diff options
Diffstat (limited to 'modules')
| -rw-r--r-- | modules/ui.py | 94 | ||||
| -rw-r--r-- | modules/ui_progress.py | 1839 |
2 files changed, 9 insertions, 1924 deletions
diff --git a/modules/ui.py b/modules/ui.py index 9b9081b5..3c458ce8 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -162,79 +162,6 @@ def save_files(js_data, images, do_make_zip, index): return gr.File.update(value=fullfns, visible=True), plaintext_to_html(f"Saved: {filenames[0]}")
-def calc_time_left(progress, threshold, label, force_display, show_eta):
- if progress == 0:
- return ""
- else:
- time_since_start = time.time() - shared.state.time_start
- eta = (time_since_start/progress)
- eta_relative = eta-time_since_start
- if (eta_relative > threshold and show_eta) or force_display:
- if eta_relative > 3600:
- return label + time.strftime('%H:%M:%S', time.gmtime(eta_relative))
- elif eta_relative > 60:
- return label + time.strftime('%M:%S', time.gmtime(eta_relative))
- else:
- return label + time.strftime('%Ss', time.gmtime(eta_relative))
- else:
- return ""
-
-
-def check_progress_call(id_part):
- if shared.state.job_count == 0:
- return "", gr_show(False), 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
-
- # Show progress percentage and time left at the same moment, and base it also on steps done
- show_eta = progress >= 0.01 or shared.state.sampling_step >= 10
-
- time_left = calc_time_left(progress, 1, " ETA: ", shared.state.time_left_force_display, show_eta)
- if time_left != "":
- shared.state.time_left_force_display = True
-
- progress = min(progress, 1)
-
- progressbar = ""
- if opts.show_progressbar:
- progressbar = f"""<div class='progressDiv'><div class='progress' style="overflow:visible;width:{progress * 100}%;white-space:nowrap;">{" " * 2 + str(int(progress*100))+"%" + time_left if show_eta else ""}</div></div>"""
-
- image = gr_show(False)
- preview_visibility = gr_show(False)
-
- if opts.show_progress_every_n_steps != 0:
- shared.state.set_current_image()
- image = shared.state.current_image
-
- if image is None:
- image = gr.update(value=None)
- else:
- preview_visibility = gr_show(True)
-
- if shared.state.textinfo is not None:
- textinfo_result = gr.HTML.update(value=shared.state.textinfo, visible=True)
- else:
- textinfo_result = gr_show(False)
-
- return f"<span id='{id_part}_progress_span' style='display: none'>{time.time()}</span><p>{progressbar}</p>", preview_visibility, image, textinfo_result
-
-
-def check_progress_call_initial(id_part):
- shared.state.job_count = -1
- shared.state.current_latent = None
- shared.state.current_image = None
- shared.state.textinfo = None
- shared.state.time_start = time.time()
- shared.state.time_left_force_display = False
-
- return check_progress_call(id_part)
-
-
def visit(x, func, path=""):
if hasattr(x, 'children'):
for c in x.children:
@@ -456,25 +383,10 @@ def create_toprow(is_img2img): return prompt, prompt_style, negative_prompt, prompt_style2, submit, button_interrogate, button_deepbooru, prompt_style_apply, save_style, paste, token_counter, token_button
-def setup_progressbar(progressbar, preview, id_part, textinfo=None):
- if textinfo is None:
- textinfo = gr.HTML(visible=False)
+def setup_progressbar(*args, **kwargs):
+ import modules.ui_progress
- check_progress = gr.Button('Check progress', elem_id=f"{id_part}_check_progress", visible=False)
- check_progress.click(
- fn=lambda: check_progress_call(id_part),
- show_progress=False,
- inputs=[],
- outputs=[progressbar, preview, preview, textinfo],
- )
-
- check_progress_initial = gr.Button('Check progress (first)', elem_id=f"{id_part}_check_progress_initial", visible=False)
- check_progress_initial.click(
- fn=lambda: check_progress_call_initial(id_part),
- show_progress=False,
- inputs=[],
- outputs=[progressbar, preview, preview, textinfo],
- )
+ modules.ui_progress.setup_progressbar(*args, **kwargs)
def apply_setting(key, value):
diff --git a/modules/ui_progress.py b/modules/ui_progress.py index 9b9081b5..592fda55 100644 --- a/modules/ui_progress.py +++ b/modules/ui_progress.py @@ -1,165 +1,10 @@ -import html
-import json
-import math
-import mimetypes
-import os
-import platform
-import random
-import subprocess as sp
-import sys
-import tempfile
import time
-import traceback
-from functools import partial, reduce
import gradio as gr
-import gradio.routes
-import gradio.utils
-import numpy as np
-from PIL import Image, PngImagePlugin
-from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_gradio_call
-from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru
-from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML
-from modules.paths import script_path
+from modules.shared import opts
-from modules.shared import opts, cmd_opts, restricted_opts
-
-import modules.codeformer_model
-import modules.generation_parameters_copypaste as parameters_copypaste
-import modules.gfpgan_model
-import modules.hypernetworks.ui
-import modules.scripts
import modules.shared as shared
-import modules.styles
-import modules.textual_inversion.ui
-from modules import prompt_parser
-from modules.images import save_image
-from modules.sd_hijack import model_hijack
-from modules.sd_samplers import samplers, samplers_for_img2img
-from modules.textual_inversion import textual_inversion
-import modules.hypernetworks.ui
-from modules.generation_parameters_copypaste import image_from_url_text
-
-# this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser 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'
-
-if cmd_opts.ngrok is not None:
- import modules.ngrok as ngrok
- print('ngrok authtoken detected, trying to connect...')
- ngrok.connect(
- cmd_opts.ngrok,
- cmd_opts.port if cmd_opts.port is not None else 7860,
- cmd_opts.ngrok_region
- )
-
-
-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..." }
-.wrap .z-20 svg { display:none!important; }
-.wrap .z-20::before { content:"Loading..." }
-.progress-bar { display:none!important; }
-.meta-text { display:none!important; }
-.meta-text-center { 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' # ♻️
-paste_symbol = '\u2199\ufe0f' # ↙
-folder_symbol = '\U0001f4c2' # 📂
-refresh_symbol = '\U0001f504' # 🔄
-save_style_symbol = '\U0001f4be' # 💾
-apply_style_symbol = '\U0001f4cb' # 📋
-clear_prompt_symbol = '\U0001F5D1' # 🗑️
-
-
-def plaintext_to_html(text):
- text = "<p>" + "<br>\n".join([f"{html.escape(x)}" for x in text.split('\n')]) + "</p>"
- return text
-
-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, do_make_zip, index):
- import csv
- filenames = []
- fullfns = []
-
- #quick dictionary to class object conversion. Its necessary due apply_filename_pattern requiring it
- class MyObject:
- def __init__(self, d=None):
- if d is not None:
- for key, value in d.items():
- setattr(self, key, value)
-
- data = json.loads(js_data)
-
- p = MyObject(data)
- path = opts.outdir_save
- save_to_dirs = opts.use_save_to_dirs_for_ui
- extension: str = opts.samples_format
- start_index = 0
-
- if index > -1 and opts.save_selected_only and (index >= data["index_of_first_image"]): # ensures we are looking at a specific non-grid picture, and we have save_selected_only
-
- images = [images[index]]
- start_index = index
-
- os.makedirs(opts.outdir_save, exist_ok=True)
-
- 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"])
-
- for image_index, filedata in enumerate(images, start_index):
- image = image_from_url_text(filedata)
-
- is_grid = image_index < p.index_of_first_image
- i = 0 if is_grid else (image_index - p.index_of_first_image)
-
- fullfn, txt_fullfn = save_image(image, path, "", seed=p.all_seeds[i], prompt=p.all_prompts[i], extension=extension, info=p.infotexts[image_index], grid=is_grid, p=p, save_to_dirs=save_to_dirs)
-
- filename = os.path.relpath(fullfn, path)
- filenames.append(filename)
- fullfns.append(fullfn)
- if txt_fullfn:
- filenames.append(os.path.basename(txt_fullfn))
- fullfns.append(txt_fullfn)
-
- writer.writerow([data["prompt"], data["seed"], data["width"], data["height"], data["sampler_name"], data["cfg_scale"], data["steps"], filenames[0], data["negative_prompt"]])
-
- # Make Zip
- if do_make_zip:
- zip_filepath = os.path.join(path, "images.zip")
-
- from zipfile import ZipFile
- with ZipFile(zip_filepath, "w") as zip_file:
- for i in range(len(fullfns)):
- with open(fullfns[i], mode="rb") as f:
- zip_file.writestr(filenames[i], f.read())
- fullfns.insert(0, zip_filepath)
-
- return gr.File.update(value=fullfns, visible=True), plaintext_to_html(f"Saved: {filenames[0]}")
def calc_time_left(progress, threshold, label, force_display, show_eta):
@@ -182,7 +27,7 @@ def calc_time_left(progress, threshold, label, force_display, show_eta): def check_progress_call(id_part):
if shared.state.job_count == 0:
- return "", gr_show(False), gr_show(False), gr_show(False)
+ return "", gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)
progress = 0
@@ -204,8 +49,8 @@ def check_progress_call(id_part): if opts.show_progressbar:
progressbar = f"""<div class='progressDiv'><div class='progress' style="overflow:visible;width:{progress * 100}%;white-space:nowrap;">{" " * 2 + str(int(progress*100))+"%" + time_left if show_eta else ""}</div></div>"""
- image = gr_show(False)
- preview_visibility = gr_show(False)
+ image = gr.update(visible=False)
+ preview_visibility = gr.update(visible=False)
if opts.show_progress_every_n_steps != 0:
shared.state.set_current_image()
@@ -214,12 +59,12 @@ def check_progress_call(id_part): if image is None:
image = gr.update(value=None)
else:
- preview_visibility = gr_show(True)
+ preview_visibility = gr.update(visible=True)
if shared.state.textinfo is not None:
textinfo_result = gr.HTML.update(value=shared.state.textinfo, visible=True)
else:
- textinfo_result = gr_show(False)
+ textinfo_result = gr.update(visible=False)
return f"<span id='{id_part}_progress_span' style='display: none'>{time.time()}</span><p>{progressbar}</p>", preview_visibility, image, textinfo_result
@@ -235,227 +80,6 @@ def check_progress_call_initial(id_part): return check_progress_call(id_part)
-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() for x in range(4)]
-
- 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)
-
- return [gr.Dropdown.update(visible=True, choices=list(shared.prompt_styles.styles)) for _ in range(4)]
-
-
-def calc_resolution_hires(enable, width, height, hr_scale, hr_resize_x, hr_resize_y):
- from modules import processing, devices
-
- if not enable:
- return ""
-
- p = processing.StableDiffusionProcessingTxt2Img(width=width, height=height, enable_hr=True, hr_scale=hr_scale, hr_resize_x=hr_resize_x, hr_resize_y=hr_resize_y)
-
- with devices.autocast():
- p.init([""], [0], [0])
-
- return f"resize: from <span class='resolution'>{p.width}x{p.height}</span> to <span class='resolution'>{p.hr_resize_x or p.hr_upscale_to_x}x{p.hr_resize_y or p.hr_upscale_to_y}</span>"
-
-
-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.convert("RGB"))
-
- return gr_show(True) if prompt is None else prompt
-
-
-def interrogate_deepbooru(image):
- prompt = deepbooru.model.tag(image)
- return gr_show(True) if prompt is None else prompt
-
-
-def create_seed_inputs(target_interface):
- with FormRow(elem_id=target_interface + '_seed_row'):
- seed = (gr.Textbox if cmd_opts.use_textbox_seed else gr.Number)(label='Seed', value=-1, elem_id=target_interface + '_seed')
- seed.style(container=False)
- random_seed = gr.Button(random_symbol, elem_id=target_interface + '_random_seed')
- reuse_seed = gr.Button(reuse_symbol, elem_id=target_interface + '_reuse_seed')
-
- with gr.Group(elem_id=target_interface + '_subseed_show_box'):
- seed_checkbox = gr.Checkbox(label='Extra', elem_id=target_interface + '_subseed_show', value=False)
-
- # Components to show/hide based on the 'Extra' checkbox
- seed_extras = []
-
- with FormRow(visible=False, elem_id=target_interface + '_subseed_row') as seed_extra_row_1:
- seed_extras.append(seed_extra_row_1)
- subseed = gr.Number(label='Variation seed', value=-1, elem_id=target_interface + '_subseed')
- subseed.style(container=False)
- random_subseed = gr.Button(random_symbol, elem_id=target_interface + '_random_subseed')
- reuse_subseed = gr.Button(reuse_symbol, elem_id=target_interface + '_reuse_subseed')
- subseed_strength = gr.Slider(label='Variation strength', value=0.0, minimum=0, maximum=1, step=0.01, elem_id=target_interface + '_subseed_strength')
-
- with FormRow(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=8, label="Resize seed from width", value=0, elem_id=target_interface + '_seed_resize_from_w')
- seed_resize_from_h = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from height", value=0, elem_id=target_interface + '_seed_resize_from_h')
-
- 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, seed_checkbox
-
-
-
-def connect_clear_prompt(button):
- """Given clear button, prompt, and token_counter objects, setup clear prompt button click event"""
- button.click(
- _js="clear_prompt",
- fn=None,
- inputs=[],
- outputs=[],
- )
-
-
-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 update_token_counter(text, steps):
- try:
- _, prompt_flat_list, _ = prompt_parser.get_multicond_prompt_list([text])
- prompt_schedules = prompt_parser.get_learned_conditioning_prompt_schedules(prompt_flat_list, steps)
-
- except Exception:
- # a parsing error can happen here during typing, and we don't want to bother the user with
- # messages related to it in console
- prompt_schedules = [[[steps, text]]]
-
- flat_prompts = reduce(lambda list1, list2: list1+list2, prompt_schedules)
- prompts = [prompt_text for step, prompt_text in flat_prompts]
- token_count, max_length = max([model_hijack.get_prompt_lengths(prompt) for prompt in prompts], key=lambda args: args[0])
- style_class = ' class="red"' if (token_count > max_length) else ""
- return f"<span {style_class}>{token_count}/{max_length}</span>"
-
-
-def create_toprow(is_img2img):
- id_part = "img2img" if is_img2img else "txt2img"
-
- with gr.Row(elem_id="toprow"):
- with gr.Column(scale=6):
- with gr.Row():
- with gr.Column(scale=80):
- with gr.Row():
- prompt = gr.Textbox(label="Prompt", elem_id=f"{id_part}_prompt", show_label=False, lines=2,
- placeholder="Prompt (press Ctrl+Enter or Alt+Enter to generate)"
- )
-
- with gr.Row():
- with gr.Column(scale=80):
- with gr.Row():
- negative_prompt = gr.Textbox(label="Negative prompt", elem_id=f"{id_part}_neg_prompt", show_label=False, lines=2,
- placeholder="Negative prompt (press Ctrl+Enter or Alt+Enter to generate)"
- )
-
- with gr.Column(scale=1, elem_id="roll_col"):
- paste = gr.Button(value=paste_symbol, elem_id="paste")
- save_style = gr.Button(value=save_style_symbol, elem_id="style_create")
- prompt_style_apply = gr.Button(value=apply_style_symbol, elem_id="style_apply")
- clear_prompt_button = gr.Button(value=clear_prompt_symbol, elem_id=f"{id_part}_clear_prompt")
- token_counter = gr.HTML(value="<span></span>", elem_id=f"{id_part}_token_counter")
- token_button = gr.Button(visible=False, elem_id=f"{id_part}_token_button")
-
- clear_prompt_button.click(
- fn=lambda *x: x,
- _js="confirm_clear_prompt",
- inputs=[prompt, negative_prompt],
- outputs=[prompt, negative_prompt],
- )
-
- button_interrogate = None
- button_deepbooru = None
- if is_img2img:
- with gr.Column(scale=1, elem_id="interrogate_col"):
- button_interrogate = gr.Button('Interrogate\nCLIP', elem_id="interrogate")
- button_deepbooru = gr.Button('Interrogate\nDeepBooru', elem_id="deepbooru")
-
- with gr.Column(scale=1):
- with gr.Row():
- skip = gr.Button('Skip', elem_id=f"{id_part}_skip")
- interrupt = gr.Button('Interrupt', elem_id=f"{id_part}_interrupt")
- submit = gr.Button('Generate', elem_id=f"{id_part}_generate", variant='primary')
-
- skip.click(
- fn=lambda: shared.state.skip(),
- inputs=[],
- outputs=[],
- )
-
- interrupt.click(
- fn=lambda: shared.state.interrupt(),
- inputs=[],
- outputs=[],
- )
-
- with gr.Row():
- with gr.Column(scale=1, elem_id="style_pos_col"):
- prompt_style = gr.Dropdown(label="Style 1", elem_id=f"{id_part}_style_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys())))
-
- with gr.Column(scale=1, elem_id="style_neg_col"):
- prompt_style2 = gr.Dropdown(label="Style 2", elem_id=f"{id_part}_style2_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys())))
-
- return prompt, prompt_style, negative_prompt, prompt_style2, submit, button_interrogate, button_deepbooru, prompt_style_apply, save_style, paste, token_counter, token_button
-
-
def setup_progressbar(progressbar, preview, id_part, textinfo=None):
if textinfo is None:
textinfo = gr.HTML(visible=False)
@@ -475,1454 +99,3 @@ def setup_progressbar(progressbar, preview, id_part, textinfo=None): inputs=[],
outputs=[progressbar, preview, preview, textinfo],
)
-
-
-def apply_setting(key, value):
- if value is None:
- return gr.update()
-
- if shared.cmd_opts.freeze_settings:
- return gr.update()
-
- # dont allow model to be swapped when model hash exists in prompt
- if key == "sd_model_checkpoint" and opts.disable_weights_auto_swap:
- return gr.update()
-
- if key == "sd_model_checkpoint":
- ckpt_info = sd_models.get_closet_checkpoint_match(value)
-
- if ckpt_info is not None:
- value = ckpt_info.title
- else:
- return gr.update()
-
- comp_args = opts.data_labels[key].component_args
- if comp_args and isinstance(comp_args, dict) and comp_args.get('visible') is False:
- return
-
- valtype = type(opts.data_labels[key].default)
- oldval = opts.data.get(key, None)
- opts.data[key] = valtype(value) if valtype != type(None) else value
- if oldval != value and opts.data_labels[key].onchange is not None:
- opts.data_labels[key].onchange()
-
- opts.save(shared.config_filename)
- return value
-
-
-def update_generation_info(args):
- generation_info, html_info, img_index = args
- try:
- generation_info = json.loads(generation_info)
- if img_index < 0 or img_index >= len(generation_info["infotexts"]):
- return html_info
- return plaintext_to_html(generation_info["infotexts"][img_index])
- except Exception:
- pass
- # if the json parse or anything else fails, just return the old html_info
- return html_info
-
-
-def create_refresh_button(refresh_component, refresh_method, refreshed_args, elem_id):
- def refresh():
- refresh_method()
- args = refreshed_args() if callable(refreshed_args) else refreshed_args
-
- for k, v in args.items():
- setattr(refresh_component, k, v)
-
- return gr.update(**(args or {}))
-
- refresh_button = ToolButton(value=refresh_symbol, elem_id=elem_id)
- refresh_button.click(
- fn=refresh,
- inputs=[],
- outputs=[refresh_component]
- )
- return refresh_button
-
-
-def create_output_panel(tabname, outdir):
- def open_folder(f):
- if not os.path.exists(f):
- print(f'Folder "{f}" does not exist. After you create an image, the folder will be created.')
- return
- elif not os.path.isdir(f):
- print(f"""
-WARNING
-An open_folder request was made with an argument that is not a folder.
-This could be an error or a malicious attempt to run code on your computer.
-Requested path was: {f}
-""", file=sys.stderr)
- return
-
- if not shared.cmd_opts.hide_ui_dir_config:
- path = os.path.normpath(f)
- if platform.system() == "Windows":
- os.startfile(path)
- elif platform.system() == "Darwin":
- sp.Popen(["open", path])
- elif "microsoft-standard-WSL2" in platform.uname().release:
- sp.Popen(["wsl-open", path])
- else:
- sp.Popen(["xdg-open", path])
-
- with gr.Column(variant='panel'):
- with gr.Group():
- result_gallery = gr.Gallery(label='Output', show_label=False, elem_id=f"{tabname}_gallery").style(grid=4)
-
- generation_info = None
- with gr.Column():
- with gr.Row(elem_id=f"image_buttons_{tabname}"):
- open_folder_button = gr.Button(folder_symbol, elem_id="hidden_element" if shared.cmd_opts.hide_ui_dir_config else f'open_folder_{tabname}')
-
- if tabname != "extras":
- save = gr.Button('Save', elem_id=f'save_{tabname}')
- save_zip = gr.Button('Zip', elem_id=f'save_zip_{tabname}')
-
- buttons = parameters_copypaste.create_buttons(["img2img", "inpaint", "extras"])
-
- open_folder_button.click(
- fn=lambda: open_folder(opts.outdir_samples or outdir),
- inputs=[],
- outputs=[],
- )
-
- if tabname != "extras":
- with gr.Row():
- download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False, elem_id=f'download_files_{tabname}')
-
- with gr.Group():
- html_info = gr.HTML(elem_id=f'html_info_{tabname}')
- html_log = gr.HTML(elem_id=f'html_log_{tabname}')
-
- generation_info = gr.Textbox(visible=False, elem_id=f'generation_info_{tabname}')
- if tabname == 'txt2img' or tabname == 'img2img':
- generation_info_button = gr.Button(visible=False, elem_id=f"{tabname}_generation_info_button")
- generation_info_button.click(
- fn=update_generation_info,
- _js="(x, y) => [x, y, selected_gallery_index()]",
- inputs=[generation_info, html_info],
- outputs=[html_info],
- preprocess=False
- )
-
- save.click(
- fn=wrap_gradio_call(save_files),
- _js="(x, y, z, w) => [x, y, false, selected_gallery_index()]",
- inputs=[
- generation_info,
- result_gallery,
- html_info,
- html_info,
- ],
- outputs=[
- download_files,
- html_log,
- ]
- )
-
- save_zip.click(
- fn=wrap_gradio_call(save_files),
- _js="(x, y, z, w) => [x, y, true, selected_gallery_index()]",
- inputs=[
- generation_info,
- result_gallery,
- html_info,
- html_info,
- ],
- outputs=[
- download_files,
- html_log,
- ]
- )
-
- else:
- html_info_x = gr.HTML(elem_id=f'html_info_x_{tabname}')
- html_info = gr.HTML(elem_id=f'html_info_{tabname}')
- html_log = gr.HTML(elem_id=f'html_log_{tabname}')
-
- parameters_copypaste.bind_buttons(buttons, result_gallery, "txt2img" if tabname == "txt2img" else None)
- return result_gallery, generation_info if tabname != "extras" else html_info_x, html_info, html_log
-
-
-def create_sampler_and_steps_selection(choices, tabname):
- if opts.samplers_in_dropdown:
- with FormRow(elem_id=f"sampler_selection_{tabname}"):
- sampler_index = gr.Dropdown(label='Sampling method', elem_id=f"{tabname}_sampling", choices=[x.name for x in choices], value=choices[0].name, type="index")
- steps = gr.Slider(minimum=1, maximum=150, step=1, elem_id=f"{tabname}_steps", label="Sampling steps", value=20)
- else:
- with FormGroup(elem_id=f"sampler_selection_{tabname}"):
- steps = gr.Slider(minimum=1, maximum=150, step=1, elem_id=f"{tabname}_steps", label="Sampling steps", value=20)
- sampler_index = gr.Radio(label='Sampling method', elem_id=f"{tabname}_sampling", choices=[x.name for x in choices], value=choices[0].name, type="index")
-
- return steps, sampler_index
-
-
-def ordered_ui_categories():
- user_order = {x.strip(): i for i, x in enumerate(shared.opts.ui_reorder.split(","))}
-
- for i, category in sorted(enumerate(shared.ui_reorder_categories), key=lambda x: user_order.get(x[1], x[0] + 1000)):
- yield category
-
-
-def create_ui():
- import modules.img2img
- import modules.txt2img
-
- reload_javascript()
-
- parameters_copypaste.reset()
-
- modules.scripts.scripts_current = modules.scripts.scripts_txt2img
- modules.scripts.scripts_txt2img.initialize_scripts(is_img2img=False)
-
- with gr.Blocks(analytics_enabled=False) as txt2img_interface:
- txt2img_prompt, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, _,txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, token_counter, token_button = create_toprow(is_img2img=False)
-
- dummy_component = gr.Label(visible=False)
- txt_prompt_img = gr.File(label="", elem_id="txt2img_prompt_image", file_count="single", type="bytes", visible=False)
-
- with gr.Row(elem_id='txt2img_progress_row'):
- with gr.Column(scale=1):
- pass
-
- with gr.Column(scale=1):
- progressbar = gr.HTML(elem_id="txt2img_progressbar")
- txt2img_preview = gr.Image(elem_id='txt2img_preview', visible=False)
- setup_progressbar(progressbar, txt2img_preview, 'txt2img')
-
- with gr.Row().style(equal_height=False):
- with gr.Column(variant='panel', elem_id="txt2img_settings"):
- for category in ordered_ui_categories():
- if category == "sampler":
- steps, sampler_index = create_sampler_and_steps_selection(samplers, "txt2img")
-
- elif category == "dimensions":
- with FormRow():
- with gr.Column(elem_id="txt2img_column_size", scale=4):
- width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="txt2img_width")
- height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="txt2img_height")
-
- if opts.dimensions_and_batch_together:
- with gr.Column(elem_id="txt2img_column_batch"):
- batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="txt2img_batch_count")
- batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="txt2img_batch_size")
-
- elif category == "cfg":
- cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0, elem_id="txt2img_cfg_scale")
-
- elif category == "seed":
- seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs('txt2img')
-
- elif category == "checkboxes":
- with FormRow(elem_id="txt2img_checkboxes"):
- restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="txt2img_restore_faces")
- tiling = gr.Checkbox(label='Tiling', value=False, elem_id="txt2img_tiling")
- enable_hr = gr.Checkbox(label='Hires. fix', value=False, elem_id="txt2img_enable_hr")
- hr_final_resolution = FormHTML(value="", elem_id="txtimg_hr_finalres", label="Upscaled resolution", interactive=False)
-
- elif category == "hires_fix":
- with FormGroup(visible=False, elem_id="txt2img_hires_fix") as hr_options:
- with FormRow(elem_id="txt2img_hires_fix_row1"):
- hr_upscaler = gr.Dropdown(label="Upscaler", elem_id="txt2img_hr_upscaler", choices=[*shared.latent_upscale_modes, *[x.name for x in shared.sd_upscalers]], value=shared.latent_upscale_default_mode)
- hr_second_pass_steps = gr.Slider(minimum=0, maximum=150, step=1, label='Hires steps', value=0, elem_id="txt2img_hires_steps")
- denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7, elem_id="txt2img_denoising_strength")
-
- with FormRow(elem_id="txt2img_hires_fix_row2"):
- hr_scale = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label="Upscale by", value=2.0, elem_id="txt2img_hr_scale")
- hr_resize_x = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize width to", value=0, elem_id="txt2img_hr_resize_x")
- hr_resize_y = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize height to", value=0, elem_id="txt2img_hr_resize_y")
-
- elif category == "batch":
- if not opts.dimensions_and_batch_together:
- with FormRow(elem_id="txt2img_column_batch"):
- batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="txt2img_batch_count")
- batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="txt2img_batch_size")
-
- elif category == "scripts":
- with FormGroup(elem_id="txt2img_script_container"):
- custom_inputs = modules.scripts.scripts_txt2img.setup_ui()
-
- hr_resolution_preview_inputs = [enable_hr, width, height, hr_scale, hr_resize_x, hr_resize_y]
- for input in hr_resolution_preview_inputs:
- input.change(
- fn=calc_resolution_hires,
- inputs=hr_resolution_preview_inputs,
- outputs=[hr_final_resolution],
- show_progress=False,
- )
- input.change(
- None,
- _js="onCalcResolutionHires",
- inputs=hr_resolution_preview_inputs,
- outputs=[],
- show_progress=False,
- )
-
- txt2img_gallery, generation_info, html_info, html_log = create_output_panel("txt2img", opts.outdir_txt2img_samples)
- parameters_copypaste.bind_buttons({"txt2img": txt2img_paste}, None, txt2img_prompt)
-
- 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=wrap_gradio_gpu_call(modules.txt2img.txt2img, extra_outputs=[None, '', '']),
- _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, seed_checkbox,
- height,
- width,
- enable_hr,
- denoising_strength,
- hr_scale,
- hr_upscaler,
- hr_second_pass_steps,
- hr_resize_x,
- hr_resize_y,
- ] + custom_inputs,
-
- outputs=[
- txt2img_gallery,
- generation_info,
- html_info,
- html_log,
- ],
- show_progress=False,
- )
-
- txt2img_prompt.submit(**txt2img_args)
- submit.click(**txt2img_args)
-
- txt_prompt_img.change(
- fn=modules.images.image_data,
- inputs=[
- txt_prompt_img
- ],
- outputs=[
- txt2img_prompt,
- txt_prompt_img
- ]
- )
-
- enable_hr.change(
- fn=lambda x: gr_show(x),
- inputs=[enable_hr],
- outputs=[hr_options],
- show_progress = False,
- )
-
- txt2img_paste_fields = [
- (txt2img_prompt, "Prompt"),
- (txt2img_negative_prompt, "Negative prompt"),
- (steps, "Steps"),
- (sampler_index, "Sampler"),
- (restore_faces, "Face restoration"),
- (cfg_scale, "CFG scale"),
- (seed, "Seed"),
- (width, "Size-1"),
- (height, "Size-2"),
- (batch_size, "Batch size"),
- (subseed, "Variation seed"),
- (subseed_strength, "Variation seed strength"),
- (seed_resize_from_w, "Seed resize from-1"),
- (seed_resize_from_h, "Seed resize from-2"),
- (denoising_strength, "Denoising strength"),
- (enable_hr, lambda d: "Denoising strength" in d),
- (hr_options, lambda d: gr.Row.update(visible="Denoising strength" in d)),
- (hr_scale, "Hires upscale"),
- (hr_upscaler, "Hires upscaler"),
- (hr_second_pass_steps, "Hires steps"),
- (hr_resize_x, "Hires resize-1"),
- (hr_resize_y, "Hires resize-2"),
- *modules.scripts.scripts_txt2img.infotext_fields
- ]
- parameters_copypaste.add_paste_fields("txt2img", None, txt2img_paste_fields)
-
- txt2img_preview_params = [
- txt2img_prompt,
- txt2img_negative_prompt,
- steps,
- sampler_index,
- cfg_scale,
- seed,
- width,
- height,
- ]
-
- token_button.click(fn=wrap_queued_call(update_token_counter), inputs=[txt2img_prompt, steps], outputs=[token_counter])
-
- modules.scripts.scripts_current = modules.scripts.scripts_img2img
- modules.scripts.scripts_img2img.initialize_scripts(is_img2img=True)
-
- with gr.Blocks(analytics_enabled=False) as img2img_interface:
- img2img_prompt, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, img2img_paste,token_counter, token_button = create_toprow(is_img2img=True)
-
- with gr.Row(elem_id='img2img_progress_row'):
- img2img_prompt_img = gr.File(label="", elem_id="img2img_prompt_image", file_count="single", type="bytes", visible=False)
-
- with gr.Column(scale=1):
- pass
-
- with gr.Column(scale=1):
- progressbar = gr.HTML(elem_id="img2img_progressbar")
- img2img_preview = gr.Image(elem_id='img2img_preview', visible=False)
- setup_progressbar(progressbar, img2img_preview, 'img2img')
-
- with FormRow().style(equal_height=False):
- with gr.Column(variant='panel', elem_id="img2img_settings"):
-
- with gr.Tabs(elem_id="mode_img2img") as tabs_img2img_mode:
- with gr.TabItem('img2img', id='img2img', elem_id="img2img_img2img_tab"):
- init_img = gr.Image(label="Image for img2img", elem_id="img2img_image", show_label=False, source="upload", interactive=True, type="pil", tool=cmd_opts.gradio_img2img_tool, image_mode="RGBA").style(height=480)
-
- with gr.TabItem('Inpaint', id='inpaint', elem_id="img2img_inpaint_tab"):
- init_img_with_mask = gr.Image(label="Image for inpainting with mask", show_label=False, elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool=cmd_opts.gradio_inpaint_tool, image_mode="RGBA").style(height=480)
- init_img_with_mask_orig = gr.State(None)
-
- use_color_sketch = cmd_opts.gradio_inpaint_tool == "color-sketch"
- if use_color_sketch:
- def update_orig(image, state):
- if image is not None:
- same_size = state is not None and state.size == image.size
- has_exact_match = np.any(np.all(np.array(image) == np.array(state), axis=-1))
- edited = same_size and has_exact_match
- return image if not edited or state is None else state
-
- init_img_with_mask.change(update_orig, [init_img_with_mask, init_img_with_mask_orig], init_img_with_mask_orig)
-
- init_img_inpaint = gr.Image(label="Image for img2img", show_label=False, source="upload", interactive=True, type="pil", visible=False, elem_id="img_inpaint_base")
- init_mask_inpaint = gr.Image(label="Mask", source="upload", interactive=True, type="pil", visible=False, elem_id="img_inpaint_mask")
-
- with FormRow():
- mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=4, elem_id="img2img_mask_blur")
- mask_alpha = gr.Slider(label="Mask transparency", interactive=use_color_sketch, visible=use_color_sketch, elem_id="img2img_mask_alpha")
-
- with FormRow():
- mask_mode = gr.Radio(label="Mask source", choices=["Draw mask", "Upload mask"], type="index", value="Draw mask", elem_id="mask_mode")
- inpainting_mask_invert = gr.Radio(label='Mask mode', choices=['Inpaint masked', 'Inpaint not masked'], value='Inpaint masked', type="index", elem_id="img2img_mask_mode")
-
- with FormRow():
- inpainting_fill = gr.Radio(label='Masked content', choices=['fill', 'original', 'latent noise', 'latent nothing'], value='original', type="index", elem_id="img2img_inpainting_fill")
-
- with FormRow():
- with gr.Column():
- inpaint_full_res = gr.Radio(label="Inpaint area", choices=["Whole picture", "Only masked"], type="index", value="Whole picture", elem_id="img2img_inpaint_full_res")
-
- with gr.Column(scale=4):
- inpaint_full_res_padding = gr.Slider(label='Only masked padding, pixels', minimum=0, maximum=256, step=4, value=32, elem_id="img2img_inpaint_full_res_padding")
-
- with gr.TabItem('Batch img2img', id='batch', elem_id="img2img_batch_tab"):
- hidden = '<br>Disabled when launched with --hide-ui-dir-config.' if shared.cmd_opts.hide_ui_dir_config else ''
- gr.HTML(f"<p class=\"text-gray-500\">Process images in a directory on the same machine where the server is running.<br>Use an empty output directory to save pictures normally instead of writing to the output directory.{hidden}</p>")
- img2img_batch_input_dir = gr.Textbox(label="Input directory", **shared.hide_dirs, elem_id="img2img_batch_input_dir")
- img2img_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs, elem_id="img2img_batch_output_dir")
-
- with FormRow():
- resize_mode = gr.Radio(label="Resize mode", elem_id="resize_mode", choices=["Just resize", "Crop and resize", "Resize and fill", "Just resize (latent upscale)"], type="index", value="Just resize")
-
- for category in ordered_ui_categories():
- if category == "sampler":
- steps, sampler_index = create_sampler_and_steps_selection(samplers_for_img2img, "img2img")
-
- elif category == "dimensions":
- with FormRow():
- with gr.Column(elem_id="img2img_column_size", scale=4):
- width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="img2img_width")
- height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="img2img_height")
-
- if opts.dimensions_and_batch_together:
- with gr.Column(elem_id="img2img_column_batch"):
- batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="img2img_batch_count")
- batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="img2img_batch_size")
-
- elif category == "cfg":
- with FormGroup():
- cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0, elem_id="img2img_cfg_scale")
- denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.75, elem_id="img2img_denoising_strength")
-
- elif category == "seed":
- seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs('img2img')
-
- elif category == "checkboxes":
- with FormRow(elem_id="img2img_checkboxes"):
- restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="img2img_restore_faces")
- tiling = gr.Checkbox(label='Tiling', value=False, elem_id="img2img_tiling")
-
- elif category == "batch":
- if not opts.dimensions_and_batch_together:
- with FormRow(elem_id="img2img_column_batch"):
- batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="img2img_batch_count")
- batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="img2img_batch_size")
-
- elif category == "scripts":
- with FormGroup(elem_id="img2img_script_container"):
- custom_inputs = modules.scripts.scripts_img2img.setup_ui()
-
- img2img_gallery, generation_info, html_info, html_log = create_output_panel("img2img", opts.outdir_img2img_samples)
- parameters_copypaste.bind_buttons({"img2img": img2img_paste}, None, img2img_prompt)
-
- 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)
-
- img2img_prompt_img.change(
- fn=modules.images.image_data,
- inputs=[
- img2img_prompt_img
- ],
- outputs=[
- img2img_prompt,
- img2img_prompt_img
- ]
- )
-
- mask_mode.change(
- lambda mode, img: {
- init_img_with_mask: gr_show(mode == 0),
- init_img_inpaint: gr_show(mode == 1),
- init_mask_inpaint: gr_show(mode == 1),
- },
- inputs=[mask_mode, init_img_with_mask],
- outputs=[
- init_img_with_mask,
- init_img_inpaint,
- init_mask_inpaint,
- ],
- )
-
- img2img_args = dict(
- fn=wrap_gradio_gpu_call(modules.img2img.img2img, extra_outputs=[None, '', '']),
- _js="submit_img2img",
- inputs=[
- dummy_component,
- img2img_prompt,
- img2img_negative_prompt,
- img2img_prompt_style,
- img2img_prompt_style2,
- init_img,
- init_img_with_mask,
- init_img_with_mask_orig,
- init_img_inpaint,
- init_mask_inpaint,
- mask_mode,
- steps,
- sampler_index,
- mask_blur,
- mask_alpha,
- inpainting_fill,
- restore_faces,
- tiling,
- batch_count,
- batch_size,
- cfg_scale,
- denoising_strength,
- seed,
- subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox,
- height,
- width,
- resize_mode,
- inpaint_full_res,
- inpaint_full_res_padding,
- inpainting_mask_invert,
- img2img_batch_input_dir,
- img2img_batch_output_dir,
- ] + custom_inputs,
- outputs=[
- img2img_gallery,
- generation_info,
- html_info,
- html_log,
- ],
- show_progress=False,
- )
-
- img2img_prompt.submit(**img2img_args)
- submit.click(**img2img_args)
-
- img2img_interrogate.click(
- fn=interrogate,
- inputs=[init_img],
- outputs=[img2img_prompt],
- )
-
- img2img_deepbooru.click(
- fn=interrogate_deepbooru,
- inputs=[init_img],
- 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)]
- style_js_funcs = ["update_txt2img_tokens", "update_img2img_tokens"]
-
- 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), js_func in zip([txt2img_prompt_style_apply, img2img_prompt_style_apply], prompts, style_dropdowns, style_js_funcs):
- button.click(
- fn=apply_styles,
- _js=js_func,
- inputs=[prompt, negative_prompt, style1, style2],
- outputs=[prompt, negative_prompt, style1, style2],
- )
-
- token_button.click(fn=update_token_counter, inputs=[img2img_prompt, steps], outputs=[token_counter])
-
- img2img_paste_fields = [
- (img2img_prompt, "Prompt"),
- (img2img_negative_prompt, "Negative prompt"),
- (steps, "Steps"),
- (sampler_index, "Sampler"),
- (restore_faces, "Face restoration"),
- (cfg_scale, "CFG scale"),
- (seed, "Seed"),
- (width, "Size-1"),
- (height, "Size-2"),
- (batch_size, "Batch size"),
- (subseed, "Variation seed"),
- (subseed_strength, "Variation seed strength"),
- (seed_resize_from_w, "Seed resize from-1"),
- (seed_resize_from_h, "Seed resize from-2"),
- (denoising_strength, "Denoising strength"),
- (mask_blur, "Mask blur"),
- *modules.scripts.scripts_img2img.infotext_fields
- ]
- parameters_copypaste.add_paste_fields("img2img", init_img, img2img_paste_fields)
- parameters_copypaste.add_paste_fields("inpaint", init_img_with_mask, img2img_paste_fields)
-
- modules.scripts.scripts_current = None
-
- with gr.Blocks(analytics_enabled=False) as extras_interface:
- with gr.Row().style(equal_height=False):
- with gr.Column(variant='panel'):
- with gr.Tabs(elem_id="mode_extras"):
- with gr.TabItem('Single Image', elem_id="extras_single_tab"):
- extras_image = gr.Image(label="Source", source="upload", interactive=True, type="pil", elem_id="extras_image")
-
- with gr.TabItem('Batch Process', elem_id="extras_batch_process_tab"):
- image_batch = gr.File(label="Batch Process", file_count="multiple", interactive=True, type="file", elem_id="extras_image_batch")
-
- with gr.TabItem('Batch from Directory', elem_id="extras_batch_directory_tab"):
- extras_batch_input_dir = gr.Textbox(label="Input directory", **shared.hide_dirs, placeholder="A directory on the same machine where the server is running.", elem_id="extras_batch_input_dir")
- extras_batch_output_dir = gr.Textbox(label="Output directory", **shared.hide_dirs, placeholder="Leave blank to save images to the default path.", elem_id="extras_batch_output_dir")
- show_extras_results = gr.Checkbox(label='Show result images', value=True, elem_id="extras_show_extras_results")
-
- submit = gr.Button('Generate', elem_id="extras_generate", variant='primary')
-
- with gr.Tabs(elem_id="extras_resize_mode"):
- with gr.TabItem('Scale by', elem_id="extras_scale_by_tab"):
- upscaling_resize = gr.Slider(minimum=1.0, maximum=8.0, step=0.05, label="Resize", value=4, elem_id="extras_upscaling_resize")
- with gr.TabItem('Scale to', elem_id="extras_scale_to_tab"):
- with gr.Group():
- with gr.Row():
- upscaling_resize_w = gr.Number(label="Width", value=512, precision=0, elem_id="extras_upscaling_resize_w")
- upscaling_resize_h = gr.Number(label="Height", value=512, precision=0, elem_id="extras_upscaling_resize_h")
- upscaling_crop = gr.Checkbox(label='Crop to fit', value=True, elem_id="extras_upscaling_crop")
-
- with gr.Group():
- extras_upscaler_1 = gr.Radio(label='Upscaler 1', elem_id="extras_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', elem_id="extras_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, elem_id="extras_upscaler_2_visibility")
-
- 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, elem_id="extras_gfpgan_visibility")
-
- 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, elem_id="extras_codeformer_visibility")
- 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, elem_id="extras_codeformer_weight")
-
- with gr.Group():
- upscale_before_face_fix = gr.Checkbox(label='Upscale Before Restoring Faces', value=False, elem_id="extras_upscale_before_face_fix")
-
- result_images, html_info_x, html_info, html_log = create_output_panel("extras", opts.outdir_extras_samples)
-
- submit.click(
- fn=wrap_gradio_gpu_call(modules.extras.run_extras, extra_outputs=[None, '']),
- _js="get_extras_tab_index",
- inputs=[
- dummy_component,
- dummy_component,
- extras_image,
- image_batch,
- extras_batch_input_dir,
- extras_batch_output_dir,
- show_extras_results,
- gfpgan_visibility,
- codeformer_visibility,
- codeformer_weight,
- upscaling_resize,
- upscaling_resize_w,
- upscaling_resize_h,
- upscaling_crop,
- extras_upscaler_1,
- extras_upscaler_2,
- extras_upscaler_2_visibility,
- upscale_before_face_fix,
- ],
- outputs=[
- result_images,
- html_info_x,
- html_info,
- ]
- )
- parameters_copypaste.add_paste_fields("extras", extras_image, None)
-
- extras_image.change(
- fn=modules.extras.clear_cache,
- inputs=[], outputs=[]
- )
-
- with gr.Blocks(analytics_enabled=False) as pnginfo_interface:
- with gr.Row().style(equal_height=False):
- with gr.Column(variant='panel'):
- image = gr.Image(elem_id="pnginfo_image", label="Source", source="upload", interactive=True, type="pil")
-
- with gr.Column(variant='panel'):
- html = gr.HTML()
- generation_info = gr.Textbox(visible=False, elem_id="pnginfo_generation_info")
- html2 = gr.HTML()
- with gr.Row():
- buttons = parameters_copypaste.create_buttons(["txt2img", "img2img", "inpaint", "extras"])
- parameters_copypaste.bind_buttons(buttons, image, generation_info)
-
- image.change(
- fn=wrap_gradio_call(modules.extras.run_pnginfo),
- inputs=[image],
- outputs=[html, generation_info, html2],
- )
-
- with gr.Blocks(analytics_enabled=False) as modelmerger_interface:
- with gr.Row().style(equal_height=False):
- with gr.Column(variant='panel'):
- gr.HTML(value="<p>A merger of the two checkpoints will be generated in your <b>checkpoint</b> directory.</p>")
-
- with gr.Row():
- primary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_primary_model_name", label="Primary model (A)")
- create_refresh_button(primary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_A")
-
- secondary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_secondary_model_name", label="Secondary model (B)")
- create_refresh_button(secondary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_B")
-
- tertiary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_tertiary_model_name", label="Tertiary model (C)")
- create_refresh_button(tertiary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_C")
-
- custom_name = gr.Textbox(label="Custom Name (Optional)", elem_id="modelmerger_custom_name")
- interp_amount = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Multiplier (M) - set to 0 to get model A', value=0.3, elem_id="modelmerger_interp_amount")
- interp_method = gr.Radio(choices=["Weighted sum", "Add difference"], value="Weighted sum", label="Interpolation Method", elem_id="modelmerger_interp_method")
-
- with gr.Row():
- checkpoint_format = gr.Radio(choices=["ckpt", "safetensors"], value="ckpt", label="Checkpoint format", elem_id="modelmerger_checkpoint_format")
- save_as_half = gr.Checkbox(value=False, label="Save as float16", elem_id="modelmerger_save_as_half")
-
- modelmerger_merge = gr.Button(elem_id="modelmerger_merge", label="Merge", variant='primary')
-
- with gr.Column(variant='panel'):
- submit_result = gr.Textbox(elem_id="modelmerger_result", show_label=False)
-
- with gr.Blocks(analytics_enabled=False) as train_interface:
- with gr.Row().style(equal_height=False):
- gr.HTML(value="<p style='margin-bottom: 0.7em'>See <b><a href=\"https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Textual-Inversion\">wiki</a></b> for detailed explanation.</p>")
-
- with gr.Row().style(equal_height=False):
- with gr.Tabs(elem_id="train_tabs"):
-
- with gr.Tab(label="Create embedding"):
- new_embedding_name = gr.Textbox(label="Name", elem_id="train_new_embedding_name")
- initialization_text = gr.Textbox(label="Initialization text", value="*", elem_id="train_initialization_text")
- nvpt = gr.Slider(label="Number of vectors per token", minimum=1, maximum=75, step=1, value=1, elem_id="train_nvpt")
- overwrite_old_embedding = gr.Checkbox(value=False, label="Overwrite Old Embedding", elem_id="train_overwrite_old_embedding")
-
- with gr.Row():
- with gr.Column(scale=3):
- gr.HTML(value="")
-
- with gr.Column():
- create_embedding = gr.Button(value="Create embedding", variant='primary', elem_id="train_create_embedding")
-
- with gr.Tab(label="Create hypernetwork"):
- new_hypernetwork_name = gr.Textbox(label="Name", elem_id="train_new_hypernetwork_name")
- new_hypernetwork_sizes = gr.CheckboxGroup(label="Modules", value=["768", "320", "640", "1280"], choices=["768", "1024", "320", "640", "1280"], elem_id="train_new_hypernetwork_sizes")
- new_hypernetwork_layer_structure = gr.Textbox("1, 2, 1", label="Enter hypernetwork layer structure", placeholder="1st and last digit must be 1. ex:'1, 2, 1'", elem_id="train_new_hypernetwork_layer_structure")
- new_hypernetwork_activation_func = gr.Dropdown(value="linear", label="Select activation function of hypernetwork. Recommended : Swish / Linear(none)", choices=modules.hypernetworks.ui.keys, elem_id="train_new_hypernetwork_activation_func")
- new_hypernetwork_initialization_option = gr.Dropdown(value = "Normal", label="Select Layer weights initialization. Recommended: Kaiming for relu-like, Xavier for sigmoid-like, Normal otherwise", choices=["Normal", "KaimingUniform", "KaimingNormal", "XavierUniform", "XavierNormal"], elem_id="train_new_hypernetwork_initialization_option")
- new_hypernetwork_add_layer_norm = gr.Checkbox(label="Add layer normalization", elem_id="train_new_hypernetwork_add_layer_norm")
- new_hypernetwork_use_dropout = gr.Checkbox(label="Use dropout", elem_id="train_new_hypernetwork_use_dropout")
- new_hypernetwork_dropout_structure = gr.Textbox("0, 0, 0", label="Enter hypernetwork Dropout structure (or empty). Recommended : 0~0.35 incrementing sequence: 0, 0.05, 0.15", placeholder="1st and last digit must be 0 and values should be between 0 and 1. ex:'0, 0.01, 0'")
- overwrite_old_hypernetwork = gr.Checkbox(value=False, label="Overwrite Old Hypernetwork", elem_id="train_overwrite_old_hypernetwork")
-
- with gr.Row():
- with gr.Column(scale=3):
- gr.HTML(value="")
-
- with gr.Column():
- create_hypernetwork = gr.Button(value="Create hypernetwork", variant='primary', elem_id="train_create_hypernetwork")
-
- with gr.Tab(label="Preprocess images"):
- process_src = gr.Textbox(label='Source directory', elem_id="train_process_src")
- process_dst = gr.Textbox(label='Destination directory', elem_id="train_process_dst")
- process_width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="train_process_width")
- process_height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="train_process_height")
- preprocess_txt_action = gr.Dropdown(label='Existing Caption txt Action', value="ignore", choices=["ignore", "copy", "prepend", "append"], elem_id="train_preprocess_txt_action")
-
- with gr.Row():
- process_flip = gr.Checkbox(label='Create flipped copies', elem_id="train_process_flip")
- process_split = gr.Checkbox(label='Split oversized images', elem_id="train_process_split")
- process_focal_crop = gr.Checkbox(label='Auto focal point crop', elem_id="train_process_focal_crop")
- process_caption = gr.Checkbox(label='Use BLIP for caption', elem_id="train_process_caption")
- process_caption_deepbooru = gr.Checkbox(label='Use deepbooru for caption', visible=True, elem_id="train_process_caption_deepbooru")
-
- with gr.Row(visible=False) as process_split_extra_row:
- process_split_threshold = gr.Slider(label='Split image threshold', value=0.5, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_split_threshold")
- process_overlap_ratio = gr.Slider(label='Split image overlap ratio', value=0.2, minimum=0.0, maximum=0.9, step=0.05, elem_id="train_process_overlap_ratio")
-
- with gr.Row(visible=False) as process_focal_crop_row:
- process_focal_crop_face_weight = gr.Slider(label='Focal point face weight', value=0.9, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_focal_crop_face_weight")
- process_focal_crop_entropy_weight = gr.Slider(label='Focal point entropy weight', value=0.15, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_focal_crop_entropy_weight")
- process_focal_crop_edges_weight = gr.Slider(label='Focal point edges weight', value=0.5, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_focal_crop_edges_weight")
- process_focal_crop_debug = gr.Checkbox(label='Create debug image', elem_id="train_process_focal_crop_debug")
-
- with gr.Row():
- with gr.Column(scale=3):
- gr.HTML(value="")
-
- with gr.Column():
- with gr.Row():
- interrupt_preprocessing = gr.Button("Interrupt", elem_id="train_interrupt_preprocessing")
- run_preprocess = gr.Button(value="Preprocess", variant='primary', elem_id="train_run_preprocess")
-
- process_split.change(
- fn=lambda show: gr_show(show),
- inputs=[process_split],
- outputs=[process_split_extra_row],
- )
-
- process_focal_crop.change(
- fn=lambda show: gr_show(show),
- inputs=[process_focal_crop],
- outputs=[process_focal_crop_row],
- )
-
- def get_textual_inversion_template_names():
- return sorted([x for x in textual_inversion.textual_inversion_templates])
-
- with gr.Tab(label="Train"):
- gr.HTML(value="<p style='margin-bottom: 0.7em'>Train an embedding or Hypernetwork; you must specify a directory with a set of 1:1 ratio images <a href=\"https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Textual-Inversion\" style=\"font-weight:bold;\">[wiki]</a></p>")
- with FormRow():
- train_embedding_name = gr.Dropdown(label='Embedding', elem_id="train_embedding", choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys()))
- create_refresh_button(train_embedding_name, sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings, lambda: {"choices": sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())}, "refresh_train_embedding_name")
-
- train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', elem_id="train_hypernetwork", choices=[x for x in shared.hypernetworks.keys()])
- create_refresh_button(train_hypernetwork_name, shared.reload_hypernetworks, lambda: {"choices": sorted([x for x in shared.hypernetworks.keys()])}, "refresh_train_hypernetwork_name")
-
- with FormRow():
- embedding_learn_rate = gr.Textbox(label='Embedding Learning rate', placeholder="Embedding Learning rate", value="0.005", elem_id="train_embedding_learn_rate")
- hypernetwork_learn_rate = gr.Textbox(label='Hypernetwork Learning rate', placeholder="Hypernetwork Learning rate", value="0.00001", elem_id="train_hypernetwork_learn_rate")
-
- with FormRow():
- clip_grad_mode = gr.Dropdown(value="disabled", label="Gradient Clipping", choices=["disabled", "value", "norm"])
- clip_grad_value = gr.Textbox(placeholder="Gradient clip value", value="0.1", show_label=False)
-
- with FormRow():
- batch_size = gr.Number(label='Batch size', value=1, precision=0, elem_id="train_batch_size")
- gradient_step = gr.Number(label='Gradient accumulation steps', value=1, precision=0, elem_id="train_gradient_step")
-
- dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images", elem_id="train_dataset_directory")
- log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion", elem_id="train_log_directory")
-
- with FormRow():
- template_file = gr.Dropdown(label='Prompt template', value="style_filewords.txt", elem_id="train_template_file", choices=get_textual_inversion_template_names())
- create_refresh_button(template_file, textual_inversion.list_textual_inversion_templates, lambda: {"choices": get_textual_inversion_template_names()}, "refrsh_train_template_file")
-
- training_width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="train_training_width")
- training_height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="train_training_height")
- varsize = gr.Checkbox(label="Do not resize images", value=False, elem_id="train_varsize")
- steps = gr.Number(label='Max steps', value=100000, precision=0, elem_id="train_steps")
-
- with FormRow():
- create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0, elem_id="train_create_image_every")
- save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0, elem_id="train_save_embedding_every")
-
- save_image_with_stored_embedding = gr.Checkbox(label='Save images with embedding in PNG chunks', value=True, elem_id="train_save_image_with_stored_embedding")
- preview_from_txt2img = gr.Checkbox(label='Read parameters (prompt, etc...) from txt2img tab when making previews', value=False, elem_id="train_preview_from_txt2img")
-
- shuffle_tags = gr.Checkbox(label="Shuffle tags by ',' when creating prompts.", value=False, elem_id="train_shuffle_tags")
- tag_drop_out = gr.Slider(minimum=0, maximum=1, step=0.1, label="Drop out tags when creating prompts.", value=0, elem_id="train_tag_drop_out")
-
- latent_sampling_method = gr.Radio(label='Choose latent sampling method', value="once", choices=['once', 'deterministic', 'random'], elem_id="train_latent_sampling_method")
-
- with gr.Row():
- train_embedding = gr.Button(value="Train Embedding", variant='primary', elem_id="train_train_embedding")
- interrupt_training = gr.Button(value="Interrupt", elem_id="train_interrupt_training")
- train_hypernetwork = gr.Button(value="Train Hypernetwork", variant='primary', elem_id="train_train_hypernetwork")
-
- params = script_callbacks.UiTrainTabParams(txt2img_preview_params)
-
- script_callbacks.ui_train_tabs_callback(params)
-
- with gr.Column():
- progressbar = gr.HTML(elem_id="ti_progressbar")
- ti_output = gr.Text(elem_id="ti_output", value="", show_label=False)
-
- ti_gallery = gr.Gallery(label='Output', show_label=False, elem_id='ti_gallery').style(grid=4)
- ti_preview = gr.Image(elem_id='ti_preview', visible=False)
- ti_progress = gr.HTML(elem_id="ti_progress", value="")
- ti_outcome = gr.HTML(elem_id="ti_error", value="")
- setup_progressbar(progressbar, ti_preview, 'ti', textinfo=ti_progress)
-
- create_embedding.click(
- fn=modules.textual_inversion.ui.create_embedding,
- inputs=[
- new_embedding_name,
- initialization_text,
- nvpt,
- overwrite_old_embedding,
- ],
- outputs=[
- train_embedding_name,
- ti_output,
- ti_outcome,
- ]
- )
-
- create_hypernetwork.click(
- fn=modules.hypernetworks.ui.create_hypernetwork,
- inputs=[
- new_hypernetwork_name,
- new_hypernetwork_sizes,
- overwrite_old_hypernetwork,
- new_hypernetwork_layer_structure,
- new_hypernetwork_activation_func,
- new_hypernetwork_initialization_option,
- new_hypernetwork_add_layer_norm,
- new_hypernetwork_use_dropout,
- new_hypernetwork_dropout_structure
- ],
- outputs=[
- train_hypernetwork_name,
- ti_output,
- ti_outcome,
- ]
- )
-
- run_preprocess.click(
- fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]),
- _js="start_training_textual_inversion",
- inputs=[
- process_src,
- process_dst,
- process_width,
- process_height,
- preprocess_txt_action,
- process_flip,
- process_split,
- process_caption,
- process_caption_deepbooru,
- process_split_threshold,
- process_overlap_ratio,
- process_focal_crop,
- process_focal_crop_face_weight,
- process_focal_crop_entropy_weight,
- process_focal_crop_edges_weight,
- process_focal_crop_debug,
- ],
- outputs=[
- ti_output,
- ti_outcome,
- ],
- )
-
- train_embedding.click(
- fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.train_embedding, extra_outputs=[gr.update()]),
- _js="start_training_textual_inversion",
- inputs=[
- train_embedding_name,
- embedding_learn_rate,
- batch_size,
- gradient_step,
- dataset_directory,
- log_directory,
- training_width,
- training_height,
- varsize,
- steps,
- clip_grad_mode,
- clip_grad_value,
- shuffle_tags,
- tag_drop_out,
- latent_sampling_method,
- create_image_every,
- save_embedding_every,
- template_file,
- save_image_with_stored_embedding,
- preview_from_txt2img,
- *txt2img_preview_params,
- ],
- outputs=[
- ti_output,
- ti_outcome,
- ]
- )
-
- train_hypernetwork.click(
- fn=wrap_gradio_gpu_call(modules.hypernetworks.ui.train_hypernetwork, extra_outputs=[gr.update()]),
- _js="start_training_textual_inversion",
- inputs=[
- train_hypernetwork_name,
- hypernetwork_learn_rate,
- batch_size,
- gradient_step,
- dataset_directory,
- log_directory,
- training_width,
- training_height,
- varsize,
- steps,
- clip_grad_mode,
- clip_grad_value,
- shuffle_tags,
- tag_drop_out,
- latent_sampling_method,
- create_image_every,
- save_embedding_every,
- template_file,
- preview_from_txt2img,
- *txt2img_preview_params,
- ],
- outputs=[
- ti_output,
- ti_outcome,
- ]
- )
-
- interrupt_training.click(
- fn=lambda: shared.state.interrupt(),
- inputs=[],
- outputs=[],
- )
-
- interrupt_preprocessing.click(
- fn=lambda: shared.state.interrupt(),
- inputs=[],
- outputs=[],
- )
-
- def create_setting_component(key, is_quicksettings=False):
- 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}')
-
- elem_id = "setting_"+key
-
- if info.refresh is not None:
- if is_quicksettings:
- res = comp(label=info.label, value=fun(), elem_id=elem_id, **(args or {}))
- create_refresh_button(res, info.refresh, info.component_args, "refresh_" + key)
- else:
- with FormRow():
- res = comp(label=info.label, value=fun(), elem_id=elem_id, **(args or {}))
- create_refresh_button(res, info.refresh, info.component_args, "refresh_" + key)
- else:
- res = comp(label=info.label, value=fun(), elem_id=elem_id, **(args or {}))
-
- return res
-
- components = []
- component_dict = {}
-
- script_callbacks.ui_settings_callback()
- opts.reorder()
-
- def run_settings(*args):
- changed = []
-
- for key, value, comp in zip(opts.data_labels.keys(), args, components):
- assert comp == dummy_component or opts.same_type(value, opts.data_labels[key].default), f"Bad value for setting {key}: {value}; expecting {type(opts.data_labels[key].default).__name__}"
-
- for key, value, comp in zip(opts.data_labels.keys(), args, components):
- if comp == dummy_component:
- continue
-
- if opts.set(key, value):
- changed.append(key)
-
- try:
- opts.save(shared.config_filename)
- except RuntimeError:
- return opts.dumpjson(), f'{len(changed)} settings changed without save: {", ".join(changed)}.'
- return opts.dumpjson(), f'{len(changed)} settings changed{": " if len(changed) > 0 else ""}{", ".join(changed)}.'
-
- def run_settings_single(value, key):
- if not opts.same_type(value, opts.data_labels[key].default):
- return gr.update(visible=True), opts.dumpjson()
-
- if not opts.set(key, value):
- return gr.update(value=getattr(opts, key)), opts.dumpjson()
-
- opts.save(shared.config_filename)
-
- return gr.update(value=value), opts.dumpjson()
-
- with gr.Blocks(analytics_enabled=False) as settings_interface:
- with gr.Row():
- with gr.Column(scale=6):
- settings_submit = gr.Button(value="Apply settings", variant='primary', elem_id="settings_submit")
- with gr.Column():
- restart_gradio = gr.Button(value='Reload UI', variant='primary', elem_id="settings_restart_gradio")
-
- result = gr.HTML(elem_id="settings_result")
-
- quicksettings_names = [x.strip() for x in opts.quicksettings.split(",")]
- quicksettings_names = {x: i for i, x in enumerate(quicksettings_names) if x != 'quicksettings'}
-
- quicksettings_list = []
-
- previous_section = None
- current_tab = None
- with gr.Tabs(elem_id="settings"):
- for i, (k, item) in enumerate(opts.data_labels.items()):
- section_must_be_skipped = item.section[0] is None
-
- if previous_section != item.section and not section_must_be_skipped:
- elem_id, text = item.section
-
- if current_tab is not None:
- current_tab.__exit__()
-
- current_tab = gr.TabItem(elem_id="settings_{}".format(elem_id), label=text)
- current_tab.__enter__()
-
- previous_section = item.section
-
- if k in quicksettings_names and not shared.cmd_opts.freeze_settings:
- quicksettings_list.append((i, k, item))
- components.append(dummy_component)
- elif section_must_be_skipped:
- components.append(dummy_component)
- else:
- component = create_setting_component(k)
- component_dict[k] = component
- components.append(component)
-
- if current_tab is not None:
- current_tab.__exit__()
-
- with gr.TabItem("Actions"):
- request_notifications = gr.Button(value='Request browser notifications', elem_id="request_notifications")
- download_localization = gr.Button(value='Download localization template', elem_id="download_localization")
- reload_script_bodies = gr.Button(value='Reload custom script bodies (No ui updates, No restart)', variant='secondary', elem_id="settings_reload_script_bodies")
-
- if os.path.exists("html/licenses.html"):
- with open("html/licenses.html", encoding="utf8") as file:
- with gr.TabItem("Licenses"):
- gr.HTML(file.read(), elem_id="licenses")
-
- gr.Button(value="Show all pages", elem_id="settings_show_all_pages")
-
- request_notifications.click(
- fn=lambda: None,
- inputs=[],
- outputs=[],
- _js='function(){}'
- )
-
- download_localization.click(
- fn=lambda: None,
- inputs=[],
- outputs=[],
- _js='download_localization'
- )
-
- def reload_scripts():
- modules.scripts.reload_script_body_only()
- reload_javascript() # need to refresh the html page
-
- reload_script_bodies.click(
- fn=reload_scripts,
- inputs=[],
- outputs=[]
- )
-
- def request_restart():
- shared.state.interrupt()
- shared.state.need_restart = True
-
- restart_gradio.click(
- fn=request_restart,
- _js='restart_reload',
- inputs=[],
- outputs=[],
- )
-
- interfaces = [
- (txt2img_interface, "txt2img", "txt2img"),
- (img2img_interface, "img2img", "img2img"),
- (extras_interface, "Extras", "extras"),
- (pnginfo_interface, "PNG Info", "pnginfo"),
- (modelmerger_interface, "Checkpoint Merger", "modelmerger"),
- (train_interface, "Train", "ti"),
- ]
-
- css = ""
-
- for cssfile in modules.scripts.list_files_with_name("style.css"):
- if not os.path.isfile(cssfile):
- continue
-
- with open(cssfile, "r", encoding="utf8") as file:
- css += file.read() + "\n"
-
- 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:
- css += file.read() + "\n"
-
- if not cmd_opts.no_progressbar_hiding:
- css += css_hide_progressbar
-
- interfaces += script_callbacks.ui_tabs_callback()
- interfaces += [(settings_interface, "Settings", "settings")]
-
- extensions_interface = ui_extensions.create_ui()
- interfaces += [(extensions_interface, "Extensions", "extensions")]
-
- with gr.Blocks(css=css, analytics_enabled=False, title="Stable Diffusion") as demo:
- with gr.Row(elem_id="quicksettings"):
- for i, k, item in sorted(quicksettings_list, key=lambda x: quicksettings_names.get(x[1], x[0])):
- component = create_setting_component(k, is_quicksettings=True)
- component_dict[k] = component
-
- parameters_copypaste.integrate_settings_paste_fields(component_dict)
- parameters_copypaste.run_bind()
-
- with gr.Tabs(elem_id="tabs") as tabs:
- for interface, label, ifid in interfaces:
- with gr.TabItem(label, id=ifid, elem_id='tab_' + ifid):
- interface.render()
-
- if os.path.exists(os.path.join(script_path, "notification.mp3")):
- audio_notification = gr.Audio(interactive=False, value=os.path.join(script_path, "notification.mp3"), elem_id="audio_notification", visible=False)
-
- if os.path.exists("html/footer.html"):
- with open("html/footer.html", encoding="utf8") as file:
- footer = file.read()
- footer = footer.format(versions=versions_html())
- gr.HTML(footer, elem_id="footer")
-
- text_settings = gr.Textbox(elem_id="settings_json", value=lambda: opts.dumpjson(), visible=False)
- settings_submit.click(
- fn=wrap_gradio_call(run_settings, extra_outputs=[gr.update()]),
- inputs=components,
- outputs=[text_settings, result],
- )
-
- for i, k, item in quicksettings_list:
- component = component_dict[k]
-
- component.change(
- fn=lambda value, k=k: run_settings_single(value, key=k),
- inputs=[component],
- outputs=[component, text_settings],
- )
-
- component_keys = [k for k in opts.data_labels.keys() if k in component_dict]
-
- def get_settings_values():
- return [getattr(opts, key) for key in component_keys]
-
- demo.load(
- fn=get_settings_values,
- inputs=[],
- outputs=[component_dict[k] for k in component_keys],
- )
-
- def modelmerger(*args):
- try:
- results = modules.extras.run_modelmerger(*args)
- except Exception as e:
- print("Error loading/saving model file:", file=sys.stderr)
- print(traceback.format_exc(), file=sys.stderr)
- modules.sd_models.list_models() # to remove the potentially missing models from the list
- return [f"Error merging checkpoints: {e}"] + [gr.Dropdown.update(choices=modules.sd_models.checkpoint_tiles()) for _ in range(4)]
- return results
-
- modelmerger_merge.click(
- fn=modelmerger,
- inputs=[
- primary_model_name,
- secondary_model_name,
- tertiary_model_name,
- interp_method,
- interp_amount,
- save_as_half,
- custom_name,
- checkpoint_format,
- ],
- outputs=[
- submit_result,
- primary_model_name,
- secondary_model_name,
- tertiary_model_name,
- component_dict['sd_model_checkpoint'],
- ]
- )
-
- 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, init_field=None):
- key = path + "/" + field
-
- if getattr(obj, 'custom_script_source', None) is not None:
- key = 'customscript/' + obj.custom_script_source + '/' + key
-
- if getattr(obj, 'do_not_save_to_config', False):
- return
-
- saved_value = ui_settings.get(key, None)
- if saved_value is None:
- ui_settings[key] = getattr(obj, field)
- elif condition and not condition(saved_value):
- print(f'Warning: Bad ui setting value: {key}: {saved_value}; Default value "{getattr(obj, field)}" will be used instead.')
- else:
- setattr(obj, field, saved_value)
- if init_field is not None:
- init_field(saved_value)
-
- if type(x) in [gr.Slider, gr.Radio, gr.Checkbox, gr.Textbox, gr.Number, gr.Dropdown] and x.visible:
- apply_field(x, 'visible')
-
- 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)
-
- if type(x) == gr.Checkbox:
- apply_field(x, 'value')
-
- if type(x) == gr.Textbox:
- apply_field(x, 'value')
-
- if type(x) == gr.Number:
- apply_field(x, 'value')
-
- if type(x) == gr.Dropdown:
- apply_field(x, 'value', lambda val: val in x.choices, getattr(x, 'init_field', None))
-
- visit(txt2img_interface, loadsave, "txt2img")
- visit(img2img_interface, loadsave, "img2img")
- visit(extras_interface, loadsave, "extras")
- visit(modelmerger_interface, loadsave, "modelmerger")
- visit(train_interface, loadsave, "train")
-
- 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
-
-
-def reload_javascript():
- with open(os.path.join(script_path, "script.js"), "r", encoding="utf8") as jsfile:
- javascript = f'<script>{jsfile.read()}</script>'
-
- scripts_list = modules.scripts.list_scripts("javascript", ".js")
-
- for basedir, filename, path in scripts_list:
- with open(path, "r", encoding="utf8") as jsfile:
- javascript += f"\n<!-- {filename} --><script>{jsfile.read()}</script>"
-
- if cmd_opts.theme is not None:
- javascript += f"\n<script>set_theme('{cmd_opts.theme}');</script>\n"
-
- javascript += f"\n<script>{localization.localization_js(shared.opts.localization)}</script>"
-
- def template_response(*args, **kwargs):
- res = shared.GradioTemplateResponseOriginal(*args, **kwargs)
- res.body = res.body.replace(
- b'</head>', f'{javascript}</head>'.encode("utf8"))
- res.init_headers()
- return res
-
- gradio.routes.templates.TemplateResponse = template_response
-
-
-if not hasattr(shared, 'GradioTemplateResponseOriginal'):
- shared.GradioTemplateResponseOriginal = gradio.routes.templates.TemplateResponse
-
-
-def versions_html():
- import torch
- import launch
-
- python_version = ".".join([str(x) for x in sys.version_info[0:3]])
- commit = launch.commit_hash()
- short_commit = commit[0:8]
-
- if shared.xformers_available:
- import xformers
- xformers_version = xformers.__version__
- else:
- xformers_version = "N/A"
-
- return f"""
-python: <span title="{sys.version}">{python_version}</span>
- •
-torch: {torch.__version__}
- •
-xformers: {xformers_version}
- •
-gradio: {gr.__version__}
- •
-commit: <a href="https://github.com/AUTOMATIC1111/stable-diffusion-webui/commit/{commit}">{short_commit}</a>
-"""
|