Merge branch 'dev' into main

CHANGELOG.md

@@ -1,10 +1,20 @@
 # Changelog
 
+## 2023-07-28
+
+- v23.7.10
+- ultralytics, mediapipe import문 정리
+- traceback에서 컬러를 없앰 (api 때문), 라이브러리 버전도 보여주게 설정.
+- huggingface_hub, pydantic을 install.py에서 없앰
+- 안쓰는 컨트롤넷 관련 코드 삭제
+
+
 ## 2023-07-23
 
 - v23.7.9
 - `ultralytics.utils` ModuleNotFoundError 해결 (https://github.com/ultralytics/ultralytics/issues/3856)
 - `pydantic` 2.0 이상 버전 설치안되도록 함
+- `controlnet_dir` cmd args 문제 수정 (PR #107)
 
 ## 2023-07-20
 

README.md

@@ -44,15 +44,26 @@ Applied in this order: x, y offset → erosion/dilation → merge/invert.
 
 #### Inpainting
 
-![image](https://i.imgur.com/wyWlT1n.png)
-
-Each option corresponds to a corresponding option on the inpaint tab.
+Each option corresponds to a corresponding option on the inpaint tab. Therefore, please refer to the inpaint tab for usage details on how to use each option.
 
 ## ControlNet Inpainting
 
 You can use the ControlNet extension if you have ControlNet installed and ControlNet models.
 
-Support `inpaint, scribble, lineart, openpose, tile` controlnet models. Once you choose a model, the preprocessor is set automatically.
+Support `inpaint, scribble, lineart, openpose, tile` controlnet models. Once you choose a model, the preprocessor is set automatically. It works separately from the model set by the Controlnet extension.
+
+## Advanced Options
+
+API request example: [wiki/API](https://github.com/Bing-su/adetailer/wiki/API)
+
+`ui-config.json` entries: [wiki/ui-config.json](https://github.com/Bing-su/adetailer/wiki/ui-config.json)
+
+`[SEP], [SKIP]` tokens: [wiki/Advanced](https://github.com/Bing-su/adetailer/wiki/Advanced)
+
+## Media
+
+- 🎥 [どこよりも詳しいAfter Detailer (adetailer)の使い方① 【Stable Diffusion】](https://youtu.be/sF3POwPUWCE)
+- 🎥 [どこよりも詳しいAfter Detailer (adetailer)の使い方② 【Stable Diffusion】](https://youtu.be/urNISRdbIEg)
 
 ## Model
 
@@ -69,34 +80,12 @@ Support `inpaint, scribble, lineart, openpose, tile` controlnet models. Once you
 
 The yolo models can be found on huggingface [Bingsu/adetailer](https://huggingface.co/Bingsu/adetailer).
 
-### User Model
+### Additional Model
 
-Put your [ultralytics](https://github.com/ultralytics/ultralytics) model in `webui/models/adetailer`. The model name should end with `.pt` or `.pth`.
+Put your [ultralytics](https://github.com/ultralytics/ultralytics) yolo model in `webui/models/adetailer`. The model name should end with `.pt` or `.pth`.
 
 It must be a bbox detection or segment model and use all label.
 
-### Dataset
-
-Datasets used for training the yolo models are:
-
-#### Face
-
-- [Anime Face CreateML](https://universe.roboflow.com/my-workspace-mph8o/anime-face-createml)
-- [xml2txt](https://universe.roboflow.com/0oooooo0/xml2txt-njqx1)
-- [AN](https://universe.roboflow.com/sed-b8vkf/an-lfg5i)
-- [wider face](http://shuoyang1213.me/WIDERFACE/index.html)
-
-#### Hand
-
-- [AnHDet](https://universe.roboflow.com/1-yshhi/anhdet)
-- [hand-detection-fuao9](https://universe.roboflow.com/catwithawand/hand-detection-fuao9)
-
-#### Person
-
-- [coco2017](https://cocodataset.org/#home) (only person)
-- [AniSeg](https://github.com/jerryli27/AniSeg)
-- [skytnt/anime-segmentation](https://huggingface.co/datasets/skytnt/anime-segmentation)
-
 ## Example
 
 ![image](https://i.imgur.com/38RSxSO.png)

adetailer/__version__.py

@@ -1 +1 @@
-__version__ = "23.7.9"
+__version__ = "23.7.10"

adetailer/mediapipe.py

@@ -2,6 +2,7 @@ from __future__ import annotations
 
 from functools import partial
 
+import mediapipe as mp
 import numpy as np
 from PIL import Image, ImageDraw
 
@@ -28,8 +29,6 @@ def mediapipe_predict(
 def mediapipe_face_detection(
     model_type: int, image: Image.Image, confidence: float = 0.3
 ) -> PredictOutput:
-    import mediapipe as mp
-
     img_width, img_height = image.size
 
     mp_face_detection = mp.solutions.face_detection
@@ -85,8 +84,6 @@ def get_convexhull(points: np.ndarray) -> list[tuple[int, int]]:
 
 
 def mediapipe_face_mesh(image: Image.Image, confidence: float = 0.3) -> PredictOutput:
-    import mediapipe as mp
-
     mp_face_mesh = mp.solutions.face_mesh
     draw_util = mp.solutions.drawing_utils
     drawing_styles = mp.solutions.drawing_styles
@@ -130,8 +127,6 @@ def mediapipe_face_mesh(image: Image.Image, confidence: float = 0.3) -> PredictO
 def mediapipe_face_mesh_eyes_only(
     image: Image.Image, confidence: float = 0.3
 ) -> PredictOutput:
-    import mediapipe as mp
-
     mp_face_mesh = mp.solutions.face_mesh
 
     left_idx = np.array(list(mp_face_mesh.FACEMESH_LEFT_EYE)).flatten()

adetailer/traceback.py

@@ -3,6 +3,7 @@ from __future__ import annotations
 import io
 import platform
 import sys
+from importlib.metadata import version
 from typing import Any, Callable
 
 from rich.console import Console, Group
@@ -85,6 +86,17 @@ def ad_args(*args: Any) -> dict[str, Any]:
     }
 
 
+def library_version():
+    libraries = ["torch", "torchvision", "ultralytics", "mediapipe"]
+    d = {}
+    for lib in libraries:
+        try:
+            d[lib] = version(lib)
+        except Exception:
+            d[lib] = "Unknown"
+    return d
+
+
 def sys_info() -> dict[str, Any]:
     try:
         import launch
@@ -93,7 +105,7 @@ def sys_info() -> dict[str, Any]:
         commit = launch.commit_hash()
     except Exception:
         version = "Unknown (too old or vladmandic)"
-        commit = "-------"
+        commit = "Unknown"
 
     return {
         "Platform": platform.platform(),
@@ -101,6 +113,7 @@ def sys_info() -> dict[str, Any]:
         "Version": version,
         "Commit": commit,
         "Commandline": sys.argv,
+        "Libraries": library_version(),
     }
 
 
@@ -116,23 +129,12 @@ def get_table(title: str, data: dict[str, Any]) -> Table:
     return table
 
 
-def force_terminal_value():
-    try:
-        from modules.shared import cmd_opts
-
-        return True if hasattr(cmd_opts, "skip_torch_cuda_test") else None
-    except Exception:
-        return None
-
-
 def rich_traceback(func: Callable) -> Callable:
-    force_terminal = force_terminal_value()
-
     def wrapper(*args, **kwargs):
         string = io.StringIO()
         width = Console().width
         width = width - 4 if width > 4 else None
-        console = Console(file=string, force_terminal=force_terminal, width=width)
+        console = Console(file=string, width=width)
         try:
             return func(*args, **kwargs)
         except Exception as e:

adetailer/ultralytics.py

@@ -4,14 +4,14 @@ from pathlib import Path
 
 import cv2
 from PIL import Image
+from torchvision.transforms.functional import to_pil_image
+from ultralytics import YOLO
 
 from adetailer import PredictOutput
 from adetailer.common import create_mask_from_bbox
 
 
 def load_yolo(model_path: str | Path):
-    from ultralytics import YOLO
-
     try:
         return YOLO(model_path)
     except ModuleNotFoundError:
@@ -57,7 +57,5 @@ def mask_to_pil(masks, shape: tuple[int, int]) -> list[Image.Image]:
     shape: tuple[int, int]
         (width, height) of the original image
     """
-    from torchvision.transforms.functional import to_pil_image
-
     n = masks.shape[0]
     return [to_pil_image(masks[i], mode="L").resize(shape) for i in range(n)]

controlnet_ext/restore.py

@@ -5,12 +5,6 @@ from contextlib import contextmanager
 from modules import img2img, processing, shared
 
 
-def cn_restore_unet_hook(p, cn_latest_network):
-    if cn_latest_network is not None:
-        unet = p.sd_model.model.diffusion_model
-        cn_latest_network.restore(unet)
-
-
 class CNHijackRestore:
     def __init__(self):
         self.process = hasattr(processing, "__controlnet_original_process_images_inner")

install.py

@@ -46,8 +46,6 @@ def install():
         # requirements
         ("ultralytics", "8.0.97", None),
         ("mediapipe", "0.10.0", None),
-        ("huggingface_hub", None, None),
-        ("pydantic", "1.10.8", "1.999999.999999"),
         ("rich", "13.4.2", None),
         # ultralytics
         ("py-cpuinfo", None, None),

scripts/!adetailer.py

@@ -101,8 +101,6 @@ class AfterDetailerScript(scripts.Script):
         self.ultralytics_device = self.get_ultralytics_device()
 
         self.controlnet_ext = None
-        self.cn_script = None
-        self.cn_latest_network = None
 
     def __repr__(self):
         return f"{self.__class__.__name__}(version={__version__})"
@@ -347,9 +345,6 @@ class AfterDetailerScript(scripts.Script):
             filename = Path(filepath).stem
             if filename in script_names_set:
                 filtered_alwayson.append(script_object)
-            if filename == "controlnet":
-                self.cn_script = script_object
-                self.cn_latest_network = script_object.latest_network
 
         script_runner.alwayson_scripts = filtered_alwayson
         return script_runner, script_args

sd_webui/processing.py

@@ -157,6 +157,9 @@ if TYPE_CHECKING:
         comments: Any,
         iteration: int = 0,
         position_in_batch: int = 0,
+        use_main_prompt: bool = False,
+        index: int | None = None,
+        all_negative_prompts: list[str] | None = None,
     ) -> str:
         pass