|
101 |
+
# ffmpeg -i video.mp4 -i audio.wav -c:v copy -c:a aac -map 0:v:0 -map 1:a:0 output.mp4
|
102 |
+
|
103 |
+
subprocess.call("ffmpeg -i " + no_snd_movie_path + " -i " + sound_path + " -c:v copy -c:a aac -map 0:v:0 -map 1:a:0 " + output_path, shell=True)
|
104 |
+
return True
|
105 |
+
|
106 |
+
return False
|
107 |
+
|
108 |
+
def ebsynth_utility_stage7(dbg, project_args, blend_rate,export_type,is_invert_mask):
|
109 |
+
dbg.print("stage7")
|
110 |
+
dbg.print("")
|
111 |
+
|
112 |
+
project_dir, original_movie_path, _, _, _, _, _ = project_args
|
113 |
+
|
114 |
+
fps = 30
|
115 |
+
clip = cv2.VideoCapture(original_movie_path)
|
116 |
+
if clip:
|
117 |
+
fps = clip.get(cv2.CAP_PROP_FPS)
|
118 |
+
clip.release()
|
119 |
+
|
120 |
+
blend_rate = clamp(blend_rate, 0.0, 1.0)
|
121 |
+
|
122 |
+
dbg.print("blend_rate: {}".format(blend_rate))
|
123 |
+
dbg.print("export_type: {}".format(export_type))
|
124 |
+
dbg.print("fps: {}".format(fps))
|
125 |
+
|
126 |
+
if is_invert_mask:
|
127 |
+
project_dir = os.path.join( project_dir , "inv")
|
128 |
+
|
129 |
+
tmp_dir = os.path.join( project_dir , "crossfade_tmp")
|
130 |
+
|
131 |
+
|
132 |
+
if os.path.isdir(tmp_dir):
|
133 |
+
shutil.rmtree(tmp_dir)
|
134 |
+
os.mkdir(tmp_dir)
|
135 |
+
|
136 |
+
number_of_digits, out_dirs = search_out_dirs( project_dir, blend_rate )
|
137 |
+
|
138 |
+
if number_of_digits == -1:
|
139 |
+
dbg.print('no out dir')
|
140 |
+
return
|
141 |
+
|
142 |
+
### create frame imgs
|
143 |
+
|
144 |
+
start = out_dirs[0]['startframe']
|
145 |
+
end = out_dirs[-1]['endframe']
|
146 |
+
|
147 |
+
cur_clip = 0
|
148 |
+
next_clip = cur_clip+1 if len(out_dirs) > cur_clip+1 else -1
|
149 |
+
|
150 |
+
current_frame = 0
|
151 |
+
|
152 |
+
print(str(start) + " -> " + str(end+1))
|
153 |
+
|
154 |
+
black_img = np.zeros_like( cv2.imread( os.path.join(out_dirs[cur_clip]['path'], str(start).zfill(number_of_digits) + ".png") ) )
|
155 |
+
|
156 |
+
for i in range(start, end+1):
|
157 |
+
|
158 |
+
print(str(i) + " / " + str(end))
|
159 |
+
|
160 |
+
if next_clip == -1:
|
161 |
+
break
|
162 |
+
|
163 |
+
if i in range( out_dirs[cur_clip]['startframe'], out_dirs[cur_clip]['endframe'] +1):
|
164 |
+
pass
|
165 |
+
elif i in range( out_dirs[next_clip]['startframe'], out_dirs[next_clip]['endframe'] +1):
|
166 |
+
cur_clip = next_clip
|
167 |
+
next_clip = cur_clip+1 if len(out_dirs) > cur_clip+1 else -1
|
168 |
+
if next_clip == -1:
|
169 |
+
break
|
170 |
+
else:
|
171 |
+
### black
|
172 |
+
# front ... none
|
173 |
+
# back ... none
|
174 |
+
cv2.imwrite( os.path.join(tmp_dir, filename) , black_img)
|
175 |
+
current_frame = i
|
176 |
+
continue
|
177 |
+
|
178 |
+
filename = str(i).zfill(number_of_digits) + ".png"
|
179 |
+
|
180 |
+
# front ... cur_clip
|
181 |
+
# back ... next_clip or none
|
182 |
+
|
183 |
+
if i in range( out_dirs[next_clip]['startframe'], out_dirs[next_clip]['endframe'] +1):
|
184 |
+
# front ... cur_clip
|
185 |
+
# back ... next_clip
|
186 |
+
img_f = cv2.imread( os.path.join(out_dirs[cur_clip]['path'] , filename) )
|
187 |
+
img_b = cv2.imread( os.path.join(out_dirs[next_clip]['path'] , filename) )
|
188 |
+
|
189 |
+
back_rate = (i - out_dirs[next_clip]['startframe'])/ max( 1 , (out_dirs[cur_clip]['endframe'] - out_dirs[next_clip]['startframe']) )
|
190 |
+
|
191 |
+
img = cv2.addWeighted(img_f, 1.0 - back_rate, img_b, back_rate, 0)
|
192 |
+
|
193 |
+
cv2.imwrite( os.path.join(tmp_dir , filename) , img)
|
194 |
+
else:
|
195 |
+
# front ... cur_clip
|
196 |
+
# back ... none
|
197 |
+
filename = str(i).zfill(number_of_digits) + ".png"
|
198 |
+
shutil.copy( os.path.join(out_dirs[cur_clip]['path'] , filename) , os.path.join(tmp_dir , filename) )
|
199 |
+
|
200 |
+
current_frame = i
|
201 |
+
|
202 |
+
|
203 |
+
start2 = current_frame+1
|
204 |
+
|
205 |
+
print(str(start2) + " -> " + str(end+1))
|
206 |
+
|
207 |
+
for i in range(start2, end+1):
|
208 |
+
filename = str(i).zfill(number_of_digits) + ".png"
|
209 |
+
shutil.copy( os.path.join(out_dirs[cur_clip]['path'] , filename) , os.path.join(tmp_dir , filename) )
|
210 |
+
|
211 |
+
### create movie
|
212 |
+
movie_base_name = time.strftime("%Y%m%d-%H%M%S")
|
213 |
+
if is_invert_mask:
|
214 |
+
movie_base_name = "inv_" + movie_base_name
|
215 |
+
|
216 |
+
nosnd_path = os.path.join(project_dir , movie_base_name + get_ext(export_type))
|
217 |
+
|
218 |
+
start = out_dirs[0]['startframe']
|
219 |
+
end = out_dirs[-1]['endframe']
|
220 |
+
|
221 |
+
create_movie_from_frames( tmp_dir, start, end, number_of_digits, fps, nosnd_path, export_type)
|
222 |
+
|
223 |
+
dbg.print("exported : " + nosnd_path)
|
224 |
+
|
225 |
+
if export_type == "mp4":
|
226 |
+
|
227 |
+
with_snd_path = os.path.join(project_dir , movie_base_name + '_with_snd.mp4')
|
228 |
+
|
229 |
+
if trying_to_add_audio(original_movie_path, nosnd_path, with_snd_path, tmp_dir):
|
230 |
+
dbg.print("exported : " + with_snd_path)
|
231 |
+
|
232 |
+
dbg.print("")
|
233 |
+
dbg.print("completed.")
|
234 |
+
|
ebsynth_utility/stage8.py
ADDED
@@ -0,0 +1,146 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
import os
|
2 |
+
import re
|
3 |
+
import subprocess
|
4 |
+
import glob
|
5 |
+
import shutil
|
6 |
+
import time
|
7 |
+
import cv2
|
8 |
+
import numpy as np
|
9 |
+
import itertools
|
10 |
+
from extensions.ebsynth_utility.stage7 import create_movie_from_frames, get_ext, trying_to_add_audio
|
11 |
+
|
12 |
+
def clamp(n, smallest, largest):
|
13 |
+
return sorted([smallest, n, largest])[1]
|
14 |
+
|
15 |
+
def resize_img(img, w, h):
|
16 |
+
if img.shape[0] + img.shape[1] < h + w:
|
17 |
+
interpolation = interpolation=cv2.INTER_CUBIC
|
18 |
+
else:
|
19 |
+
interpolation = interpolation=cv2.INTER_AREA
|
20 |
+
|
21 |
+
return cv2.resize(img, (w, h), interpolation=interpolation)
|
22 |
+
|
23 |
+
def merge_bg_src(base_frame_dir, bg_dir, frame_mask_path, tmp_dir, bg_type, mask_blur_size, mask_threshold, fg_transparency):
|
24 |
+
|
25 |
+
base_frames = sorted(glob.glob( os.path.join(base_frame_dir, "[0-9]*.png"), recursive=False) )
|
26 |
+
|
27 |
+
bg_frames = sorted(glob.glob( os.path.join(bg_dir, "*.png"), recursive=False) )
|
28 |
+
|
29 |
+
def bg_frame(total_frames):
|
30 |
+
bg_len = len(bg_frames)
|
31 |
+
|
32 |
+
if bg_type == "Loop":
|
33 |
+
itr = itertools.cycle(bg_frames)
|
34 |
+
while True:
|
35 |
+
yield next(itr)
|
36 |
+
else:
|
37 |
+
for i in range(total_frames):
|
38 |
+
yield bg_frames[ int(bg_len * (i/total_frames))]
|
39 |
+
|
40 |
+
bg_itr = bg_frame(len(base_frames))
|
41 |
+
|
42 |
+
for base_frame in base_frames:
|
43 |
+
im = cv2.imread(base_frame)
|
44 |
+
bg = cv2.imread( next(bg_itr) )
|
45 |
+
bg = resize_img(bg, im.shape[1], im.shape[0] )
|
46 |
+
|
47 |
+
basename = os.path.basename(base_frame)
|
48 |
+
mask_path = os.path.join(frame_mask_path, basename)
|
49 |
+
mask = cv2.imread(mask_path)[:,:,0]
|
50 |
+
|
51 |
+
mask[mask < int( 255 * mask_threshold )] = 0
|
52 |
+
|
53 |
+
if mask_blur_size > 0:
|
54 |
+
mask_blur_size = mask_blur_size//2 * 2 + 1
|
55 |
+
mask = cv2.GaussianBlur(mask, (mask_blur_size, mask_blur_size), 0)
|
56 |
+
mask = mask[:, :, np.newaxis]
|
57 |
+
|
58 |
+
fore_rate = (mask/255) * (1 - fg_transparency)
|
59 |
+
|
60 |
+
im = im * fore_rate + bg * (1- fore_rate)
|
61 |
+
im = im.astype(np.uint8)
|
62 |
+
cv2.imwrite( os.path.join( tmp_dir , basename ) , im)
|
63 |
+
|
64 |
+
def extract_frames(movie_path , output_dir, fps):
|
65 |
+
png_path = os.path.join(output_dir , "%05d.png")
|
66 |
+
# ffmpeg.exe -ss 00:00:00 -y -i %1 -qscale 0 -f image2 -c:v png "%05d.png"
|
67 |
+
subprocess.call("ffmpeg -ss 00:00:00 -y -i " + movie_path + " -vf fps=" + str( round(fps, 2)) + " -qscale 0 -f image2 -c:v png " + png_path, shell=True)
|
68 |
+
|
69 |
+
def ebsynth_utility_stage8(dbg, project_args, bg_src, bg_type, mask_blur_size, mask_threshold, fg_transparency, export_type):
|
70 |
+
dbg.print("stage8")
|
71 |
+
dbg.print("")
|
72 |
+
|
73 |
+
if not bg_src:
|
74 |
+
dbg.print("Fill [configuration] -> [stage 8] -> [Background source]")
|
75 |
+
return
|
76 |
+
|
77 |
+
project_dir, original_movie_path, _, frame_mask_path, _, _, _ = project_args
|
78 |
+
|
79 |
+
fps = 30
|
80 |
+
clip = cv2.VideoCapture(original_movie_path)
|
81 |
+
if clip:
|
82 |
+
fps = clip.get(cv2.CAP_PROP_FPS)
|
83 |
+
clip.release()
|
84 |
+
|
85 |
+
dbg.print("bg_src: {}".format(bg_src))
|
86 |
+
dbg.print("bg_type: {}".format(bg_type))
|
87 |
+
dbg.print("mask_blur_size: {}".format(mask_blur_size))
|
88 |
+
dbg.print("export_type: {}".format(export_type))
|
89 |
+
dbg.print("fps: {}".format(fps))
|
90 |
+
|
91 |
+
base_frame_dir = os.path.join( project_dir , "crossfade_tmp")
|
92 |
+
|
93 |
+
if not os.path.isdir(base_frame_dir):
|
94 |
+
dbg.print(base_frame_dir + " base frame not found")
|
95 |
+
return
|
96 |
+
|
97 |
+
tmp_dir = os.path.join( project_dir , "bg_merge_tmp")
|
98 |
+
if os.path.isdir(tmp_dir):
|
99 |
+
shutil.rmtree(tmp_dir)
|
100 |
+
os.mkdir(tmp_dir)
|
101 |
+
|
102 |
+
### create frame imgs
|
103 |
+
if os.path.isfile(bg_src):
|
104 |
+
bg_ext = os.path.splitext(os.path.basename(bg_src))[1]
|
105 |
+
if bg_ext == ".mp4":
|
106 |
+
bg_tmp_dir = os.path.join( project_dir , "bg_extract_tmp")
|
107 |
+
if os.path.isdir(bg_tmp_dir):
|
108 |
+
shutil.rmtree(bg_tmp_dir)
|
109 |
+
os.mkdir(bg_tmp_dir)
|
110 |
+
|
111 |
+
extract_frames(bg_src, bg_tmp_dir, fps)
|
112 |
+
|
113 |
+
bg_src = bg_tmp_dir
|
114 |
+
else:
|
115 |
+
dbg.print(bg_src + " must be mp4 or directory")
|
116 |
+
return
|
117 |
+
elif not os.path.isdir(bg_src):
|
118 |
+
dbg.print(bg_src + " must be mp4 or directory")
|
119 |
+
return
|
120 |
+
|
121 |
+
merge_bg_src(base_frame_dir, bg_src, frame_mask_path, tmp_dir, bg_type, mask_blur_size, mask_threshold, fg_transparency)
|
122 |
+
|
123 |
+
### create movie
|
124 |
+
movie_base_name = time.strftime("%Y%m%d-%H%M%S")
|
125 |
+
movie_base_name = "merge_" + movie_base_name
|
126 |
+
|
127 |
+
nosnd_path = os.path.join(project_dir , movie_base_name + get_ext(export_type))
|
128 |
+
|
129 |
+
merged_frames = sorted(glob.glob( os.path.join(tmp_dir, "[0-9]*.png"), recursive=False) )
|
130 |
+
start = int(os.path.splitext(os.path.basename(merged_frames[0]))[0])
|
131 |
+
end = int(os.path.splitext(os.path.basename(merged_frames[-1]))[0])
|
132 |
+
|
133 |
+
create_movie_from_frames(tmp_dir,start,end,5,fps,nosnd_path,export_type)
|
134 |
+
|
135 |
+
dbg.print("exported : " + nosnd_path)
|
136 |
+
|
137 |
+
if export_type == "mp4":
|
138 |
+
|
139 |
+
with_snd_path = os.path.join(project_dir , movie_base_name + '_with_snd.mp4')
|
140 |
+
|
141 |
+
if trying_to_add_audio(original_movie_path, nosnd_path, with_snd_path, tmp_dir):
|
142 |
+
dbg.print("exported : " + with_snd_path)
|
143 |
+
|
144 |
+
dbg.print("")
|
145 |
+
dbg.print("completed.")
|
146 |
+
|
ebsynth_utility/style.css
ADDED
@@ -0,0 +1,39 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
#ebs_info_area {
|
2 |
+
border: black 2px solid;
|
3 |
+
border-radius: 5px;
|
4 |
+
font-size: 15px;
|
5 |
+
margin: 10px;
|
6 |
+
padding: 10px;
|
7 |
+
}
|
8 |
+
|
9 |
+
#ebs_configuration_tab1>div{
|
10 |
+
margin: 5px;
|
11 |
+
padding: 5px;
|
12 |
+
}
|
13 |
+
|
14 |
+
#ebs_configuration_tab2>div{
|
15 |
+
margin: 5px;
|
16 |
+
padding: 5px;
|
17 |
+
}
|
18 |
+
|
19 |
+
#ebs_configuration_tab3_5>div{
|
20 |
+
margin: 5px;
|
21 |
+
padding: 5px;
|
22 |
+
}
|
23 |
+
|
24 |
+
#ebs_configuration_tab7>div{
|
25 |
+
margin: 5px;
|
26 |
+
padding: 5px;
|
27 |
+
}
|
28 |
+
|
29 |
+
#ebs_configuration_tab8>div{
|
30 |
+
margin: 5px;
|
31 |
+
padding: 5px;
|
32 |
+
}
|
33 |
+
|
34 |
+
#ebs_configuration_tab_etc>div{
|
35 |
+
margin: 5px;
|
36 |
+
padding: 5px;
|
37 |
+
}
|
38 |
+
|
39 |
+
|
microsoftexcel-controlnet/__pycache__/preload.cpython-310.pyc
CHANGED
Binary files a/microsoftexcel-controlnet/__pycache__/preload.cpython-310.pyc and b/microsoftexcel-controlnet/__pycache__/preload.cpython-310.pyc differ
|
|
microsoftexcel-controlnet/annotator/__pycache__/util.cpython-310.pyc
CHANGED
Binary files a/microsoftexcel-controlnet/annotator/__pycache__/util.cpython-310.pyc and b/microsoftexcel-controlnet/annotator/__pycache__/util.cpython-310.pyc differ
|
|