Merge branch 'dev' into main

.pre-commit-config.yaml

@@ -12,8 +12,8 @@ repos:
     hooks:
       - id: isort
 
-  - repo: https://github.com/charliermarsh/ruff-pre-commit
-    rev: "v0.0.270"
+  - repo: https://github.com/astral-sh/ruff-pre-commit
+    rev: "v0.0.272"
     hooks:
       - id: ruff
         args: [--fix, --exit-non-zero-on-fix]

CHANGELOG.md

@@ -1,5 +1,12 @@
 # Changelog
 
+## 2023-06-20
+
+- v23.6.3
+- 컨트롤넷 inpaint 모델에 대해, 3가지 모듈을 사용할 수 있도록 함
+- Noise Multiplier 옵션 추가 (PR #149)
+- pydantic 최소 버전 1.10.8로 설정 (Issue #146)
+
 ## 2023-06-05
 
 - v23.6.2

adetailer/__version__.py

@@ -1 +1 @@
-__version__ = "23.6.2"
+__version__ = "23.6.3"

adetailer/args.py

@@ -2,7 +2,7 @@
 
 from collections import UserList
 from functools import cached_property, partial
-from typing import Any, Literal, NamedTuple, Union
+from typing import Any, Literal, NamedTuple, Optional, Union
 
 import pydantic
 from pydantic import (
@@ -13,6 +13,7 @@
     PositiveInt,
     confloat,
     constr,
+    root_validator,
 )
 
 cn_model_regex = r".*(inpaint|tile|scribble|lineart|openpose).*|^None$"
@@ -55,12 +56,23 @@ class ADetailerArgs(BaseModel, extra=Extra.forbid):
     ad_steps: PositiveInt = 28
     ad_use_cfg_scale: bool = False
     ad_cfg_scale: NonNegativeFloat = 7.0
+    ad_use_noise_multiplier: bool = False
+    ad_noise_multiplier: confloat(ge=0.5, le=1.5) = 1.0
     ad_restore_face: bool = False
     ad_controlnet_model: constr(regex=cn_model_regex) = "None"
+    ad_controlnet_module: Optional[constr(regex=r".*inpaint.*|^None$")] = None
     ad_controlnet_weight: confloat(ge=0.0, le=1.0) = 1.0
     ad_controlnet_guidance_start: confloat(ge=0.0, le=1.0) = 0.0
     ad_controlnet_guidance_end: confloat(ge=0.0, le=1.0) = 1.0
 
+    @root_validator
+    def ad_controlnt_module_validator(cls, values):  # noqa: N805
+        cn_model = values.get("ad_controlnet_model", "None")
+        cn_module = values.get("ad_controlnet_module", None)
+        if "inpaint" not in cn_model or cn_module == "None":
+            values["ad_controlnet_module"] = None
+        return values
+
     @staticmethod
     def ppop(
         p: dict[str, Any],
@@ -110,17 +122,24 @@ def extra_params(self, suffix: str = ""):
             "ADetailer use separate CFG scale",
             ["ADetailer use separate CFG scale", "ADetailer CFG scale"],
         )
+        ppop(
+            "ADetailer use separate noise multiplier",
+            ["ADetailer use separate noise multiplier", "ADetailer noise multiplier"],
+        )
+
         ppop("ADetailer restore face")
         ppop(
             "ADetailer ControlNet model",
             [
                 "ADetailer ControlNet model",
+                "ADetailer ControlNet module",
                 "ADetailer ControlNet weight",
                 "ADetailer ControlNet guidance start",
                 "ADetailer ControlNet guidance end",
             ],
             cond="None",
         )
+        ppop("ADetailer ControlNet module")
         ppop("ADetailer ControlNet weight", cond=1.0)
         ppop("ADetailer ControlNet guidance start", cond=0.0)
         ppop("ADetailer ControlNet guidance end", cond=1.0)
@@ -167,8 +186,11 @@ def is_enabled(self) -> bool:
     ("ad_steps", "ADetailer steps"),
     ("ad_use_cfg_scale", "ADetailer use separate CFG scale"),
     ("ad_cfg_scale", "ADetailer CFG scale"),
+    ("ad_use_noise_multiplier", "ADetailer use separate noise multiplier"),
+    ("ad_noise_multiplier", "ADetailer noise multiplier"),
     ("ad_restore_face", "ADetailer restore face"),
     ("ad_controlnet_model", "ADetailer ControlNet model"),
+    ("ad_controlnet_module", "ADetailer ControlNet module"),
     ("ad_controlnet_weight", "ADetailer ControlNet weight"),
     ("ad_controlnet_guidance_start", "ADetailer ControlNet guidance start"),
     ("ad_controlnet_guidance_end", "ADetailer ControlNet guidance end"),

adetailer/mediapipe.py

@@ -20,7 +20,8 @@ def mediapipe_predict(
     if model_type in mapping:
         func = mapping[model_type]
         return func(image, confidence)
-    raise RuntimeError(f"[-] ADetailer: Invalid mediapipe model type: {model_type}")
+    msg = f"[-] ADetailer: Invalid mediapipe model type: {model_type}"
+    raise RuntimeError(msg)
 
 
 def mediapipe_face_detection(

adetailer/ui.py

@@ -10,6 +10,12 @@
 from adetailer.args import AD_ENABLE, ALL_ARGS, MASK_MERGE_INVERT
 from controlnet_ext import controlnet_exists, get_cn_models
 
+cn_module_choices = [
+    "inpaint_global_harmonious",
+    "inpaint_only",
+    "inpaint_only+lama",
+]
+
 
 class Widgets(SimpleNamespace):
     def tolist(self):
@@ -40,6 +46,14 @@ def on_generate_click(state: dict, *values: Any):
     return state
 
 
+def on_cn_model_update(cn_model: str):
+    if "inpaint" in cn_model:
+        return gr.update(
+            visible=True, choices=cn_module_choices, value=cn_module_choices[0]
+        )
+    return gr.update(visible=False, choices=["None"], value="None")
+
+
 def elem_id(item_id: str, n: int, is_img2img: bool) -> str:
     tap = "img2img" if is_img2img else "txt2img"
     suf = suffix(n, "_")
@@ -90,7 +104,7 @@ def adui(
                 infotext_fields.extend(infofields)
 
     # components: [bool, dict, dict, ...]
-    components = [ad_enable] + states
+    components = [ad_enable, *states]
     return components, infotext_fields
 
 
@@ -106,7 +120,7 @@ def one_ui_group(
     eid = partial(elem_id, n=n, is_img2img=is_img2img)
 
     with gr.Row():
-        model_choices = model_list + ["None"] if n == 0 else ["None"] + model_list
+        model_choices = [*model_list, "None"] if n == 0 else ["None", *model_list]
 
         w.ad_model = gr.Dropdown(
             label="ADetailer model" + suffix(n),
@@ -164,7 +178,7 @@ def one_ui_group(
             fn=on_change, inputs=[state, widget], outputs=[state], queue=False
         )
 
-    all_inputs = [state] + w.tolist()
+    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
@@ -393,6 +407,31 @@ def inpainting(w: Widgets, n: int, is_img2img: bool):
                 )
 
         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,
+                )
+
             w.ad_restore_face = gr.Checkbox(
                 label="Restore faces after ADetailer" + suffix(n),
                 value=False,
@@ -402,7 +441,7 @@ def inpainting(w: Widgets, n: int, is_img2img: bool):
 
 def controlnet(w: Widgets, n: int, is_img2img: bool):
     eid = partial(elem_id, n=n, is_img2img=is_img2img)
-    cn_models = ["None"] + get_cn_models()
+    cn_models = ["None", *get_cn_models()]
 
     with gr.Row(variant="panel"):
         with gr.Column(variant="compact"):
@@ -416,6 +455,16 @@ def controlnet(w: Widgets, n: int, is_img2img: bool):
                 elem_id=eid("ad_controlnet_model"),
             )
 
+            w.ad_controlnet_module = gr.Dropdown(
+                label="ControlNet module" + suffix(n),
+                choices=cn_module_choices,
+                value="inpaint_global_harmonious",
+                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,
@@ -427,6 +476,13 @@ def controlnet(w: Widgets, n: int, is_img2img: bool):
                 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),

controlnet_ext/controlnet_ext.py

@@ -49,16 +49,22 @@ def init_controlnet(self):
         self.cn_models.extend(m for m in models if cn_model_regex.search(m))
 
     def update_scripts_args(
-        self, p, model: str, weight: float, guidance_start: float, guidance_end: float
+        self,
+        p,
+        model: str,
+        module: str | None,
+        weight: float,
+        guidance_start: float,
+        guidance_end: float,
     ):
         if (not self.cn_available) or model == "None":
             return
 
-        module = None
-        for m, v in cn_model_module.items():
-            if m in model:
-                module = v
-                break
+        if module is None:
+            for m, v in cn_model_module.items():
+                if m in model:
+                    module = v
+                    break
 
         cn_units = [
             self.external_cn.ControlNetUnit(

install.py

@@ -47,7 +47,7 @@ def install():
         ("ultralytics", "8.0.97", None),
         ("mediapipe", "0.10.0", None),
         ("huggingface_hub", None, None),
-        ("pydantic", None, None),
+        ("pydantic", "1.10.8", None),
         # mediapipe
         ("protobuf", "3.20.0", "3.20.9999"),
     ]

pyproject.toml

@@ -16,7 +16,7 @@ profile = "black"
 known_first_party = ["launch", "modules"]
 
 [tool.ruff]
-select = ["A", "B", "C4", "E", "F", "I001", "ISC", "N", "PIE", "PT", "RET", "SIM", "UP", "W"]
+select = ["A", "B", "C4", "C90", "E", "EM", "F", "FA", "I001", "ISC", "N", "PIE", "PT", "RET", "RUF", "SIM", "UP", "W"]
 ignore = ["B008", "B905", "E501", "F401", "UP007"]
 
 [tool.ruff.isort]

scripts/!adetailer.py

@@ -15,7 +15,7 @@
 import gradio as gr
 import torch
 
-import modules  # noqa: F401
+import modules
 from adetailer import (
     AFTER_DETAILER,
     __version__,
@@ -141,6 +141,7 @@ def update_controlnet_args(self, p, args: ADetailerArgs) -> None:
             self.controlnet_ext.update_scripts_args(
                 p,
                 model=args.ad_controlnet_model,
+                module=args.ad_controlnet_module,
                 weight=args.ad_controlnet_weight,
                 guidance_start=args.ad_controlnet_guidance_start,
                 guidance_end=args.ad_controlnet_guidance_end,
@@ -281,6 +282,11 @@ def get_cfg_scale(self, p, args: ADetailerArgs) -> float:
             return args.ad_cfg_scale
         return p.cfg_scale
 
+    def get_initial_noise_multiplier(self, p, args: ADetailerArgs) -> float | None:
+        if args.ad_use_noise_multiplier:
+            return args.ad_noise_multiplier
+        return None
+
     def infotext(self, p) -> str:
         return create_infotext(
             p, p.all_prompts, p.all_seeds, p.all_subseeds, None, 0, 0
@@ -339,6 +345,7 @@ def get_i2i_p(self, p, args: ADetailerArgs, image):
         width, height = self.get_width_height(p, args)
         steps = self.get_steps(p, args)
         cfg_scale = self.get_cfg_scale(p, args)
+        initial_noise_multiplier = self.get_initial_noise_multiplier(p, args)
 
         sampler_name = p.sampler_name
         if sampler_name in ["PLMS", "UniPC"]:
@@ -354,6 +361,7 @@ def get_i2i_p(self, p, args: ADetailerArgs, image):
             inpaint_full_res=args.ad_inpaint_only_masked,
             inpaint_full_res_padding=args.ad_inpaint_only_masked_padding,
             inpainting_mask_invert=0,
+            initial_noise_multiplier=initial_noise_multiplier,
             sd_model=p.sd_model,
             outpath_samples=p.outpath_samples,
             outpath_grids=p.outpath_grids,
@@ -647,7 +655,7 @@ def make_axis_on_xyz_grid():
     if xyz_grid is None:
         return
 
-    model_list = ["None"] + list(model_mapping.keys())
+    model_list = ["None", *model_mapping.keys()]
 
     def set_value(p, x, xs, *, field: str):
         if not hasattr(p, "adetailer_xyz"):
@@ -696,7 +704,7 @@ def set_value(p, x, xs, *, field: str):
             "[ADetailer] ControlNet model 1st",
             str,
             partial(set_value, field="ad_controlnet_model"),
-            choices=lambda: ["None"] + get_cn_models(),
+            choices=lambda: ["None", *get_cn_models()],
         ),
     ]