Merge branch 'main' of https://github.com/chflame163/ComfyUI_LayerStyle

py/imagefunc.py

@@ -21,17 +21,15 @@ from functools import lru_cache
 from typing import Union, List
 from PIL import Image, ImageFilter, ImageChops, ImageDraw, ImageOps, ImageEnhance, ImageFont
 from skimage import img_as_float, img_as_ubyte
-from transformers import VitMatteImageProcessor, VitMatteForImageMatting
 import torchvision.transforms.functional as TF
 import torch.nn.functional as F
 import colorsys
-import wget
-from colour.io.luts.iridas_cube import read_LUT_IridasCube, LUT3D, LUT3x1D
 from typing import Union
 import folder_paths
 from .briarmbg import BriaRMBG
 from .filmgrainer import processing as processing_utils
 from .filmgrainer import filmgrainer as filmgrainer
+import wget
 
 def log(message:str, message_type:str='info'):
     name = 'LayerStyle'
@@ -868,6 +866,7 @@ def gamma_trans(image:Image, gamma:float) -> Image:
     return cv22pil(_corrected)
 
 def apply_lut(image:Image, lut_file:str, log:bool=False) -> Image:
+    from colour.io.luts.iridas_cube import read_LUT_IridasCube, LUT3D, LUT3x1D
     lut: Union[LUT3x1D, LUT3D] = read_LUT_IridasCube(lut_file)
     lut.name = os.path.splitext(os.path.basename(lut_file))[0]  # use base filename instead of internal LUT name
 
@@ -1045,6 +1044,7 @@ class VITMatteModel:
         self.processor = processor
 
 def load_VITMatte_model(model_name:str) -> object:
+    from transformers import VitMatteForImageMatting, VitMatteImageProcessor
     model = VitMatteForImageMatting.from_pretrained(model_name)
     processor = VitMatteImageProcessor.from_pretrained(model_name)
     vitmatte = VITMatteModel(model, processor)

py/person_mask_ultra_v2.py

@@ -1,7 +1,6 @@
 from .imagefunc import *
 from functools import reduce
 import wget
-import mediapipe as mp
 import folder_paths
 from .segment_anything_func import *
 
@@ -47,7 +46,8 @@ class PersonMaskUltraV2:
     CATEGORY = '😺dzNodes/LayerMask'
     OUTPUT_NODE = True
 
-    def get_mediapipe_image(self, image: Image) -> mp.Image:
+    def get_mediapipe_image(self, image: Image):
+        import mediapipe as mp
         # Convert image to NumPy array
         numpy_image = np.asarray(image)
         image_format = mp.ImageFormat.SRGB
@@ -63,7 +63,7 @@ class PersonMaskUltraV2:
                           accessories, background, confidence,
                           detail_method, detail_erode, detail_dilate,
                           black_point, white_point, process_detail):
-
+        import mediapipe as mp
         a_person_mask_generator_model_path = get_a_person_mask_generator_model_path()
         a_person_mask_generator_model_buffer = None
         with open(a_person_mask_generator_model_path, "rb") as f:

py/segment_anything_func.py

@@ -15,10 +15,7 @@ import folder_paths
 import comfy.model_management
 from sam_hq.predictor import SamPredictorHQ
 from sam_hq.build_sam_hq import sam_model_registry
-from local_groundingdino.datasets import transforms as T
-from local_groundingdino.util.utils import clean_state_dict as local_groundingdino_clean_state_dict
-from local_groundingdino.util.slconfig import SLConfig as local_groundingdino_SLConfig
-from local_groundingdino.models import build_model as local_groundingdino_build_model
+
 import glob
 import folder_paths
 
@@ -109,6 +106,9 @@ def get_local_filepath(url, dirname, local_file_name=None):
     return destination
 
 def load_groundingdino_model(model_name):
+    from local_groundingdino.util.utils import clean_state_dict as local_groundingdino_clean_state_dict
+    from local_groundingdino.util.slconfig import SLConfig as local_groundingdino_SLConfig
+    from local_groundingdino.models import build_model as local_groundingdino_build_model
     dino_model_args = local_groundingdino_SLConfig.fromfile(
         get_local_filepath(
             groundingdino_model_list[model_name]["config_url"],
@@ -142,6 +142,7 @@ def groundingdino_predict(
     prompt,
     threshold
 ):
+    from local_groundingdino.datasets import transforms as T
     def load_dino_image(image_pil):
         transform = T.Compose(
             [