app wip

app.py

@@ -166,9 +166,24 @@ default_negative_prompt = "Logo,Watermark,Text,Ugly,Morbid,Extra fingers,Poorly
 app = FaceAnalysis(name='antelopev2', root='./', providers=['CPUExecutionProvider'])
 app.prepare(ctx_id=0, det_size=(640, 640))
 
-base_dir = "./instantID_ckpt/checkpoint_174000"
-face_adapter = f'{base_dir}/pytorch_model.bin'
-controlnet_path = f'{base_dir}/controlnet'
+
+# download checkpoints
+from huggingface_hub import hf_hub_download
+
+hf_hub_download(repo_id="briaai/ID_preservation_2.3", filename="controlnet/config.json", local_dir="./checkpoints")
+hf_hub_download(repo_id="briaai/ID_preservation_2.3", filename="controlnet/diffusion_pytorch_model.safetensors", local_dir="./checkpoints")
+hf_hub_download(repo_id="briaai/ID_preservation_2.3", filename="ip-adapter.bin", local_dir="./checkpoints")
+hf_hub_download(repo_id="briaai/ID_preservation_2.3", filename="image_encoder", local_dir="./checkpoints")
+
+
+
+# base_dir = "./instantID_ckpt/checkpoint_174000"
+# face_adapter = f'{base_dir}/pytorch_model.bin'
+# controlnet_path = f'{base_dir}/controlnet'
+face_adapter = f"./checkpoints/ip-adapter.bin"
+controlnet_path = f"./checkpoints/controlnet"
+
+
 base_model_path = f'briaai/BRIA-2.3'
 resolution = 1024
 
@@ -182,7 +197,7 @@ controlnet = [controlnet_lnmks, controlnet_canny]
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
 image_encoder = CLIPVisionModelWithProjection.from_pretrained(
-        '/home/ubuntu/BRIA-2.3-InstantID/ip_adapter/image_encoder',
+        f"./checkpoints//image_encoder",
         torch_dtype=torch.float16,
     )