Spaces:
Running
Running
Upload 13 files
Browse files- README.md +1 -1
- app.py +119 -89
- model.py +1 -1
- multit2i.py +57 -27
- requirements.txt +2 -5
- tagger/tagger.py +21 -21
README.md
CHANGED
@@ -4,7 +4,7 @@ emoji: ๐ผ๏ธ๐
|
|
4 |
colorFrom: blue
|
5 |
colorTo: purple
|
6 |
sdk: gradio
|
7 |
-
sdk_version:
|
8 |
app_file: app.py
|
9 |
pinned: false
|
10 |
short_description: Text-to-Image
|
|
|
4 |
colorFrom: blue
|
5 |
colorTo: purple
|
6 |
sdk: gradio
|
7 |
+
sdk_version: 5.0.1
|
8 |
app_file: app.py
|
9 |
pinned: false
|
10 |
short_description: Text-to-Image
|
app.py
CHANGED
@@ -3,7 +3,7 @@ from model import models
|
|
3 |
from multit2i import (load_models, infer_fn, infer_rand_fn, save_gallery,
|
4 |
change_model, warm_model, get_model_info_md, loaded_models,
|
5 |
get_positive_prefix, get_positive_suffix, get_negative_prefix, get_negative_suffix,
|
6 |
-
get_recom_prompt_type, set_recom_prompt_preset, get_tag_type)
|
7 |
from tagger.tagger import (predict_tags_wd, remove_specific_prompt, convert_danbooru_to_e621_prompt,
|
8 |
insert_recom_prompt, compose_prompt_to_copy)
|
9 |
from tagger.fl2sd3longcap import predict_tags_fl2_sd3
|
@@ -22,97 +22,124 @@ css = """
|
|
22 |
"""
|
23 |
|
24 |
with gr.Blocks(theme="NoCrypt/miku@>=1.2.2", fill_width=True, css=css) as demo:
|
25 |
-
with gr.
|
26 |
-
with gr.
|
27 |
-
with gr.
|
28 |
-
with gr.
|
29 |
-
|
30 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
31 |
with gr.Row():
|
32 |
-
|
33 |
-
|
34 |
-
tagger_tag_type = gr.Radio(label="Convert tags to", info="danbooru for common, e621 for Pony.", choices=["danbooru", "e621"], value="danbooru")
|
35 |
with gr.Row():
|
36 |
-
|
37 |
-
|
38 |
-
|
39 |
-
|
40 |
-
|
41 |
-
|
42 |
-
|
43 |
-
|
44 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
45 |
with gr.Row():
|
46 |
-
|
47 |
-
|
48 |
-
|
49 |
-
|
50 |
-
v2_copy = gr.Button(value="Copy to clipboard", variant="secondary", size="sm", interactive=False)
|
51 |
with gr.Row():
|
52 |
-
|
53 |
-
|
54 |
-
|
55 |
-
|
56 |
-
|
57 |
-
|
58 |
-
|
59 |
-
|
60 |
-
width = gr.Slider(label="Width", info="If 0, the default value is used.", maximum=1216, step=32, value=0)
|
61 |
-
height = gr.Slider(label="Height", info="If 0, the default value is used.", maximum=1216, step=32, value=0)
|
62 |
with gr.Row():
|
63 |
-
|
64 |
-
|
65 |
-
|
66 |
-
|
67 |
-
|
68 |
-
|
69 |
-
|
70 |
-
|
71 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
72 |
|
73 |
-
|
74 |
-
|
75 |
-
|
76 |
-
|
77 |
-
|
78 |
-
|
79 |
-
|
80 |
-
|
81 |
-
|
82 |
-
|
83 |
-
|
84 |
-
|
85 |
-
|
86 |
-
|
87 |
-
with gr.Group():
|
88 |
-
results = gr.Gallery(label="Gallery", elem_classes="gallery", interactive=False, show_download_button=True, show_share_button=False,
|
89 |
-
container=True, format="png", object_fit="cover", columns=2, rows=2)
|
90 |
-
image_files = gr.Files(label="Download", interactive=False)
|
91 |
-
clear_results = gr.Button("Clear Gallery / Download ๐๏ธ", variant="secondary")
|
92 |
-
with gr.Column():
|
93 |
-
examples = gr.Examples(
|
94 |
-
examples = [
|
95 |
-
["souryuu asuka langley, 1girl, neon genesis evangelion, plugsuit, pilot suit, red bodysuit, sitting, crossing legs, black eye patch, cat hat, throne, symmetrical, looking down, from bottom, looking at viewer, outdoors"],
|
96 |
-
["sailor moon, magical girl transformation, sparkles and ribbons, soft pastel colors, crescent moon motif, starry night sky background, shoujo manga style"],
|
97 |
-
["kafuu chino, 1girl, solo"],
|
98 |
-
["1girl"],
|
99 |
-
["beautiful sunset"],
|
100 |
-
],
|
101 |
-
inputs=[prompt],
|
102 |
-
)
|
103 |
-
gr.Markdown(
|
104 |
-
f"""This demo was created in reference to the following demos.<br>
|
105 |
-
[Nymbo/Flood](https://huggingface.co/spaces/Nymbo/Flood),
|
106 |
-
[Yntec/ToyWorldXL](https://huggingface.co/spaces/Yntec/ToyWorldXL),
|
107 |
-
[Yntec/Diffusion80XX](https://huggingface.co/spaces/Yntec/Diffusion80XX).
|
108 |
-
"""
|
109 |
-
)
|
110 |
-
gr.DuplicateButton(value="Duplicate Space")
|
111 |
-
gr.Markdown(f"Just a few edits to *model.py* are all it takes to complete your own collection.")
|
112 |
|
113 |
-
gr.on(triggers=[run_button.click, prompt.submit, random_button.click], fn=lambda: gr.update(interactive=True), inputs=None, outputs=stop_button, show_api=False)
|
114 |
model_name.change(change_model, [model_name], [model_info], queue=False, show_api=False)\
|
115 |
-
.success(warm_model, [model_name], None, queue=
|
116 |
for i, o in enumerate(output):
|
117 |
img_i = gr.Number(i, visible=False)
|
118 |
image_num.change(lambda i, n: gr.update(visible = (i < n)), [img_i, image_num], o, show_api=False)
|
@@ -120,19 +147,22 @@ with gr.Blocks(theme="NoCrypt/miku@>=1.2.2", fill_width=True, css=css) as demo:
|
|
120 |
fn=lambda i, n, m, t1, t2, n1, n2, n3, n4, n5, l1, l2, l3, l4: infer_fn(m, t1, t2, n1, n2, n3, n4, n5, l1, l2, l3, l4) if (i < n) else None,
|
121 |
inputs=[img_i, image_num, model_name, prompt, neg_prompt, height, width, steps, cfg, seed,
|
122 |
positive_prefix, positive_suffix, negative_prefix, negative_suffix],
|
123 |
-
outputs=[o], queue=
|
124 |
gen_event2 = gr.on(triggers=[random_button.click],
|
125 |
fn=lambda i, n, m, t1, t2, n1, n2, n3, n4, n5, l1, l2, l3, l4: infer_rand_fn(m, t1, t2, n1, n2, n3, n4, n5, l1, l2, l3, l4) if (i < n) else None,
|
126 |
inputs=[img_i, image_num, model_name, prompt, neg_prompt, height, width, steps, cfg, seed,
|
127 |
positive_prefix, positive_suffix, negative_prefix, negative_suffix],
|
128 |
-
outputs=[o], queue=
|
129 |
o.change(save_gallery, [o, results], [results, image_files], show_api=False)
|
130 |
-
stop_button.click(lambda: gr.update(interactive=False), None, stop_button, cancels=[gen_event, gen_event2], show_api=False)
|
131 |
|
132 |
-
clear_prompt.click(lambda: None, None, [prompt], queue=False, show_api=False)
|
133 |
clear_results.click(lambda: (None, None), None, [results, image_files], queue=False, show_api=False)
|
134 |
recom_prompt_preset.change(set_recom_prompt_preset, [recom_prompt_preset],
|
135 |
[positive_prefix, positive_suffix, negative_prefix, negative_suffix], queue=False, show_api=False)
|
|
|
|
|
|
|
136 |
|
137 |
random_prompt.click(
|
138 |
v2_random_prompt, [prompt, v2_series, v2_character, v2_rating, v2_aspect_ratio, v2_length,
|
@@ -151,5 +181,5 @@ with gr.Blocks(theme="NoCrypt/miku@>=1.2.2", fill_width=True, css=css) as demo:
|
|
151 |
).success(insert_recom_prompt, [prompt, neg_prompt, tagger_recom_prompt], [prompt, neg_prompt], queue=False, show_api=False,
|
152 |
).success(compose_prompt_to_copy, [v2_character, v2_series, prompt], [prompt], queue=False, show_api=False)
|
153 |
|
154 |
-
demo.queue(default_concurrency_limit=200, max_size=200)
|
155 |
demo.launch(max_threads=400)
|
|
|
3 |
from multit2i import (load_models, infer_fn, infer_rand_fn, save_gallery,
|
4 |
change_model, warm_model, get_model_info_md, loaded_models,
|
5 |
get_positive_prefix, get_positive_suffix, get_negative_prefix, get_negative_suffix,
|
6 |
+
get_recom_prompt_type, set_recom_prompt_preset, get_tag_type, randomize_seed, translate_to_en)
|
7 |
from tagger.tagger import (predict_tags_wd, remove_specific_prompt, convert_danbooru_to_e621_prompt,
|
8 |
insert_recom_prompt, compose_prompt_to_copy)
|
9 |
from tagger.fl2sd3longcap import predict_tags_fl2_sd3
|
|
|
22 |
"""
|
23 |
|
24 |
with gr.Blocks(theme="NoCrypt/miku@>=1.2.2", fill_width=True, css=css) as demo:
|
25 |
+
with gr.Tab("Image Generator"):
|
26 |
+
with gr.Row():
|
27 |
+
with gr.Column(scale=10):
|
28 |
+
with gr.Group():
|
29 |
+
with gr.Accordion("Prompt from Image File", open=False):
|
30 |
+
tagger_image = gr.Image(label="Input image", type="pil", format="png", sources=["upload", "clipboard"], height=256)
|
31 |
+
with gr.Accordion(label="Advanced options", open=False):
|
32 |
+
with gr.Row():
|
33 |
+
tagger_general_threshold = gr.Slider(label="Threshold", minimum=0.0, maximum=1.0, value=0.3, step=0.01, interactive=True)
|
34 |
+
tagger_character_threshold = gr.Slider(label="Character threshold", minimum=0.0, maximum=1.0, value=0.8, step=0.01, interactive=True)
|
35 |
+
tagger_tag_type = gr.Radio(label="Convert tags to", info="danbooru for common, e621 for Pony.", choices=["danbooru", "e621"], value="danbooru")
|
36 |
+
with gr.Row():
|
37 |
+
tagger_recom_prompt = gr.Radio(label="Insert reccomended prompt", choices=["None", "Animagine", "Pony"], value="None", interactive=True)
|
38 |
+
tagger_keep_tags = gr.Radio(label="Remove tags leaving only the following", choices=["body", "dress", "all"], value="all")
|
39 |
+
tagger_algorithms = gr.CheckboxGroup(["Use WD Tagger", "Use Florence-2-SD3-Long-Captioner"], label="Algorithms", value=["Use WD Tagger"])
|
40 |
+
tagger_generate_from_image = gr.Button(value="Generate Tags from Image", variant="secondary")
|
41 |
+
with gr.Accordion("Prompt Transformer", open=False):
|
42 |
with gr.Row():
|
43 |
+
v2_character = gr.Textbox(label="Character", placeholder="hatsune miku", scale=2)
|
44 |
+
v2_series = gr.Textbox(label="Series", placeholder="vocaloid", scale=2)
|
|
|
45 |
with gr.Row():
|
46 |
+
v2_rating = gr.Radio(label="Rating", choices=list(V2_RATING_OPTIONS), value="sfw")
|
47 |
+
v2_aspect_ratio = gr.Radio(label="Aspect ratio", info="The aspect ratio of the image.", choices=list(V2_ASPECT_RATIO_OPTIONS), value="square", visible=False)
|
48 |
+
v2_length = gr.Radio(label="Length", info="The total length of the tags.", choices=list(V2_LENGTH_OPTIONS), value="long")
|
49 |
+
with gr.Row():
|
50 |
+
v2_identity = gr.Radio(label="Keep identity", info="How strictly to keep the identity of the character or subject. If you specify the detail of subject in the prompt, you should choose `strict`. Otherwise, choose `none` or `lax`. `none` is very creative but sometimes ignores the input prompt.", choices=list(V2_IDENTITY_OPTIONS), value="lax")
|
51 |
+
v2_ban_tags = gr.Textbox(label="Ban tags", info="Tags to ban from the output.", placeholder="alternate costumen, ...", value="censored")
|
52 |
+
v2_tag_type = gr.Radio(label="Tag Type", info="danbooru for common, e621 for Pony.", choices=["danbooru", "e621"], value="danbooru", visible=False)
|
53 |
+
v2_model = gr.Dropdown(label="Model", choices=list(V2_ALL_MODELS.keys()), value=list(V2_ALL_MODELS.keys())[0])
|
54 |
+
v2_copy = gr.Button(value="Copy to clipboard", variant="secondary", size="sm", interactive=False)
|
55 |
+
random_prompt = gr.Button(value="Extend ๐ฒ", variant="secondary")
|
56 |
+
prompt = gr.Text(label="Prompt", lines=2, max_lines=8, placeholder="1girl, solo, ...", show_copy_button=True)
|
57 |
+
with gr.Accordion("Advanced options", open=False):
|
58 |
+
neg_prompt = gr.Text(label="Negative Prompt", lines=1, max_lines=8, placeholder="")
|
59 |
+
with gr.Row():
|
60 |
+
width = gr.Slider(label="Width", info="If 0, the default value is used.", maximum=1216, step=32, value=0)
|
61 |
+
height = gr.Slider(label="Height", info="If 0, the default value is used.", maximum=1216, step=32, value=0)
|
62 |
+
steps = gr.Slider(label="Number of inference steps", info="If 0, the default value is used.", maximum=100, step=1, value=0)
|
63 |
+
with gr.Row():
|
64 |
+
cfg = gr.Slider(label="Guidance scale", info="If 0, the default value is used.", maximum=30.0, step=0.1, value=0)
|
65 |
+
seed = gr.Slider(label="Seed", info="Randomize Seed if -1.", minimum=-1, maximum=MAX_SEED, step=1, value=-1)
|
66 |
+
seed_rand = gr.Button("Randomize Seed ๐ฒ", size="sm", variant="secondary")
|
67 |
+
recom_prompt_preset = gr.Radio(label="Set Presets", choices=get_recom_prompt_type(), value="Common")
|
68 |
+
with gr.Row():
|
69 |
+
positive_prefix = gr.CheckboxGroup(label="Use Positive Prefix", choices=get_positive_prefix(), value=[])
|
70 |
+
positive_suffix = gr.CheckboxGroup(label="Use Positive Suffix", choices=get_positive_suffix(), value=["Common"])
|
71 |
+
negative_prefix = gr.CheckboxGroup(label="Use Negative Prefix", choices=get_negative_prefix(), value=[])
|
72 |
+
negative_suffix = gr.CheckboxGroup(label="Use Negative Suffix", choices=get_negative_suffix(), value=["Common"])
|
73 |
with gr.Row():
|
74 |
+
image_num = gr.Slider(label="Number of images", minimum=1, maximum=max_images, value=1, step=1, interactive=True, scale=2)
|
75 |
+
trans_prompt = gr.Button(value="Translate ๐", variant="secondary", size="sm", scale=2)
|
76 |
+
clear_prompt = gr.Button(value="Clear ๐๏ธ", variant="secondary", size="sm", scale=1)
|
77 |
+
|
|
|
78 |
with gr.Row():
|
79 |
+
run_button = gr.Button("Generate Image", variant="primary", scale=6)
|
80 |
+
random_button = gr.Button("Random Model ๐ฒ", variant="secondary", scale=3)
|
81 |
+
#stop_button = gr.Button('Stop', variant="stop", interactive=False, scale=1)
|
82 |
+
with gr.Group():
|
83 |
+
model_name = gr.Dropdown(label="Select Model", choices=list(loaded_models.keys()), value=list(loaded_models.keys())[0], allow_custom_value=True)
|
84 |
+
model_info = gr.Markdown(value=get_model_info_md(list(loaded_models.keys())[0]), elem_classes="model_info")
|
85 |
+
with gr.Column(scale=10):
|
86 |
+
with gr.Group():
|
|
|
|
|
87 |
with gr.Row():
|
88 |
+
output = [gr.Image(label='', elem_classes="output", type="filepath", format="png",
|
89 |
+
show_download_button=True, show_share_button=False, show_label=False,
|
90 |
+
interactive=False, min_width=80, visible=True, width=112, height=112) for _ in range(max_images)]
|
91 |
+
with gr.Group():
|
92 |
+
results = gr.Gallery(label="Gallery", elem_classes="gallery", interactive=False, show_download_button=True, show_share_button=False,
|
93 |
+
container=True, format="png", object_fit="cover", columns=2, rows=2)
|
94 |
+
image_files = gr.Files(label="Download", interactive=False)
|
95 |
+
clear_results = gr.Button("Clear Gallery / Download ๐๏ธ", variant="secondary")
|
96 |
+
with gr.Column():
|
97 |
+
examples = gr.Examples(
|
98 |
+
examples = [
|
99 |
+
["souryuu asuka langley, 1girl, neon genesis evangelion, plugsuit, pilot suit, red bodysuit, sitting, crossing legs, black eye patch, cat hat, throne, symmetrical, looking down, from bottom, looking at viewer, outdoors"],
|
100 |
+
["sailor moon, magical girl transformation, sparkles and ribbons, soft pastel colors, crescent moon motif, starry night sky background, shoujo manga style"],
|
101 |
+
["kafuu chino, 1girl, solo"],
|
102 |
+
["1girl"],
|
103 |
+
["beautiful sunset"],
|
104 |
+
],
|
105 |
+
inputs=[prompt],
|
106 |
+
cache_examples=False,
|
107 |
+
)
|
108 |
+
with gr.Tab("PNG Info"):
|
109 |
+
def extract_exif_data(image):
|
110 |
+
if image is None: return ""
|
111 |
+
try:
|
112 |
+
metadata_keys = ['parameters', 'metadata', 'prompt', 'Comment']
|
113 |
+
for key in metadata_keys:
|
114 |
+
if key in image.info:
|
115 |
+
return image.info[key]
|
116 |
+
return str(image.info)
|
117 |
+
except Exception as e:
|
118 |
+
return f"Error extracting metadata: {str(e)}"
|
119 |
+
with gr.Row():
|
120 |
+
with gr.Column():
|
121 |
+
image_metadata = gr.Image(label="Image with metadata", type="pil", sources=["upload"])
|
122 |
+
with gr.Column():
|
123 |
+
result_metadata = gr.Textbox(label="Metadata", show_label=True, show_copy_button=True, interactive=False, container=True, max_lines=99)
|
124 |
|
125 |
+
image_metadata.change(
|
126 |
+
fn=extract_exif_data,
|
127 |
+
inputs=[image_metadata],
|
128 |
+
outputs=[result_metadata],
|
129 |
+
)
|
130 |
+
gr.Markdown(
|
131 |
+
f"""This demo was created in reference to the following demos.<br>
|
132 |
+
[Nymbo/Flood](https://huggingface.co/spaces/Nymbo/Flood),
|
133 |
+
[Yntec/ToyWorldXL](https://huggingface.co/spaces/Yntec/ToyWorldXL),
|
134 |
+
[Yntec/Diffusion80XX](https://huggingface.co/spaces/Yntec/Diffusion80XX).
|
135 |
+
"""
|
136 |
+
)
|
137 |
+
gr.DuplicateButton(value="Duplicate Space")
|
138 |
+
gr.Markdown(f"Just a few edits to *model.py* are all it takes to complete your own collection.")
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
139 |
|
140 |
+
#gr.on(triggers=[run_button.click, prompt.submit, random_button.click], fn=lambda: gr.update(interactive=True), inputs=None, outputs=stop_button, show_api=False)
|
141 |
model_name.change(change_model, [model_name], [model_info], queue=False, show_api=False)\
|
142 |
+
.success(warm_model, [model_name], None, queue=False, show_api=False)
|
143 |
for i, o in enumerate(output):
|
144 |
img_i = gr.Number(i, visible=False)
|
145 |
image_num.change(lambda i, n: gr.update(visible = (i < n)), [img_i, image_num], o, show_api=False)
|
|
|
147 |
fn=lambda i, n, m, t1, t2, n1, n2, n3, n4, n5, l1, l2, l3, l4: infer_fn(m, t1, t2, n1, n2, n3, n4, n5, l1, l2, l3, l4) if (i < n) else None,
|
148 |
inputs=[img_i, image_num, model_name, prompt, neg_prompt, height, width, steps, cfg, seed,
|
149 |
positive_prefix, positive_suffix, negative_prefix, negative_suffix],
|
150 |
+
outputs=[o], queue=False, show_api=False) # Be sure to delete ", queue=False" when activating the stop button
|
151 |
gen_event2 = gr.on(triggers=[random_button.click],
|
152 |
fn=lambda i, n, m, t1, t2, n1, n2, n3, n4, n5, l1, l2, l3, l4: infer_rand_fn(m, t1, t2, n1, n2, n3, n4, n5, l1, l2, l3, l4) if (i < n) else None,
|
153 |
inputs=[img_i, image_num, model_name, prompt, neg_prompt, height, width, steps, cfg, seed,
|
154 |
positive_prefix, positive_suffix, negative_prefix, negative_suffix],
|
155 |
+
outputs=[o], queue=False, show_api=False) # Be sure to delete ", queue=False" when activating the stop button
|
156 |
o.change(save_gallery, [o, results], [results, image_files], show_api=False)
|
157 |
+
#stop_button.click(lambda: gr.update(interactive=False), None, stop_button, cancels=[gen_event, gen_event2], show_api=False)
|
158 |
|
159 |
+
clear_prompt.click(lambda: (None, None, None, None), None, [prompt, neg_prompt, v2_character, v2_series], queue=False, show_api=False)
|
160 |
clear_results.click(lambda: (None, None), None, [results, image_files], queue=False, show_api=False)
|
161 |
recom_prompt_preset.change(set_recom_prompt_preset, [recom_prompt_preset],
|
162 |
[positive_prefix, positive_suffix, negative_prefix, negative_suffix], queue=False, show_api=False)
|
163 |
+
seed_rand.click(randomize_seed, None, [seed], queue=False, show_api=False)
|
164 |
+
trans_prompt.click(translate_to_en, [prompt], [prompt], queue=False, show_api=False)\
|
165 |
+
.then(translate_to_en, [neg_prompt], [neg_prompt], queue=False, show_api=False)
|
166 |
|
167 |
random_prompt.click(
|
168 |
v2_random_prompt, [prompt, v2_series, v2_character, v2_rating, v2_aspect_ratio, v2_length,
|
|
|
181 |
).success(insert_recom_prompt, [prompt, neg_prompt, tagger_recom_prompt], [prompt, neg_prompt], queue=False, show_api=False,
|
182 |
).success(compose_prompt_to_copy, [v2_character, v2_series, prompt], [prompt], queue=False, show_api=False)
|
183 |
|
184 |
+
#demo.queue(default_concurrency_limit=200, max_size=200)
|
185 |
demo.launch(max_threads=400)
|
model.py
CHANGED
@@ -1,7 +1,7 @@
|
|
1 |
from multit2i import find_model_list
|
2 |
|
3 |
|
4 |
-
models = find_model_list("John6666", ["anime"], "", "last_modified", 250)
|
5 |
|
6 |
|
7 |
# Examples:
|
|
|
1 |
from multit2i import find_model_list
|
2 |
|
3 |
|
4 |
+
models = find_model_list("John6666", ["anime"], "Flux", "last_modified", 250)
|
5 |
|
6 |
|
7 |
# Examples:
|
multit2i.py
CHANGED
@@ -60,7 +60,7 @@ def find_model_list(author: str="", tags: list[str]=[], not_tag="", sort: str="l
|
|
60 |
limit = limit * 20 if check_status and force_gpu else limit * 5
|
61 |
models = []
|
62 |
try:
|
63 |
-
model_infos = api.list_models(author=author, task="text-to-image",
|
64 |
tags=list_uniq(default_tags + tags), cardData=True, sort=sort, limit=limit)
|
65 |
except Exception as e:
|
66 |
print(f"Error: Failed to list models.")
|
@@ -110,7 +110,7 @@ def get_t2i_model_info_dict(repo_id: str):
|
|
110 |
|
111 |
|
112 |
def rename_image(image_path: str | None, model_name: str, save_path: str | None = None):
|
113 |
-
|
114 |
from datetime import datetime, timezone, timedelta
|
115 |
if image_path is None: return None
|
116 |
dt_now = datetime.now(timezone(timedelta(hours=9)))
|
@@ -118,7 +118,7 @@ def rename_image(image_path: str | None, model_name: str, save_path: str | None
|
|
118 |
try:
|
119 |
if Path(image_path).exists():
|
120 |
png_path = "image.png"
|
121 |
-
|
122 |
if save_path is not None:
|
123 |
new_path = str(Path(png_path).resolve().rename(Path(save_path).resolve()))
|
124 |
else:
|
@@ -363,16 +363,16 @@ def warm_model(model_name: str):
|
|
363 |
|
364 |
# https://huggingface.co/docs/api-inference/detailed_parameters
|
365 |
# https://huggingface.co/docs/huggingface_hub/package_reference/inference_client
|
366 |
-
def infer_body(client: InferenceClient | gr.Interface | object, prompt: str, neg_prompt: str
|
367 |
-
height: int
|
368 |
-
steps: int | None = None, cfg: int | None = None, seed: int = -1):
|
369 |
png_path = "image.png"
|
370 |
kwargs = {}
|
371 |
-
if height
|
372 |
-
if width
|
373 |
-
if steps
|
374 |
-
if cfg
|
375 |
-
if seed
|
|
|
376 |
try:
|
377 |
if isinstance(client, InferenceClient):
|
378 |
image = client.text_to_image(prompt=prompt, negative_prompt=neg_prompt, **kwargs, token=HF_TOKEN)
|
@@ -380,26 +380,18 @@ def infer_body(client: InferenceClient | gr.Interface | object, prompt: str, neg
|
|
380 |
image = client.fn(prompt=prompt, negative_prompt=neg_prompt, **kwargs, token=HF_TOKEN)
|
381 |
else: return None
|
382 |
if isinstance(image, tuple): return None
|
383 |
-
image
|
384 |
-
return str(Path(png_path).resolve())
|
385 |
except Exception as e:
|
386 |
print(e)
|
387 |
raise Exception() from e
|
388 |
|
389 |
|
390 |
-
async def infer(model_name: str, prompt: str, neg_prompt: str
|
391 |
-
|
392 |
-
steps: int | None = None, cfg: int | None = None, seed: int = -1,
|
393 |
save_path: str | None = None, timeout: float = inference_timeout):
|
394 |
-
import random
|
395 |
-
noise = ""
|
396 |
-
if seed < 0:
|
397 |
-
rand = random.randint(1, 500)
|
398 |
-
for i in range(rand):
|
399 |
-
noise += " "
|
400 |
model = load_model(model_name)
|
401 |
if not model: return None
|
402 |
-
task = asyncio.create_task(asyncio.to_thread(infer_body, model,
|
403 |
height, width, steps, cfg, seed))
|
404 |
await asyncio.sleep(0)
|
405 |
try:
|
@@ -423,8 +415,8 @@ async def infer(model_name: str, prompt: str, neg_prompt: str | None = None,
|
|
423 |
|
424 |
|
425 |
# https://github.com/aio-libs/pytest-aiohttp/issues/8 # also AsyncInferenceClient is buggy.
|
426 |
-
def infer_fn(model_name: str, prompt: str, neg_prompt: str
|
427 |
-
|
428 |
pos_pre: list = [], pos_suf: list = [], neg_pre: list = [], neg_suf: list = [], save_path: str | None = None):
|
429 |
if model_name == 'NA':
|
430 |
return None
|
@@ -446,8 +438,8 @@ def infer_fn(model_name: str, prompt: str, neg_prompt: str | None = None, height
|
|
446 |
return result
|
447 |
|
448 |
|
449 |
-
def infer_rand_fn(model_name_dummy: str, prompt: str, neg_prompt: str
|
450 |
-
|
451 |
pos_pre: list = [], pos_suf: list = [], neg_pre: list = [], neg_suf: list = [], save_path: str | None = None):
|
452 |
import random
|
453 |
if model_name_dummy == 'NA':
|
@@ -470,3 +462,41 @@ def infer_rand_fn(model_name_dummy: str, prompt: str, neg_prompt: str | None = N
|
|
470 |
finally:
|
471 |
loop.close()
|
472 |
return result
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
60 |
limit = limit * 20 if check_status and force_gpu else limit * 5
|
61 |
models = []
|
62 |
try:
|
63 |
+
model_infos = api.list_models(author=author, #task="text-to-image",
|
64 |
tags=list_uniq(default_tags + tags), cardData=True, sort=sort, limit=limit)
|
65 |
except Exception as e:
|
66 |
print(f"Error: Failed to list models.")
|
|
|
110 |
|
111 |
|
112 |
def rename_image(image_path: str | None, model_name: str, save_path: str | None = None):
|
113 |
+
import shutil
|
114 |
from datetime import datetime, timezone, timedelta
|
115 |
if image_path is None: return None
|
116 |
dt_now = datetime.now(timezone(timedelta(hours=9)))
|
|
|
118 |
try:
|
119 |
if Path(image_path).exists():
|
120 |
png_path = "image.png"
|
121 |
+
if str(Path(image_path).resolve()) != str(Path(png_path).resolve()): shutil.copy(image_path, png_path)
|
122 |
if save_path is not None:
|
123 |
new_path = str(Path(png_path).resolve().rename(Path(save_path).resolve()))
|
124 |
else:
|
|
|
363 |
|
364 |
# https://huggingface.co/docs/api-inference/detailed_parameters
|
365 |
# https://huggingface.co/docs/huggingface_hub/package_reference/inference_client
|
366 |
+
def infer_body(client: InferenceClient | gr.Interface | object, model_str: str, prompt: str, neg_prompt: str = "",
|
367 |
+
height: int = 0, width: int = 0, steps: int = 0, cfg: int = 0, seed: int = -1):
|
|
|
368 |
png_path = "image.png"
|
369 |
kwargs = {}
|
370 |
+
if height > 0: kwargs["height"] = height
|
371 |
+
if width > 0: kwargs["width"] = width
|
372 |
+
if steps > 0: kwargs["num_inference_steps"] = steps
|
373 |
+
if cfg > 0: cfg = kwargs["guidance_scale"] = cfg
|
374 |
+
if seed == -1: kwargs["seed"] = randomize_seed()
|
375 |
+
else: kwargs["seed"] = seed
|
376 |
try:
|
377 |
if isinstance(client, InferenceClient):
|
378 |
image = client.text_to_image(prompt=prompt, negative_prompt=neg_prompt, **kwargs, token=HF_TOKEN)
|
|
|
380 |
image = client.fn(prompt=prompt, negative_prompt=neg_prompt, **kwargs, token=HF_TOKEN)
|
381 |
else: return None
|
382 |
if isinstance(image, tuple): return None
|
383 |
+
return save_image(image, png_path, model_str, prompt, neg_prompt, height, width, steps, cfg, seed)
|
|
|
384 |
except Exception as e:
|
385 |
print(e)
|
386 |
raise Exception() from e
|
387 |
|
388 |
|
389 |
+
async def infer(model_name: str, prompt: str, neg_prompt: str ="", height: int = 0, width: int = 0,
|
390 |
+
steps: int = 0, cfg: int = 0, seed: int = -1,
|
|
|
391 |
save_path: str | None = None, timeout: float = inference_timeout):
|
|
|
|
|
|
|
|
|
|
|
|
|
392 |
model = load_model(model_name)
|
393 |
if not model: return None
|
394 |
+
task = asyncio.create_task(asyncio.to_thread(infer_body, model, model_name, prompt, neg_prompt,
|
395 |
height, width, steps, cfg, seed))
|
396 |
await asyncio.sleep(0)
|
397 |
try:
|
|
|
415 |
|
416 |
|
417 |
# https://github.com/aio-libs/pytest-aiohttp/issues/8 # also AsyncInferenceClient is buggy.
|
418 |
+
def infer_fn(model_name: str, prompt: str, neg_prompt: str = "", height: int = 0, width: int = 0,
|
419 |
+
steps: int = 0, cfg: int = 0, seed: int = -1,
|
420 |
pos_pre: list = [], pos_suf: list = [], neg_pre: list = [], neg_suf: list = [], save_path: str | None = None):
|
421 |
if model_name == 'NA':
|
422 |
return None
|
|
|
438 |
return result
|
439 |
|
440 |
|
441 |
+
def infer_rand_fn(model_name_dummy: str, prompt: str, neg_prompt: str = "", height: int = 0, width: int = 0,
|
442 |
+
steps: int = 0, cfg: int = 0, seed: int = -1,
|
443 |
pos_pre: list = [], pos_suf: list = [], neg_pre: list = [], neg_suf: list = [], save_path: str | None = None):
|
444 |
import random
|
445 |
if model_name_dummy == 'NA':
|
|
|
462 |
finally:
|
463 |
loop.close()
|
464 |
return result
|
465 |
+
|
466 |
+
|
467 |
+
def save_image(image, savefile, modelname, prompt, nprompt, height=0, width=0, steps=0, cfg=0, seed=-1):
|
468 |
+
from PIL import Image, PngImagePlugin
|
469 |
+
import json
|
470 |
+
try:
|
471 |
+
metadata = {"prompt": prompt, "negative_prompt": nprompt, "Model": {"Model": modelname.split("/")[-1]}}
|
472 |
+
if steps > 0: metadata["num_inference_steps"] = steps
|
473 |
+
if cfg > 0: metadata["guidance_scale"] = cfg
|
474 |
+
if seed != -1: metadata["seed"] = seed
|
475 |
+
if width > 0 and height > 0: metadata["resolution"] = f"{width} x {height}"
|
476 |
+
metadata_str = json.dumps(metadata)
|
477 |
+
info = PngImagePlugin.PngInfo()
|
478 |
+
info.add_text("metadata", metadata_str)
|
479 |
+
image.save(savefile, "PNG", pnginfo=info)
|
480 |
+
return str(Path(savefile).resolve())
|
481 |
+
except Exception as e:
|
482 |
+
print(f"Failed to save image file: {e}")
|
483 |
+
raise Exception(f"Failed to save image file:") from e
|
484 |
+
|
485 |
+
|
486 |
+
def randomize_seed():
|
487 |
+
from random import seed, randint
|
488 |
+
MAX_SEED = 2**32-1
|
489 |
+
seed()
|
490 |
+
rseed = randint(0, MAX_SEED)
|
491 |
+
return rseed
|
492 |
+
|
493 |
+
|
494 |
+
from translatepy import Translator
|
495 |
+
translator = Translator()
|
496 |
+
def translate_to_en(input: str):
|
497 |
+
try:
|
498 |
+
output = str(translator.translate(input, 'English'))
|
499 |
+
except Exception as e:
|
500 |
+
output = input
|
501 |
+
print(e)
|
502 |
+
return output
|
requirements.txt
CHANGED
@@ -2,11 +2,8 @@ huggingface_hub
|
|
2 |
torch==2.2.0
|
3 |
torchvision
|
4 |
accelerate
|
5 |
-
transformers
|
6 |
optimum[onnxruntime]
|
7 |
-
spaces
|
8 |
dartrs
|
9 |
-
|
10 |
-
httpcore
|
11 |
-
googletrans==4.0.0rc1
|
12 |
timm
|
|
|
2 |
torch==2.2.0
|
3 |
torchvision
|
4 |
accelerate
|
5 |
+
transformers==4.44.0
|
6 |
optimum[onnxruntime]
|
|
|
7 |
dartrs
|
8 |
+
translatepy
|
|
|
|
|
9 |
timm
|
tagger/tagger.py
CHANGED
@@ -2,10 +2,7 @@ import spaces
|
|
2 |
from PIL import Image
|
3 |
import torch
|
4 |
import gradio as gr
|
5 |
-
from transformers import
|
6 |
-
AutoImageProcessor,
|
7 |
-
AutoModelForImageClassification,
|
8 |
-
)
|
9 |
from pathlib import Path
|
10 |
|
11 |
|
@@ -190,18 +187,16 @@ def convert_danbooru_to_e621_prompt(input_prompt: str = "", prompt_type: str = "
|
|
190 |
return output_prompt
|
191 |
|
192 |
|
193 |
-
|
194 |
-
|
195 |
-
|
196 |
-
|
197 |
-
from googletrans import Translator
|
198 |
-
translator = Translator()
|
199 |
try:
|
200 |
-
|
201 |
-
return translated_prompt
|
202 |
except Exception as e:
|
|
|
203 |
print(e)
|
204 |
-
|
205 |
|
206 |
def is_japanese(s):
|
207 |
import unicodedata
|
@@ -223,18 +218,23 @@ def translate_prompt(prompt: str = ""):
|
|
223 |
return ", ".join(outputs)
|
224 |
|
225 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
226 |
def translate_prompt_to_ja(prompt: str = ""):
|
227 |
-
def translate_to_japanese(
|
228 |
-
import httpcore
|
229 |
-
setattr(httpcore, 'SyncHTTPTransport', 'AsyncHTTPProxy')
|
230 |
-
from googletrans import Translator
|
231 |
-
translator = Translator()
|
232 |
try:
|
233 |
-
|
234 |
-
return translated_prompt
|
235 |
except Exception as e:
|
|
|
236 |
print(e)
|
237 |
-
|
238 |
|
239 |
def is_japanese(s):
|
240 |
import unicodedata
|
|
|
2 |
from PIL import Image
|
3 |
import torch
|
4 |
import gradio as gr
|
5 |
+
from transformers import AutoImageProcessor, AutoModelForImageClassification
|
|
|
|
|
|
|
6 |
from pathlib import Path
|
7 |
|
8 |
|
|
|
187 |
return output_prompt
|
188 |
|
189 |
|
190 |
+
from translatepy import Translator
|
191 |
+
translator = Translator()
|
192 |
+
def translate_prompt_old(prompt: str = ""):
|
193 |
+
def translate_to_english(input: str):
|
|
|
|
|
194 |
try:
|
195 |
+
output = str(translator.translate(input, 'English'))
|
|
|
196 |
except Exception as e:
|
197 |
+
output = input
|
198 |
print(e)
|
199 |
+
return output
|
200 |
|
201 |
def is_japanese(s):
|
202 |
import unicodedata
|
|
|
218 |
return ", ".join(outputs)
|
219 |
|
220 |
|
221 |
+
def translate_prompt(input: str):
|
222 |
+
try:
|
223 |
+
output = str(translator.translate(input, 'English'))
|
224 |
+
except Exception as e:
|
225 |
+
output = input
|
226 |
+
print(e)
|
227 |
+
return output
|
228 |
+
|
229 |
+
|
230 |
def translate_prompt_to_ja(prompt: str = ""):
|
231 |
+
def translate_to_japanese(input: str):
|
|
|
|
|
|
|
|
|
232 |
try:
|
233 |
+
output = str(translator.translate(input, 'Japanese'))
|
|
|
234 |
except Exception as e:
|
235 |
+
output = input
|
236 |
print(e)
|
237 |
+
return output
|
238 |
|
239 |
def is_japanese(s):
|
240 |
import unicodedata
|