m

handler.py

@@ -8,17 +8,20 @@ from diffusers.utils import load_image
 
 import torch
 import torch.nn.functional as F
-# from torchvision.transforms import Compose
+from torchvision.transforms import Compose
 
+import PIL
 from PIL import Image
 
-# from depth_anything.dpt import DepthAnything
-# from depth_anything.util.transform import Resize, NormalizeImage, PrepareForNet
+from depth_anything.dpt import DepthAnything
+from depth_anything.util.transform import Resize, NormalizeImage, PrepareForNet
 
 from insightface.app import FaceAnalysis
 from pipeline_stable_diffusion_xl_instantid_full import StableDiffusionXLInstantIDPipeline, draw_kps
 from controlnet_aux import OpenposeDetector
-from transformers import AutoModel
+
+
+# end_test
 
 device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
 if device.type != 'cuda':
@@ -31,7 +34,7 @@ class EndpointHandler():
         print("Loading model from", model_dir)
         
         face_adapter = f"./checkpoints/ip-adapter.bin"
-        controlnet_path = f"/repository/checkpoints/ControlNetModel"
+        controlnet_path = f"./checkpoints/ControlNetModel"
 
         # transform = Compose([
         #     Resize(
@@ -47,9 +50,9 @@ class EndpointHandler():
         #     PrepareForNet(),
         # ])
 
-
-        self.controlnet_identitynet = AutoModel.from_pretrained(controlnet_path, torch_dtype=dtype)
-
+        self.controlnet_identitynet = ControlNetModel.from_pretrained(
+            controlnet_path, torch_dtype=dtype
+        )
 
         pretrained_model_name_or_path = "wangqixun/YamerMIX_v8"