File size: 9,661 Bytes
5501872 085828a 769f850 085828a 4c314b0 9307b26 5501872 9307b26 5501872 6035d36 5501872 b38a20b 5501872 b38a20b 5501872 7dc91c1 5501872 7dc91c1 5501872 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 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 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 |
import gradio as gr
from model import models
from multit2i import (load_models, infer_fn, infer_rand_fn, save_gallery,
change_model, warm_model, get_model_info_md, loaded_models,
get_positive_prefix, get_positive_suffix, get_negative_prefix, get_negative_suffix,
get_recom_prompt_type, set_recom_prompt_preset, get_tag_type, randomize_seed, translate_to_en)
import os
from diffusers import StableDiffusionPipeline
import torch
max_images = 8
MAX_SEED = 2**32-1
load_models(models)
css = """
.model_info { text-align: center; }
.output { width=112px; height=112px; max_width=112px; max_height=112px; !important; }
.gallery { min_width=512px; min_height=512px; max_height=1024px; !important; }
"""
with gr.Blocks(theme="NoCrypt/miku@>=1.2.2", fill_width=True, css=css) as demo:
with gr.Tab("Image Generator"):
with gr.Row():
with gr.Column(scale=10):
with gr.Group():
prompt = gr.Text(label="Prompt", lines=2, max_lines=8, placeholder="1girl, solo, ...", show_copy_button=True)
with gr.Accordion("Advanced options", open=False):
neg_prompt = gr.Text(label="Negative Prompt", lines=1, max_lines=8, placeholder="")
with gr.Row():
width = gr.Slider(label="Width", info="If 0, the default value is used.", maximum=4096, step=32, value=0)
height = gr.Slider(label="Height", info="If 0, the default value is used.", maximum=4096, step=32, value=0)
steps = gr.Slider(label="Number of inference steps", info="If 0, the default value is used.", maximum=100, step=1, value=0)
with gr.Row():
cfg = gr.Slider(label="Guidance scale", info="If 0, the default value is used.", maximum=30.0, step=0.1, value=0)
seed = gr.Slider(label="Seed", info="Randomize Seed if -1.", minimum=-1, maximum=MAX_SEED, step=1, value=-1)
seed_rand = gr.Button("Randomize Seed π²", size="sm", variant="secondary")
recom_prompt_preset = gr.Radio(label="Set Presets", choices=get_recom_prompt_type(), value="Common")
with gr.Row():
positive_prefix = gr.CheckboxGroup(label="Use Positive Prefix", choices=get_positive_prefix(), value=[])
positive_suffix = gr.CheckboxGroup(label="Use Positive Suffix", choices=get_positive_suffix(), value=["Common"])
negative_prefix = gr.CheckboxGroup(label="Use Negative Prefix", choices=get_negative_prefix(), value=[])
negative_suffix = gr.CheckboxGroup(label="Use Negative Suffix", choices=get_negative_suffix(), value=["Common"])
with gr.Row():
image_num = gr.Slider(label="Number of images", minimum=1, maximum=max_images, value=1, step=1, interactive=True, scale=2)
trans_prompt = gr.Button(value="Translate π", variant="secondary", size="sm", scale=2)
clear_prompt = gr.Button(value="Clear ποΈ", variant="secondary", size="sm", scale=1)
with gr.Row():
run_button = gr.Button("Generate Image", variant="primary", scale=8)
random_button = gr.Button("Random Model π²", variant="secondary", scale=3)
stop_button = gr.Button('Stop', interactive=False, variant="stop", scale=1)
with gr.Group():
model_name = gr.Dropdown(label="Select Model", choices=list(loaded_models.keys()), value=list(loaded_models.keys())[0], allow_custom_value=True)
model_info = gr.Markdown(value=get_model_info_md(list(loaded_models.keys())[0]), elem_classes="model_info")
with gr.Column(scale=10):
with gr.Group():
with gr.Row():
output = [gr.Image(label='', elem_classes="output", type="filepath", format="png",
show_download_button=True, show_share_button=False, show_label=False,
interactive=False, min_width=80, visible=True, width=112, height=112) for _ in range(max_images)]
with gr.Group():
results = gr.Gallery(label="Gallery", elem_classes="gallery", interactive=False, show_download_button=True, show_share_button=False,
container=True, format="png", object_fit="cover", columns=2, rows=2)
image_files = gr.Files(label="Download", interactive=False)
clear_results = gr.Button("Clear Gallery / Download ποΈ", variant="secondary")
with gr.Column():
examples = gr.Examples(
examples = [
["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"],
["sailor moon, magical girl transformation, sparkles and ribbons, soft pastel colors, crescent moon motif, starry night sky background, shoujo manga style"],
["kafuu chino, 1girl, solo"],
["1girl"],
["beautiful sunset"],
],
inputs=[prompt],
cache_examples=False,
)
with gr.Tab("PNG Info"):
def extract_exif_data(image):
if image is None: return ""
try:
metadata_keys = ['parameters', 'metadata', 'prompt', 'Comment']
for key in metadata_keys:
if key in image.info:
return image.info[key]
return str(image.info)
except Exception as e:
return f"Error extracting metadata: {str(e)}"
with gr.Row():
with gr.Column():
image_metadata = gr.Image(label="Image with metadata", type="pil", sources=["upload"])
with gr.Column():
result_metadata = gr.Textbox(label="Metadata", show_label=True, show_copy_button=True, interactive=False, container=True, max_lines=99)
image_metadata.change(
fn=extract_exif_data,
inputs=[image_metadata],
outputs=[result_metadata],
)
gr.Markdown(
f"""This demo was created in reference to the following demos.<br>
[Nymbo/Flood](https://huggingface.co/spaces/Nymbo/Flood),
[Yntec/ToyWorldXL](https://huggingface.co/spaces/Yntec/ToyWorldXL),
[Yntec/Diffusion80XX](https://huggingface.co/spaces/Yntec/Diffusion80XX).
"""
)
gr.DuplicateButton(value="Duplicate Space")
gr.Markdown(f"Just a few edits to *model.py* are all it takes to complete your own collection.")
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)
model_name.change(change_model, [model_name], [model_info], queue=True, show_api=True)\
.success(warm_model, [model_name], None, queue=True, show_api=True)
for i, o in enumerate(output):
img_i = gr.Number(i, visible=False)
image_num.change(lambda i, n: gr.update(visible = (i < n)), [img_i, image_num], o, show_api=True)
gen_event = gr.on(triggers=[run_button.click, prompt.submit],
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,
inputs=[img_i, image_num, model_name, prompt, neg_prompt, height, width, steps, cfg, seed,
positive_prefix, positive_suffix, negative_prefix, negative_suffix],
outputs=[o], queue=True, show_api=False) # Be sure to delete ", queue=False" when activating the stop button
gen_event2 = gr.on(triggers=[random_button.click],
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,
inputs=[img_i, image_num, model_name, prompt, neg_prompt, height, width, steps, cfg, seed,
positive_prefix, positive_suffix, negative_prefix, negative_suffix],
outputs=[o], queue=True, show_api=False) # Be sure to delete ", queue=False" when activating the stop button
o.change(save_gallery, [o, results], [results, image_files], show_api=False)
stop_button.click(lambda: gr.update(interactive=False), None, stop_button, cancels=[gen_event, gen_event2], show_api=False)
clear_prompt.click(lambda: (None, None), None, [prompt, neg_prompt], queue=True, show_api=True)
clear_results.click(lambda: (None, None), None, [results, image_files], queue=True, show_api=True)
recom_prompt_preset.change(set_recom_prompt_preset, [recom_prompt_preset],
[positive_prefix, positive_suffix, negative_prefix, negative_suffix], queue=True, show_api=True)
seed_rand.click(randomize_seed, None, [seed], queue=True, show_api=True)
trans_prompt.click(translate_to_en, [prompt], [prompt], queue=True, show_api=True)\
.then(translate_to_en, [neg_prompt], [neg_prompt], queue=True, show_api=True)
#demo.queue(default_concurrency_limit=240, max_size=240)
#demo.launch(max_threads=400, ssr_mode=True)
# https://github.com/gradio-app/gradio/issues/6339
#demo.queue(concurrency_count=50)
demo.launch() |