stable-diffusion-webui/modules/ui.py
2022-09-03 17:21:15 +03:00

530 lines
20 KiB
Python

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
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
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
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():
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)
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,
use_gfpgan,
batch_count,
batch_size,
cfg_scale,
seed,
height,
width,
] + 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():
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)
with gr.Group():
custom_inputs = modules.scripts.setup_ui(is_img2img=False)
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),
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,
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,
] + 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
with open(os.path.join(script_path, "script.js"), "r", encoding="utf8") as jsfile:
javascript = jsfile.read()
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
gradio_routes_templates_response = gradio.routes.templates.TemplateResponse
gradio.routes.templates.TemplateResponse = template_response