import gradio as gr
import random
import os
import json
import time
import shared
import modules.config
import fooocus_version
import modules.html
import modules.async_worker as worker
import modules.constants as constants
import modules.flags as flags
import modules.gradio_hijack as grh
import modules.style_sorter as style_sorter
import modules.meta_parser
import args_manager
import copy
import launch
from extras.inpaint_mask import SAMOptions
from modules.sdxl_styles import legal_style_names
from modules.private_logger import get_current_html_path
from modules.ui_gradio_extensions import reload_javascript
from modules.auth import auth_enabled, check_auth
from modules.util import is_json
# ──────────────────────────────────────────────────────────────────
# UI Settings (保存先など永続設定)
# ──────────────────────────────────────────────────────────────────
_UI_SETTINGS_PATH = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'ui_settings.json')
def _ui_cfg_load() -> dict:
if os.path.exists(_UI_SETTINGS_PATH):
try:
with open(_UI_SETTINGS_PATH, 'r', encoding='utf-8') as f:
return json.load(f)
except Exception:
pass
return {}
def _ui_cfg_save(d: dict):
with open(_UI_SETTINGS_PATH, 'w', encoding='utf-8') as f:
json.dump(d, f, ensure_ascii=False, indent=2)
# 起動時に保存先を復元
_ui_cfg = _ui_cfg_load()
if 'path_outputs' in _ui_cfg:
import modules.config as _cfg_mod
_cfg_mod.path_outputs = _ui_cfg['path_outputs']
os.makedirs(_ui_cfg['path_outputs'], exist_ok=True)
# ──────────────────────────────────────────────────────────────────
# User Setting Presets helpers
# ──────────────────────────────────────────────────────────────────
_USER_SP_PATH = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'user_setting_presets.json')
def _sp_load() -> dict:
if os.path.exists(_USER_SP_PATH):
try:
with open(_USER_SP_PATH, 'r', encoding='utf-8') as f:
return json.load(f)
except Exception:
pass
return {}
def _sp_save(presets: dict):
with open(_USER_SP_PATH, 'w', encoding='utf-8') as f:
json.dump(presets, f, ensure_ascii=False, indent=2)
def _sp_aspect_to_resolution(aspect_label: str) -> str:
"""'1024×1024 | 1:1' → '(1024, 1024)'"""
try:
part = aspect_label.split('|')[0].strip()
w, h = part.split('×')
return f'({int(w.strip())}, {int(h.strip())})'
except Exception:
return '(1024, 1024)'
def get_task(*args):
args = list(args)
args.pop(0)
return worker.AsyncTask(args=args)
def generate_clicked(task: worker.AsyncTask):
import ldm_patched.modules.model_management as model_management
with model_management.interrupt_processing_mutex:
model_management.interrupt_processing = False
# outputs=[progress_html, progress_window, progress_gallery, gallery, gallery_paths]
if len(task.args) == 0:
return
execution_start_time = time.perf_counter()
finished = False
yield gr.update(visible=True, value=modules.html.make_progress_html(1, 'Waiting for task to start ...')), \
gr.update(visible=True, value=None), \
gr.update(visible=False, value=None), \
gr.update(visible=False), \
gr.update()
worker.async_tasks.append(task)
while not finished:
time.sleep(0.01)
if len(task.yields) > 0:
flag, product = task.yields.pop(0)
if flag == 'preview':
# help bad internet connection by skipping duplicated preview
if len(task.yields) > 0: # if we have the next item
if task.yields[0][0] == 'preview': # if the next item is also a preview
# print('Skipped one preview for better internet connection.')
continue
percentage, title, image = product
yield gr.update(visible=True, value=modules.html.make_progress_html(percentage, title)), \
gr.update(visible=True, value=image) if image is not None else gr.update(), \
gr.update(), \
gr.update(visible=False), \
gr.update()
if flag == 'results':
yield gr.update(visible=True), \
gr.update(visible=True), \
gr.update(visible=True, value=product), \
gr.update(visible=False), \
gr.update()
if flag == 'finish':
if not args_manager.args.disable_enhance_output_sorting:
product = sort_enhance_images(product, task)
yield gr.update(visible=False), \
gr.update(visible=False), \
gr.update(visible=False), \
gr.update(visible=True, value=product), \
product
finished = True
# delete Fooocus temp images, only keep gradio temp images
if args_manager.args.disable_image_log:
for filepath in product:
if isinstance(filepath, str) and os.path.exists(filepath):
os.remove(filepath)
execution_time = time.perf_counter() - execution_start_time
print(f'Total time: {execution_time:.2f} seconds')
return
def sort_enhance_images(images, task):
if not task.should_enhance or len(images) <= task.images_to_enhance_count:
return images
sorted_images = []
walk_index = task.images_to_enhance_count
for index, enhanced_img in enumerate(images[:task.images_to_enhance_count]):
sorted_images.append(enhanced_img)
if index not in task.enhance_stats:
continue
target_index = walk_index + task.enhance_stats[index]
if walk_index < len(images) and target_index <= len(images):
sorted_images += images[walk_index:target_index]
walk_index += task.enhance_stats[index]
return sorted_images
def inpaint_mode_change(mode, inpaint_engine_version):
assert mode in modules.flags.inpaint_options
# inpaint_additional_prompt, outpaint_selections, example_inpaint_prompts,
# inpaint_disable_initial_latent, inpaint_engine,
# inpaint_strength, inpaint_respective_field
if mode == modules.flags.inpaint_option_detail:
return [
gr.update(visible=True), gr.update(visible=False, value=[]),
gr.Dataset.update(visible=True, samples=modules.config.example_inpaint_prompts),
False, 'None', 0.5, 0.0
]
if inpaint_engine_version == 'empty':
inpaint_engine_version = modules.config.default_inpaint_engine_version
if mode == modules.flags.inpaint_option_modify:
return [
gr.update(visible=True), gr.update(visible=False, value=[]),
gr.Dataset.update(visible=False, samples=modules.config.example_inpaint_prompts),
True, inpaint_engine_version, 1.0, 0.0
]
return [
gr.update(visible=False, value=''), gr.update(visible=True),
gr.Dataset.update(visible=False, samples=modules.config.example_inpaint_prompts),
False, inpaint_engine_version, 1.0, 0.618
]
reload_javascript()
title = f'Fooocus {fooocus_version.version}'
if isinstance(args_manager.args.preset, str):
title += ' ' + args_manager.args.preset
shared.gradio_root = gr.Blocks(title=title).queue()
with shared.gradio_root:
currentTask = gr.State(worker.AsyncTask(args=[]))
inpaint_engine_state = gr.State('empty')
with gr.Row():
with gr.Column(scale=2):
with gr.Row():
progress_window = grh.Image(label='プレビュー', show_label=True, visible=False, height=768,
elem_classes=['main_view'])
progress_gallery = gr.Gallery(label='生成完了', show_label=True, object_fit='contain',
height=768, visible=False, elem_classes=['main_view', 'image_gallery'])
progress_html = gr.HTML(value=modules.html.make_progress_html(32, 'Progress 32%'), visible=False,
elem_id='progress-bar', elem_classes='progress-bar')
gallery = gr.Gallery(label='ギャラリー', show_label=False, object_fit='contain', visible=True, height=768,
elem_classes=['resizable_area', 'main_view', 'final_gallery', 'image_gallery'],
elem_id='final_gallery')
# ── ブラッシュアップ & OpenCV エディットパネル ──
brushup_selected = gr.State(None)
brushup_original = gr.State(None)
gallery_paths = gr.State([])
with gr.Row(elem_id='brushup_bar'):
with gr.Column(scale=0, min_width=114, elem_classes='brushup_btn_col', visible=False) as brushup_btn_col:
brushup_subtle_btn = gr.Button('🎨 微調整', variant='secondary', min_width=0)
brushup_strong_btn = gr.Button('🎭 強変更', variant='secondary', min_width=0)
brushup_upscale_btn = gr.Button('🔍 ×2拡大', variant='secondary', min_width=0)
brushup_gen_btn = gr.Button('⚡ 変更して生成', variant='primary', min_width=0)
with gr.Column(scale=1):
brushup_status_html = gr.HTML(
value=''
'💡 ギャラリーの画像をクリックして選択 → ブラッシュアップ / 編集',
elem_id='brushup_status_html')
with gr.Row(visible=False, elem_id='edit_panel') as edit_panel:
with gr.Column(scale=1):
# ── プリセット ──
with gr.Row(elem_id='edit_presets'):
edit_preset_vivid = gr.Button('🔆 ビビッド', min_width=0, elem_classes='preset_btn')
edit_preset_cinema = gr.Button('🎬 シネマ', min_width=0, elem_classes='preset_btn')
edit_preset_warm = gr.Button('🌅 ウォーム', min_width=0, elem_classes='preset_btn')
edit_preset_cool = gr.Button('❄️ クール', min_width=0, elem_classes='preset_btn')
edit_preset_soft = gr.Button('🌫️ ソフト', min_width=0, elem_classes='preset_btn')
# ── スライダー ──
edit_brightness = gr.Slider(label='明るさ', minimum=-100, maximum=100, value=0, step=1)
edit_contrast = gr.Slider(label='コントラスト', minimum=0.1, maximum=3.0, value=1.0, step=0.05)
edit_saturation = gr.Slider(label='彩度', minimum=0.0, maximum=3.0, value=1.0, step=0.05)
edit_hue = gr.Slider(label='色相シフト', minimum=-90, maximum=90, value=0, step=1)
edit_temperature = gr.Slider(label='色温度 ❄→🌅', minimum=-100, maximum=100, value=0, step=1)
edit_sharpness = gr.Slider(label='シャープネス', minimum=0.0, maximum=3.0, value=1.0, step=0.1)
# ── 回転・反転 ──
with gr.Row():
edit_rot_l = gr.Button('↺ 左90°', min_width=0)
edit_rot_r = gr.Button('↻ 右90°', min_width=0)
edit_flip_h = gr.Button('↔ 水平反転', min_width=0)
edit_flip_v = gr.Button('↕ 垂直反転', min_width=0)
# ── アクション ──
with gr.Row():
edit_reset_btn = gr.Button('🔄 リセット', min_width=0)
edit_apply_btn = gr.Button('✓ 適用 (選択更新)', variant='primary', min_width=0)
with gr.Column(scale=1):
edit_preview = gr.Image(label='編集プレビュー', type='numpy', interactive=False, height=340)
edit_ba_btn = gr.Button('🔍 元画像を確認 (B/A)', min_width=0)
with gr.Row():
with gr.Column(scale=17):
prompt = gr.Textbox(show_label=False, placeholder="プロンプトを入力、またはパラメータを貼り付け", elem_id='positive_prompt',
autofocus=True, lines=3)
default_prompt = modules.config.default_prompt
if isinstance(default_prompt, str) and default_prompt != '':
shared.gradio_root.load(lambda: default_prompt, outputs=prompt)
with gr.Column(scale=3, min_width=0):
generate_button = gr.Button(label="生成", value="生成", elem_classes='type_row', elem_id='generate_button', visible=True)
reset_button = gr.Button(label="再接続", value="再接続", elem_classes='type_row', elem_id='reset_button', visible=False)
load_parameter_button = gr.Button(label="パラメータ読込", value="パラメータ読込", elem_classes='type_row', elem_id='load_parameter_button', visible=False)
skip_button = gr.Button(label="スキップ", value="スキップ", elem_classes='type_row_half', elem_id='skip_button', visible=False)
stop_button = gr.Button(label="停止", value="停止", elem_classes='type_row_half', elem_id='stop_button', visible=False)
def stop_clicked(currentTask):
import ldm_patched.modules.model_management as model_management
currentTask.last_stop = 'stop'
if (currentTask.processing):
model_management.interrupt_current_processing()
return currentTask
def skip_clicked(currentTask):
import ldm_patched.modules.model_management as model_management
currentTask.last_stop = 'skip'
if (currentTask.processing):
model_management.interrupt_current_processing()
return currentTask
stop_button.click(stop_clicked, inputs=currentTask, outputs=currentTask, queue=False, show_progress=False, _js='cancelGenerateForever')
skip_button.click(skip_clicked, inputs=currentTask, outputs=currentTask, queue=False, show_progress=False)
with gr.Accordion('🔮 Prompt Forge — タグ選択＆翻訳', open=False, elem_id='pf_accordion'):
gr.HTML(value=(
''
'
'
'
'
'
Prompt Forge を読み込み中...'
'
'
' '
'
'
'
')
# ── プリセット操作 ──
with gr.Row():
user_sp_dropdown = gr.Dropdown(
label='保存済みプリセット',
choices=list(_sp_load().keys()),
value=None, scale=4, interactive=True)
user_sp_load_btn = gr.Button('📂 読込', variant='primary', scale=1, min_width=0)
user_sp_delete_btn = gr.Button('🗑️ 削除', variant='stop', scale=1, min_width=0)
with gr.Row():
user_sp_name = gr.Textbox(
label='保存名', placeholder='プリセット名を入力して保存...', scale=4)
user_sp_save_btn = gr.Button('💾 現在の設定を保存', variant='secondary', scale=2, min_width=0)
user_sp_status = gr.Markdown(value='')
performance_selection = gr.Radio(label='パフォーマンス',
choices=flags.Performance.values(),
value=modules.config.default_performance,
elem_classes=['performance_selection'])
with gr.Accordion(label='アスペクト比', open=False, elem_id='aspect_ratios_accordion') as aspect_ratios_accordion:
aspect_ratios_selection = gr.Radio(label='アスペクト比', show_label=False,
choices=modules.config.available_aspect_ratios_labels,
value=modules.config.default_aspect_ratio,
info='幅 × 高さ',
elem_classes='aspect_ratios')
aspect_ratios_selection.change(lambda x: None, inputs=aspect_ratios_selection, queue=False, show_progress=False, _js='(x)=>{refresh_aspect_ratios_label(x);}')
shared.gradio_root.load(lambda x: None, inputs=aspect_ratios_selection, queue=False, show_progress=False, _js='(x)=>{refresh_aspect_ratios_label(x);}')
image_number = gr.Slider(label='生成枚数', minimum=1, maximum=modules.config.default_max_image_number, step=1, value=modules.config.default_image_number)
output_format = gr.Radio(label='出力形式',
choices=flags.OutputFormat.list(),
value=modules.config.default_output_format)
negative_prompt = gr.Textbox(label='ネガティブプロンプト', show_label=True, placeholder="ここにプロンプトを入力",
info='生成したくない要素を入力してください。', lines=2,
elem_id='negative_prompt',
value=modules.config.default_prompt_negative)
seed_random = gr.Checkbox(label='ランダム', value=True)
image_seed = gr.Textbox(label='シード', value=0, max_lines=1, visible=False) # workaround for https://github.com/gradio-app/gradio/issues/5354
def random_checked(r):
return gr.update(visible=not r)
def refresh_seed(r, seed_string):
if r:
return random.randint(constants.MIN_SEED, constants.MAX_SEED)
else:
try:
seed_value = int(seed_string)
if constants.MIN_SEED <= seed_value <= constants.MAX_SEED:
return seed_value
except ValueError:
pass
return random.randint(constants.MIN_SEED, constants.MAX_SEED)
seed_random.change(random_checked, inputs=[seed_random], outputs=[image_seed],
queue=False, show_progress=False)
def update_history_link():
if args_manager.args.disable_image_log:
return gr.update(value='')
return gr.update(value=f'📚 生成履歴')
history_link = gr.HTML()
shared.gradio_root.load(update_history_link, outputs=history_link, queue=False, show_progress=False)
with gr.Tab(label='スタイル', elem_classes=['style_selections_tab']):
style_sorter.try_load_sorted_styles(
style_names=legal_style_names,
default_selected=modules.config.default_styles)
style_search_bar = gr.Textbox(show_label=False, container=False,
placeholder="🔍 スタイルを検索...",
value="",
label='スタイル検索')
style_selections = gr.CheckboxGroup(show_label=False, container=False,
choices=copy.deepcopy(style_sorter.all_styles),
value=copy.deepcopy(modules.config.default_styles),
label='選択中のスタイル',
elem_classes=['style_selections'])
gradio_receiver_style_selections = gr.Textbox(elem_id='gradio_receiver_style_selections', visible=False)
shared.gradio_root.load(lambda: gr.update(choices=copy.deepcopy(style_sorter.all_styles)),
outputs=style_selections)
style_search_bar.change(style_sorter.search_styles,
inputs=[style_selections, style_search_bar],
outputs=style_selections,
queue=False,
show_progress=False).then(
lambda: None, _js='()=>{refresh_style_localization();}')
gradio_receiver_style_selections.input(style_sorter.sort_styles,
inputs=style_selections,
outputs=style_selections,
queue=False,
show_progress=False).then(
lambda: None, _js='()=>{refresh_style_localization();}')
with gr.Tab(label='モデル'):
with gr.Group():
with gr.Row():
base_model = gr.Dropdown(label='ベースモデル（SDXL のみ）', choices=modules.config.model_filenames, value=modules.config.default_base_model_name, show_label=True)
refiner_model = gr.Dropdown(label='リファイナー（SDXL または SD 1.5）', choices=['None'] + modules.config.model_filenames, value=modules.config.default_refiner_model_name, show_label=True)
refiner_switch = gr.Slider(label='リファイナー切替タイミング', minimum=0.1, maximum=1.0, step=0.0001,
info='SD1.5 リアル系: 0.4 / アニメ系: 0.667 / XL リファイナー: 0.8 / 2モデル切替: 任意の値',
value=modules.config.default_refiner_switch,
visible=modules.config.default_refiner_model_name != 'None')
refiner_model.change(lambda x: gr.update(visible=x != 'None'),
inputs=refiner_model, outputs=refiner_switch, show_progress=False, queue=False)
with gr.Group():
lora_ctrls = []
for i, (enabled, filename, weight) in enumerate(modules.config.default_loras):
with gr.Row():
lora_enabled = gr.Checkbox(label='有効', value=enabled,
elem_classes=['lora_enable', 'min_check'], scale=1)
lora_model = gr.Dropdown(label=f'LoRA {i + 1}',
choices=['None'] + modules.config.lora_filenames, value=filename,
elem_classes='lora_model', scale=5)
lora_weight = gr.Slider(label='ウェイト', minimum=modules.config.default_loras_min_weight,
maximum=modules.config.default_loras_max_weight, step=0.01, value=weight,
elem_classes='lora_weight', scale=5)
lora_ctrls += [lora_enabled, lora_model, lora_weight]
with gr.Row():
refresh_files = gr.Button(label='更新', value='🔄 全ファイルを更新', variant='secondary', elem_classes='refresh_button')
with gr.Tab(label='詳細設定'):
guidance_scale = gr.Slider(label='ガイダンススケール', minimum=1.0, maximum=30.0, step=0.01,
value=modules.config.default_cfg_scale,
info='値が高いほどスタイルが鮮明・鮮やか・芸術的になります。')
sharpness = gr.Slider(label='画像シャープネス', minimum=0.0, maximum=30.0, step=0.001,
value=modules.config.default_sample_sharpness,
info='値が高いほど画像とテクスチャがシャープになります。')
gr.HTML('📖 ドキュメント')
dev_mode = gr.Checkbox(label='開発者デバッグモード', value=modules.config.default_developer_debug_mode_checkbox, container=False)
with gr.Column(visible=modules.config.default_developer_debug_mode_checkbox) as dev_tools:
with gr.Tab(label='デバッグツール'):
adm_scaler_positive = gr.Slider(label='ポジティブ ADM ガイダンス スケーラー', minimum=0.1, maximum=3.0,
step=0.001, value=1.5, info='ポジティブ ADM に乗算するスケーラー（無効にするには 1.0）。')
adm_scaler_negative = gr.Slider(label='ネガティブ ADM ガイダンス スケーラー', minimum=0.1, maximum=3.0,
step=0.001, value=0.8, info='ネガティブ ADM に乗算するスケーラー（無効にするには 1.0）。')
adm_scaler_end = gr.Slider(label='ADM ガイダンス終了ステップ', minimum=0.0, maximum=1.0,
step=0.001, value=0.3,
info='ポジティブ/ネガティブ ADM ガイダンスを終了するタイミング。')
refiner_swap_method = gr.Dropdown(label='リファイナー スワップ方式', value=flags.refiner_swap_method,
choices=['joint', 'separate', 'vae'])
adaptive_cfg = gr.Slider(label='CFG TSNR ミミッキング', minimum=1.0, maximum=30.0, step=0.01,
value=modules.config.default_cfg_tsnr,
info='TSNR 向け CFG ミミッキングを有効化します（実 CFG > ミミッキング CFG のとき有効）。')
clip_skip = gr.Slider(label='CLIP スキップ', minimum=1, maximum=flags.clip_skip_max, step=1,
value=modules.config.default_clip_skip,
info='過学習を避けるため CLIP レイヤーをスキップします（1: スキップなし、推奨: 2）。')
sampler_name = gr.Dropdown(label='サンプラー', choices=flags.sampler_list,
value=modules.config.default_sampler)
scheduler_name = gr.Dropdown(label='スケジューラー', choices=flags.scheduler_list,
value=modules.config.default_scheduler)
vae_name = gr.Dropdown(label='VAE', choices=[modules.flags.default_vae] + modules.config.vae_filenames,
value=modules.config.default_vae, show_label=True)
generate_image_grid = gr.Checkbox(label='バッチごとに画像グリッドを生成',
info='（実験的）環境によってはパフォーマンスに影響する場合があります。',
value=False)
overwrite_step = gr.Slider(label='サンプリングステップ 強制上書き',
minimum=-1, maximum=200, step=1,
value=modules.config.default_overwrite_step,
info='-1 で無効。開発者向けデバッグ用。')
overwrite_switch = gr.Slider(label='リファイナー切替ステップ 強制上書き',
minimum=-1, maximum=200, step=1,
value=modules.config.default_overwrite_switch,
info='-1 で無効。開発者向けデバッグ用。')
overwrite_width = gr.Slider(label='生成幅 強制上書き',
minimum=-1, maximum=2048, step=1, value=-1,
info='-1 で無効。SDXL の学習外の値は品質が低下します。')
overwrite_height = gr.Slider(label='生成高さ 強制上書き',
minimum=-1, maximum=2048, step=1, value=-1,
info='-1 で無効。SDXL の学習外の値は品質が低下します。')
overwrite_vary_strength = gr.Slider(label='「バリエーション」デノイズ強度 強制上書き',
minimum=-1, maximum=1.0, step=0.001, value=-1,
info='負の値で無効。開発者向けデバッグ用。')
overwrite_upscale_strength = gr.Slider(label='「アップスケール」デノイズ強度 強制上書き',
minimum=-1, maximum=1.0, step=0.001,
value=modules.config.default_overwrite_upscale,
info='負の値で無効。開発者向けデバッグ用。')
disable_preview = gr.Checkbox(label='プレビューを無効化', value=modules.config.default_black_out_nsfw,
interactive=not modules.config.default_black_out_nsfw,
info='生成中のプレビュー表示を無効にします。')
disable_intermediate_results = gr.Checkbox(label='中間結果を無効化',
value=flags.Performance.has_restricted_features(modules.config.default_performance),
info='生成中の中間結果を非表示にし、最終ギャラリーのみ表示します。')
disable_seed_increment = gr.Checkbox(label='シード自動増加を無効化',
info='生成枚数が 1 より多い場合の自動シード増加を無効にします。',
value=False)
read_wildcards_in_order = gr.Checkbox(label="ワイルドカードを順番に読む", value=False)
black_out_nsfw = gr.Checkbox(label='NSFW を黒塗り', value=modules.config.default_black_out_nsfw,
interactive=not modules.config.default_black_out_nsfw,
info='NSFW が検出された場合に黒い画像を表示します。')
black_out_nsfw.change(lambda x: gr.update(value=x, interactive=not x),
inputs=black_out_nsfw, outputs=disable_preview, queue=False,
show_progress=False)
if not args_manager.args.disable_image_log:
save_final_enhanced_image_only = gr.Checkbox(label='最終強化画像のみ保存',
value=modules.config.default_save_only_final_enhanced_image)
if not args_manager.args.disable_metadata:
save_metadata_to_images = gr.Checkbox(label='メタデータを画像に保存', value=modules.config.default_save_metadata_to_images,
info='生成パラメータを画像に埋め込み、後から再生成できるようにします。')
metadata_scheme = gr.Radio(label='メタデータスキーム', choices=flags.metadata_scheme, value=modules.config.default_metadata_scheme,
info='画像プロンプトのパラメータは含まれません。Civitai との互換性には png と a1111 を使用してください。',
visible=modules.config.default_save_metadata_to_images)
save_metadata_to_images.change(lambda x: gr.update(visible=x), inputs=[save_metadata_to_images], outputs=[metadata_scheme],
queue=False, show_progress=False)
with gr.Tab(label='コントロール'):
debugging_cn_preprocessor = gr.Checkbox(label='プリプロセッサーをデバッグ', value=False,
info='プリプロセッサーの処理結果を確認します。')
skipping_cn_preprocessor = gr.Checkbox(label='プリプロセッサーをスキップ', value=False,
info='画像を前処理しません（入力が既に Canny/Depth 等の場合に使用）。')
mixing_image_prompt_and_vary_upscale = gr.Checkbox(label='画像プロンプトとバリエーション/拡大を混合',
value=False)
mixing_image_prompt_and_inpaint = gr.Checkbox(label='画像プロンプトとインペイントを混合',
value=False)
controlnet_softness = gr.Slider(label='ControlNet ソフトネス', minimum=0.0, maximum=1.0,
step=0.001, value=0.25,
info='A1111 のコントロールモードに相当します（0.0 で無効）。')
with gr.Tab(label='Canny'):
canny_low_threshold = gr.Slider(label='Canny 低閾値', minimum=1, maximum=255,
step=1, value=64)
canny_high_threshold = gr.Slider(label='Canny 高閾値', minimum=1, maximum=255,
step=1, value=128)
with gr.Tab(label='インペイント'):
debugging_inpaint_preprocessor = gr.Checkbox(label='インペイント前処理をデバッグ', value=False)
debugging_enhance_masks_checkbox = gr.Checkbox(label='強化マスクをデバッグ', value=False,
info='プレビューと最終結果に強化マスクを表示します。')
debugging_dino = gr.Checkbox(label='GroundingDINO をデバッグ', value=False,
info='SAM マスクの代わりに GroundingDINO のボックスを使用します。')
inpaint_disable_initial_latent = gr.Checkbox(label='インペイントの初期潜在を無効化', value=False)
inpaint_engine = gr.Dropdown(label='インペイントエンジン',
value=modules.config.default_inpaint_engine_version,
choices=flags.inpaint_engine_versions,
info='Fooocus インペイントモデルのバージョン。Quality または Speed を推奨。')
inpaint_strength = gr.Slider(label='インペイント デノイズ強度',
minimum=0.0, maximum=1.0, step=0.001, value=1.0,
info='A1111 インペイントのデノイズ強度と同じです。'
'インペイントのみ有効（アウトペイントは常に 1.0）。')
inpaint_respective_field = gr.Slider(label='インペイント対象範囲',
minimum=0.0, maximum=1.0, step=0.001, value=0.618,
info='インペイントする領域。'
'0 = A1111 の「マスクのみ」、'
'1 = 「画像全体」。'
'インペイントのみ有効（アウトペイントは常に 1.0）。')
inpaint_erode_or_dilate = gr.Slider(label='マスク 侵食/膨張',
minimum=-64, maximum=64, step=1, value=0,
info='正の値はマスクの白い領域を拡大、'
'負の値は縮小します。'
'（デフォルト 0、マスク反転前に処理）')
dino_erode_or_dilate = gr.Slider(label='GroundingDINO ボックス 侵食/膨張',
minimum=-64, maximum=64, step=1, value=0,
info='正の値はマスクの白い領域を拡大、'
'負の値は縮小します。'
'（デフォルト 0、SAM 処理前に実行）')
inpaint_mask_color = gr.ColorPicker(label='インペイントブラシの色', value='#FFFFFF', elem_id='inpaint_brush_color')
inpaint_ctrls = [debugging_inpaint_preprocessor, inpaint_disable_initial_latent, inpaint_engine,
inpaint_strength, inpaint_respective_field,
inpaint_advanced_masking_checkbox, invert_mask_checkbox, inpaint_erode_or_dilate]
inpaint_advanced_masking_checkbox.change(lambda x: [gr.update(visible=x)] * 2,
inputs=inpaint_advanced_masking_checkbox,
outputs=[inpaint_mask_image, inpaint_mask_generation_col],
queue=False, show_progress=False)
inpaint_mask_color.change(lambda x: gr.update(brush_color=x), inputs=inpaint_mask_color,
outputs=inpaint_input_image,
queue=False, show_progress=False)
with gr.Tab(label='FreeU'):
freeu_enabled = gr.Checkbox(label='有効化', value=False)
freeu_b1 = gr.Slider(label='B1', minimum=0, maximum=2, step=0.01, value=1.01)
freeu_b2 = gr.Slider(label='B2', minimum=0, maximum=2, step=0.01, value=1.02)
freeu_s1 = gr.Slider(label='S1', minimum=0, maximum=4, step=0.01, value=0.99)
freeu_s2 = gr.Slider(label='S2', minimum=0, maximum=4, step=0.01, value=0.95)
freeu_ctrls = [freeu_enabled, freeu_b1, freeu_b2, freeu_s1, freeu_s2]
def dev_mode_checked(r):
return gr.update(visible=r)
dev_mode.change(dev_mode_checked, inputs=[dev_mode], outputs=[dev_tools],
queue=False, show_progress=False)
def refresh_files_clicked():
modules.config.update_files()
results = [gr.update(choices=modules.config.model_filenames)]
results += [gr.update(choices=['None'] + modules.config.model_filenames)]
results += [gr.update(choices=[flags.default_vae] + modules.config.vae_filenames)]
if not args_manager.args.disable_preset_selection:
results += [gr.update(choices=modules.config.available_presets)]
for i in range(modules.config.default_max_lora_number):
results += [gr.update(interactive=True),
gr.update(choices=['None'] + modules.config.lora_filenames), gr.update()]
return results
refresh_files_output = [base_model, refiner_model, vae_name]
if not args_manager.args.disable_preset_selection:
refresh_files_output += [preset_selection]
refresh_files.click(refresh_files_clicked, [], refresh_files_output + lora_ctrls,
queue=False, show_progress=False)
state_is_generating = gr.State(False)
load_data_outputs = [advanced_checkbox, image_number, prompt, negative_prompt, style_selections,
performance_selection, overwrite_step, overwrite_switch, aspect_ratios_selection,
overwrite_width, overwrite_height, guidance_scale, sharpness, adm_scaler_positive,
adm_scaler_negative, adm_scaler_end, refiner_swap_method, adaptive_cfg, clip_skip,
base_model, refiner_model, refiner_switch, sampler_name, scheduler_name, vae_name,
seed_random, image_seed, inpaint_engine, inpaint_engine_state,
inpaint_mode] + enhance_inpaint_mode_ctrls + [generate_button,
load_parameter_button] + freeu_ctrls + lora_ctrls
if not args_manager.args.disable_preset_selection:
def preset_selection_change(preset, is_generating, inpaint_mode):
preset_content = modules.config.try_get_preset_content(preset) if preset != 'initial' else {}
preset_prepared = modules.meta_parser.parse_meta_from_preset(preset_content)
default_model = preset_prepared.get('base_model')
previous_default_models = preset_prepared.get('previous_default_models', [])
checkpoint_downloads = preset_prepared.get('checkpoint_downloads', {})
embeddings_downloads = preset_prepared.get('embeddings_downloads', {})
lora_downloads = preset_prepared.get('lora_downloads', {})
vae_downloads = preset_prepared.get('vae_downloads', {})
preset_prepared['base_model'], preset_prepared['checkpoint_downloads'] = launch.download_models(
default_model, previous_default_models, checkpoint_downloads, embeddings_downloads, lora_downloads,
vae_downloads)
if 'prompt' in preset_prepared and preset_prepared.get('prompt') == '':
del preset_prepared['prompt']
return modules.meta_parser.load_parameter_button_click(json.dumps(preset_prepared), is_generating, inpaint_mode)
def inpaint_engine_state_change(inpaint_engine_version, *args):
if inpaint_engine_version == 'empty':
inpaint_engine_version = modules.config.default_inpaint_engine_version
result = []
for inpaint_mode in args:
if inpaint_mode != modules.flags.inpaint_option_detail:
result.append(gr.update(value=inpaint_engine_version))
else:
result.append(gr.update())
return result
preset_selection.change(preset_selection_change, inputs=[preset_selection, state_is_generating, inpaint_mode], outputs=load_data_outputs, queue=False, show_progress=True) \
.then(fn=style_sorter.sort_styles, inputs=style_selections, outputs=style_selections, queue=False, show_progress=False) \
.then(lambda: None, _js='()=>{refresh_style_localization();}') \
.then(inpaint_engine_state_change, inputs=[inpaint_engine_state] + enhance_inpaint_mode_ctrls, outputs=enhance_inpaint_engine_ctrls, queue=False, show_progress=False)
# ── 保存先変更 イベント ──
def _do_change_output_path(new_path):
try:
p = str(new_path).strip()
if not p:
return gr.update(), '❌ パスを入力してください'
os.makedirs(p, exist_ok=True)
modules.config.path_outputs = p
cfg = _ui_cfg_load()
cfg['path_outputs'] = p
_ui_cfg_save(cfg)
return gr.update(value=p), f'✅ 保存先を変更しました: `{p}`'
except Exception as e:
return gr.update(), f'❌ エラー: {e}'
output_path_btn.click(
fn=_do_change_output_path, inputs=[output_path_box],
outputs=[output_path_box, output_path_status], queue=False, show_progress=False)
# ── User Setting Presets イベント ──
_sp_save_inputs = [
user_sp_name, prompt, negative_prompt, style_selections,
performance_selection, aspect_ratios_selection, image_number,
guidance_scale, sharpness, base_model, refiner_model, refiner_switch,
sampler_name, scheduler_name, vae_name,
seed_random, image_seed,
adm_scaler_positive, adm_scaler_negative, adm_scaler_end,
refiner_swap_method, adaptive_cfg, clip_skip,
input_image_checkbox, enhance_checkbox, uov_method,
] + freeu_ctrls + lora_ctrls
def sp_do_save(name, prompt_v, neg_v, styles_v, perf_v, aspect_v, img_num,
guidance_v, sharp_v, base_v, ref_v, ref_sw_v,
sampler_v, sched_v, vae_v,
seed_rnd, seed_v,
adm_p, adm_n, adm_e,
ref_swap_v, adap_v, clip_v,
input_img_cb, enhance_cb, uov_m,
*rest):
try:
if not name or not str(name).strip():
return gr.update(), '❌ プリセット名を入力してください'
n = str(name).strip()
# rest = [freeu_en, freeu_b1, freeu_b2, freeu_s1, freeu_s2, lora_en1, lora_m1, lora_w1, ...]
freeu_en = rest[0] if len(rest) > 0 else False
freeu_b1_v = rest[1] if len(rest) > 1 else 1.01
freeu_b2_v = rest[2] if len(rest) > 2 else 1.02
freeu_s1_v = rest[3] if len(rest) > 3 else 0.99
freeu_s2_v = rest[4] if len(rest) > 4 else 0.95
lora_vals = rest[5:]
meta = {
'prompt': str(prompt_v) if prompt_v else '',
'negative_prompt': str(neg_v) if neg_v else '',
'styles': str(styles_v) if styles_v else '[]',
'performance': str(perf_v) if perf_v else 'Speed',
'resolution': _sp_aspect_to_resolution(str(aspect_v) if aspect_v else ''),
'image_number': int(float(img_num)) if img_num is not None else 1,
'guidance_scale': float(guidance_v) if guidance_v is not None else 7.0,
'sharpness': float(sharp_v) if sharp_v is not None else 2.0,
'base_model': str(base_v) if base_v else '',
'refiner_model': str(ref_v) if ref_v else 'None',
'refiner_switch': float(ref_sw_v) if ref_sw_v is not None else 0.5,
'sampler': str(sampler_v) if sampler_v else 'dpmpp_2m_sde_gpu',
'scheduler': str(sched_v) if sched_v else 'karras',
'vae': str(vae_v) if vae_v else 'Default (model)',
'adm_guidance': f'({adm_p}, {adm_n}, {adm_e})',
'refiner_swap_method': str(ref_swap_v) if ref_swap_v else 'joint',
'adaptive_cfg': float(adap_v) if adap_v is not None else 7.0,
'clip_skip': int(float(clip_v)) if clip_v is not None else 2,
'input_image_enabled': bool(input_img_cb),
'enhance_enabled': bool(enhance_cb),
'uov_method': str(uov_m) if uov_m else flags.disabled,
}
if not seed_rnd:
try:
meta['seed'] = int(float(seed_v))
except Exception:
pass
if freeu_en:
meta['freeu'] = f'({freeu_b1_v}, {freeu_b2_v}, {freeu_s1_v}, {freeu_s2_v})'
for i in range(0, len(lora_vals), 3):
en = lora_vals[i]
nm = lora_vals[i + 1]
wt = lora_vals[i + 2]
meta[f'lora_combined_{i // 3 + 1}'] = f'{"True" if en else "False"} : {nm} : {wt}'
presets = _sp_load()
presets[n] = meta
_sp_save(presets)
choices = list(presets.keys())
print(f'[UserPreset] 保存完了: {n} / 合計{len(choices)}件 → {_USER_SP_PATH}')
return gr.update(choices=choices, value=n), f'✅ 保存しました：{n}'
except Exception as e:
import traceback
msg = traceback.format_exc()
print(f'[UserPreset] 保存エラー:\n{msg}')
return gr.update(), f'❌ 保存エラー: {e}'
def sp_do_load(name, is_gen, inpaint_m):
_no_change = [gr.update()] * 5 # input_img_cb, enhance_cb, img_panel, enhance_panel, uov_m
try:
if not name:
return [gr.update()] * len(load_data_outputs) + ['❌ プリセットを選択してください'] + _no_change
presets = _sp_load()
if name not in presets:
return [gr.update()] * len(load_data_outputs) + [f'❌ 「{name}」が見つかりません'] + _no_change
meta = presets[name]
result = modules.meta_parser.load_parameter_button_click(meta, is_gen, inpaint_m)
print(f'[UserPreset] 読込完了: {name}')
# 追加フィールド: 入力画像 / 強化 / UoV メソッド
img_en = bool(meta.get('input_image_enabled', False))
enh_en = bool(meta.get('enhance_enabled', False))
uov_val = meta.get('uov_method', flags.disabled)
return (result
+ [f'✅ 読み込みました：{name}']
+ [gr.update(value=img_en),
gr.update(value=enh_en),
gr.update(visible=img_en),
gr.update(visible=enh_en),
gr.update(value=uov_val)])
except Exception as e:
import traceback
msg = traceback.format_exc()
print(f'[UserPreset] 読込エラー:\n{msg}')
return [gr.update()] * len(load_data_outputs) + [f'❌ 読込エラー: {e}'] + _no_change
def sp_do_delete(name):
try:
if not name:
return gr.update(), '❌ プリセットを選択してください'
presets = _sp_load()
if name not in presets:
return gr.update(), f'❌ 「{name}」が見つかりません'
del presets[name]
_sp_save(presets)
choices = list(presets.keys())
return gr.update(choices=choices, value=choices[0] if choices else None), f'🗑️ 削除しました：{name}'
except Exception as e:
return gr.update(), f'❌ 削除エラー: {e}'
def sp_refresh_dropdown():
choices = list(_sp_load().keys())
return gr.update(choices=choices, value=choices[0] if choices else None)
shared.gradio_root.load(fn=sp_refresh_dropdown, inputs=[], outputs=[user_sp_dropdown],
queue=False, show_progress=False)
user_sp_save_btn.click(
fn=sp_do_save,
inputs=_sp_save_inputs,
outputs=[user_sp_dropdown, user_sp_status],
queue=False, show_progress=False)
user_sp_load_btn.click(
fn=sp_do_load,
inputs=[user_sp_dropdown, state_is_generating, inpaint_mode],
outputs=load_data_outputs + [user_sp_status,
input_image_checkbox, enhance_checkbox,
image_input_panel, enhance_input_panel, uov_method],
queue=False, show_progress=True) \
.then(fn=style_sorter.sort_styles, inputs=style_selections, outputs=style_selections, queue=False, show_progress=False) \
.then(lambda: None, _js='()=>{refresh_style_localization();}')
user_sp_delete_btn.click(
fn=sp_do_delete,
inputs=[user_sp_dropdown],
outputs=[user_sp_dropdown, user_sp_status],
queue=False, show_progress=False)
# ── ブラッシュアップ & OpenCV エディット イベント ──
_brushup_outputs = [
uov_input_image, uov_method, input_image_checkbox, image_input_panel,
image_input_tabs, current_tab,
]
_brushup_select_outputs = [
brushup_selected, brushup_original, brushup_status_html,
brushup_btn_col, edit_panel, edit_preview,
]
def on_brushup_select(evt: gr.SelectData, paths_state):
# Gradio 3.41.2: evt.value = caption (usually None), evt.index = int index
_hide = gr.update(visible=False)
_fail = (None, None,
''
'💡 ギャラリーの画像をクリックして選択',
_hide, _hide, None)
try:
idx = evt.index
if not (paths_state and isinstance(idx, int) and 0 <= idx < len(paths_state)):
return _fail
path = paths_state[idx]
if not (isinstance(path, str) and os.path.exists(path)):
return _fail
from PIL import Image as PILImage
import numpy as np
from modules.image_editor import resize_for_preview as _rfp
arr = np.array(PILImage.open(path).convert('RGB'))
h, w = arr.shape[:2]
fname = os.path.basename(path)
html = (f''
f'✓ {fname} ({w}×{h}px) — 方法を選択 または ↓ で編集')
preview = _rfp(arr, 768)
return arr, arr, html, gr.update(visible=True), gr.update(visible=True), preview
except Exception as e:
return (None, None,
f'❌ {e}',
_hide, _hide, None)
gallery.select(fn=on_brushup_select, inputs=[gallery_paths], outputs=_brushup_select_outputs, queue=False, show_progress=False)
progress_gallery.select(fn=on_brushup_select, inputs=[gallery_paths], outputs=_brushup_select_outputs, queue=False, show_progress=False)
def do_brushup(img, method):
if img is None:
return (gr.update(), gr.update(), gr.update(), gr.update(visible=False),
gr.update(), gr.update())
return (img, method, True, gr.update(visible=True),
gr.update(selected='uov_tab'), 'uov')
_scroll_js = '() => { setTimeout(function(){ var el=document.getElementById("image_input_panel"); if(!el) el=document.querySelector(".image_input_panel"); if(el) el.scrollIntoView({behavior:"smooth",block:"start"}); }, 200); return []; }'
brushup_subtle_btn.click(
fn=lambda img: do_brushup(img, flags.subtle_variation),
inputs=[brushup_selected], outputs=_brushup_outputs, queue=False, show_progress=False
).then(fn=lambda: None, _js=_scroll_js)
brushup_strong_btn.click(
fn=lambda img: do_brushup(img, flags.strong_variation),
inputs=[brushup_selected], outputs=_brushup_outputs, queue=False, show_progress=False
).then(fn=lambda: None, _js=_scroll_js)
brushup_upscale_btn.click(
fn=lambda img: do_brushup(img, flags.upscale_2),
inputs=[brushup_selected], outputs=_brushup_outputs, queue=False, show_progress=False
).then(fn=lambda: None, _js=_scroll_js)
brushup_gen_btn.click(
fn=lambda img: do_brushup(img, flags.subtle_variation),
inputs=[brushup_selected], outputs=_brushup_outputs, queue=False, show_progress=False
).then(fn=lambda: None, _js='() => { setTimeout(function(){ var b=document.getElementById("generate_button"); if(b&&!b.disabled)b.click(); },600); return []; }')
# ── OpenCV エディター イベント ──
from modules.image_editor import apply_adjustments, resize_for_preview, rotate_image, flip_image
# プリセット定義: (brightness, contrast, saturation, hue, temperature, sharpness)
_PRESETS = {
'vivid': (10, 1.25, 1.6, 0, 0, 1.3),
'cinema': (-8, 1.35, 0.7, 0, 15, 1.0),
'warm': (12, 1.05, 1.2, 0, 40, 1.0),
'cool': (0, 1.1, 0.85, 0, -40, 1.0),
'soft': (8, 0.88, 0.88, 0, 0, 0.4),
}
# スライダーの入力リスト (順番をそろえる)
_edit_inputs = [brushup_original,
edit_brightness, edit_contrast, edit_saturation,
edit_hue, edit_temperature, edit_sharpness]
_slider_outputs = [edit_brightness, edit_contrast, edit_saturation,
edit_hue, edit_temperature, edit_sharpness]
def _update_preview(orig, brightness, contrast, saturation, hue_shift, temperature, sharpness):
small = resize_for_preview(orig, 768)
return apply_adjustments(small, brightness=brightness, contrast=contrast,
saturation=saturation, hue_shift=hue_shift,
sharpness=sharpness, temperature=temperature)
# スライダー変更 → リアルタイムプレビュー
for _sl in [edit_brightness, edit_contrast, edit_saturation, edit_hue, edit_temperature, edit_sharpness]:
_sl.change(fn=_update_preview, inputs=_edit_inputs, outputs=edit_preview,
queue=False, show_progress=False)
# リセット
def _reset_edit(orig):
preview = resize_for_preview(orig, 768)
return 0, 1.0, 1.0, 0, 0, 1.0, preview
edit_reset_btn.click(
fn=_reset_edit, inputs=[brushup_original],
outputs=_slider_outputs + [edit_preview],
queue=False, show_progress=False
)
# 適用 → brushup_selected を編集版に更新
def _apply_edit(orig, brightness, contrast, saturation, hue_shift, temperature, sharpness):
edited = apply_adjustments(orig, brightness=brightness, contrast=contrast,
saturation=saturation, hue_shift=hue_shift,
sharpness=sharpness, temperature=temperature)
if edited is None:
return gr.update(), gr.update()
preview = resize_for_preview(edited, 768)
return edited, preview
edit_apply_btn.click(
fn=_apply_edit, inputs=_edit_inputs,
outputs=[brushup_selected, edit_preview],
queue=False, show_progress=False
)
# ── プリセット ──────────────────────────────
def _apply_preset(key, orig):
br, ct, sat, hue, temp, sharp = _PRESETS[key]
preview = _update_preview(orig, br, ct, sat, hue, temp, sharp)
return br, ct, sat, hue, temp, sharp, preview
_preset_outs = _slider_outputs + [edit_preview]
edit_preset_vivid.click( fn=lambda o: _apply_preset('vivid', o), inputs=[brushup_original], outputs=_preset_outs, queue=False, show_progress=False)
edit_preset_cinema.click(fn=lambda o: _apply_preset('cinema', o), inputs=[brushup_original], outputs=_preset_outs, queue=False, show_progress=False)
edit_preset_warm.click( fn=lambda o: _apply_preset('warm', o), inputs=[brushup_original], outputs=_preset_outs, queue=False, show_progress=False)
edit_preset_cool.click( fn=lambda o: _apply_preset('cool', o), inputs=[brushup_original], outputs=_preset_outs, queue=False, show_progress=False)
edit_preset_soft.click( fn=lambda o: _apply_preset('soft', o), inputs=[brushup_original], outputs=_preset_outs, queue=False, show_progress=False)
# ── 回転・反転 ──────────────────────────────
_transform_inputs = [brushup_original] + _slider_outputs
_transform_outputs = [brushup_original, edit_preview]
def _do_rotate(orig, brightness, contrast, saturation, hue_shift, temperature, sharpness, deg):
rotated = rotate_image(orig, deg)
if rotated is None:
return gr.update(), gr.update()
return rotated, _update_preview(rotated, brightness, contrast, saturation, hue_shift, temperature, sharpness)
def _do_flip(orig, brightness, contrast, saturation, hue_shift, temperature, sharpness, direction):
flipped = flip_image(orig, direction)
if flipped is None:
return gr.update(), gr.update()
return flipped, _update_preview(flipped, brightness, contrast, saturation, hue_shift, temperature, sharpness)
edit_rot_l.click( fn=lambda *a: _do_rotate(*a, 270), inputs=_transform_inputs, outputs=_transform_outputs, queue=False, show_progress=False)
edit_rot_r.click( fn=lambda *a: _do_rotate(*a, 90), inputs=_transform_inputs, outputs=_transform_outputs, queue=False, show_progress=False)
edit_flip_h.click(fn=lambda *a: _do_flip(*a, 'h'), inputs=_transform_inputs, outputs=_transform_outputs, queue=False, show_progress=False)
edit_flip_v.click(fn=lambda *a: _do_flip(*a, 'v'), inputs=_transform_inputs, outputs=_transform_outputs, queue=False, show_progress=False)
# ── Before / After ─────────────────────────
edit_ba_btn.click(
fn=lambda orig: resize_for_preview(orig, 768),
inputs=[brushup_original], outputs=edit_preview,
queue=False, show_progress=False
)
performance_selection.change(lambda x: [gr.update(interactive=not flags.Performance.has_restricted_features(x))] * 11 +
[gr.update(visible=not flags.Performance.has_restricted_features(x))] * 1 +
[gr.update(value=flags.Performance.has_restricted_features(x))] * 1,
inputs=performance_selection,
outputs=[
guidance_scale, sharpness, adm_scaler_end, adm_scaler_positive,
adm_scaler_negative, refiner_switch, refiner_model, sampler_name,
scheduler_name, adaptive_cfg, refiner_swap_method, negative_prompt, disable_intermediate_results
], queue=False, show_progress=False)
output_format.input(lambda x: gr.update(output_format=x), inputs=output_format)
advanced_checkbox.change(lambda x: gr.update(visible=x), advanced_checkbox, advanced_column,
queue=False, show_progress=False) \
.then(fn=lambda: None, _js='refresh_grid_delayed', queue=False, show_progress=False)
inpaint_mode.change(inpaint_mode_change, inputs=[inpaint_mode, inpaint_engine_state], outputs=[
inpaint_additional_prompt, outpaint_selections, example_inpaint_prompts,
inpaint_disable_initial_latent, inpaint_engine,
inpaint_strength, inpaint_respective_field
], show_progress=False, queue=False)
# load configured default_inpaint_method
default_inpaint_ctrls = [inpaint_mode, inpaint_disable_initial_latent, inpaint_engine, inpaint_strength, inpaint_respective_field]
for mode, disable_initial_latent, engine, strength, respective_field in [default_inpaint_ctrls] + enhance_inpaint_update_ctrls:
shared.gradio_root.load(inpaint_mode_change, inputs=[mode, inpaint_engine_state], outputs=[
inpaint_additional_prompt, outpaint_selections, example_inpaint_prompts, disable_initial_latent,
engine, strength, respective_field
], show_progress=False, queue=False)
generate_mask_button.click(fn=generate_mask,
inputs=[inpaint_input_image, inpaint_mask_model, inpaint_mask_cloth_category,
inpaint_mask_dino_prompt_text, inpaint_mask_sam_model,
inpaint_mask_box_threshold, inpaint_mask_text_threshold,
inpaint_mask_sam_max_detections, dino_erode_or_dilate, debugging_dino],
outputs=inpaint_mask_image, show_progress=True, queue=True)
ctrls = [currentTask, generate_image_grid]
ctrls += [
prompt, negative_prompt, style_selections,
performance_selection, aspect_ratios_selection, image_number, output_format, image_seed,
read_wildcards_in_order, sharpness, guidance_scale
]
ctrls += [base_model, refiner_model, refiner_switch] + lora_ctrls
ctrls += [input_image_checkbox, current_tab]
ctrls += [uov_method, uov_input_image]
ctrls += [outpaint_selections, inpaint_input_image, inpaint_additional_prompt, inpaint_mask_image]
ctrls += [disable_preview, disable_intermediate_results, disable_seed_increment, black_out_nsfw]
ctrls += [adm_scaler_positive, adm_scaler_negative, adm_scaler_end, adaptive_cfg, clip_skip]
ctrls += [sampler_name, scheduler_name, vae_name]
ctrls += [overwrite_step, overwrite_switch, overwrite_width, overwrite_height, overwrite_vary_strength]
ctrls += [overwrite_upscale_strength, mixing_image_prompt_and_vary_upscale, mixing_image_prompt_and_inpaint]
ctrls += [debugging_cn_preprocessor, skipping_cn_preprocessor, canny_low_threshold, canny_high_threshold]
ctrls += [refiner_swap_method, controlnet_softness]
ctrls += freeu_ctrls
ctrls += inpaint_ctrls
if not args_manager.args.disable_image_log:
ctrls += [save_final_enhanced_image_only]
if not args_manager.args.disable_metadata:
ctrls += [save_metadata_to_images, metadata_scheme]
ctrls += ip_ctrls
ctrls += [debugging_dino, dino_erode_or_dilate, debugging_enhance_masks_checkbox,
enhance_input_image, enhance_checkbox, enhance_uov_method, enhance_uov_processing_order,
enhance_uov_prompt_type]
ctrls += enhance_ctrls
def parse_meta(raw_prompt_txt, is_generating):
loaded_json = None
if is_json(raw_prompt_txt):
loaded_json = json.loads(raw_prompt_txt)
if loaded_json is None:
if is_generating:
return gr.update(), gr.update(), gr.update()
else:
return gr.update(), gr.update(visible=True), gr.update(visible=False)
return json.dumps(loaded_json), gr.update(visible=False), gr.update(visible=True)
prompt.input(parse_meta, inputs=[prompt, state_is_generating], outputs=[prompt, generate_button, load_parameter_button], queue=False, show_progress=False)
load_parameter_button.click(modules.meta_parser.load_parameter_button_click, inputs=[prompt, state_is_generating, inpaint_mode], outputs=load_data_outputs, queue=False, show_progress=False)
def trigger_metadata_import(file, state_is_generating):
parameters, metadata_scheme = modules.meta_parser.read_info_from_image(file)
if parameters is None:
print('画像にメタデータが見つかりませんでした。')
parsed_parameters = {}
else:
metadata_parser = modules.meta_parser.get_metadata_parser(metadata_scheme)
parsed_parameters = metadata_parser.to_json(parameters)
return modules.meta_parser.load_parameter_button_click(parsed_parameters, state_is_generating, inpaint_mode)
metadata_import_button.click(trigger_metadata_import, inputs=[metadata_input_image, state_is_generating], outputs=load_data_outputs, queue=False, show_progress=True) \
.then(style_sorter.sort_styles, inputs=style_selections, outputs=style_selections, queue=False, show_progress=False)
generate_button.click(lambda: (gr.update(visible=True, interactive=True), gr.update(visible=True, interactive=True), gr.update(visible=False, interactive=False), [], True),
outputs=[stop_button, skip_button, generate_button, gallery, state_is_generating]) \
.then(fn=refresh_seed, inputs=[seed_random, image_seed], outputs=image_seed) \
.then(fn=get_task, inputs=ctrls, outputs=currentTask) \
.then(fn=generate_clicked, inputs=currentTask, outputs=[progress_html, progress_window, progress_gallery, gallery, gallery_paths]) \
.then(lambda: (gr.update(visible=True, interactive=True), gr.update(visible=False, interactive=False), gr.update(visible=False, interactive=False), False),
outputs=[generate_button, stop_button, skip_button, state_is_generating]) \
.then(fn=update_history_link, outputs=history_link) \
.then(fn=lambda: None, _js='playNotification').then(fn=lambda: None, _js='refresh_grid_delayed')
reset_button.click(lambda: [worker.AsyncTask(args=[]), False, gr.update(visible=True, interactive=True)] +
[gr.update(visible=False)] * 6 +
[gr.update(visible=True, value=[])],
outputs=[currentTask, state_is_generating, generate_button,
reset_button, stop_button, skip_button,
progress_html, progress_window, progress_gallery, gallery],
queue=False)
for notification_file in ['notification.ogg', 'notification.mp3']:
if os.path.exists(notification_file):
gr.Audio(interactive=False, value=notification_file, elem_id='audio_notification', visible=False)
break
def trigger_describe(modes, img, apply_styles):
describe_prompts = []
styles = set()
if flags.describe_type_photo in modes:
from extras.interrogate import default_interrogator as default_interrogator_photo
describe_prompts.append(default_interrogator_photo(img))
styles.update(["Fooocus V2", "Fooocus Enhance", "Fooocus Sharp"])
if flags.describe_type_anime in modes:
from extras.wd14tagger import default_interrogator as default_interrogator_anime
describe_prompts.append(default_interrogator_anime(img))
styles.update(["Fooocus V2", "Fooocus Masterpiece"])
if len(styles) == 0 or not apply_styles:
styles = gr.update()
else:
styles = list(styles)
if len(describe_prompts) == 0:
describe_prompt = gr.update()
else:
describe_prompt = ', '.join(describe_prompts)
return describe_prompt, styles
describe_btn.click(trigger_describe, inputs=[describe_methods, describe_input_image, describe_apply_styles],
outputs=[prompt, style_selections], show_progress=True, queue=True) \
.then(fn=style_sorter.sort_styles, inputs=style_selections, outputs=style_selections, queue=False, show_progress=False) \
.then(lambda: None, _js='()=>{refresh_style_localization();}')
# ── Prompt Forge 統合：postMessage リスナー ──
shared.gradio_root.load(
fn=lambda: None, inputs=[], outputs=[],
queue=False, show_progress=False,
_js="""
function() {
if (window._pfListenerAdded) return [];
window._pfListenerAdded = true;
// React管理のtextareaに値をセットしてイベントを発火する
function pfSetTextarea(selector, value) {
var el = document.querySelector(selector);
if (!el) return false;
try {
var nativeSetter = Object.getOwnPropertyDescriptor(window.HTMLTextAreaElement.prototype, 'value').set;
nativeSetter.call(el, value);
} catch(e) {
el.value = value;
}
el.dispatchEvent(new Event('input', {bubbles: true}));
el.dispatchEvent(new Event('change', {bubbles: true}));
return true;
}
// 転送後、テキストエリアをハイライト（緑フラッシュ）
function pfFlash(selector) {
var el = document.querySelector(selector);
if (!el) return;
el.style.transition = 'box-shadow 0.15s ease';
el.style.boxShadow = '0 0 0 3px rgba(100,255,150,0.7)';
setTimeout(function() { el.style.boxShadow = ''; }, 1000);
}
// アコーディオンを閉じる（複数のセレクタを試みる）
function pfCloseAccordion() {
var btn = document.querySelector('#pf_accordion button[aria-expanded="true"]');
if (!btn) btn = document.querySelector('#pf_accordion .toggle-icon[aria-expanded="true"]');
if (!btn) btn = document.querySelector('#pf_accordion > button:first-child');
if (btn) {
try { btn.click(); } catch(e) {}
}
}
window.addEventListener('message', function(ev) {
if (!ev.data || ev.data.type !== 'pf_send') return;
// アコーディオンを閉じる
pfCloseAccordion();
// positive_prompt を更新
var posOk = pfSetTextarea('#positive_prompt textarea', ev.data.pos || '');
// negative_prompt を更新（Settingsタブが閉じていてもGradioはDOMに保持する）
pfSetTextarea('#negative_prompt textarea', ev.data.neg || '');
// フォーカス＆フラッシュ
setTimeout(function() {
var posEl = document.querySelector('#positive_prompt textarea');
if (posEl) {
posEl.focus();
posEl.scrollIntoView({behavior: 'smooth', block: 'center'});
}
pfFlash('#positive_prompt textarea');
}, 150);
// 生成ボタン自動クリック
if (ev.data.generate) {
setTimeout(function() {
var btn = document.getElementById('generate_button');
if (btn) btn.click();
}, 600);
}
});
return [];
}
"""
)
if args_manager.args.enable_auto_describe_image:
def trigger_auto_describe(mode, img, prompt, apply_styles):
# keep prompt if not empty
if prompt == '':
return trigger_describe(mode, img, apply_styles)
return gr.update(), gr.update()
uov_input_image.upload(trigger_auto_describe, inputs=[describe_methods, uov_input_image, prompt, describe_apply_styles],
outputs=[prompt, style_selections], show_progress=True, queue=True) \
.then(fn=style_sorter.sort_styles, inputs=style_selections, outputs=style_selections, queue=False, show_progress=False) \
.then(lambda: None, _js='()=>{refresh_style_localization();}')
enhance_input_image.upload(lambda: gr.update(value=True), outputs=enhance_checkbox, queue=False, show_progress=False) \
.then(trigger_auto_describe, inputs=[describe_methods, enhance_input_image, prompt, describe_apply_styles],
outputs=[prompt, style_selections], show_progress=True, queue=True) \
.then(fn=style_sorter.sort_styles, inputs=style_selections, outputs=style_selections, queue=False, show_progress=False) \
.then(lambda: None, _js='()=>{refresh_style_localization();}')
def dump_default_english_config():
from modules.localization import dump_english_config
dump_english_config(grh.all_components)
# dump_default_english_config()
# ── Prompt Forge ブリッジサーバーを起動 ──
try:
import prompt_forge_bridge
prompt_forge_bridge.start_bridge()
except Exception as _pf_err:
print(f'[PromptForge] ブリッジ起動失敗: {_pf_err}')
shared.gradio_root.launch(
inbrowser=args_manager.args.in_browser,
server_name=args_manager.args.listen,
server_port=args_manager.args.port,
share=args_manager.args.share,
auth=check_auth if (args_manager.args.share or args_manager.args.listen) and auth_enabled else None,
allowed_paths=[modules.config.path_outputs],
blocked_paths=[constants.AUTH_FILENAME]
)