Kohaku-Blueleaf
commited on
Commit
•
4f72b76
1
Parent(s):
ff3b374
Modify introductions
Browse files
app.py
CHANGED
@@ -30,7 +30,7 @@ from kgen.formatter import seperate_tags, apply_format
|
|
30 |
from kgen.generate import generate
|
31 |
|
32 |
from diff import load_model, encode_prompts
|
33 |
-
from meta import DEFAULT_NEGATIVE_PROMPT
|
34 |
|
35 |
|
36 |
sdxl_pipe = load_model()
|
@@ -41,17 +41,6 @@ models.load_model(
|
|
41 |
subfolder="dan-cc-coyo_epoch2",
|
42 |
)
|
43 |
generate(max_new_tokens=4)
|
44 |
-
|
45 |
-
|
46 |
-
DEFAULT_FORMAT = """<|special|>, <|characters|>, <|copyrights|>,
|
47 |
-
<|artist|>,
|
48 |
-
|
49 |
-
<|general|>,
|
50 |
-
|
51 |
-
<|extended|>.
|
52 |
-
|
53 |
-
<|quality|>, <|meta|>, <|rating|>
|
54 |
-
""".strip()
|
55 |
DEFAULT_TAGS = """
|
56 |
1girl, king halo (umamusume), umamusume,
|
57 |
ningen mame, ciloranko, ogipote, misu kasumi,
|
@@ -103,6 +92,7 @@ def generate(
|
|
103 |
nl_prompt,
|
104 |
black_list,
|
105 |
temp,
|
|
|
106 |
target_length,
|
107 |
top_p,
|
108 |
min_p,
|
@@ -110,6 +100,7 @@ def generate(
|
|
110 |
seed,
|
111 |
escape_brackets,
|
112 |
):
|
|
|
113 |
titpop.BAN_TAGS = [t.strip() for t in black_list.split(",") if t.strip()]
|
114 |
generation_setting = {
|
115 |
"seed": seed,
|
@@ -120,11 +111,11 @@ def generate(
|
|
120 |
}
|
121 |
inputs = seperate_tags(tags.split(","))
|
122 |
if nl_prompt:
|
123 |
-
if "<|extended|>" in
|
124 |
inputs["extended"] = nl_prompt
|
125 |
-
elif "<|generated|>" in
|
126 |
inputs["generated"] = nl_prompt
|
127 |
-
input_prompt = apply_format(inputs,
|
128 |
if escape_brackets:
|
129 |
input_prompt = re.sub(r"([()\[\]])", r"\\\1", input_prompt)
|
130 |
|
@@ -132,13 +123,13 @@ def generate(
|
|
132 |
seperate_tags(tags.split(",")),
|
133 |
nl_prompt,
|
134 |
tag_length_target=target_length,
|
135 |
-
generate_extra_nl_prompt="<|generated|>" in
|
136 |
)
|
137 |
t0 = time()
|
138 |
for result, timing in titpop.titpop_runner_generator(
|
139 |
meta, operations, general, nl_prompt, **generation_setting
|
140 |
):
|
141 |
-
result = apply_format(result,
|
142 |
if escape_brackets:
|
143 |
result = re.sub(r"([()\[\]])", r"\\\1", result)
|
144 |
timing["total"] = time() - t0
|
@@ -153,11 +144,11 @@ def generate_image(
|
|
153 |
prompt2,
|
154 |
):
|
155 |
torch.cuda.empty_cache()
|
|
|
156 |
prompt_embeds, negative_prompt_embeds, pooled_embeds2, neg_pooled_embeds2 = (
|
157 |
-
encode_prompts(sdxl_pipe,
|
158 |
)
|
159 |
-
|
160 |
-
result = sdxl_pipe(
|
161 |
prompt_embeds=prompt_embeds,
|
162 |
negative_prompt_embeds=negative_prompt_embeds,
|
163 |
pooled_prompt_embeds=pooled_embeds2,
|
@@ -167,11 +158,13 @@ def generate_image(
|
|
167 |
height=1024,
|
168 |
guidance_scale=6.0,
|
169 |
).images[0]
|
|
|
|
|
170 |
prompt_embeds, negative_prompt_embeds, pooled_embeds2, neg_pooled_embeds2 = (
|
171 |
-
encode_prompts(sdxl_pipe,
|
172 |
)
|
173 |
set_seed(seed)
|
174 |
-
|
175 |
prompt_embeds=prompt_embeds,
|
176 |
negative_prompt_embeds=negative_prompt_embeds,
|
177 |
pooled_prompt_embeds=pooled_embeds2,
|
@@ -182,19 +175,39 @@ def generate_image(
|
|
182 |
guidance_scale=6.0,
|
183 |
).images[0]
|
184 |
torch.cuda.empty_cache()
|
185 |
-
|
186 |
|
187 |
|
188 |
if __name__ == "__main__":
|
189 |
with gr.Blocks(theme=gr.themes.Soft()) as demo:
|
190 |
-
gr.Markdown("""# TITPOP DEMO""")
|
191 |
with gr.Accordion("Introduction and Instructions", open=False):
|
192 |
gr.Markdown(
|
193 |
"""
|
194 |
-
|
195 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
196 |
|
197 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
198 |
"""
|
199 |
)
|
200 |
with gr.Row():
|
@@ -203,7 +216,7 @@ TITPOP
|
|
203 |
with gr.Column(scale=3):
|
204 |
tags_input = gr.TextArea(
|
205 |
label="Danbooru Tags",
|
206 |
-
lines=
|
207 |
show_copy_button=True,
|
208 |
interactive=True,
|
209 |
value=DEFAULT_TAGS,
|
@@ -211,7 +224,7 @@ TITPOP
|
|
211 |
)
|
212 |
nl_prompt_input = gr.Textbox(
|
213 |
label="Natural Language Prompt",
|
214 |
-
lines=
|
215 |
show_copy_button=True,
|
216 |
interactive=True,
|
217 |
value=DEFAULT_NL,
|
@@ -225,6 +238,11 @@ TITPOP
|
|
225 |
placeholder="Enter tag/nl black list here",
|
226 |
)
|
227 |
with gr.Column(scale=2):
|
|
|
|
|
|
|
|
|
|
|
228 |
target_length = gr.Dropdown(
|
229 |
label="Target Length",
|
230 |
choices=["very_short", "short", "long", "very_long"],
|
@@ -293,6 +311,7 @@ TITPOP
|
|
293 |
nl_prompt_input,
|
294 |
black_list,
|
295 |
temp,
|
|
|
296 |
target_length,
|
297 |
top_p,
|
298 |
min_p,
|
@@ -308,8 +327,13 @@ TITPOP
|
|
308 |
],
|
309 |
queue=True,
|
310 |
)
|
|
|
|
|
|
|
|
|
|
|
311 |
gen_img.click(
|
312 |
-
|
313 |
[seed, result, input_prompt],
|
314 |
[img1, img2, submit],
|
315 |
queue=True,
|
|
|
30 |
from kgen.generate import generate
|
31 |
|
32 |
from diff import load_model, encode_prompts
|
33 |
+
from meta import DEFAULT_NEGATIVE_PROMPT, DEFAULT_FORMAT
|
34 |
|
35 |
|
36 |
sdxl_pipe = load_model()
|
|
|
41 |
subfolder="dan-cc-coyo_epoch2",
|
42 |
)
|
43 |
generate(max_new_tokens=4)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
44 |
DEFAULT_TAGS = """
|
45 |
1girl, king halo (umamusume), umamusume,
|
46 |
ningen mame, ciloranko, ogipote, misu kasumi,
|
|
|
92 |
nl_prompt,
|
93 |
black_list,
|
94 |
temp,
|
95 |
+
output_format,
|
96 |
target_length,
|
97 |
top_p,
|
98 |
min_p,
|
|
|
100 |
seed,
|
101 |
escape_brackets,
|
102 |
):
|
103 |
+
default_format = DEFAULT_FORMAT[output_format]
|
104 |
titpop.BAN_TAGS = [t.strip() for t in black_list.split(",") if t.strip()]
|
105 |
generation_setting = {
|
106 |
"seed": seed,
|
|
|
111 |
}
|
112 |
inputs = seperate_tags(tags.split(","))
|
113 |
if nl_prompt:
|
114 |
+
if "<|extended|>" in default_format:
|
115 |
inputs["extended"] = nl_prompt
|
116 |
+
elif "<|generated|>" in default_format:
|
117 |
inputs["generated"] = nl_prompt
|
118 |
+
input_prompt = apply_format(inputs, default_format)
|
119 |
if escape_brackets:
|
120 |
input_prompt = re.sub(r"([()\[\]])", r"\\\1", input_prompt)
|
121 |
|
|
|
123 |
seperate_tags(tags.split(",")),
|
124 |
nl_prompt,
|
125 |
tag_length_target=target_length,
|
126 |
+
generate_extra_nl_prompt="<|generated|>" in default_format or not nl_prompt,
|
127 |
)
|
128 |
t0 = time()
|
129 |
for result, timing in titpop.titpop_runner_generator(
|
130 |
meta, operations, general, nl_prompt, **generation_setting
|
131 |
):
|
132 |
+
result = apply_format(result, default_format)
|
133 |
if escape_brackets:
|
134 |
result = re.sub(r"([()\[\]])", r"\\\1", result)
|
135 |
timing["total"] = time() - t0
|
|
|
144 |
prompt2,
|
145 |
):
|
146 |
torch.cuda.empty_cache()
|
147 |
+
set_seed(seed)
|
148 |
prompt_embeds, negative_prompt_embeds, pooled_embeds2, neg_pooled_embeds2 = (
|
149 |
+
encode_prompts(sdxl_pipe, prompt2, DEFAULT_NEGATIVE_PROMPT)
|
150 |
)
|
151 |
+
result2 = sdxl_pipe(
|
|
|
152 |
prompt_embeds=prompt_embeds,
|
153 |
negative_prompt_embeds=negative_prompt_embeds,
|
154 |
pooled_prompt_embeds=pooled_embeds2,
|
|
|
158 |
height=1024,
|
159 |
guidance_scale=6.0,
|
160 |
).images[0]
|
161 |
+
yield result2, None
|
162 |
+
|
163 |
prompt_embeds, negative_prompt_embeds, pooled_embeds2, neg_pooled_embeds2 = (
|
164 |
+
encode_prompts(sdxl_pipe, prompt, DEFAULT_NEGATIVE_PROMPT)
|
165 |
)
|
166 |
set_seed(seed)
|
167 |
+
result = sdxl_pipe(
|
168 |
prompt_embeds=prompt_embeds,
|
169 |
negative_prompt_embeds=negative_prompt_embeds,
|
170 |
pooled_prompt_embeds=pooled_embeds2,
|
|
|
175 |
guidance_scale=6.0,
|
176 |
).images[0]
|
177 |
torch.cuda.empty_cache()
|
178 |
+
yield result2, result
|
179 |
|
180 |
|
181 |
if __name__ == "__main__":
|
182 |
with gr.Blocks(theme=gr.themes.Soft()) as demo:
|
|
|
183 |
with gr.Accordion("Introduction and Instructions", open=False):
|
184 |
gr.Markdown(
|
185 |
"""
|
186 |
+
## TITPOP Demo
|
187 |
+
### What is this
|
188 |
+
TITPOP is a tool to extend, generate, refine the input prompt for T2I models.
|
189 |
+
<br>It can work on both Danbooru tags and Natural Language. Which means you can use it on almost all the existed T2I models.
|
190 |
+
<br>You can take it as "pro max" version of [DTG](https://huggingface.co/KBlueLeaf/DanTagGen-delta-rev2)
|
191 |
+
|
192 |
+
### How to use this demo
|
193 |
+
1. Enter your tags(optional): put the desired tags into "danboru tags" box
|
194 |
+
2. Enter your NL Prompt(optional): put the desired natural language prompt into "Natural Language Prompt" box
|
195 |
+
3. Enter your black list(optional): put the desired black list into "black list" box
|
196 |
+
4. Adjust the settings: length, temp, top_p, min_p, top_k, seed ...
|
197 |
+
4. Click "TITPOP" button: you will see refined prompt on "result" box
|
198 |
+
5. If you like the result, click "Generate Image From Result" button
|
199 |
+
* You will see 2 generated images, left one is based on your prompt, right one is based on refined prompt
|
200 |
+
* The backend is diffusers, there are no weighting mechanism, so Escape Brackets is default to False
|
201 |
|
202 |
+
### Why inference code is private? When will it be open sourced?
|
203 |
+
1. This model/tool is still under development, currently is early Alpha version.
|
204 |
+
2. I'm doing some research and projects based on this.
|
205 |
+
3. The model is released under CC-BY-NC-ND License currently. If you have interest, you can implement inference by yourself.
|
206 |
+
4. Once the project/research are done, I will open source all these models/codes with Apache2 license.
|
207 |
+
|
208 |
+
### Notification
|
209 |
+
**ITPOP is NOT a T2I model. It is Prompt Gen, or, Text-to-Text model.
|
210 |
+
<br>The generated image is come from [Kohaku-XL-Zeta](https://huggingface.co/KBlueLeaf/Kohaku-XL-Zeta) model**
|
211 |
"""
|
212 |
)
|
213 |
with gr.Row():
|
|
|
216 |
with gr.Column(scale=3):
|
217 |
tags_input = gr.TextArea(
|
218 |
label="Danbooru Tags",
|
219 |
+
lines=7,
|
220 |
show_copy_button=True,
|
221 |
interactive=True,
|
222 |
value=DEFAULT_TAGS,
|
|
|
224 |
)
|
225 |
nl_prompt_input = gr.Textbox(
|
226 |
label="Natural Language Prompt",
|
227 |
+
lines=7,
|
228 |
show_copy_button=True,
|
229 |
interactive=True,
|
230 |
value=DEFAULT_NL,
|
|
|
238 |
placeholder="Enter tag/nl black list here",
|
239 |
)
|
240 |
with gr.Column(scale=2):
|
241 |
+
output_format = gr.Dropdown(
|
242 |
+
label="Output Format",
|
243 |
+
choices=list(DEFAULT_FORMAT.keys()),
|
244 |
+
value="Both, tag first (recommend)"
|
245 |
+
)
|
246 |
target_length = gr.Dropdown(
|
247 |
label="Target Length",
|
248 |
choices=["very_short", "short", "long", "very_long"],
|
|
|
311 |
nl_prompt_input,
|
312 |
black_list,
|
313 |
temp,
|
314 |
+
output_format,
|
315 |
target_length,
|
316 |
top_p,
|
317 |
min_p,
|
|
|
327 |
],
|
328 |
queue=True,
|
329 |
)
|
330 |
+
|
331 |
+
def generate_image_wrapper(seed, result, input_prompt):
|
332 |
+
for img1, img2 in generate_image(seed, result, input_prompt):
|
333 |
+
yield img1, img2, gr.update(interactive=False)
|
334 |
+
yield img1, img2, gr.update(interactive=True)
|
335 |
gen_img.click(
|
336 |
+
generate_image_wrapper,
|
337 |
[seed, result, input_prompt],
|
338 |
[img1, img2, submit],
|
339 |
queue=True,
|
meta.py
CHANGED
@@ -8,47 +8,52 @@ DEFAULT_STYLE_LIST = {
|
|
8 |
"no style": "",
|
9 |
}
|
10 |
|
11 |
-
|
12 |
-
|
13 |
-
|
14 |
-
|
15 |
-
|
16 |
-
}
|
17 |
|
18 |
-
|
19 |
-
"
|
20 |
-
<|characters|>, <|copyrights|>,
|
21 |
<|artist|>,
|
22 |
|
23 |
-
<|general|>,
|
24 |
|
25 |
-
<|quality|>, <|meta|>, <|rating|>
|
26 |
-
|
27 |
-
|
|
|
|
|
28 |
<|artist|>,
|
29 |
|
30 |
-
<|general|>,
|
31 |
|
32 |
-
<|
|
33 |
-
|
34 |
-
<|
|
|
|
|
|
|
|
35 |
<|artist|>,
|
36 |
|
37 |
-
<|
|
|
|
|
|
38 |
|
39 |
-
<|quality|>, <|meta|>, <|rating|>
|
40 |
-
|
41 |
-
|
|
|
42 |
<|artist|>,
|
43 |
|
44 |
-
<|
|
45 |
|
46 |
-
<|
|
47 |
-
}
|
48 |
|
|
|
49 |
|
50 |
-
|
51 |
-
|
52 |
-
|
53 |
-
multiple tails, multiple views, copyright name, watermark, artist name, signature
|
54 |
-
"""
|
|
|
8 |
"no style": "",
|
9 |
}
|
10 |
|
11 |
+
DEFAULT_NEGATIVE_PROMPT = """
|
12 |
+
low quality, worst quality, normal quality, text, signature, jpeg artifacts,
|
13 |
+
bad anatomy, old, early, mini skirt, nsfw, chibi, multiple girls, multiple boys,
|
14 |
+
multiple tails, multiple views, copyright name, watermark, artist name, signature
|
15 |
+
"""
|
|
|
16 |
|
17 |
+
DEFAULT_FORMAT = {
|
18 |
+
"tag only (DTG mode)":"""
|
19 |
+
<|special|>, <|characters|>, <|copyrights|>,
|
20 |
<|artist|>,
|
21 |
|
22 |
+
<|general|>,
|
23 |
|
24 |
+
<|quality|>, <|meta|>, <|rating|>
|
25 |
+
""".strip(),
|
26 |
+
"NL only (Tag to NL)": """<|extended|>.""".strip(),
|
27 |
+
"Both, tag first (recommend)": """
|
28 |
+
<|special|>, <|characters|>, <|copyrights|>,
|
29 |
<|artist|>,
|
30 |
|
31 |
+
<|general|>,
|
32 |
|
33 |
+
<|extended|>.
|
34 |
+
|
35 |
+
<|quality|>, <|meta|>, <|rating|>
|
36 |
+
""".strip(),
|
37 |
+
"Both, NL first (recommend)": """
|
38 |
+
<|special|>, <|characters|>, <|copyrights|>,
|
39 |
<|artist|>,
|
40 |
|
41 |
+
<|extended|>.
|
42 |
+
|
43 |
+
<|general|>,
|
44 |
|
45 |
+
<|quality|>, <|meta|>, <|rating|>
|
46 |
+
""".strip(),
|
47 |
+
"Both + generated NL": """
|
48 |
+
<|special|>, <|characters|>, <|copyrights|>,
|
49 |
<|artist|>,
|
50 |
|
51 |
+
<|generated|>.
|
52 |
|
53 |
+
<|general|>,
|
|
|
54 |
|
55 |
+
<|extended|>.
|
56 |
|
57 |
+
<|quality|>, <|meta|>, <|rating|>
|
58 |
+
""".strip()
|
59 |
+
}
|
|
|
|