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Bingsu
2023-05-15 14:19:46 +09:00
parent 8df934c3ae cde0acd38f
commit 44a4cbf404
6 changed files with 420 additions and 337 deletions
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9
CHANGELOG.md
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@@ -1,5 +1,14 @@
# Changelog
### 2023-05-15
- v23.5.13
- `[SEP]`으로 ad prompt를 분리하여 적용하는 기능 추가
- enable checker를 다시 pydantic으로 변경함
- ui 관련 함수를 adetailer.ui 폴더로 분리함
- controlnet을 사용할 때 모든 controlnet unit 비활성화
- adetailer 폴더가 없으면 만들게 함
### 2023-05-13
- v23.5.12

7
adetailer/__init__.py
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@@ -1,16 +1,19 @@
from .__version__ import __version__
from .args import AD_ENABLE, ALL_ARGS, ADetailerArgs, enable_check
from .args import AD_ENABLE, ALL_ARGS, ADetailerArgs, EnableChecker
from .common import PredictOutput, get_models
from .mediapipe import mediapipe_predict
from .ultralytics import ultralytics_predict
AFTER_DETAILER = "After Detailer"
__all__ = [
"__version__",
"AD_ENABLE",
"ADetailerArgs",
"AFTER_DETAILER",
"ALL_ARGS",
"EnableChecker",
"PredictOutput",
"enable_check",
"get_models",
"mediapipe_predict",
"ultralytics_predict",

2
adetailer/__version__.py
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@@ -1 +1 @@
__version__ = "23.5.12"
__version__ = "23.5.13"

26
adetailer/args.py
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@@ -1,9 +1,8 @@
from __future__ import annotations
from collections import UserList
from collections.abc import Mapping
from functools import cached_property
from typing import Any, NamedTuple
from typing import Any, NamedTuple, Optional, Union
import pydantic
from pydantic import (
@@ -109,20 +108,17 @@ class ADetailerArgs(BaseModel, extra=Extra.forbid):
return params
def enable_check(*args: Any) -> bool:
if not args:
return False
a0: bool | Mapping = args[0]
ad_model = ALL_ARGS[0].attr
class EnableChecker(BaseModel):
a0: Union[bool, dict]
a1: Optional[dict]
if isinstance(a0, Mapping):
return a0.get(ad_model, "None") != "None"
if len(args) == 1:
return False
a1 = args[1]
a1_model = a1.get(ad_model, "None")
return a0 and a1_model != "None"
def is_enabled(self) -> bool:
ad_model = ALL_ARGS[0].attr
if isinstance(self.a0, dict):
return self.a0.get(ad_model, "None") != "None"
if self.a1 is None:
return False
return self.a0 and self.a1.get(ad_model, "None") != "None"
_all_args = [

319
adetailer/ui.py Normal file
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@@ -0,0 +1,319 @@
from __future__ import annotations
from functools import partial
from typing import Any
import gradio as gr
from adetailer import AFTER_DETAILER
from adetailer.args import AD_ENABLE, ALL_ARGS
from controlnet_ext import controlnet_exists, get_cn_inpaint_models
class Widgets:
def tolist(self):
return [getattr(self, attr) for attr in ALL_ARGS.attrs]
def gr_interactive(value: bool = True):
return gr.update(interactive=value)
def ordinal(n: int) -> str:
d = {1: "st", 2: "nd", 3: "rd"}
return str(n) + ("th" if 11 <= n % 100 <= 13 else d.get(n % 10, "th"))
def suffix(n: int, c: str = " ") -> str:
return "" if n == 0 else c + ordinal(n + 1)
def on_widget_change(state: dict, value: Any, *, attr: str):
state[attr] = value
return state
def on_generate_click(state: dict, *values: Any):
for attr, value in zip(ALL_ARGS.attrs, values):
state[attr] = value
return state
def adui(
num_models: int,
is_img2img: bool,
model_list: list[str],
t2i_button: gr.Button,
i2i_button: gr.Button,
):
widgets = []
states = []
infotext_fields = []
with gr.Accordion(AFTER_DETAILER, open=False, elem_id="AD_main_acc"):
with gr.Row():
ad_enable = gr.Checkbox(
label="Enable ADetailer",
value=False,
visible=True,
)
infotext_fields.append((ad_enable, AD_ENABLE.name))
with gr.Group(), gr.Tabs():
for n in range(num_models):
with gr.Tab(ordinal(n + 1)):
w, state, infofields = one_ui_group(
n=n,
is_img2img=is_img2img,
model_list=model_list,
t2i_button=t2i_button,
i2i_button=i2i_button,
)
widgets.append(w)
states.append(state)
infotext_fields.extend(infofields)
# components: [bool, dict, dict, ...]
components = [ad_enable] + states
return components, infotext_fields
def one_ui_group(
n: int,
is_img2img: bool,
model_list: list[str],
t2i_button: gr.Button,
i2i_button: gr.Button,
):
w = Widgets()
state = gr.State({})
with gr.Row():
model_choices = model_list if n == 0 else ["None"] + model_list
w.ad_model = gr.Dropdown(
label="ADetailer model" + suffix(n),
choices=model_choices,
value=model_choices[0],
visible=True,
type="value",
)
with gr.Group():
with gr.Row(elem_id="AD_toprow_prompt" + suffix(n, "_")):
w.ad_prompt = gr.Textbox(
label="ad_prompt" + suffix(n),
show_label=False,
lines=3,
placeholder="ADetailer prompt" + suffix(n),
elem_id="AD_prompt" + suffix(n, "_"),
)
with gr.Row(elem_id="AD_toprow_negative_prompt" + suffix(n, "_")):
w.ad_negative_prompt = gr.Textbox(
label="ad_negative_prompt" + suffix(n),
show_label=False,
lines=2,
placeholder="ADetailer negative prompt" + suffix(n),
elem_id="AD_negative_prompt" + suffix(n, "_"),
)
with gr.Group():
with gr.Row():
w.ad_conf = gr.Slider(
label="Detection model confidence threshold %" + suffix(n),
minimum=0,
maximum=100,
step=1,
value=30,
visible=True,
)
w.ad_dilate_erode = gr.Slider(
label="Mask erosion (-) / dilation (+)" + suffix(n),
minimum=-128,
maximum=128,
step=4,
value=32,
visible=True,
)
with gr.Row():
w.ad_x_offset = gr.Slider(
label="Mask x(→) offset" + suffix(n),
minimum=-200,
maximum=200,
step=1,
value=0,
visible=True,
)
w.ad_y_offset = gr.Slider(
label="Mask y(↑) offset" + suffix(n),
minimum=-200,
maximum=200,
step=1,
value=0,
visible=True,
)
with gr.Row():
w.ad_mask_blur = gr.Slider(
label="Inpaint mask blur" + suffix(n),
minimum=0,
maximum=64,
step=1,
value=4,
visible=True,
)
w.ad_denoising_strength = gr.Slider(
label="Inpaint denoising strength" + suffix(n),
minimum=0.0,
maximum=1.0,
step=0.01,
value=0.4,
visible=True,
)
with gr.Group():
with gr.Row():
with gr.Column(variant="compact"):
w.ad_inpaint_full_res = gr.Checkbox(
label="Inpaint at full resolution " + suffix(n),
value=True,
visible=True,
)
w.ad_inpaint_full_res_padding = gr.Slider(
label="Inpaint at full resolution padding, pixels " + suffix(n),
minimum=0,
maximum=256,
step=4,
value=0,
visible=True,
)
w.ad_inpaint_full_res.change(
gr_interactive,
inputs=w.ad_inpaint_full_res,
outputs=w.ad_inpaint_full_res_padding,
queue=False,
)
with gr.Column(variant="compact"):
w.ad_use_inpaint_width_height = gr.Checkbox(
label="Use separate width/height" + suffix(n),
value=False,
visible=True,
)
w.ad_inpaint_width = gr.Slider(
label="inpaint width" + suffix(n),
minimum=64,
maximum=2048,
step=4,
value=512,
visible=True,
)
w.ad_inpaint_height = gr.Slider(
label="inpaint height" + suffix(n),
minimum=64,
maximum=2048,
step=4,
value=512,
visible=True,
)
w.ad_use_inpaint_width_height.change(
lambda value: (gr_interactive(value), gr_interactive(value)),
inputs=w.ad_use_inpaint_width_height,
outputs=[w.ad_inpaint_width, w.ad_inpaint_height],
queue=False,
)
with gr.Row():
with gr.Column(variant="compact"):
w.ad_use_steps = gr.Checkbox(
label="Use separate steps" + suffix(n),
value=False,
visible=True,
)
w.ad_steps = gr.Slider(
label="ADetailer steps" + suffix(n),
minimum=1,
maximum=150,
step=1,
value=28,
visible=True,
)
w.ad_use_steps.change(
gr_interactive,
inputs=w.ad_use_steps,
outputs=w.ad_steps,
queue=False,
)
with gr.Column(variant="compact"):
w.ad_use_cfg_scale = gr.Checkbox(
label="Use separate CFG scale" + suffix(n),
value=False,
visible=True,
)
w.ad_cfg_scale = gr.Slider(
label="ADetailer CFG scale" + suffix(n),
minimum=0.0,
maximum=30.0,
step=0.5,
value=7.0,
visible=True,
)
w.ad_use_cfg_scale.change(
gr_interactive,
inputs=w.ad_use_cfg_scale,
outputs=w.ad_cfg_scale,
queue=False,
)
with gr.Group(), gr.Row(variant="panel"):
cn_inpaint_models = ["None"] + get_cn_inpaint_models()
w.ad_controlnet_model = gr.Dropdown(
label="ControlNet model" + suffix(n),
choices=cn_inpaint_models,
value="None",
visible=True,
type="value",
interactive=controlnet_exists,
)
w.ad_controlnet_weight = gr.Slider(
label="ControlNet weight" + suffix(n),
minimum=0.0,
maximum=1.0,
step=0.05,
value=1.0,
visible=True,
interactive=controlnet_exists,
)
for attr in ALL_ARGS.attrs:
widget = getattr(w, attr)
on_change = partial(on_widget_change, attr=attr)
widget.change(
fn=on_change, inputs=[state, widget], outputs=[state], queue=False
)
all_inputs = [state] + w.tolist()
target_button = i2i_button if is_img2img else t2i_button
target_button.click(
fn=on_generate_click, inputs=all_inputs, outputs=state, queue=False
)
infotext_fields = [(getattr(w, attr), name + suffix(n)) for attr, name in ALL_ARGS]
return w, state, infotext_fields

394
scripts/!adetailer.py
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@@ -1,11 +1,11 @@
from __future__ import annotations
import os
import platform
import re
import sys
import traceback
from collections.abc import Mapping
from copy import copy, deepcopy
from functools import partial
from pathlib import Path
from textwrap import dedent
from typing import Any
@@ -15,17 +15,18 @@ import torch
import modules # noqa: F401
from adetailer import (
AD_ENABLE,
AFTER_DETAILER,
ALL_ARGS,
ADetailerArgs,
EnableChecker,
__version__,
enable_check,
get_models,
mediapipe_predict,
ultralytics_predict,
)
from adetailer.common import mask_preprocess
from controlnet_ext import ControlNetExt, controlnet_exists, get_cn_inpaint_models
from adetailer.ui import adui, ordinal, suffix
from controlnet_ext import ControlNetExt, controlnet_exists
from modules import images, safe, script_callbacks, scripts, shared
from modules.paths import data_path, models_path
from modules.processing import (
@@ -43,23 +44,23 @@ try:
except Exception:
pass
AFTER_DETAILER = "After Detailer"
no_huggingface = getattr(cmd_opts, "ad_no_huggingface", False)
adetailer_dir = Path(models_path, "adetailer")
model_mapping = get_models(adetailer_dir, huggingface=not no_huggingface)
txt2img_submit_button = img2img_submit_button = None
if (
not adetailer_dir.exists()
and adetailer_dir.parent.exists()
and os.access(adetailer_dir.parent, os.W_OK)
):
adetailer_dir.mkdir()
print(
f"[-] ADetailer initialized. version: {__version__}, num models: {len(model_mapping)}"
)
class Widgets:
def tolist(self):
return [getattr(self, attr) for attr in ALL_ARGS.attrs]
class ChangeTorchLoad:
def __enter__(self):
self.orig = torch.load
@@ -69,30 +70,6 @@ class ChangeTorchLoad:
torch.load = self.orig
def gr_interactive(value: bool = True):
return gr.update(interactive=value)
def ordinal(n: int) -> str:
d = {1: "st", 2: "nd", 3: "rd"}
return str(n) + ("th" if 11 <= n % 100 <= 13 else d.get(n % 10, "th"))
def suffix(n: int, c: str = " ") -> str:
return "" if n == 0 else c + ordinal(n + 1)
def on_widget_change(state: dict, value: Any, *, attr: str):
state[attr] = value
return state
def on_generate_click(state: dict, *values: Any):
for attr, value in zip(ALL_ARGS.attrs, values):
state[attr] = value
return state
class AfterDetailerScript(scripts.Script):
def __init__(self):
super().__init__()
@@ -107,266 +84,18 @@ class AfterDetailerScript(scripts.Script):
def ui(self, is_img2img):
num_models = opts.data.get("ad_max_models", 2)
widgets = []
states = []
self.infotext_fields = []
with gr.Accordion(AFTER_DETAILER, open=False, elem_id="AD_main_acc"):
with gr.Row():
ad_enable = gr.Checkbox(
label="Enable ADetailer",
value=False,
visible=True,
)
self.infotext_fields.append((ad_enable, AD_ENABLE.name))
with gr.Group(), gr.Tabs():
for n in range(num_models):
with gr.Tab(ordinal(n + 1)):
w, state, infofields = self.one_ui_group(n, is_img2img)
widgets.append(w)
states.append(state)
self.infotext_fields.extend(infofields)
# return: [bool, dict, dict, ...]
return [ad_enable] + states
def one_ui_group(self, n: int, is_img2img: bool):
model_list = list(model_mapping.keys())
w = Widgets()
state = gr.State({})
with gr.Row():
model_choices = model_list if n == 0 else ["None"] + model_list
w.ad_model = gr.Dropdown(
label="ADetailer model" + suffix(n),
choices=model_choices,
value=model_choices[0],
visible=True,
type="value",
)
with gr.Group():
with gr.Row(elem_id="AD_toprow_prompt" + suffix(n, "_")):
w.ad_prompt = gr.Textbox(
label="ad_prompt" + suffix(n),
show_label=False,
lines=3,
placeholder="ADetailer prompt" + suffix(n),
elem_id="AD_prompt" + suffix(n, "_"),
)
with gr.Row(elem_id="AD_toprow_negative_prompt" + suffix(n, "_")):
w.ad_negative_prompt = gr.Textbox(
label="ad_negative_prompt" + suffix(n),
show_label=False,
lines=2,
placeholder="ADetailer negative prompt" + suffix(n),
elem_id="AD_negative_prompt" + suffix(n, "_"),
)
with gr.Group():
with gr.Row():
w.ad_conf = gr.Slider(
label="Detection model confidence threshold %" + suffix(n),
minimum=0,
maximum=100,
step=1,
value=30,
visible=True,
)
w.ad_dilate_erode = gr.Slider(
label="Mask erosion (-) / dilation (+)" + suffix(n),
minimum=-128,
maximum=128,
step=4,
value=32,
visible=True,
)
with gr.Row():
w.ad_x_offset = gr.Slider(
label="Mask x(→) offset" + suffix(n),
minimum=-200,
maximum=200,
step=1,
value=0,
visible=True,
)
w.ad_y_offset = gr.Slider(
label="Mask y(↑) offset" + suffix(n),
minimum=-200,
maximum=200,
step=1,
value=0,
visible=True,
)
with gr.Row():
w.ad_mask_blur = gr.Slider(
label="Inpaint mask blur" + suffix(n),
minimum=0,
maximum=64,
step=1,
value=4,
visible=True,
)
w.ad_denoising_strength = gr.Slider(
label="Inpaint denoising strength" + suffix(n),
minimum=0.0,
maximum=1.0,
step=0.01,
value=0.4,
visible=True,
)
with gr.Group():
with gr.Row():
with gr.Column(variant="compact"):
w.ad_inpaint_full_res = gr.Checkbox(
label="Inpaint at full resolution " + suffix(n),
value=True,
visible=True,
)
w.ad_inpaint_full_res_padding = gr.Slider(
label="Inpaint at full resolution padding, pixels " + suffix(n),
minimum=0,
maximum=256,
step=4,
value=0,
visible=True,
)
w.ad_inpaint_full_res.change(
gr_interactive,
inputs=w.ad_inpaint_full_res,
outputs=w.ad_inpaint_full_res_padding,
queue=False,
)
with gr.Column(variant="compact"):
w.ad_use_inpaint_width_height = gr.Checkbox(
label="Use separate width/height" + suffix(n),
value=False,
visible=True,
)
w.ad_inpaint_width = gr.Slider(
label="inpaint width" + suffix(n),
minimum=64,
maximum=2048,
step=4,
value=512,
visible=True,
)
w.ad_inpaint_height = gr.Slider(
label="inpaint height" + suffix(n),
minimum=64,
maximum=2048,
step=4,
value=512,
visible=True,
)
w.ad_use_inpaint_width_height.change(
lambda value: (gr_interactive(value), gr_interactive(value)),
inputs=w.ad_use_inpaint_width_height,
outputs=[w.ad_inpaint_width, w.ad_inpaint_height],
queue=False,
)
with gr.Row():
with gr.Column(variant="compact"):
w.ad_use_steps = gr.Checkbox(
label="Use separate steps" + suffix(n),
value=False,
visible=True,
)
w.ad_steps = gr.Slider(
label="ADetailer steps" + suffix(n),
minimum=1,
maximum=150,
step=1,
value=28,
visible=True,
)
w.ad_use_steps.change(
gr_interactive,
inputs=w.ad_use_steps,
outputs=w.ad_steps,
queue=False,
)
with gr.Column(variant="compact"):
w.ad_use_cfg_scale = gr.Checkbox(
label="Use separate CFG scale" + suffix(n),
value=False,
visible=True,
)
w.ad_cfg_scale = gr.Slider(
label="ADetailer CFG scale" + suffix(n),
minimum=0.0,
maximum=30.0,
step=0.5,
value=7.0,
visible=True,
)
w.ad_use_cfg_scale.change(
gr_interactive,
inputs=w.ad_use_cfg_scale,
outputs=w.ad_cfg_scale,
queue=False,
)
with gr.Group(), gr.Row(variant="panel"):
cn_inpaint_models = ["None"] + get_cn_inpaint_models()
w.ad_controlnet_model = gr.Dropdown(
label="ControlNet model" + suffix(n),
choices=cn_inpaint_models,
value="None",
visible=True,
type="value",
interactive=controlnet_exists,
)
w.ad_controlnet_weight = gr.Slider(
label="ControlNet weight" + suffix(n),
minimum=0.0,
maximum=1.0,
step=0.05,
value=1.0,
visible=True,
interactive=controlnet_exists,
)
for attr in ALL_ARGS.attrs:
widget = getattr(w, attr)
on_change = partial(on_widget_change, attr=attr)
widget.change(
fn=on_change, inputs=[state, widget], outputs=[state], queue=False
)
all_inputs = [state] + w.tolist()
target_button = img2img_submit_button if is_img2img else txt2img_submit_button
target_button.click(
fn=on_generate_click, inputs=all_inputs, outputs=state, queue=False
components, infotext_fields = adui(
num_models,
is_img2img,
model_list,
txt2img_submit_button,
img2img_submit_button,
)
infotext_fields = [
(getattr(w, attr), name + suffix(n)) for attr, name in ALL_ARGS
]
return w, state, infotext_fields
self.infotext_fields = infotext_fields
return components
def init_controlnet_ext(self) -> None:
if self.controlnet_ext is not None:
@@ -403,7 +132,10 @@ class AfterDetailerScript(scripts.Script):
input: {args_!r}
"""
raise ValueError(dedent(message))
return enable_check(*args_)
a0 = args_[0]
a1 = args_[1] if len(args_) > 1 else None
checker = EnableChecker(a0=a0, a1=a1)
return checker.is_enabled()
def get_args(self, *args_) -> list[ADetailerArgs]:
"""
@@ -453,28 +185,33 @@ class AfterDetailerScript(scripts.Script):
return device
def get_prompt(self, p, args: ADetailerArgs) -> tuple[str, str]:
def prompt_blank_replacement(
self, all_prompts: list[str], i: int, default: str
) -> str:
if not all_prompts:
return default
if i < len(all_prompts):
return all_prompts[i]
j = i % len(all_prompts)
return all_prompts[j]
def _get_prompt(
self, ad_prompt: str, all_prompts: list[str], i: int, default: str
) -> list[str]:
prompts = re.split(r"\s*\[SEP\]\s*", ad_prompt)
blank_replacement = self.prompt_blank_replacement(all_prompts, i, default)
for n in range(len(prompts)):
if not prompts[n]:
prompts[n] = blank_replacement
return prompts
def get_prompt(self, p, args: ADetailerArgs) -> tuple[list[str], list[str]]:
i = p._idx
if args.ad_prompt:
prompt = args.ad_prompt
elif not p.all_prompts:
prompt = p.prompt
elif i < len(p.all_prompts):
prompt = p.all_prompts[i]
else:
j = i % len(p.all_prompts)
prompt = p.all_prompts[j]
if args.ad_negative_prompt:
negative_prompt = args.ad_negative_prompt
elif not p.all_negative_prompts:
negative_prompt = p.negative_prompt
elif i < len(p.all_negative_prompts):
negative_prompt = p.all_negative_prompts[i]
else:
j = i % len(p.all_negative_prompts)
negative_prompt = p.all_negative_prompts[j]
prompt = self._get_prompt(args.ad_prompt, p.all_prompts, i, p.prompt)
negative_prompt = self._get_prompt(
args.ad_negative_prompt, p.all_negative_prompts, i, p.negative_prompt
)
return prompt, negative_prompt
@@ -531,10 +268,11 @@ class AfterDetailerScript(scripts.Script):
def script_filter(self, p, args: ADetailerArgs):
script_runner = copy(p.scripts)
script_args = deepcopy(p.script_args)
ad_only_seleted_scripts = opts.data.get("ad_only_seleted_scripts", True)
if not ad_only_seleted_scripts:
return script_runner
return script_runner, script_args
default = "dynamic_prompting,dynamic_thresholding,wildcards,wildcard_recursive"
ad_script_names = opts.data.get("ad_script_names", default)
@@ -544,6 +282,7 @@ class AfterDetailerScript(scripts.Script):
for name in (script_name, script_name.strip())
}
if args.ad_controlnet_model != "None":
self.disable_controlnet_units(script_args)
script_names_set.add("controlnet")
filtered_alwayson = []
@@ -554,10 +293,16 @@ class AfterDetailerScript(scripts.Script):
filtered_alwayson.append(script_object)
script_runner.alwayson_scripts = filtered_alwayson
return script_runner
return script_runner, script_args
def disable_controlnet_units(self, script_args: list[Any]) -> None:
for obj in script_args:
if "controlnet" in obj.__class__.__name__.lower() and hasattr(
obj, "enabled"
):
obj.enabled = False
def get_i2i_p(self, p, args: ADetailerArgs, image):
prompt, negative_prompt = self.get_prompt(p, args)
seed, subseed = self.get_seed(p)
width, height = self.get_width_height(p, args)
steps = self.get_steps(p, args)
@@ -580,8 +325,8 @@ class AfterDetailerScript(scripts.Script):
sd_model=p.sd_model,
outpath_samples=p.outpath_samples,
outpath_grids=p.outpath_grids,
prompt=prompt,
negative_prompt=negative_prompt,
prompt="", # replace later
negative_prompt="",
styles=p.styles,
seed=seed,
subseed=subseed,
@@ -601,8 +346,7 @@ class AfterDetailerScript(scripts.Script):
do_not_save_grid=True,
)
i2i.scripts = self.script_filter(p, args)
i2i.script_args = deepcopy(p.script_args)
i2i.scripts, i2i.script_args = self.script_filter(p, args)
i2i._disable_adetailer = True
if args.ad_controlnet_model != "None":
@@ -632,6 +376,16 @@ class AfterDetailerScript(scripts.Script):
raise ValueError(msg)
return model_mapping[name]
def i2i_prompts_replace(
self, i2i, prompts: list[str], negative_prompts: list[str], j: int
):
i1 = min(j, len(prompts) - 1)
i2 = min(j, len(negative_prompts) - 1)
prompt = prompts[i1]
negative_prompt = negative_prompts[i2]
i2i.prompt = prompt
i2i.negative_prompt = negative_prompt
def process(self, p, *args_):
if getattr(p, "_disable_adetailer", False):
return
@@ -653,6 +407,7 @@ class AfterDetailerScript(scripts.Script):
i2i = self.get_i2i_p(p, args, pp.image)
seed, subseed = self.get_seed(p)
ad_prompts, ad_negatives = self.get_prompt(p, args)
is_mediapipe = args.ad_model.lower().startswith("mediapipe")
@@ -697,6 +452,7 @@ class AfterDetailerScript(scripts.Script):
p2 = copy(i2i)
for j in range(steps):
p2.image_mask = masks[j]
self.i2i_prompts_replace(p2, ad_prompts, ad_negatives, j)
processed = process_images(p2)
p2 = copy(i2i)