Upload tag_tool.py with huggingface_hub
Browse files- tag_tool.py +527 -0
tag_tool.py
ADDED
@@ -0,0 +1,527 @@
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1 |
+
import dateutil.parser
|
2 |
+
|
3 |
+
|
4 |
+
rating_map = {
|
5 |
+
"general": ["safe"],
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6 |
+
"sensitive": ["sensitive"],
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7 |
+
"questionable": ["nsfw"],
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8 |
+
"explicit": ["explicit", "nsfw"],
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9 |
+
"g": ["safe"],
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10 |
+
"s": ["sensitive"],
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11 |
+
"q": ["nsfw"],
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12 |
+
"e": ["explicit", "nsfw"],
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13 |
+
}
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14 |
+
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15 |
+
special_tags = {
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16 |
+
"1girl",
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17 |
+
"2girls",
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18 |
+
"3girls",
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19 |
+
"4girls",
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20 |
+
"5girls",
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21 |
+
"6+girls",
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22 |
+
"multiple_girls",
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23 |
+
"1boy",
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24 |
+
"2boys",
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25 |
+
"3boys",
|
26 |
+
"4boys",
|
27 |
+
"5boys",
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28 |
+
"6+boys",
|
29 |
+
"multiple_boys",
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30 |
+
"male_focus",
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31 |
+
"1other",
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32 |
+
"2others",
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33 |
+
"3others",
|
34 |
+
"4others",
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35 |
+
"5others",
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36 |
+
"6+others",
|
37 |
+
"multiple_others",
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38 |
+
}
|
39 |
+
|
40 |
+
|
41 |
+
|
42 |
+
meta_keywords_black_list_path = "meta_tag_black_list.txt"
|
43 |
+
with open(meta_keywords_black_list_path, "r") as f:
|
44 |
+
meta_keywords_black_list = f.read().splitlines()
|
45 |
+
|
46 |
+
|
47 |
+
|
48 |
+
fav_count_percentile_full = {
|
49 |
+
"general": {
|
50 |
+
5: 1, 10: 1, 15: 2, 20: 3, 25: 3, 30: 4, 35: 5,
|
51 |
+
40: 6, 45: 7, 50: 8, 55: 9, 60: 10, 65: 12,
|
52 |
+
70: 14, 75: 16, 80: 18, 85: 22, 90: 27, 95: 37
|
53 |
+
},
|
54 |
+
"g": {
|
55 |
+
5: 1, 10: 1, 15: 2, 20: 3, 25: 3, 30: 4, 35: 5,
|
56 |
+
40: 6, 45: 7, 50: 8, 55: 9, 60: 10, 65: 12,
|
57 |
+
70: 14, 75: 16, 80: 18, 85: 22, 90: 27, 95: 37
|
58 |
+
},
|
59 |
+
"sensitive": {
|
60 |
+
5: 1, 10: 2, 15: 4, 20: 5, 25: 6, 30: 8, 35: 9,
|
61 |
+
40: 11, 45: 13, 50: 15, 55: 17, 60: 19, 65: 22,
|
62 |
+
70: 26, 75: 30, 80: 36, 85: 44, 90: 56, 95: 81
|
63 |
+
},
|
64 |
+
"s": {
|
65 |
+
5: 1, 10: 2, 15: 4, 20: 5, 25: 6, 30: 8, 35: 9,
|
66 |
+
40: 11, 45: 13, 50: 15, 55: 17, 60: 19, 65: 22,
|
67 |
+
70: 26, 75: 30, 80: 36, 85: 44, 90: 56, 95: 81
|
68 |
+
},
|
69 |
+
"questionable": {
|
70 |
+
5: 4, 10: 8, 15: 11, 20: 14, 25: 18, 30: 21, 35: 25,
|
71 |
+
40: 29, 45: 33, 50: 38, 55: 43, 60: 49, 65: 56,
|
72 |
+
70: 65, 75: 75, 80: 88, 85: 105, 90: 132, 95: 182
|
73 |
+
},
|
74 |
+
"q": {
|
75 |
+
5: 4, 10: 8, 15: 11, 20: 14, 25: 18, 30: 21, 35: 25,
|
76 |
+
40: 29, 45: 33, 50: 38, 55: 43, 60: 49, 65: 56,
|
77 |
+
70: 65, 75: 75, 80: 88, 85: 105, 90: 132, 95: 182
|
78 |
+
},
|
79 |
+
"explicit": {
|
80 |
+
5: 4, 10: 9, 15: 13, 20: 18, 25: 22, 30: 27, 35: 33,
|
81 |
+
40: 39, 45: 45, 50: 52, 55: 60, 60: 69, 65: 79,
|
82 |
+
70: 92, 75: 106, 80: 125, 85: 151, 90: 190, 95: 262
|
83 |
+
},
|
84 |
+
"e": {
|
85 |
+
5: 4, 10: 9, 15: 13, 20: 18, 25: 22, 30: 27, 35: 33,
|
86 |
+
40: 39, 45: 45, 50: 52, 55: 60, 60: 69, 65: 79,
|
87 |
+
70: 92, 75: 106, 80: 125, 85: 151, 90: 190, 95: 262
|
88 |
+
},
|
89 |
+
}
|
90 |
+
|
91 |
+
score_percentile_full = {
|
92 |
+
"general": {
|
93 |
+
5: 0,
|
94 |
+
10: 1,
|
95 |
+
15: 2,
|
96 |
+
20: 3,
|
97 |
+
25: 3,
|
98 |
+
30: 4,
|
99 |
+
35: 5,
|
100 |
+
40: 5,
|
101 |
+
45: 6,
|
102 |
+
50: 7,
|
103 |
+
55: 8,
|
104 |
+
60: 9,
|
105 |
+
65: 11,
|
106 |
+
70: 12,
|
107 |
+
75: 14,
|
108 |
+
80: 16,
|
109 |
+
85: 19,
|
110 |
+
90: 24,
|
111 |
+
95: 33,
|
112 |
+
},
|
113 |
+
"sensitive": {
|
114 |
+
5: 0,
|
115 |
+
10: 1,
|
116 |
+
15: 2,
|
117 |
+
20: 3,
|
118 |
+
25: 4,
|
119 |
+
30: 5,
|
120 |
+
35: 6,
|
121 |
+
40: 7,
|
122 |
+
45: 8,
|
123 |
+
50: 9,
|
124 |
+
55: 11,
|
125 |
+
60: 12,
|
126 |
+
65: 15,
|
127 |
+
70: 17,
|
128 |
+
75: 20,
|
129 |
+
80: 25,
|
130 |
+
85: 31,
|
131 |
+
90: 41,
|
132 |
+
95: 62,
|
133 |
+
},
|
134 |
+
"questionable": {
|
135 |
+
5: 2,
|
136 |
+
10: 4,
|
137 |
+
15: 5,
|
138 |
+
20: 7,
|
139 |
+
25: 9,
|
140 |
+
30: 11,
|
141 |
+
35: 14,
|
142 |
+
40: 16,
|
143 |
+
45: 19,
|
144 |
+
50: 23,
|
145 |
+
55: 26,
|
146 |
+
60: 31,
|
147 |
+
65: 36,
|
148 |
+
70: 42,
|
149 |
+
75: 49,
|
150 |
+
80: 59,
|
151 |
+
85: 73,
|
152 |
+
90: 93,
|
153 |
+
95: 134,
|
154 |
+
},
|
155 |
+
"explicit": {
|
156 |
+
5: 2,
|
157 |
+
10: 4,
|
158 |
+
15: 7,
|
159 |
+
20: 10,
|
160 |
+
25: 13,
|
161 |
+
30: 17,
|
162 |
+
35: 20,
|
163 |
+
40: 25,
|
164 |
+
45: 29,
|
165 |
+
50: 35,
|
166 |
+
55: 41,
|
167 |
+
60: 48,
|
168 |
+
65: 56,
|
169 |
+
70: 66,
|
170 |
+
75: 78,
|
171 |
+
80: 94,
|
172 |
+
85: 115,
|
173 |
+
90: 148,
|
174 |
+
95: 211,
|
175 |
+
},
|
176 |
+
"g": {
|
177 |
+
5: 0,
|
178 |
+
10: 1,
|
179 |
+
15: 2,
|
180 |
+
20: 3,
|
181 |
+
25: 3,
|
182 |
+
30: 4,
|
183 |
+
35: 5,
|
184 |
+
40: 5,
|
185 |
+
45: 6,
|
186 |
+
50: 7,
|
187 |
+
55: 8,
|
188 |
+
60: 9,
|
189 |
+
65: 11,
|
190 |
+
70: 12,
|
191 |
+
75: 14,
|
192 |
+
80: 16,
|
193 |
+
85: 19,
|
194 |
+
90: 24,
|
195 |
+
95: 33,
|
196 |
+
},
|
197 |
+
"s": {
|
198 |
+
5: 0,
|
199 |
+
10: 1,
|
200 |
+
15: 2,
|
201 |
+
20: 3,
|
202 |
+
25: 4,
|
203 |
+
30: 5,
|
204 |
+
35: 6,
|
205 |
+
40: 7,
|
206 |
+
45: 8,
|
207 |
+
50: 9,
|
208 |
+
55: 11,
|
209 |
+
60: 12,
|
210 |
+
65: 15,
|
211 |
+
70: 17,
|
212 |
+
75: 20,
|
213 |
+
80: 25,
|
214 |
+
85: 31,
|
215 |
+
90: 41,
|
216 |
+
95: 62,
|
217 |
+
},
|
218 |
+
"q": {
|
219 |
+
5: 2,
|
220 |
+
10: 4,
|
221 |
+
15: 5,
|
222 |
+
20: 7,
|
223 |
+
25: 9,
|
224 |
+
30: 11,
|
225 |
+
35: 14,
|
226 |
+
40: 16,
|
227 |
+
45: 19,
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228 |
+
50: 23,
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+
55: 26,
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60: 31,
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65: 36,
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70: 42,
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75: 49,
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80: 59,
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+
85: 73,
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+
90: 93,
|
237 |
+
95: 134,
|
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+
},
|
239 |
+
"e": {
|
240 |
+
5: 2,
|
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+
10: 4,
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+
15: 7,
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+
20: 10,
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25: 13,
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30: 17,
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35: 20,
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40: 25,
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45: 29,
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50: 35,
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55: 41,
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60: 48,
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65: 56,
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70: 66,
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75: 78,
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80: 94,
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85: 115,
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90: 148,
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95: 211,
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},
|
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}
|
261 |
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|
262 |
+
score_percentile_after_5m = {
|
263 |
+
"general": {
|
264 |
+
5: 1,
|
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+
10: 1,
|
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15: 2,
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20: 3,
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25: 4,
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30: 5,
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35: 5,
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40: 6,
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45: 7,
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50: 8,
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55: 10,
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60: 11,
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65: 13,
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70: 14,
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75: 17,
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80: 19,
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+
85: 23,
|
281 |
+
90: 28,
|
282 |
+
95: 38,
|
283 |
+
},
|
284 |
+
"sensitive": {
|
285 |
+
5: 2,
|
286 |
+
10: 4,
|
287 |
+
15: 7,
|
288 |
+
20: 9,
|
289 |
+
25: 11,
|
290 |
+
30: 13,
|
291 |
+
35: 16,
|
292 |
+
40: 18,
|
293 |
+
45: 21,
|
294 |
+
50: 24,
|
295 |
+
55: 28,
|
296 |
+
60: 31,
|
297 |
+
65: 36,
|
298 |
+
70: 41,
|
299 |
+
75: 48,
|
300 |
+
80: 56,
|
301 |
+
85: 67,
|
302 |
+
90: 84,
|
303 |
+
95: 118,
|
304 |
+
},
|
305 |
+
"questionable": {
|
306 |
+
5: 4,
|
307 |
+
10: 9,
|
308 |
+
15: 14,
|
309 |
+
20: 19,
|
310 |
+
25: 24,
|
311 |
+
30: 29,
|
312 |
+
35: 34,
|
313 |
+
40: 40,
|
314 |
+
45: 45,
|
315 |
+
50: 52,
|
316 |
+
55: 59,
|
317 |
+
60: 67,
|
318 |
+
65: 75,
|
319 |
+
70: 86,
|
320 |
+
75: 98,
|
321 |
+
80: 114,
|
322 |
+
85: 136,
|
323 |
+
90: 168,
|
324 |
+
95: 228,
|
325 |
+
},
|
326 |
+
"explicit": {
|
327 |
+
5: 5,
|
328 |
+
10: 11,
|
329 |
+
15: 16,
|
330 |
+
20: 22,
|
331 |
+
25: 28,
|
332 |
+
30: 34,
|
333 |
+
35: 40,
|
334 |
+
40: 47,
|
335 |
+
45: 54,
|
336 |
+
50: 63,
|
337 |
+
55: 72,
|
338 |
+
60: 82,
|
339 |
+
65: 94,
|
340 |
+
70: 108,
|
341 |
+
75: 124,
|
342 |
+
80: 145,
|
343 |
+
85: 174,
|
344 |
+
90: 216,
|
345 |
+
95: 296,
|
346 |
+
},
|
347 |
+
"g": {
|
348 |
+
5: 1,
|
349 |
+
10: 1,
|
350 |
+
15: 2,
|
351 |
+
20: 3,
|
352 |
+
25: 4,
|
353 |
+
30: 5,
|
354 |
+
35: 5,
|
355 |
+
40: 6,
|
356 |
+
45: 7,
|
357 |
+
50: 8,
|
358 |
+
55: 10,
|
359 |
+
60: 11,
|
360 |
+
65: 13,
|
361 |
+
70: 14,
|
362 |
+
75: 17,
|
363 |
+
80: 19,
|
364 |
+
85: 23,
|
365 |
+
90: 28,
|
366 |
+
95: 38,
|
367 |
+
},
|
368 |
+
"s": {
|
369 |
+
5: 2,
|
370 |
+
10: 4,
|
371 |
+
15: 7,
|
372 |
+
20: 9,
|
373 |
+
25: 11,
|
374 |
+
30: 13,
|
375 |
+
35: 16,
|
376 |
+
40: 18,
|
377 |
+
45: 21,
|
378 |
+
50: 24,
|
379 |
+
55: 28,
|
380 |
+
60: 31,
|
381 |
+
65: 36,
|
382 |
+
70: 41,
|
383 |
+
75: 48,
|
384 |
+
80: 56,
|
385 |
+
85: 67,
|
386 |
+
90: 84,
|
387 |
+
95: 118,
|
388 |
+
},
|
389 |
+
"q": {
|
390 |
+
5: 4,
|
391 |
+
10: 9,
|
392 |
+
15: 14,
|
393 |
+
20: 19,
|
394 |
+
25: 24,
|
395 |
+
30: 29,
|
396 |
+
35: 34,
|
397 |
+
40: 40,
|
398 |
+
45: 45,
|
399 |
+
50: 52,
|
400 |
+
55: 59,
|
401 |
+
60: 67,
|
402 |
+
65: 75,
|
403 |
+
70: 86,
|
404 |
+
75: 98,
|
405 |
+
80: 114,
|
406 |
+
85: 136,
|
407 |
+
90: 168,
|
408 |
+
95: 228,
|
409 |
+
},
|
410 |
+
"e": {
|
411 |
+
5: 5,
|
412 |
+
10: 11,
|
413 |
+
15: 16,
|
414 |
+
20: 22,
|
415 |
+
25: 28,
|
416 |
+
30: 34,
|
417 |
+
35: 40,
|
418 |
+
40: 47,
|
419 |
+
45: 54,
|
420 |
+
50: 63,
|
421 |
+
55: 72,
|
422 |
+
60: 82,
|
423 |
+
65: 94,
|
424 |
+
70: 108,
|
425 |
+
75: 124,
|
426 |
+
80: 145,
|
427 |
+
85: 174,
|
428 |
+
90: 216,
|
429 |
+
95: 296,
|
430 |
+
},
|
431 |
+
}
|
432 |
+
|
433 |
+
|
434 |
+
|
435 |
+
def year_tag(
|
436 |
+
created_at
|
437 |
+
) -> str:
|
438 |
+
year = 0
|
439 |
+
try:
|
440 |
+
date = dateutil.parser.parse(created_at)
|
441 |
+
year = date.year
|
442 |
+
except:
|
443 |
+
pass
|
444 |
+
if 2005 <= year <= 2010:
|
445 |
+
year_tag = "old"
|
446 |
+
elif year <= 2014:
|
447 |
+
year_tag = "early"
|
448 |
+
elif year <= 2017:
|
449 |
+
year_tag = "mid"
|
450 |
+
elif year <= 2020:
|
451 |
+
year_tag = "recent"
|
452 |
+
elif year <= 2024:
|
453 |
+
year_tag = "newest"
|
454 |
+
else:
|
455 |
+
return None
|
456 |
+
|
457 |
+
return year_tag
|
458 |
+
|
459 |
+
|
460 |
+
def rating_tag(
|
461 |
+
rating
|
462 |
+
) -> str:
|
463 |
+
if (tag := rating_map.get(rating, None)) is not None:
|
464 |
+
return tag[0]
|
465 |
+
else:
|
466 |
+
return None
|
467 |
+
|
468 |
+
|
469 |
+
def quality_tag(
|
470 |
+
id,
|
471 |
+
fav_count,
|
472 |
+
rating,
|
473 |
+
|
474 |
+
percentile_map: dict[str, dict[int, int]] = fav_count_percentile_full,
|
475 |
+
) -> tuple[list[str], list[str]]:
|
476 |
+
if int(id) > 7800000:
|
477 |
+
# Don't add quality tag for posts which are new.
|
478 |
+
return None
|
479 |
+
else:
|
480 |
+
percentile_map = fav_count_percentile_full
|
481 |
+
rating = rating
|
482 |
+
score = fav_count
|
483 |
+
percentile = percentile_map[rating]
|
484 |
+
|
485 |
+
if score > percentile[95]:
|
486 |
+
quality_tag = "masterpiece"
|
487 |
+
elif score > percentile[85]:
|
488 |
+
quality_tag = "best quality"
|
489 |
+
elif score > percentile[75]:
|
490 |
+
quality_tag = "great quality"
|
491 |
+
elif score > percentile[50]:
|
492 |
+
quality_tag = "good quality"
|
493 |
+
elif score > percentile[25]:
|
494 |
+
quality_tag = "normal quality"
|
495 |
+
elif score > percentile[10]:
|
496 |
+
quality_tag = "low quality"
|
497 |
+
else:
|
498 |
+
quality_tag = "worst quality"
|
499 |
+
|
500 |
+
|
501 |
+
|
502 |
+
return quality_tag
|
503 |
+
|
504 |
+
def tags_filter(tag, black_list: list[str]) -> bool:
|
505 |
+
return not any(keyword in tag for keyword in black_list)
|
506 |
+
|
507 |
+
|
508 |
+
def meta_tags_filter(tags) -> list[str]:
|
509 |
+
|
510 |
+
|
511 |
+
# NOTE: we only filter out meta tags with these keywords
|
512 |
+
# Which is definitely not related to the content of image
|
513 |
+
return [tag for tag in tags if tags_filter(tag, meta_keywords_black_list)]
|
514 |
+
|
515 |
+
def extract_special_tags(tag_list) -> tuple[list[str], list[str]]:
|
516 |
+
special = []
|
517 |
+
general = []
|
518 |
+
for tag in tag_list:
|
519 |
+
if tag in special_tags:
|
520 |
+
special.append(tag)
|
521 |
+
else:
|
522 |
+
general.append(tag)
|
523 |
+
return special, general
|
524 |
+
|
525 |
+
|
526 |
+
|
527 |
+
|