How do I create a mask but not optimize it? about adetailer HOT 10 CLOSED

def mediapipe_face_mesh(
    image: Image.Image, confidence: float = 0.3
) -> PredictOutput[int]:
    import mediapipe as mp

    mp_face_mesh = mp.solutions.face_mesh
    draw_util = mp.solutions.drawing_utils
    drawing_styles = mp.solutions.drawing_styles

    w, h = image.size

    with mp_face_mesh.FaceMesh(
        static_image_mode=True, max_num_faces=20, min_detection_confidence=confidence
    ) as face_mesh:
        arr = np.array(image)
        pred = face_mesh.process(arr)

        if pred.multi_face_landmarks is None:
            return PredictOutput()

        preview = arr.copy()
        masks = []

        for landmarks in pred.multi_face_landmarks:
            draw_util.draw_landmarks(
                image=preview,
                landmark_list=landmarks,
                connections=mp_face_mesh.FACEMESH_TESSELATION,
                landmark_drawing_spec=None,
                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], dtype=int
            )
            outline = cv2.convexHull(points).reshape(-1).tolist()

            mask = Image.new("L", image.size, "black")
            draw = ImageDraw.Draw(mask)
            draw.polygon(outline, fill="white")
            masks.append(mask)

        bboxes = create_bbox_from_mask(masks, image.size)
        preview = Image.fromarray(preview)
        return PredictOutput(bboxes=bboxes, masks=masks, preview=preview)

from PIL import Image
from adetailer.mask import mask_preprocess

# Preprocess the mask
processed_masks = mask_preprocess(masks, kernel=0, x_offset=0, y_offset=0, merge_invert='NONE')

def mediapipe_face_mesh(
    image: Image.Image, confidence: float = 0.3
) -> PredictOutput[int]:
    import mediapipe as mp

    mp_face_mesh = mp.solutions.face_mesh
    draw_util = mp.solutions.drawing_utils
    drawing_styles = mp.solutions.drawing_styles

    w, h = image.size

    with mp_face_mesh.FaceMesh(
        static_image_mode=True, max_num_faces=20, min_detection_confidence=confidence
    ) as face_mesh:
        arr = np.array(image)
        pred = face_mesh.process(arr)

        if pred.multi_face_landmarks is None:
            return PredictOutput()

        preview = arr.copy()
        masks = []

        for landmarks in pred.multi_face_landmarks:
            draw_util.draw_landmarks(
                image=preview,
                landmark_list=landmarks,
                connections=mp_face_mesh.FACEMESH_TESSELATION,
                landmark_drawing_spec=None,
                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], dtype=int
            )
            outline = cv2.convexHull(points).reshape(-1).tolist()

            mask = Image.new("L", image.size, "black")
            draw = ImageDraw.Draw(mask)
            draw.polygon(outline, fill="white")
            masks.append(mask)

        bboxes = create_bbox_from_mask(masks, image.size)
        preview = Image.fromarray(preview)
        return PredictOutput(bboxes=bboxes, masks=masks, preview=preview)