mirror of
https://github.com/Bing-su/adetailer.git
synced 2026-01-26 11:19:53 +00:00
705 lines
23 KiB
Python
705 lines
23 KiB
Python
from __future__ import annotations
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from dataclasses import dataclass
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from functools import partial
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from types import SimpleNamespace
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from typing import Any
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import gradio as gr
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from adetailer import AFTER_DETAILER, __version__
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from adetailer.args import ALL_ARGS, MASK_MERGE_INVERT
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from controlnet_ext import controlnet_exists, controlnet_type, get_cn_models
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if controlnet_type == "forge":
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from lib_controlnet import global_state
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cn_module_choices = {
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"inpaint": list(global_state.get_filtered_preprocessors("Inpaint")),
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"lineart": list(global_state.get_filtered_preprocessors("Lineart")),
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"openpose": list(global_state.get_filtered_preprocessors("OpenPose")),
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"tile": list(global_state.get_filtered_preprocessors("Tile")),
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"scribble": list(global_state.get_filtered_preprocessors("Scribble")),
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"depth": list(global_state.get_filtered_preprocessors("Depth")),
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}
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else:
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cn_module_choices = {
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"inpaint": [
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"inpaint_global_harmonious",
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"inpaint_only",
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"inpaint_only+lama",
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],
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"lineart": [
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"lineart_coarse",
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"lineart_realistic",
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"lineart_anime",
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"lineart_anime_denoise",
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],
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"openpose": ["openpose_full", "dw_openpose_full"],
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"tile": ["tile_resample", "tile_colorfix", "tile_colorfix+sharp"],
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"scribble": ["t2ia_sketch_pidi"],
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"depth": ["depth_midas", "depth_hand_refiner"],
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}
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class Widgets(SimpleNamespace):
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def tolist(self):
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return [getattr(self, attr) for attr in ALL_ARGS.attrs]
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@dataclass
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class WebuiInfo:
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ad_model_list: list[str]
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sampler_names: list[str]
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scheduler_names: list[str]
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t2i_button: gr.Button
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i2i_button: gr.Button
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checkpoints_list: list[str]
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vae_list: list[str]
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def gr_interactive(value: bool = True):
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return gr.update(interactive=value)
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def ordinal(n: int) -> str:
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d = {1: "st", 2: "nd", 3: "rd"}
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return str(n) + ("th" if 11 <= n % 100 <= 13 else d.get(n % 10, "th"))
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def suffix(n: int, c: str = " ") -> str:
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return "" if n == 0 else c + ordinal(n + 1)
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def on_widget_change(state: dict, value: Any, *, attr: str):
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if "is_api" in state:
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state = state.copy()
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state.pop("is_api")
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state[attr] = value
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return state
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def on_generate_click(state: dict, *values: Any):
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for attr, value in zip(ALL_ARGS.attrs, values):
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state[attr] = value
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state["is_api"] = ()
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return state
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def on_ad_model_update(model: str):
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if "-world" in model:
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return gr.update(
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visible=True,
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placeholder="Comma separated class names to detect, ex: 'person,cat'. default: COCO 80 classes",
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)
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return gr.update(visible=False, placeholder="")
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def on_cn_model_update(cn_model_name: str):
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cn_model_name = cn_model_name.replace("inpaint_depth", "depth")
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for t in cn_module_choices:
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if t in cn_model_name:
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choices = cn_module_choices[t]
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return gr.update(visible=True, choices=choices, value=choices[0])
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return gr.update(visible=False, choices=["None"], value="None")
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def elem_id(item_id: str, n: int, is_img2img: bool) -> str:
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tap = "img2img" if is_img2img else "txt2img"
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suf = suffix(n, "_")
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return f"script_{tap}_adetailer_{item_id}{suf}"
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def state_init(w: Widgets) -> dict[str, Any]:
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return {attr: getattr(w, attr).value for attr in ALL_ARGS.attrs}
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def adui(
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num_models: int,
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is_img2img: bool,
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webui_info: WebuiInfo,
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):
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states = []
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infotext_fields = []
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eid = partial(elem_id, n=0, is_img2img=is_img2img)
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with gr.Accordion(AFTER_DETAILER, open=False, elem_id=eid("ad_main_accordion")):
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with gr.Row():
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with gr.Column(scale=6):
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ad_enable = gr.Checkbox(
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label="Enable ADetailer",
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value=False,
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visible=True,
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elem_id=eid("ad_enable"),
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)
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with gr.Column(scale=6):
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ad_skip_img2img = gr.Checkbox(
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label="Skip img2img",
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value=False,
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visible=is_img2img,
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elem_id=eid("ad_skip_img2img"),
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)
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with gr.Column(scale=1, min_width=180):
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gr.Markdown(
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f"v{__version__}",
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elem_id=eid("ad_version"),
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)
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infotext_fields.append((ad_enable, "ADetailer enable"))
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infotext_fields.append((ad_skip_img2img, "ADetailer skip img2img"))
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with gr.Group(), gr.Tabs():
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for n in range(num_models):
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with gr.Tab(ordinal(n + 1)):
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state, infofields = one_ui_group(
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n=n,
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is_img2img=is_img2img,
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webui_info=webui_info,
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)
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states.append(state)
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infotext_fields.extend(infofields)
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# components: [bool, dict, dict, ...]
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components = [ad_enable, ad_skip_img2img, *states]
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return components, infotext_fields
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def one_ui_group(n: int, is_img2img: bool, webui_info: WebuiInfo):
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w = Widgets()
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eid = partial(elem_id, n=n, is_img2img=is_img2img)
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with gr.Group():
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with gr.Row():
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model_choices = (
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[*webui_info.ad_model_list, "None"]
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if n == 0
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else ["None", *webui_info.ad_model_list]
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)
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w.ad_model = gr.Dropdown(
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label="ADetailer detector" + suffix(n),
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choices=model_choices,
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value=model_choices[0],
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visible=True,
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type="value",
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elem_id=eid("ad_model"),
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info="Select a model to use for detection.",
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)
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with gr.Row():
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w.ad_model_classes = gr.Textbox(
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label="ADetailer detector classes" + suffix(n),
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value="",
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visible=False,
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elem_id=eid("ad_classes"),
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info="Comma separated class names to detect, ex: 'girl,cat'.",
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)
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w.ad_model.change(
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on_ad_model_update,
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inputs=w.ad_model,
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outputs=w.ad_model_classes,
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queue=False,
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)
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gr.HTML("<br>")
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with gr.Group():
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with gr.Row(elem_id=eid("ad_toprow_prompt")):
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w.ad_prompt = gr.Textbox(
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label="ad_prompt" + suffix(n),
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show_label=False,
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lines=3,
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placeholder="ADetailer prompt"
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+ suffix(n)
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+ "\nIf blank, the main prompt is used.",
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elem_id=eid("ad_prompt"),
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)
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with gr.Row(elem_id=eid("ad_toprow_negative_prompt")):
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w.ad_negative_prompt = gr.Textbox(
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label="ad_negative_prompt" + suffix(n),
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show_label=False,
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lines=2,
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placeholder="ADetailer negative prompt"
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+ suffix(n)
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+ "\nIf blank, the main negative prompt is used.",
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elem_id=eid("ad_negative_prompt"),
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)
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with gr.Group():
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with gr.Accordion(
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"Detection", open=False, elem_id=eid("ad_detection_accordion")
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):
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detection(w, n, is_img2img)
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with gr.Accordion(
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"Mask Preprocessing",
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open=False,
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elem_id=eid("ad_mask_preprocessing_accordion"),
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):
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mask_preprocessing(w, n, is_img2img)
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with gr.Accordion(
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"Inpainting", open=False, elem_id=eid("ad_inpainting_accordion")
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):
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inpainting(w, n, is_img2img, webui_info)
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with gr.Group():
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controlnet(w, n, is_img2img)
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state = gr.State(lambda: state_init(w))
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for attr in ALL_ARGS.attrs:
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widget = getattr(w, attr)
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on_change = partial(on_widget_change, attr=attr)
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widget.change(fn=on_change, inputs=[state, widget], outputs=state, queue=False)
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all_inputs = [state, *w.tolist()]
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target_button = webui_info.i2i_button if is_img2img else webui_info.t2i_button
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target_button.click(
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fn=on_generate_click, inputs=all_inputs, outputs=state, queue=False
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)
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infotext_fields = [(getattr(w, attr), name + suffix(n)) for attr, name in ALL_ARGS]
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return state, infotext_fields
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def detection(w: Widgets, n: int, is_img2img: bool):
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eid = partial(elem_id, n=n, is_img2img=is_img2img)
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with gr.Row():
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with gr.Column(variant="compact"):
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w.ad_confidence = gr.Slider(
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label="Detection model confidence threshold" + suffix(n),
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minimum=0.0,
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maximum=1.0,
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step=0.01,
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value=0.3,
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visible=True,
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elem_id=eid("ad_confidence"),
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info="Confidence threshold for detection model.",
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)
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w.ad_mask_k_largest = gr.Slider(
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label="Mask only the top k largest (0 to disable)" + suffix(n),
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minimum=0,
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maximum=10,
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step=1,
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value=0,
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visible=True,
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elem_id=eid("ad_mask_k_largest"),
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info="Use only the top k largest objects for masking.",
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)
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with gr.Column(variant="compact"):
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w.ad_mask_min_ratio = gr.Slider(
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label="Mask min area ratio" + suffix(n),
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minimum=0.0,
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maximum=1.0,
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step=0.001,
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value=0.0,
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visible=True,
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elem_id=eid("ad_mask_min_ratio"),
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info="Minimum area ratio for masking.",
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)
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w.ad_mask_max_ratio = gr.Slider(
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label="Mask max area ratio" + suffix(n),
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minimum=0.0,
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maximum=1.0,
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step=0.001,
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value=1.0,
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visible=True,
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elem_id=eid("ad_mask_max_ratio"),
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info="Maximum area ratio for masking.",
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)
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def mask_preprocessing(w: Widgets, n: int, is_img2img: bool):
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eid = partial(elem_id, n=n, is_img2img=is_img2img)
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with gr.Group():
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with gr.Row():
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with gr.Column(variant="compact"):
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w.ad_x_offset = gr.Slider(
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label="Mask x(→) offset" + suffix(n),
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minimum=-200,
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maximum=200,
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step=1,
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value=0,
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visible=True,
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elem_id=eid("ad_x_offset"),
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info="Mask x offset (→) in pixels.",
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)
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w.ad_y_offset = gr.Slider(
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label="Mask y(↑) offset" + suffix(n),
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minimum=-200,
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maximum=200,
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step=1,
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value=0,
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visible=True,
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elem_id=eid("ad_y_offset"),
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info="Mask y offset (↑) in pixels.",
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)
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with gr.Column(variant="compact"):
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w.ad_dilate_erode = gr.Slider(
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label="Mask erosion (-) / dilation (+)" + suffix(n),
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minimum=-128,
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maximum=128,
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step=4,
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value=4,
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visible=True,
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elem_id=eid("ad_dilate_erode"),
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info="Mask erosion (-) / dilation (+) in pixels.",
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)
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with gr.Row():
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w.ad_mask_merge_invert = gr.Radio(
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label="Mask merge mode" + suffix(n),
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choices=MASK_MERGE_INVERT,
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value="None",
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elem_id=eid("ad_mask_merge_invert"),
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info="Mask merge mode. (None: do nothing, Merge: merge masks, Merge and Invert: merge all masks and invert)",
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)
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def inpainting(w: Widgets, n: int, is_img2img: bool, webui_info: WebuiInfo):
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eid = partial(elem_id, n=n, is_img2img=is_img2img)
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with gr.Group():
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with gr.Row():
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w.ad_mask_blur = gr.Slider(
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label="Inpaint mask blur" + suffix(n),
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minimum=0,
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maximum=64,
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step=1,
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value=4,
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visible=True,
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elem_id=eid("ad_mask_blur"),
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)
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w.ad_denoising_strength = gr.Slider(
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label="Inpaint denoising strength" + suffix(n),
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minimum=0.0,
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maximum=1.0,
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step=0.01,
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value=0.4,
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visible=True,
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elem_id=eid("ad_denoising_strength"),
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)
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with gr.Row():
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with gr.Column(variant="compact"):
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w.ad_inpaint_only_masked = gr.Checkbox(
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label="Inpaint only masked" + suffix(n),
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value=True,
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visible=True,
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elem_id=eid("ad_inpaint_only_masked"),
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)
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w.ad_inpaint_only_masked_padding = gr.Slider(
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label="Inpaint only masked padding, pixels" + suffix(n),
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minimum=0,
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maximum=256,
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step=4,
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value=32,
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visible=True,
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elem_id=eid("ad_inpaint_only_masked_padding"),
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)
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w.ad_inpaint_only_masked.change(
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gr_interactive,
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inputs=w.ad_inpaint_only_masked,
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outputs=w.ad_inpaint_only_masked_padding,
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queue=False,
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)
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with gr.Column(variant="compact"):
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w.ad_use_inpaint_width_height = gr.Checkbox(
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label="Use separate width/height" + suffix(n),
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value=False,
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visible=True,
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elem_id=eid("ad_use_inpaint_width_height"),
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)
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w.ad_inpaint_width = gr.Slider(
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label="inpaint width" + suffix(n),
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minimum=64,
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maximum=2048,
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step=4,
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value=512,
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visible=True,
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elem_id=eid("ad_inpaint_width"),
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)
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w.ad_inpaint_height = gr.Slider(
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label="inpaint height" + suffix(n),
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minimum=64,
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maximum=2048,
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step=4,
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value=512,
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visible=True,
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elem_id=eid("ad_inpaint_height"),
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)
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w.ad_use_inpaint_width_height.change(
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lambda value: (gr_interactive(value), gr_interactive(value)),
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inputs=w.ad_use_inpaint_width_height,
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outputs=[w.ad_inpaint_width, w.ad_inpaint_height],
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queue=False,
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)
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with gr.Row():
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with gr.Column(variant="compact"):
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w.ad_use_steps = gr.Checkbox(
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label="Use separate steps" + suffix(n),
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value=False,
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visible=True,
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elem_id=eid("ad_use_steps"),
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)
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w.ad_steps = gr.Slider(
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label="ADetailer steps" + suffix(n),
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minimum=1,
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maximum=150,
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step=1,
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value=28,
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visible=True,
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elem_id=eid("ad_steps"),
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)
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w.ad_use_steps.change(
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gr_interactive,
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inputs=w.ad_use_steps,
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outputs=w.ad_steps,
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queue=False,
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)
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with gr.Column(variant="compact"):
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w.ad_use_cfg_scale = gr.Checkbox(
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label="Use separate CFG scale" + suffix(n),
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value=False,
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visible=True,
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elem_id=eid("ad_use_cfg_scale"),
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)
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w.ad_cfg_scale = gr.Slider(
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label="ADetailer CFG scale" + suffix(n),
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minimum=0.0,
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maximum=30.0,
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step=0.5,
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value=7.0,
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visible=True,
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elem_id=eid("ad_cfg_scale"),
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)
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w.ad_use_cfg_scale.change(
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gr_interactive,
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inputs=w.ad_use_cfg_scale,
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outputs=w.ad_cfg_scale,
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queue=False,
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)
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with gr.Row():
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with gr.Column(variant="compact"):
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w.ad_use_checkpoint = gr.Checkbox(
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label="Use separate checkpoint" + suffix(n),
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value=False,
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visible=True,
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elem_id=eid("ad_use_checkpoint"),
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)
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ckpts = ["Use same checkpoint", *webui_info.checkpoints_list]
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w.ad_checkpoint = gr.Dropdown(
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|
label="ADetailer checkpoint" + suffix(n),
|
|
choices=ckpts,
|
|
value=ckpts[0],
|
|
visible=True,
|
|
elem_id=eid("ad_checkpoint"),
|
|
)
|
|
|
|
with gr.Column(variant="compact"):
|
|
w.ad_use_vae = gr.Checkbox(
|
|
label="Use separate VAE" + suffix(n),
|
|
value=False,
|
|
visible=True,
|
|
elem_id=eid("ad_use_vae"),
|
|
)
|
|
|
|
vaes = ["Use same VAE", *webui_info.vae_list]
|
|
|
|
w.ad_vae = gr.Dropdown(
|
|
label="ADetailer VAE" + suffix(n),
|
|
choices=vaes,
|
|
value=vaes[0],
|
|
visible=True,
|
|
elem_id=eid("ad_vae"),
|
|
)
|
|
|
|
with gr.Row(), gr.Column(variant="compact"):
|
|
w.ad_use_sampler = gr.Checkbox(
|
|
label="Use separate sampler" + suffix(n),
|
|
value=False,
|
|
visible=True,
|
|
elem_id=eid("ad_use_sampler"),
|
|
)
|
|
|
|
with gr.Row():
|
|
w.ad_sampler = gr.Dropdown(
|
|
label="ADetailer sampler" + suffix(n),
|
|
choices=webui_info.sampler_names,
|
|
value=webui_info.sampler_names[0],
|
|
visible=True,
|
|
elem_id=eid("ad_sampler"),
|
|
)
|
|
|
|
scheduler_names = [
|
|
"Use same scheduler",
|
|
*webui_info.scheduler_names,
|
|
]
|
|
w.ad_scheduler = gr.Dropdown(
|
|
label="ADetailer scheduler" + suffix(n),
|
|
choices=scheduler_names,
|
|
value=scheduler_names[0],
|
|
visible=len(scheduler_names) > 1,
|
|
elem_id=eid("ad_scheduler"),
|
|
)
|
|
|
|
w.ad_use_sampler.change(
|
|
lambda value: (gr_interactive(value), gr_interactive(value)),
|
|
inputs=w.ad_use_sampler,
|
|
outputs=[w.ad_sampler, w.ad_scheduler],
|
|
queue=False,
|
|
)
|
|
|
|
with gr.Row():
|
|
with gr.Column(variant="compact"):
|
|
w.ad_use_noise_multiplier = gr.Checkbox(
|
|
label="Use separate noise multiplier" + suffix(n),
|
|
value=False,
|
|
visible=True,
|
|
elem_id=eid("ad_use_noise_multiplier"),
|
|
)
|
|
|
|
w.ad_noise_multiplier = gr.Slider(
|
|
label="Noise multiplier for img2img" + suffix(n),
|
|
minimum=0.5,
|
|
maximum=1.5,
|
|
step=0.01,
|
|
value=1.0,
|
|
visible=True,
|
|
elem_id=eid("ad_noise_multiplier"),
|
|
)
|
|
|
|
w.ad_use_noise_multiplier.change(
|
|
gr_interactive,
|
|
inputs=w.ad_use_noise_multiplier,
|
|
outputs=w.ad_noise_multiplier,
|
|
queue=False,
|
|
)
|
|
|
|
with gr.Column(variant="compact"):
|
|
w.ad_use_clip_skip = gr.Checkbox(
|
|
label="Use separate CLIP skip" + suffix(n),
|
|
value=False,
|
|
visible=True,
|
|
elem_id=eid("ad_use_clip_skip"),
|
|
)
|
|
|
|
w.ad_clip_skip = gr.Slider(
|
|
label="ADetailer CLIP skip" + suffix(n),
|
|
minimum=1,
|
|
maximum=12,
|
|
step=1,
|
|
value=1,
|
|
visible=True,
|
|
elem_id=eid("ad_clip_skip"),
|
|
)
|
|
|
|
w.ad_use_clip_skip.change(
|
|
gr_interactive,
|
|
inputs=w.ad_use_clip_skip,
|
|
outputs=w.ad_clip_skip,
|
|
queue=False,
|
|
)
|
|
|
|
with gr.Row(), gr.Column(variant="compact"):
|
|
w.ad_restore_face = gr.Checkbox(
|
|
label="Restore faces after ADetailer" + suffix(n),
|
|
value=False,
|
|
elem_id=eid("ad_restore_face"),
|
|
info="Apply face restoration after ADetailer.",
|
|
)
|
|
|
|
|
|
def controlnet(w: Widgets, n: int, is_img2img: bool):
|
|
eid = partial(elem_id, n=n, is_img2img=is_img2img)
|
|
cn_models = ["None", "Passthrough", *get_cn_models()]
|
|
|
|
with gr.Row(variant="panel"):
|
|
with gr.Column(variant="compact"):
|
|
w.ad_controlnet_model = gr.Dropdown(
|
|
label="ControlNet model" + suffix(n),
|
|
choices=cn_models,
|
|
value="None",
|
|
visible=True,
|
|
type="value",
|
|
interactive=controlnet_exists,
|
|
elem_id=eid("ad_controlnet_model"),
|
|
)
|
|
|
|
w.ad_controlnet_module = gr.Dropdown(
|
|
label="ControlNet module" + suffix(n),
|
|
choices=["None"],
|
|
value="None",
|
|
visible=False,
|
|
type="value",
|
|
interactive=controlnet_exists,
|
|
elem_id=eid("ad_controlnet_module"),
|
|
)
|
|
|
|
w.ad_controlnet_weight = gr.Slider(
|
|
label="ControlNet weight" + suffix(n),
|
|
minimum=0.0,
|
|
maximum=1.0,
|
|
step=0.01,
|
|
value=1.0,
|
|
visible=True,
|
|
interactive=controlnet_exists,
|
|
elem_id=eid("ad_controlnet_weight"),
|
|
)
|
|
|
|
w.ad_controlnet_model.change(
|
|
on_cn_model_update,
|
|
inputs=w.ad_controlnet_model,
|
|
outputs=w.ad_controlnet_module,
|
|
queue=False,
|
|
)
|
|
|
|
with gr.Column(variant="compact"):
|
|
w.ad_controlnet_guidance_start = gr.Slider(
|
|
label="ControlNet guidance start" + suffix(n),
|
|
minimum=0.0,
|
|
maximum=1.0,
|
|
step=0.01,
|
|
value=0.0,
|
|
visible=True,
|
|
interactive=controlnet_exists,
|
|
elem_id=eid("ad_controlnet_guidance_start"),
|
|
)
|
|
|
|
w.ad_controlnet_guidance_end = gr.Slider(
|
|
label="ControlNet guidance end" + suffix(n),
|
|
minimum=0.0,
|
|
maximum=1.0,
|
|
step=0.01,
|
|
value=1.0,
|
|
visible=True,
|
|
interactive=controlnet_exists,
|
|
elem_id=eid("ad_controlnet_guidance_end"),
|
|
)
|