From bfddf681dee2d8f2c6ec2b2641aceb0900e0f127 Mon Sep 17 00:00:00 2001
From: Bingsu <ks2515@naver.com>
Date: Wed, 20 Sep 2023 00:26:32 +0900
Subject: [PATCH] fix: lazy import

---
 adetailer/mediapipe.py   | 7 ++++++-
 adetailer/ultralytics.py | 3 ++-
 2 files changed, 8 insertions(+), 2 deletions(-)

diff --git a/adetailer/mediapipe.py b/adetailer/mediapipe.py
index e52b620..17fb2cc 100644
--- a/adetailer/mediapipe.py
+++ b/adetailer/mediapipe.py
@@ -2,7 +2,6 @@ from __future__ import annotations
 
 from functools import partial
 
-import mediapipe as mp
 import numpy as np
 from PIL import Image, ImageDraw
 
@@ -29,6 +28,8 @@ 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
@@ -84,6 +85,8 @@ 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
@@ -127,6 +130,8 @@ 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()
diff --git a/adetailer/ultralytics.py b/adetailer/ultralytics.py
index addd0f5..36062b7 100644
--- a/adetailer/ultralytics.py
+++ b/adetailer/ultralytics.py
@@ -5,7 +5,6 @@ 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
@@ -17,6 +16,8 @@ def ultralytics_predict(
     confidence: float = 0.3,
     device: str = "",
 ) -> PredictOutput:
+    from ultralytics import YOLO
+
     model = YOLO(model_path)
     pred = model(image, conf=confidence, device=device)