stable-diffusion-webui/modules/ui.py

1030 lines
42 KiB
Python

import base64
import html
import io
import json
import math
import mimetypes
import os
import random
import sys
import time
import traceback
import numpy as np
import torch
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.realesrgan_model as realesrgan
import modules.scripts
import modules.gfpgan_model
import modules.codeformer_model
import modules.styles
# 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 and not cmd_opts.listen:
# 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; }
"""
# Using constants for these since the variation selector isn't visible.
# Important that they exactly match script.js for tooltip to work.
random_symbol = '\U0001f3b2\ufe0f' # 🎲️
reuse_symbol = '\u267b\ufe0f' # ♻️
def plaintext_to_html(text):
text = "<p>" + "<br>\n".join([f"{html.escape(x)}" for x in text.split('\n')]) + "</p>"
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, index):
import csv
os.makedirs(opts.outdir_save, exist_ok=True)
filenames = []
data = json.loads(js_data)
if index > -1 and opts.save_selected_only and (index > 0 or not opts.return_grid): # ensures we are looking at a specific non-grid picture, and we have save_selected_only
images = [images[index]]
data["seed"] += (index - 1 if opts.return_grid else index)
with open(os.path.join(opts.outdir_save, "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", "negative_prompt"])
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], data["negative_prompt"]])
return '', '', plaintext_to_html(f"Saved: {filenames[0]}")
def wrap_gradio_call(func):
def f(*args, **kwargs):
run_memmon = opts.memmon_poll_rate > 0 and not shared.mem_mon.disabled
if run_memmon:
shared.mem_mon.monitor()
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)
shared.state.job = ""
shared.state.job_count = 0
res = [None, '', f"<div class='error'>{plaintext_to_html(type(e).__name__+': '+str(e))}</div>"]
elapsed = time.perf_counter() - t
if run_memmon:
mem_stats = {k: -(v//-(1024*1024)) for k, v in shared.mem_mon.stop().items()}
active_peak = mem_stats['active_peak']
reserved_peak = mem_stats['reserved_peak']
sys_peak = mem_stats['system_peak']
sys_total = mem_stats['total']
sys_pct = round(sys_peak/max(sys_total, 1) * 100, 2)
vram_html = f"<p class='vram'>Torch active/reserved: {active_peak}/{reserved_peak} MiB, <wbr>Sys VRAM: {sys_peak}/{sys_total} MiB ({sys_pct}%)</p>"
else:
vram_html = ''
# last item is always HTML
res[-1] += f"<div class='performance'><p class='time'>Time taken: <wbr>{elapsed:.2f}s</p>{vram_html}</div>"
shared.state.interrupted = False
return tuple(res)
return f
def check_progress_call():
if shared.state.job_count == 0:
return "", gr_show(False), gr_show(False)
progress = 0
if shared.state.job_count > 0:
progress += shared.state.job_no / shared.state.job_count
if shared.state.sampling_steps > 0:
progress += 1 / shared.state.job_count * shared.state.sampling_step / shared.state.sampling_steps
progress = min(progress, 1)
progressbar = ""
if opts.show_progressbar:
progressbar = f"""<div class='progressDiv'><div class='progress' style="width:{progress * 100}%">{str(int(progress*100))+"%" if progress > 0.01 else ""}</div></div>"""
image = gr_show(False)
preview_visibility = gr_show(False)
if opts.show_progress_every_n_steps > 0:
if shared.parallel_processing_allowed:
if shared.state.sampling_step - shared.state.current_image_sampling_step >= opts.show_progress_every_n_steps and shared.state.current_latent is not None:
shared.state.current_image = modules.sd_samplers.sample_to_image(shared.state.current_latent)
shared.state.current_image_sampling_step = shared.state.sampling_step
image = shared.state.current_image
if image is None or progress >= 1:
image = gr.update(value=None)
else:
preview_visibility = gr_show(True)
return f"<span style='display: none'>{time.time()}</span><p>{progressbar}</p>", preview_visibility, image
def check_progress_call_initial():
shared.state.job_count = -1
shared.state.current_latent = None
shared.state.current_image = None
return check_progress_call()
def roll_artist(prompt):
allowed_cats = set([x for x in shared.artist_db.categories() if len(opts.random_artist_categories)==0 or x in opts.random_artist_categories])
artist = random.choice([x for x in shared.artist_db.artists if x.category in allowed_cats])
return prompt + ", " + artist.name if prompt != '' else artist.name
def visit(x, func, path=""):
if hasattr(x, 'children'):
for c in x.children:
visit(c, func, path)
elif x.label is not None:
func(path + "/" + str(x.label), x)
def add_style(name: str, prompt: str, negative_prompt: str):
if name is None:
return [gr_show(), gr_show()]
style = modules.styles.PromptStyle(name, prompt, negative_prompt)
shared.prompt_styles.styles[style.name] = style
# Save all loaded prompt styles: this allows us to update the storage format in the future more easily, because we
# reserialize all styles every time we save them
shared.prompt_styles.save_styles(shared.styles_filename)
update = {"visible": True, "choices": list(shared.prompt_styles.styles), "__type__": "update"}
return [update, update, update, update]
def apply_styles(prompt, prompt_neg, style1_name, style2_name):
prompt = shared.prompt_styles.apply_styles_to_prompt(prompt, [style1_name, style2_name])
prompt_neg = shared.prompt_styles.apply_negative_styles_to_prompt(prompt_neg, [style1_name, style2_name])
return [gr.Textbox.update(value=prompt), gr.Textbox.update(value=prompt_neg), gr.Dropdown.update(value="None"), gr.Dropdown.update(value="None")]
def interrogate(image):
prompt = shared.interrogator.interrogate(image)
return gr_show(True) if prompt is None else prompt
def create_seed_inputs():
with gr.Row():
with gr.Box():
with gr.Row(elem_id='seed_row'):
seed = (gr.Textbox if cmd_opts.use_textbox_seed else gr.Number)(label='Seed', value=-1)
seed.style(container=False)
random_seed = gr.Button(random_symbol, elem_id='random_seed')
reuse_seed = gr.Button(reuse_symbol, elem_id='reuse_seed')
with gr.Box(elem_id='subseed_show_box'):
seed_checkbox = gr.Checkbox(label='Extra', elem_id='subseed_show', value=False)
# Components to show/hide based on the 'Extra' checkbox
seed_extras = []
with gr.Row(visible=False) as seed_extra_row_1:
seed_extras.append(seed_extra_row_1)
with gr.Box():
with gr.Row(elem_id='subseed_row'):
subseed = gr.Number(label='Variation seed', value=-1)
subseed.style(container=False)
random_subseed = gr.Button(random_symbol, elem_id='random_subseed')
reuse_subseed = gr.Button(reuse_symbol, elem_id='reuse_subseed')
subseed_strength = gr.Slider(label='Variation strength', value=0.0, minimum=0, maximum=1, step=0.01)
with gr.Row(visible=False) as seed_extra_row_2:
seed_extras.append(seed_extra_row_2)
seed_resize_from_w = gr.Slider(minimum=0, maximum=2048, step=64, label="Resize seed from width", value=0)
seed_resize_from_h = gr.Slider(minimum=0, maximum=2048, step=64, label="Resize seed from height", value=0)
random_seed.click(fn=lambda: -1, show_progress=False, inputs=[], outputs=[seed])
random_subseed.click(fn=lambda: -1, show_progress=False, inputs=[], outputs=[subseed])
def change_visibility(show):
return {comp: gr_show(show) for comp in seed_extras}
seed_checkbox.change(change_visibility, show_progress=False, inputs=[seed_checkbox], outputs=seed_extras)
return seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w
def connect_reuse_seed(seed: gr.Number, reuse_seed: gr.Button, generation_info: gr.Textbox, dummy_component, is_subseed):
""" Connects a 'reuse (sub)seed' button's click event so that it copies last used
(sub)seed value from generation info the to the seed field. If copying subseed and subseed strength
was 0, i.e. no variation seed was used, it copies the normal seed value instead."""
def copy_seed(gen_info_string: str, index):
res = -1
try:
gen_info = json.loads(gen_info_string)
index -= gen_info.get('index_of_first_image', 0)
if is_subseed and gen_info.get('subseed_strength', 0) > 0:
all_subseeds = gen_info.get('all_subseeds', [-1])
res = all_subseeds[index if 0 <= index < len(all_subseeds) else 0]
else:
all_seeds = gen_info.get('all_seeds', [-1])
res = all_seeds[index if 0 <= index < len(all_seeds) else 0]
except json.decoder.JSONDecodeError as e:
if gen_info_string != '':
print("Error parsing JSON generation info:", file=sys.stderr)
print(gen_info_string, file=sys.stderr)
return [res, gr_show(False)]
reuse_seed.click(
fn=copy_seed,
_js="(x, y) => [x, selected_gallery_index()]",
show_progress=False,
inputs=[generation_info, dummy_component],
outputs=[seed, dummy_component]
)
def create_toprow(is_img2img):
with gr.Row(elem_id="toprow"):
with gr.Column(scale=4):
with gr.Row():
with gr.Column(scale=8):
with gr.Row():
prompt = gr.Textbox(label="Prompt", elem_id="prompt", show_label=False, placeholder="Prompt", lines=2)
roll = gr.Button('Roll', elem_id="roll", visible=len(shared.artist_db.artists) > 0)
with gr.Column(scale=1, elem_id="style_pos_col"):
prompt_style = gr.Dropdown(label="Style 1", elem_id="style_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys())), visible=len(shared.prompt_styles.styles) > 1)
with gr.Row():
with gr.Column(scale=8):
negative_prompt = gr.Textbox(label="Negative prompt", elem_id="negative_prompt", show_label=False, placeholder="Negative prompt", lines=2)
with gr.Column(scale=1, elem_id="style_neg_col"):
prompt_style2 = gr.Dropdown(label="Style 2", elem_id="style2_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys())), visible=len(shared.prompt_styles.styles) > 1)
with gr.Column(scale=1):
with gr.Row():
submit = gr.Button('Generate', elem_id="generate", variant='primary')
with gr.Row():
if is_img2img:
interrogate = gr.Button('Interrogate', elem_id="interrogate")
else:
interrogate = None
prompt_style_apply = gr.Button('Apply style', elem_id="style_apply")
save_style = gr.Button('Create style', elem_id="style_create")
return prompt, roll, prompt_style, negative_prompt, prompt_style2, submit, interrogate, prompt_style_apply, save_style
def setup_progressbar(progressbar, preview):
check_progress = gr.Button('Check progress', elem_id="check_progress", visible=False)
check_progress.click(
fn=check_progress_call,
show_progress=False,
inputs=[],
outputs=[progressbar, preview, preview],
)
check_progress_initial = gr.Button('Check progress (first)', elem_id="check_progress_initial", visible=False)
check_progress_initial.click(
fn=check_progress_call_initial,
show_progress=False,
inputs=[],
outputs=[progressbar, preview, preview],
)
def create_ui(txt2img, img2img, run_extras, run_pnginfo):
with gr.Blocks(analytics_enabled=False) as txt2img_interface:
txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, txt2img_prompt_style_apply, txt2img_save_style = create_toprow(is_img2img=False)
dummy_component = gr.Label(visible=False)
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():
restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1)
tiling = gr.Checkbox(label='Tiling', value=False)
enable_hr = gr.Checkbox(label='Highres. fix', value=False)
with gr.Row(visible=False) as hr_options:
scale_latent = gr.Checkbox(label='Scale latent', value=False)
denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7)
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=30.0, step=0.5, label='CFG Scale', value=7.0)
with gr.Group():
width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512)
height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512)
seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w = create_seed_inputs()
with gr.Group():
custom_inputs = modules.scripts.scripts_txt2img.setup_ui(is_img2img=False)
with gr.Column(variant='panel'):
progressbar = gr.HTML(elem_id="progressbar")
with gr.Group():
txt2img_preview = gr.Image(elem_id='txt2img_preview', visible=False)
txt2img_gallery = gr.Gallery(label='Output', elem_id='txt2img_gallery').style(grid=4)
setup_progressbar(progressbar, txt2img_preview)
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)
connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)
connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True)
txt2img_args = dict(
fn=txt2img,
_js="submit",
inputs=[
txt2img_prompt,
txt2img_negative_prompt,
txt2img_prompt_style,
txt2img_prompt_style2,
steps,
sampler_index,
restore_faces,
tiling,
batch_count,
batch_size,
cfg_scale,
seed,
subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w,
height,
width,
enable_hr,
scale_latent,
denoising_strength,
] + custom_inputs,
outputs=[
txt2img_gallery,
generation_info,
html_info
],
show_progress=False,
)
txt2img_prompt.submit(**txt2img_args)
submit.click(**txt2img_args)
enable_hr.change(
fn=lambda x: gr_show(x),
inputs=[enable_hr],
outputs=[hr_options],
)
interrupt.click(
fn=lambda: shared.state.interrupt(),
inputs=[],
outputs=[],
)
save.click(
fn=wrap_gradio_call(save_files),
_js="(x, y, z) => [x, y, selected_gallery_index()]",
inputs=[
generation_info,
txt2img_gallery,
html_info,
],
outputs=[
html_info,
html_info,
html_info,
]
)
roll.click(
fn=roll_artist,
inputs=[
txt2img_prompt,
],
outputs=[
txt2img_prompt,
]
)
with gr.Blocks(analytics_enabled=False) as img2img_interface:
img2img_prompt, roll, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_prompt_style_apply, img2img_save_style = create_toprow(is_img2img=True)
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', '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, image_mode="RGBA")
init_mask = gr.Image(label="Mask", source="upload", interactive=True, type="pil", visible=False)
init_img_with_mask_comment = gr.HTML(elem_id="mask_bug_info", value="<small>if the editor shows ERROR, switch to another tab and back, then to another img2img mode above and back</small>", visible=False)
with gr.Row():
resize_mode = gr.Radio(label="Resize mode", elem_id="resize_mode", show_label=False, choices=["Just resize", "Crop and resize", "Resize and fill"], type="index", value="Just resize")
mask_mode = gr.Radio(label="Mask mode", show_label=False, choices=["Draw mask", "Upload mask"], type="index", value="Draw mask")
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='Masked content', choices=['fill', 'original', 'latent noise', 'latent nothing'], value='fill', type="index", visible=False)
with gr.Row():
inpaint_full_res = gr.Checkbox(label='Inpaint at full resolution', value=False, visible=False)
inpainting_mask_invert = gr.Radio(label='Masking mode', choices=['Inpaint masked', 'Inpaint not masked'], value='Inpaint masked', type="index", visible=False)
with gr.Row():
restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1)
tiling = gr.Checkbox(label='Tiling', value=False)
sd_upscale_overlap = gr.Slider(minimum=0, maximum=256, step=16, label='Tile overlap', value=64, visible=False)
with gr.Row():
sd_upscale_upscaler_name = gr.Radio(label='Upscaler', choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index", 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=30.0, 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():
width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512)
height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512)
seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w = create_seed_inputs()
with gr.Group():
custom_inputs = modules.scripts.scripts_img2img.setup_ui(is_img2img=True)
with gr.Column(variant='panel'):
progressbar = gr.HTML(elem_id="progressbar")
with gr.Group():
img2img_preview = gr.Image(elem_id='img2img_preview', visible=False)
img2img_gallery = gr.Gallery(label='Output', elem_id='img2img_gallery').style(grid=4)
setup_progressbar(progressbar, img2img_preview)
with gr.Group():
with gr.Row():
save = gr.Button('Save')
img2img_send_to_img2img = gr.Button('Send to img2img')
img2img_send_to_inpaint = gr.Button('Send to inpaint')
img2img_send_to_extras = gr.Button('Send to extras')
interrupt = gr.Button('Interrupt')
img2img_save_style = gr.Button('Save prompt as style')
with gr.Group():
html_info = gr.HTML()
generation_info = gr.Textbox(visible=False)
connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)
connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True)
def apply_mode(mode, uploadmask):
is_classic = mode == 0
is_inpaint = mode == 1
is_upscale = mode == 2
return {
init_img: gr_show(not is_inpaint or (is_inpaint and uploadmask == 1)),
init_img_with_mask: gr_show(is_inpaint and uploadmask == 0),
init_img_with_mask_comment: gr_show(is_inpaint and uploadmask == 0),
init_mask: gr_show(is_inpaint and uploadmask == 1),
mask_mode: gr_show(is_inpaint),
mask_blur: gr_show(is_inpaint),
inpainting_fill: gr_show(is_inpaint),
sd_upscale_upscaler_name: gr_show(is_upscale),
sd_upscale_overlap: gr_show(is_upscale),
inpaint_full_res: gr_show(is_inpaint),
inpainting_mask_invert: gr_show(is_inpaint),
img2img_interrogate: gr_show(not is_inpaint),
}
switch_mode.change(
apply_mode,
inputs=[switch_mode, mask_mode],
outputs=[
init_img,
init_img_with_mask,
init_img_with_mask_comment,
init_mask,
mask_mode,
mask_blur,
inpainting_fill,
sd_upscale_upscaler_name,
sd_upscale_overlap,
inpaint_full_res,
inpainting_mask_invert,
img2img_interrogate,
]
)
mask_mode.change(
lambda mode: {
init_img: gr_show(mode == 1),
init_img_with_mask: gr_show(mode == 0),
init_mask: gr_show(mode == 1),
},
inputs=[mask_mode],
outputs=[
init_img,
init_img_with_mask,
init_mask,
],
)
img2img_args = dict(
fn=img2img,
_js="submit",
inputs=[
img2img_prompt,
img2img_negative_prompt,
img2img_prompt_style,
img2img_prompt_style2,
init_img,
init_img_with_mask,
init_mask,
mask_mode,
steps,
sampler_index,
mask_blur,
inpainting_fill,
restore_faces,
tiling,
switch_mode,
batch_count,
batch_size,
cfg_scale,
denoising_strength,
seed,
subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w,
height,
width,
resize_mode,
sd_upscale_upscaler_name,
sd_upscale_overlap,
inpaint_full_res,
inpainting_mask_invert,
] + custom_inputs,
outputs=[
img2img_gallery,
generation_info,
html_info
],
show_progress=False,
)
img2img_prompt.submit(**img2img_args)
submit.click(**img2img_args)
img2img_interrogate.click(
fn=interrogate,
inputs=[init_img],
outputs=[img2img_prompt],
)
interrupt.click(
fn=lambda: shared.state.interrupt(),
inputs=[],
outputs=[],
)
save.click(
fn=wrap_gradio_call(save_files),
_js="(x, y, z) => [x, y, selected_gallery_index()]",
inputs=[
generation_info,
img2img_gallery,
html_info
],
outputs=[
html_info,
html_info,
html_info,
]
)
roll.click(
fn=roll_artist,
inputs=[
img2img_prompt,
],
outputs=[
img2img_prompt,
]
)
prompts = [(txt2img_prompt, txt2img_negative_prompt), (img2img_prompt, img2img_negative_prompt)]
style_dropdowns = [(txt2img_prompt_style, txt2img_prompt_style2), (img2img_prompt_style, img2img_prompt_style2)]
for button, (prompt, negative_prompt) in zip([txt2img_save_style, img2img_save_style], prompts):
button.click(
fn=add_style,
_js="ask_for_style_name",
# Have to pass empty dummy component here, because the JavaScript and Python function have to accept
# the same number of parameters, but we only know the style-name after the JavaScript prompt
inputs=[dummy_component, prompt, negative_prompt],
outputs=[txt2img_prompt_style, img2img_prompt_style, txt2img_prompt_style2, img2img_prompt_style2],
)
for button, (prompt, negative_prompt), (style1, style2) in zip([txt2img_prompt_style_apply, img2img_prompt_style_apply], prompts, style_dropdowns):
button.click(
fn=apply_styles,
inputs=[prompt, negative_prompt, style1, style2],
outputs=[prompt, negative_prompt, style1, style2],
)
with gr.Blocks(analytics_enabled=False) as extras_interface:
with gr.Row().style(equal_height=False):
with gr.Column(variant='panel'):
with gr.Tabs():
with gr.TabItem('Single Image'):
image = gr.Image(label="Source", source="upload", interactive=True, type="pil")
with gr.TabItem('Batch Process'):
image_batch = gr.File(label="Batch Process", file_count="multiple", interactive=True, type="file")
upscaling_resize = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label="Resize", value=2)
with gr.Group():
extras_upscaler_1 = gr.Radio(label='Upscaler 1', choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index")
with gr.Group():
extras_upscaler_2 = gr.Radio(label='Upscaler 2', choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index")
extras_upscaler_2_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Upscaler 2 visibility", value=1)
with gr.Group():
gfpgan_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="GFPGAN visibility", value=0, interactive=modules.gfpgan_model.have_gfpgan)
with gr.Group():
codeformer_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="CodeFormer visibility", value=0, interactive=modules.codeformer_model.have_codeformer)
codeformer_weight = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="CodeFormer weight (0 = maximum effect, 1 = minimum effect)", value=0, interactive=modules.codeformer_model.have_codeformer)
submit = gr.Button('Generate', elem_id="extras_generate", variant='primary')
with gr.Column(variant='panel'):
result_images = gr.Gallery(label="Result")
html_info_x = gr.HTML()
html_info = gr.HTML()
extras_args = dict(
fn=run_extras,
inputs=[
image,
image_batch,
gfpgan_visibility,
codeformer_visibility,
codeformer_weight,
upscaling_resize,
extras_upscaler_1,
extras_upscaler_2,
extras_upscaler_2_visibility,
],
outputs=[
result_images,
html_info_x,
html_info,
]
)
submit.click(**extras_args)
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,
live=True,
)
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)
args = info.component_args() if callable(info.component_args) else info.component_args
if info.component is not None:
comp = info.component
elif t == str:
comp = gr.Textbox
elif t == int:
comp = gr.Number
elif t == bool:
comp = gr.Checkbox
else:
raise Exception(f'bad options item type: {str(t)} for key {key}')
return comp(label=info.label, value=fun, **(args or {}))
components = []
keys = list(opts.data_labels.keys())
settings_cols = 3
items_per_col = math.ceil(len(keys) / settings_cols)
def run_settings(*args):
up = []
for key, value, comp in zip(opts.data_labels.keys(), args, components):
comp_args = opts.data_labels[key].component_args
if comp_args and isinstance(comp_args, dict) and comp_args.get('visible') is False:
continue
oldval = opts.data.get(key, None)
opts.data[key] = value
if oldval != value and opts.data_labels[key].onchange is not None:
opts.data_labels[key].onchange()
up.append(comp.update(value=value))
opts.save(shared.config_filename)
return 'Settings applied.'
with gr.Blocks(analytics_enabled=False) as settings_interface:
settings_submit = gr.Button(value="Apply settings", variant='primary')
result = gr.HTML()
with gr.Row(elem_id="settings").style(equal_height=False):
for colno in range(settings_cols):
with gr.Column(variant='panel'):
for rowno in range(items_per_col):
index = rowno + colno * items_per_col
if index < len(keys):
components.append(create_setting_component(keys[index]))
settings_submit.click(
fn=run_settings,
inputs=components,
outputs=[result]
)
request_notifications = gr.Button(value='Request browser notifications')
request_notifications.click(
fn=lambda: None,
inputs=[],
outputs=[],
_js='() => Notification.requestPermission()'
)
interfaces = [
(txt2img_interface, "txt2img", "txt2img"),
(img2img_interface, "img2img", "img2img"),
(extras_interface, "Extras", "extras"),
(pnginfo_interface, "PNG Info", "pnginfo"),
(settings_interface, "Settings", "settings"),
]
with open(os.path.join(script_path, "style.css"), "r", encoding="utf8") as file:
css = file.read()
if os.path.exists(os.path.join(script_path, "user.css")):
with open(os.path.join(script_path, "user.css"), "r", encoding="utf8") as file:
usercss = file.read()
css += usercss
if not cmd_opts.no_progressbar_hiding:
css += css_hide_progressbar
with gr.Blocks(css=css, analytics_enabled=False, title="Stable Diffusion") as demo:
with gr.Tabs() as tabs:
for interface, label, ifid in interfaces:
with gr.TabItem(label, id=ifid):
interface.render()
text_settings = gr.Textbox(elem_id="settings_json", value=lambda: opts.dumpjson(), visible=False)
settings_submit.click(
fn=lambda: opts.dumpjson(),
inputs=[],
outputs=[text_settings],
)
tabs.change(
fn=lambda x: x,
inputs=[init_img_with_mask],
outputs=[init_img_with_mask],
)
send_to_img2img.click(
fn=lambda x: image_from_url_text(x),
_js="extract_image_from_gallery_img2img",
inputs=[txt2img_gallery],
outputs=[init_img],
)
send_to_inpaint.click(
fn=lambda x: image_from_url_text(x),
_js="extract_image_from_gallery_img2img",
inputs=[txt2img_gallery],
outputs=[init_img_with_mask],
)
img2img_send_to_img2img.click(
fn=lambda x: image_from_url_text(x),
_js="extract_image_from_gallery",
inputs=[img2img_gallery],
outputs=[init_img],
)
img2img_send_to_inpaint.click(
fn=lambda x: image_from_url_text(x),
_js="extract_image_from_gallery",
inputs=[img2img_gallery],
outputs=[init_img_with_mask],
)
send_to_extras.click(
fn=lambda x: image_from_url_text(x),
_js="extract_image_from_gallery_extras",
inputs=[txt2img_gallery],
outputs=[image],
)
img2img_send_to_extras.click(
fn=lambda x: image_from_url_text(x),
_js="extract_image_from_gallery_extras",
inputs=[img2img_gallery],
outputs=[image],
)
ui_config_file = cmd_opts.ui_config_file
ui_settings = {}
settings_count = len(ui_settings)
error_loading = False
try:
if os.path.exists(ui_config_file):
with open(ui_config_file, "r", encoding="utf8") as file:
ui_settings = json.load(file)
except Exception:
error_loading = True
print("Error loading settings:", file=sys.stderr)
print(traceback.format_exc(), file=sys.stderr)
def loadsave(path, x):
def apply_field(obj, field, condition=None):
key = path + "/" + field
saved_value = ui_settings.get(key, None)
if saved_value is None:
ui_settings[key] = getattr(obj, field)
elif condition is None or condition(saved_value):
setattr(obj, field, saved_value)
if type(x) == gr.Slider:
apply_field(x, 'value')
apply_field(x, 'minimum')
apply_field(x, 'maximum')
apply_field(x, 'step')
if type(x) == gr.Radio:
apply_field(x, 'value', lambda val: val in x.choices)
visit(txt2img_interface, loadsave, "txt2img")
visit(img2img_interface, loadsave, "img2img")
visit(extras_interface, loadsave, "extras")
if not error_loading and (not os.path.exists(ui_config_file) or settings_count != len(ui_settings)):
with open(ui_config_file, "w", encoding="utf8") as file:
json.dump(ui_settings, file, indent=4)
return demo
with open(os.path.join(script_path, "script.js"), "r", encoding="utf8") as jsfile:
javascript = f'<script>{jsfile.read()}</script>'
jsdir = os.path.join(script_path, "javascript")
for filename in os.listdir(jsdir):
with open(os.path.join(jsdir, filename), "r", encoding="utf8") as jsfile:
javascript += f"\n<script>{jsfile.read()}</script>"
def template_response(*args, **kwargs):
res = gradio_routes_templates_response(*args, **kwargs)
res.body = res.body.replace(b'</head>', f'{javascript}</head>'.encode("utf8"))
res.init_headers()
return res
gradio_routes_templates_response = gradio.routes.templates.TemplateResponse
gradio.routes.templates.TemplateResponse = template_response