stable-diffusion-webui/modules/ui.py

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import base64
import html
import io
import json
import mimetypes
import os
import sys
import time
import traceback
from PIL import Image
import gradio as gr
import gradio.utils
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import gradio.routes
from modules.paths import script_path
from modules.shared import opts, cmd_opts
import modules.shared as shared
from modules.sd_samplers import samplers, samplers_for_img2img
import modules.gfpgan_model as gfpgan
import modules.realesrgan_model as realesrgan
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import modules.scripts
# this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the bowser will not show any UI
mimetypes.init()
mimetypes.add_type('application/javascript', '.js')
if not cmd_opts.share:
# fix gradio phoning home
gradio.utils.version_check = lambda: None
gradio.utils.get_local_ip_address = lambda: '127.0.0.1'
def gr_show(visible=True):
return {"visible": visible, "__type__": "update"}
sample_img2img = "assets/stable-samples/img2img/sketch-mountains-input.jpg"
sample_img2img = sample_img2img if os.path.exists(sample_img2img) else None
css_hide_progressbar = """
.wrap .m-12 svg { display:none!important; }
.wrap .m-12::before { content:"Loading..." }
.progress-bar { display:none!important; }
.meta-text { display:none!important; }
"""
def plaintext_to_html(text):
text = "".join([f"<p>{html.escape(x)}</p>\n" for x in text.split('\n')])
return text
def image_from_url_text(filedata):
if type(filedata) == list:
if len(filedata) == 0:
return None
filedata = filedata[0]
if filedata.startswith("data:image/png;base64,"):
filedata = filedata[len("data:image/png;base64,"):]
filedata = base64.decodebytes(filedata.encode('utf-8'))
image = Image.open(io.BytesIO(filedata))
return image
def send_gradio_gallery_to_image(x):
if len(x) == 0:
return None
return image_from_url_text(x[0])
def save_files(js_data, images):
import csv
os.makedirs(opts.outdir_save, exist_ok=True)
filenames = []
data = json.loads(js_data)
with open("log/log.csv", "a", encoding="utf8", newline='') as file:
at_start = file.tell() == 0
writer = csv.writer(file)
if at_start:
writer.writerow(["prompt", "seed", "width", "height", "sampler", "cfgs", "steps", "filename"])
filename_base = str(int(time.time() * 1000))
for i, filedata in enumerate(images):
filename = filename_base + ("" if len(images) == 1 else "-" + str(i + 1)) + ".png"
filepath = os.path.join(opts.outdir_save, filename)
if filedata.startswith("data:image/png;base64,"):
filedata = filedata[len("data:image/png;base64,"):]
with open(filepath, "wb") as imgfile:
imgfile.write(base64.decodebytes(filedata.encode('utf-8')))
filenames.append(filename)
writer.writerow([data["prompt"], data["seed"], data["width"], data["height"], data["sampler"], data["cfg_scale"], data["steps"], filenames[0]])
return '', '', plaintext_to_html(f"Saved: {filenames[0]}")
def wrap_gradio_call(func):
def f(*args, **kwargs):
t = time.perf_counter()
try:
res = list(func(*args, **kwargs))
except Exception as e:
print("Error completing request", file=sys.stderr)
print("Arguments:", args, kwargs, file=sys.stderr)
print(traceback.format_exc(), file=sys.stderr)
res = [None, '', f"<div class='error'>{plaintext_to_html(type(e).__name__+': '+str(e))}</div>"]
elapsed = time.perf_counter() - t
# last item is always HTML
res[-1] = res[-1] + f"<p class='performance'>Time taken: {elapsed:.2f}s</p>"
shared.state.interrupted = False
return tuple(res)
return f
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def create_ui(txt2img, img2img, run_extras, run_pnginfo):
with gr.Blocks(analytics_enabled=False) as txt2img_interface:
with gr.Row():
prompt = gr.Textbox(label="Prompt", elem_id="txt2img_prompt", show_label=False, placeholder="Prompt", lines=1)
negative_prompt = gr.Textbox(label="Negative prompt", elem_id="txt2img_negative_prompt", show_label=False, placeholder="Negative prompt", lines=1, visible=False)
submit = gr.Button('Generate', elem_id="txt2img_generate", variant='primary')
with gr.Row().style(equal_height=False):
with gr.Column(variant='panel'):
steps = gr.Slider(minimum=1, maximum=150, step=1, label="Sampling Steps", value=20)
sampler_index = gr.Radio(label='Sampling method', elem_id="txt2img_sampling", choices=[x.name for x in samplers], value=samplers[0].name, type="index")
with gr.Row():
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use_gfpgan = gr.Checkbox(label='GFPGAN', value=False, visible=gfpgan.have_gfpgan)
with gr.Row():
batch_count = gr.Slider(minimum=1, maximum=cmd_opts.max_batch_count, step=1, label='Batch count', value=1)
batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1)
cfg_scale = gr.Slider(minimum=1.0, maximum=15.0, step=0.5, label='CFG Scale', value=7.0)
with gr.Group():
height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512)
width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512)
seed = gr.Number(label='Seed', value=-1)
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with gr.Group():
custom_inputs = modules.scripts.setup_ui(is_img2img=False)
with gr.Column(variant='panel'):
with gr.Group():
txt2img_gallery = gr.Gallery(label='Output', elem_id='txt2img_gallery')
with gr.Group():
with gr.Row():
save = gr.Button('Save')
send_to_img2img = gr.Button('Send to img2img')
send_to_inpaint = gr.Button('Send to inpaint')
send_to_extras = gr.Button('Send to extras')
interrupt = gr.Button('Interrupt')
with gr.Group():
html_info = gr.HTML()
generation_info = gr.Textbox(visible=False)
txt2img_args = dict(
fn=txt2img,
inputs=[
prompt,
negative_prompt,
steps,
sampler_index,
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use_gfpgan,
batch_count,
batch_size,
cfg_scale,
seed,
height,
width,
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] + custom_inputs,
outputs=[
txt2img_gallery,
generation_info,
html_info
]
)
prompt.submit(**txt2img_args)
submit.click(**txt2img_args)
interrupt.click(
fn=lambda: shared.state.interrupt(),
inputs=[],
outputs=[],
)
save.click(
fn=wrap_gradio_call(save_files),
inputs=[
generation_info,
txt2img_gallery,
],
outputs=[
html_info,
html_info,
html_info,
]
)
with gr.Blocks(analytics_enabled=False) as img2img_interface:
with gr.Row():
prompt = gr.Textbox(label="Prompt", elem_id="img2img_prompt", show_label=False, placeholder="Prompt", lines=1)
submit = gr.Button('Generate', elem_id="img2img_generate", variant='primary')
with gr.Row().style(equal_height=False):
with gr.Column(variant='panel'):
with gr.Group():
switch_mode = gr.Radio(label='Mode', elem_id="img2img_mode", choices=['Redraw whole image', 'Inpaint a part of image', 'Loopback', 'SD upscale'], value='Redraw whole image', type="index", show_label=False)
init_img = gr.Image(label="Image for img2img", source="upload", interactive=True, type="pil")
init_img_with_mask = gr.Image(label="Image for inpainting with mask", elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool="sketch", visible=False)
resize_mode = gr.Radio(label="Resize mode", show_label=False, choices=["Just resize", "Crop and resize", "Resize and fill"], type="index", value="Just resize")
steps = gr.Slider(minimum=1, maximum=150, step=1, label="Sampling Steps", value=20)
sampler_index = gr.Radio(label='Sampling method', choices=[x.name for x in samplers_for_img2img], value=samplers_for_img2img[0].name, type="index")
mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=4, visible=False)
inpainting_fill = gr.Radio(label='Msked content', choices=['fill', 'original', 'latent noise', 'latent nothing'], value='fill', type="index", visible=False)
with gr.Row():
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use_gfpgan = gr.Checkbox(label='GFPGAN', value=False, visible=gfpgan.have_gfpgan)
inpaint_full_res = gr.Checkbox(label='Inpaint at full resolution', value=True, visible=False)
with gr.Row():
sd_upscale_upscaler_name = gr.Radio(label='Upscaler', choices=list(shared.sd_upscalers.keys()), value=list(shared.sd_upscalers.keys())[0], visible=False)
sd_upscale_overlap = gr.Slider(minimum=0, maximum=256, step=16, label='Tile overlap', value=64, visible=False)
with gr.Row():
batch_count = gr.Slider(minimum=1, maximum=cmd_opts.max_batch_count, step=1, label='Batch count', value=1)
batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1)
with gr.Group():
cfg_scale = gr.Slider(minimum=1.0, maximum=15.0, step=0.5, label='CFG Scale', value=7.0)
denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising Strength', value=0.75)
with gr.Group():
height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512)
width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512)
seed = gr.Number(label='Seed', value=-1)
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with gr.Group():
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custom_inputs = modules.scripts.setup_ui(is_img2img=True)
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with gr.Column(variant='panel'):
with gr.Group():
img2img_gallery = gr.Gallery(label='Output', elem_id='img2img_gallery')
with gr.Group():
with gr.Row():
interrupt = gr.Button('Interrupt')
save = gr.Button('Save')
img2img_send_to_extras = gr.Button('Send to extras')
with gr.Group():
html_info = gr.HTML()
generation_info = gr.Textbox(visible=False)
def apply_mode(mode):
is_classic = mode == 0
is_inpaint = mode == 1
is_loopback = mode == 2
is_upscale = mode == 3
return {
init_img: gr_show(not is_inpaint),
init_img_with_mask: gr_show(is_inpaint),
mask_blur: gr_show(is_inpaint),
inpainting_fill: gr_show(is_inpaint),
batch_count: gr_show(not is_upscale),
batch_size: gr_show(not is_loopback),
sd_upscale_upscaler_name: gr_show(is_upscale),
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sd_upscale_overlap: gr_show(is_upscale),
inpaint_full_res: gr_show(is_inpaint),
}
switch_mode.change(
apply_mode,
inputs=[switch_mode],
outputs=[
init_img,
init_img_with_mask,
mask_blur,
inpainting_fill,
batch_count,
batch_size,
sd_upscale_upscaler_name,
sd_upscale_overlap,
inpaint_full_res,
]
)
img2img_args = dict(
fn=img2img,
inputs=[
prompt,
init_img,
init_img_with_mask,
steps,
sampler_index,
mask_blur,
inpainting_fill,
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use_gfpgan,
switch_mode,
batch_count,
batch_size,
cfg_scale,
denoising_strength,
seed,
height,
width,
resize_mode,
sd_upscale_upscaler_name,
sd_upscale_overlap,
inpaint_full_res,
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] + custom_inputs,
outputs=[
img2img_gallery,
generation_info,
html_info
]
)
prompt.submit(**img2img_args)
submit.click(**img2img_args)
interrupt.click(
fn=lambda: shared.state.interrupt(),
inputs=[],
outputs=[],
)
save.click(
fn=wrap_gradio_call(save_files),
inputs=[
generation_info,
img2img_gallery,
],
outputs=[
html_info,
html_info,
html_info,
]
)
send_to_img2img.click(
fn=lambda x: image_from_url_text(x),
_js="extract_image_from_gallery",
inputs=[txt2img_gallery],
outputs=[init_img],
)
send_to_inpaint.click(
fn=lambda x: image_from_url_text(x),
_js="extract_image_from_gallery",
inputs=[txt2img_gallery],
outputs=[init_img_with_mask],
)
with gr.Blocks(analytics_enabled=False) as extras_interface:
with gr.Row().style(equal_height=False):
with gr.Column(variant='panel'):
with gr.Group():
image = gr.Image(label="Source", source="upload", interactive=True, type="pil")
gfpgan_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="GFPGAN strength", value=1, interactive=gfpgan.have_gfpgan)
realesrgan_resize = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label="Real-ESRGAN upscaling", value=2, interactive=realesrgan.have_realesrgan)
realesrgan_model = gr.Radio(label='Real-ESRGAN model', choices=[x.name for x in realesrgan.realesrgan_models], value=realesrgan.realesrgan_models[0].name, type="index", interactive=realesrgan.have_realesrgan)
submit = gr.Button('Generate', elem_id="extras_generate", variant='primary')
with gr.Column(variant='panel'):
result_image = gr.Image(label="Result")
html_info_x = gr.HTML()
html_info = gr.HTML()
extras_args = dict(
fn=run_extras,
inputs=[
image,
gfpgan_strength,
realesrgan_resize,
realesrgan_model,
],
outputs=[
result_image,
html_info_x,
html_info,
]
)
submit.click(**extras_args)
send_to_extras.click(
fn=lambda x: image_from_url_text(x),
_js="extract_image_from_gallery",
inputs=[txt2img_gallery],
outputs=[image],
)
img2img_send_to_extras.click(
fn=lambda x: image_from_url_text(x),
_js="extract_image_from_gallery",
inputs=[img2img_gallery],
outputs=[image],
)
pnginfo_interface = gr.Interface(
wrap_gradio_call(run_pnginfo),
inputs=[
gr.Image(label="Source", source="upload", interactive=True, type="pil"),
],
outputs=[
gr.HTML(),
gr.HTML(),
gr.HTML(),
],
allow_flagging="never",
analytics_enabled=False,
)
def create_setting_component(key):
def fun():
return opts.data[key] if key in opts.data else opts.data_labels[key].default
info = opts.data_labels[key]
t = type(info.default)
if info.component is not None:
item = info.component(label=info.label, value=fun, **(info.component_args or {}))
elif t == str:
item = gr.Textbox(label=info.label, value=fun, lines=1)
elif t == int:
item = gr.Number(label=info.label, value=fun)
elif t == bool:
item = gr.Checkbox(label=info.label, value=fun)
else:
raise Exception(f'bad options item type: {str(t)} for key {key}')
return item
def run_settings(*args):
up = []
for key, value, comp in zip(opts.data_labels.keys(), args, settings_interface.input_components):
opts.data[key] = value
up.append(comp.update(value=value))
opts.save(shared.config_filename)
return 'Settings saved.', '', ''
settings_interface = gr.Interface(
run_settings,
inputs=[create_setting_component(key) for key in opts.data_labels.keys()],
outputs=[
gr.Textbox(label='Result'),
gr.HTML(),
gr.HTML(),
],
title=None,
description=None,
allow_flagging="never",
analytics_enabled=False,
)
interfaces = [
(txt2img_interface, "txt2img"),
(img2img_interface, "img2img"),
(extras_interface, "Extras"),
(pnginfo_interface, "PNG Info"),
(settings_interface, "Settings"),
]
with open(os.path.join(script_path, "style.css"), "r", encoding="utf8") as file:
css = file.read()
if not cmd_opts.no_progressbar_hiding:
css += css_hide_progressbar
demo = gr.TabbedInterface(
interface_list=[x[0] for x in interfaces],
tab_names=[x[1] for x in interfaces],
analytics_enabled=False,
css=css,
)
return demo
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with open(os.path.join(script_path, "script.js"), "r", encoding="utf8") as jsfile:
javascript = jsfile.read()
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def template_response(*args, **kwargs):
res = gradio_routes_templates_response(*args, **kwargs)
res.body = res.body.replace(b'</head>', f'<script>{javascript}</script></head>'.encode("utf8"))
res.init_headers()
return res
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gradio_routes_templates_response = gradio.routes.templates.TemplateResponse
gradio.routes.templates.TemplateResponse = template_response