Merge branch 'dev' into main

.pre-commit-config.yaml

@@ -1,6 +1,6 @@
 repos:
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.4.0
+    rev: v4.5.0
     hooks:
       - id: trailing-whitespace
         args: [--markdown-linebreak-ext=md]

CHANGELOG.md

@@ -1,5 +1,11 @@
 # Changelog
 
+## 2023-10-15
+
+- v23.10.1
+- xyz grid에 prompt S/R 추가
+- img2img에서 steps가 1일때 에러가 발생하는 샘플러의 처리를 위해 샘플러 이름도 변경하게 수정
+
 ## 2023-10-07
 
 - v23.10.0

adetailer/__version__.py

@@ -1 +1 @@
-__version__ = "23.10.0"
+__version__ = "23.10.1"

adetailer/mediapipe.py

@@ -2,6 +2,7 @@ from __future__ import annotations
 
 from functools import partial
 
+import cv2
 import numpy as np
 from PIL import Image, ImageDraw
 
@@ -67,23 +68,6 @@ def mediapipe_face_detection(
     return PredictOutput(bboxes=bboxes, masks=masks, preview=preview)
 
 
-def get_convexhull(points: np.ndarray) -> list[tuple[int, int]]:
-    """
-    Parameters
-    ----------
-      points: An ndarray of shape (n, 2) containing the 2D points.
-
-    Returns
-    -------
-      list[tuple[int, int]]: Input for the draw.polygon function
-    """
-    from scipy.spatial import ConvexHull
-
-    hull = ConvexHull(points)
-    vertices = hull.vertices
-    return list(zip(points[vertices, 0], points[vertices, 1]))
-
-
 def mediapipe_face_mesh(image: Image.Image, confidence: float = 0.3) -> PredictOutput:
     import mediapipe as mp
 
@@ -114,8 +98,8 @@ def mediapipe_face_mesh(image: Image.Image, confidence: float = 0.3) -> PredictO
                 connection_drawing_spec=drawing_styles.get_default_face_mesh_tesselation_style(),
             )
 
-            points = np.array([(land.x * w, land.y * h) for land in landmarks.landmark])
-            outline = get_convexhull(points)
+            points = np.intp([(land.x * w, land.y * h) for land in landmarks.landmark])
+            outline = cv2.convexHull(points).reshape(-1).tolist()
 
             mask = Image.new("L", image.size, "black")
             draw = ImageDraw.Draw(mask)
@@ -152,11 +136,11 @@ def mediapipe_face_mesh_eyes_only(
         masks = []
 
         for landmarks in pred.multi_face_landmarks:
-            points = np.array([(land.x * w, land.y * h) for land in landmarks.landmark])
+            points = np.intp([(land.x * w, land.y * h) for land in landmarks.landmark])
             left_eyes = points[left_idx]
             right_eyes = points[right_idx]
-            left_outline = get_convexhull(left_eyes)
-            right_outline = get_convexhull(right_eyes)
+            left_outline = cv2.convexHull(left_eyes).reshape(-1).tolist()
+            right_outline = cv2.convexHull(right_eyes).reshape(-1).tolist()
 
             mask = Image.new("L", image.size, "black")
             draw = ImageDraw.Draw(mask)

adetailer/ui.py

@@ -217,7 +217,7 @@ def detection(w: Widgets, n: int, is_img2img: bool):
             )
             w.ad_mask_k_largest = gr.Slider(
                 label="Mask only the top k largest (0 to disable)" + suffix(n),
-                minumum=0,
+                minimum=0,
                 maximum=10,
                 step=1,
                 value=0,

install.py

@@ -44,8 +44,8 @@ def run_pip(*args):
 def install():
     deps = [
         # requirements
-        ("ultralytics", "8.0.194", None),
-        ("mediapipe", "0.10.5", None),
+        ("ultralytics", "8.0.198", None),
+        ("mediapipe", "0.10.7", None),
         ("rich", "13.0.0", None),
         # mediapipe
         ("protobuf", "3.20", "3.9999"),

scripts/!adetailer.py

@@ -10,7 +10,7 @@ from copy import copy, deepcopy
 from functools import partial
 from pathlib import Path
 from textwrap import dedent
-from typing import Any
+from typing import Any, NamedTuple
 
 import gradio as gr
 import torch
@@ -100,6 +100,22 @@ def preseve_prompts(p):
         p.all_negative_prompts = all_ng
 
 
+@contextmanager
+def change_skip_img2img_args(p):
+    if not hasattr(p, "_ad_skip_img2img") or not p._ad_skip_img2img:
+        yield
+    else:
+        steps = p.steps
+        sampler_name = p.sampler_name
+        try:
+            p.steps = p._ad_orig_steps
+            p.sampler_name = p._ad_orig_sampler_name
+            yield
+        finally:
+            p.steps = steps
+            p.sampler_name = sampler_name
+
+
 class AfterDetailerScript(scripts.Script):
     def __init__(self):
         super().__init__()
@@ -201,7 +217,9 @@ class AfterDetailerScript(scripts.Script):
             p._ad_skip_img2img = args_[1]
             if args_[1]:
                 p._ad_orig_steps = p.steps
+                p._ad_orig_sampler_name = p.sampler_name
                 p.steps = 1
+                p.sampler_name = "Euler"
         else:
             p._ad_skip_img2img = False
 
@@ -270,7 +288,12 @@ class AfterDetailerScript(scripts.Script):
         return all_prompts[j]
 
     def _get_prompt(
-        self, ad_prompt: str, all_prompts: list[str], i: int, default: str
+        self,
+        ad_prompt: str,
+        all_prompts: list[str],
+        i: int,
+        default: str,
+        replacements: list[PromptSR],
     ) -> list[str]:
         prompts = re.split(r"\s*\[SEP\]\s*", ad_prompt)
         blank_replacement = self.prompt_blank_replacement(all_prompts, i, default)
@@ -279,14 +302,22 @@ class AfterDetailerScript(scripts.Script):
                 prompts[n] = blank_replacement
             elif "[PROMPT]" in prompts[n]:
                 prompts[n] = prompts[n].replace("[PROMPT]", f" {blank_replacement} ")
+
+            for pair in replacements:
+                prompts[n] = prompts[n].replace(pair.s, pair.r)
         return prompts
 
     def get_prompt(self, p, args: ADetailerArgs) -> tuple[list[str], list[str]]:
         i = p._ad_idx
+        prompt_sr = p._ad_xyz_prompt_sr if hasattr(p, "_ad_xyz_prompt_sr") else []
 
-        prompt = self._get_prompt(args.ad_prompt, p.all_prompts, i, p.prompt)
+        prompt = self._get_prompt(args.ad_prompt, p.all_prompts, i, p.prompt, prompt_sr)
         negative_prompt = self._get_prompt(
-            args.ad_negative_prompt, p.all_negative_prompts, i, p.negative_prompt
+            args.ad_negative_prompt,
+            p.all_negative_prompts,
+            i,
+            p.negative_prompt,
+            prompt_sr,
         )
 
         return prompt, negative_prompt
@@ -333,7 +364,11 @@ class AfterDetailerScript(scripts.Script):
         return args.ad_cfg_scale if args.ad_use_cfg_scale else p.cfg_scale
 
     def get_sampler(self, p, args: ADetailerArgs) -> str:
-        return args.ad_sampler if args.ad_use_sampler else p.sampler_name
+        if args.ad_use_sampler:
+            return args.ad_sampler
+        if hasattr(p, "_ad_orig_sampler_name"):
+            return p._ad_orig_sampler_name
+        return p.sampler_name
 
     def get_override_settings(self, p, args: ADetailerArgs) -> dict[str, Any]:
         d = {}
@@ -371,19 +406,13 @@ class AfterDetailerScript(scripts.Script):
         if i % lenp != lenp - 1:
             return
 
-        prev = None
-        if hasattr(p, "_ad_orig_steps"):
-            prev = p.steps
-            p.steps = p._ad_orig_steps
+        with change_skip_img2img_args(p):
+            infotext = self.infotext(p)
 
-        infotext = self.infotext(p)
         params_txt = Path(data_path, "params.txt")
         with suppress(Exception):
             params_txt.write_text(infotext, encoding="utf-8")
 
-        if hasattr(p, "_ad_orig_steps"):
-            p.steps = prev
-
     def script_filter(self, p, args: ADetailerArgs):
         script_runner = copy(p.scripts)
         script_args = deepcopy(p.script_args)
@@ -785,6 +814,27 @@ def on_ui_settings():
 # xyz_grid
 
 
+class PromptSR(NamedTuple):
+    s: str
+    r: str
+
+
+def set_value(p, x: Any, xs: Any, *, field: str):
+    if not hasattr(p, "_ad_xyz"):
+        p._ad_xyz = {}
+    p._ad_xyz[field] = x
+
+
+def search_and_replace_prompt(p, x: Any, xs: Any, replace_in_main_prompt: bool):
+    if replace_in_main_prompt:
+        p.prompt = p.prompt.replace(xs[0], x)
+        p.negative_prompt = p.negative_prompt.replace(xs[0], x)
+
+    if not hasattr(p, "_ad_xyz_prompt_sr"):
+        p._ad_xyz_prompt_sr = []
+    p._ad_xyz_prompt_sr.append(PromptSR(s=xs[0], r=x))
+
+
 def make_axis_on_xyz_grid():
     xyz_grid = None
     for script in scripts.scripts_data:
@@ -798,11 +848,6 @@ def make_axis_on_xyz_grid():
     model_list = ["None", *model_mapping.keys()]
     samplers = [sampler.name for sampler in all_samplers]
 
-    def set_value(p, x, xs, *, field: str):
-        if not hasattr(p, "_ad_xyz"):
-            p._ad_xyz = {}
-        p._ad_xyz[field] = x
-
     axis = [
         xyz_grid.AxisOption(
             "[ADetailer] ADetailer model 1st",
@@ -820,6 +865,16 @@ def make_axis_on_xyz_grid():
             str,
             partial(set_value, field="ad_negative_prompt"),
         ),
+        xyz_grid.AxisOption(
+            "[ADetailer] Prompt S/R (AD 1st)",
+            str,
+            partial(search_and_replace_prompt, replace_in_main_prompt=False),
+        ),
+        xyz_grid.AxisOption(
+            "[ADetailer] Prompt S/R (AD 1st and main prompt)",
+            str,
+            partial(search_and_replace_prompt, replace_in_main_prompt=True),
+        ),
         xyz_grid.AxisOption(
             "[ADetailer] Mask erosion / dilation 1st",
             int,