diff --git a/adetailer/common.py b/adetailer/common.py
index c2f14c8..bd4f10b 100644
--- a/adetailer/common.py
+++ b/adetailer/common.py
@@ -2,16 +2,11 @@ from __future__ import annotations
 
 from collections import OrderedDict
 from dataclasses import dataclass
-from enum import IntEnum
-from functools import partial
-from math import dist
 from pathlib import Path
 from typing import Optional, Union
 
-import cv2
-import numpy as np
 from huggingface_hub import hf_hub_download
-from PIL import Image, ImageChops, ImageDraw
+from PIL import Image, ImageDraw
 
 repo_id = "Bingsu/adetailer"
 
@@ -23,13 +18,6 @@ class PredictOutput:
     preview: Optional[Image.Image] = None
 
 
-class SortBy(IntEnum):
-    NONE = 0
-    LEFT_TO_RIGHT = 1
-    CENTER_TO_EDGE = 2
-    AREA = 3
-
-
 def get_models(
     model_dir: Union[str, Path], huggingface: bool = True
 ) -> OrderedDict[str, Optional[str]]:
@@ -100,168 +88,3 @@ def create_mask_from_bbox(
         mask_draw.rectangle(bbox, fill=255)
         masks.append(mask)
     return masks
-
-
-def _dilate(arr: np.ndarray, value: int) -> np.ndarray:
-    kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (value, value))
-    return cv2.dilate(arr, kernel, iterations=1)
-
-
-def _erode(arr: np.ndarray, value: int) -> np.ndarray:
-    kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (value, value))
-    return cv2.erode(arr, kernel, iterations=1)
-
-
-def dilate_erode(img: Image.Image, value: int) -> Image.Image:
-    """
-    The dilate_erode function takes an image and a value.
-    If the value is positive, it dilates the image by that amount.
-    If the value is negative, it erodes the image by that amount.
-
-    Parameters
-    ----------
-        img: PIL.Image.Image
-            the image to be processed
-        value: int
-            kernel size of dilation or erosion
-
-    Returns
-    -------
-        PIL.Image.Image
-            The image that has been dilated or eroded
-    """
-    if value == 0:
-        return img
-
-    arr = np.array(img)
-    arr = _dilate(arr, value) if value > 0 else _erode(arr, -value)
-
-    return Image.fromarray(arr)
-
-
-def offset(img: Image.Image, x: int = 0, y: int = 0) -> Image.Image:
-    """
-    The offset function takes an image and offsets it by a given x(→) and y(↑) value.
-
-    Parameters
-    ----------
-        mask: Image.Image
-            Pass the mask image to the function
-        x: int
-            →
-        y: int
-            ↑
-
-    Returns
-    -------
-        PIL.Image.Image
-            A new image that is offset by x and y
-    """
-    return ImageChops.offset(img, x, -y)
-
-
-def is_all_black(img: Image.Image) -> bool:
-    arr = np.array(img)
-    return cv2.countNonZero(arr) == 0
-
-
-def mask_preprocess(
-    masks: list[Image.Image] | None,
-    kernel: int = 0,
-    x_offset: int = 0,
-    y_offset: int = 0,
-) -> list[Image.Image]:
-    """
-    The mask_preprocess function takes a list of masks and preprocesses them.
-    It dilates and erodes the masks, and offsets them by x_offset and y_offset.
-
-    Parameters
-    ----------
-        masks: list[Image.Image] | None
-            A list of masks
-        kernel: int
-            kernel size of dilation or erosion
-        x_offset: int
-            →
-        y_offset: int
-            ↑
-
-    Returns
-    -------
-        list[Image.Image]
-            A list of processed masks
-    """
-    if masks is None:
-        return []
-
-    masks = [dilate_erode(m, kernel) for m in masks]
-    masks = [m for m in masks if not is_all_black(m)]
-    if x_offset != 0 or y_offset != 0:
-        masks = [offset(m, x_offset, y_offset) for m in masks]
-
-    return masks
-
-
-# Bbox sorting
-def _key_left_to_right(bbox: list[float]) -> float:
-    """
-    Left to right
-
-    Parameters
-    ----------
-    bbox: list[float]
-        list of [x1, y1, x2, y2]
-    """
-    return bbox[0]
-
-
-def _key_center_to_edge(bbox: list[float], *, center: tuple[float, float]) -> float:
-    """
-    Center to edge
-
-    Parameters
-    ----------
-    bbox: list[float]
-        list of [x1, y1, x2, y2]
-    image: Image.Image
-        the image
-    """
-    bbox_center = ((bbox[0] + bbox[2]) / 2, (bbox[1] + bbox[3]) / 2)
-    return dist(center, bbox_center)
-
-
-def _key_area(bbox: list[float]) -> float:
-    """
-    Large to small
-
-    Parameters
-    ----------
-    bbox: list[float]
-        list of [x1, y1, x2, y2]
-    """
-    area = (bbox[2] - bbox[0]) * (bbox[3] - bbox[1])
-    return -area
-
-
-def sort_bboxes(
-    pred: PredictOutput, order: int | SortBy = SortBy.NONE
-) -> PredictOutput:
-    if order == SortBy.NONE or not pred.bboxes:
-        return pred
-
-    if order == SortBy.LEFT_TO_RIGHT:
-        key = _key_left_to_right
-    elif order == SortBy.CENTER_TO_EDGE:
-        width, height = pred.preview.size
-        center = (width / 2, height / 2)
-        key = partial(_key_center_to_edge, center=center)
-    elif order == SortBy.AREA:
-        key = _key_area
-    else:
-        raise RuntimeError
-
-    items = len(pred.bboxes)
-    idx = sorted(range(items), key=lambda i: key(pred.bboxes[i]))
-    pred.bboxes = [pred.bboxes[i] for i in idx]
-    pred.masks = [pred.masks[i] for i in idx]
-    return pred
diff --git a/adetailer/mask.py b/adetailer/mask.py
new file mode 100644
index 0000000..53faaab
--- /dev/null
+++ b/adetailer/mask.py
@@ -0,0 +1,184 @@
+from enum import IntEnum
+from functools import partial
+from math import dist
+
+import cv2
+import numpy as np
+from PIL import Image, ImageChops
+
+from adetailer.common import PredictOutput
+
+
+class SortBy(IntEnum):
+    NONE = 0
+    LEFT_TO_RIGHT = 1
+    CENTER_TO_EDGE = 2
+    AREA = 3
+
+
+def _dilate(arr: np.ndarray, value: int) -> np.ndarray:
+    kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (value, value))
+    return cv2.dilate(arr, kernel, iterations=1)
+
+
+def _erode(arr: np.ndarray, value: int) -> np.ndarray:
+    kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (value, value))
+    return cv2.erode(arr, kernel, iterations=1)
+
+
+def dilate_erode(img: Image.Image, value: int) -> Image.Image:
+    """
+    The dilate_erode function takes an image and a value.
+    If the value is positive, it dilates the image by that amount.
+    If the value is negative, it erodes the image by that amount.
+
+    Parameters
+    ----------
+        img: PIL.Image.Image
+            the image to be processed
+        value: int
+            kernel size of dilation or erosion
+
+    Returns
+    -------
+        PIL.Image.Image
+            The image that has been dilated or eroded
+    """
+    if value == 0:
+        return img
+
+    arr = np.array(img)
+    arr = _dilate(arr, value) if value > 0 else _erode(arr, -value)
+
+    return Image.fromarray(arr)
+
+
+def offset(img: Image.Image, x: int = 0, y: int = 0) -> Image.Image:
+    """
+    The offset function takes an image and offsets it by a given x(→) and y(↑) value.
+
+    Parameters
+    ----------
+        mask: Image.Image
+            Pass the mask image to the function
+        x: int
+            →
+        y: int
+            ↑
+
+    Returns
+    -------
+        PIL.Image.Image
+            A new image that is offset by x and y
+    """
+    return ImageChops.offset(img, x, -y)
+
+
+def is_all_black(img: Image.Image) -> bool:
+    arr = np.array(img)
+    return cv2.countNonZero(arr) == 0
+
+
+def bbox_area(bbox: list[float]):
+    return (bbox[2] - bbox[0]) * (bbox[3] - bbox[1])
+
+
+def mask_preprocess(
+    masks: list[Image.Image] | None,
+    kernel: int = 0,
+    x_offset: int = 0,
+    y_offset: int = 0,
+) -> list[Image.Image]:
+    """
+    The mask_preprocess function takes a list of masks and preprocesses them.
+    It dilates and erodes the masks, and offsets them by x_offset and y_offset.
+
+    Parameters
+    ----------
+        masks: list[Image.Image] | None
+            A list of masks
+        kernel: int
+            kernel size of dilation or erosion
+        x_offset: int
+            →
+        y_offset: int
+            ↑
+
+    Returns
+    -------
+        list[Image.Image]
+            A list of processed masks
+    """
+    if masks is None:
+        return []
+
+    masks = [dilate_erode(m, kernel) for m in masks]
+    masks = [m for m in masks if not is_all_black(m)]
+    if x_offset != 0 or y_offset != 0:
+        masks = [offset(m, x_offset, y_offset) for m in masks]
+
+    return masks
+
+
+# Bbox sorting
+def _key_left_to_right(bbox: list[float]) -> float:
+    """
+    Left to right
+
+    Parameters
+    ----------
+    bbox: list[float]
+        list of [x1, y1, x2, y2]
+    """
+    return bbox[0]
+
+
+def _key_center_to_edge(bbox: list[float], *, center: tuple[float, float]) -> float:
+    """
+    Center to edge
+
+    Parameters
+    ----------
+    bbox: list[float]
+        list of [x1, y1, x2, y2]
+    image: Image.Image
+        the image
+    """
+    bbox_center = ((bbox[0] + bbox[2]) / 2, (bbox[1] + bbox[3]) / 2)
+    return dist(center, bbox_center)
+
+
+def _key_area(bbox: list[float]) -> float:
+    """
+    Large to small
+
+    Parameters
+    ----------
+    bbox: list[float]
+        list of [x1, y1, x2, y2]
+    """
+    return -bbox_area(bbox)
+
+
+def sort_bboxes(
+    pred: PredictOutput, order: int | SortBy = SortBy.NONE
+) -> PredictOutput:
+    if order == SortBy.NONE or not pred.bboxes:
+        return pred
+
+    if order == SortBy.LEFT_TO_RIGHT:
+        key = _key_left_to_right
+    elif order == SortBy.CENTER_TO_EDGE:
+        width, height = pred.preview.size
+        center = (width / 2, height / 2)
+        key = partial(_key_center_to_edge, center=center)
+    elif order == SortBy.AREA:
+        key = _key_area
+    else:
+        raise RuntimeError
+
+    items = len(pred.bboxes)
+    idx = sorted(range(items), key=lambda i: key(pred.bboxes[i]))
+    pred.bboxes = [pred.bboxes[i] for i in idx]
+    pred.masks = [pred.masks[i] for i in idx]
+    return pred
diff --git a/scripts/!adetailer.py b/scripts/!adetailer.py
index 4b7f3e0..fe0934b 100644
--- a/scripts/!adetailer.py
+++ b/scripts/!adetailer.py
@@ -22,7 +22,8 @@ from adetailer import (
     ultralytics_predict,
 )
 from adetailer.args import ALL_ARGS, BBOX_SORTBY, ADetailerArgs, EnableChecker
-from adetailer.common import PredictOutput, mask_preprocess, sort_bboxes
+from adetailer.common import PredictOutput
+from adetailer.mask import mask_preprocess, sort_bboxes
 from adetailer.ui import adui, ordinal, suffix
 from controlnet_ext import ControlNetExt, controlnet_exists
 from sd_webui import images, safe, script_callbacks, scripts, shared