Update model.py

model.py

@@ -11,7 +11,7 @@ from diffusers import (
 # Import the custom pipeline from your local file
 from pipeline_stable_diffusion_xl_instantid_img2img import StableDiffusionXLInstantIDImg2ImgPipeline
 
-from huggingface_hub import snapshot_download, hf_hub_download # Ensure hf_hub_download is imported
+from huggingface_hub import snapshot_download, hf_hub_download
 from insightface.app import FaceAnalysis
 from controlnet_aux import ZoeDetector, LineartDetector
 
@@ -113,9 +113,7 @@ class ModelHandler:
         # 5. Load Adapters (IP-Adapter & LoRA)
         print("Loading Adapters (IP-Adapter & LoRA)...")
         
-        # --- START FIX for FileNotFoundError ---
-        # We must download the ip-adapter.bin file and pass its local path,
-        # not the repository name.
+        # Download the ip-adapter.bin file and pass its local path
         ip_adapter_filename = "ip-adapter.bin"
         ip_adapter_local_path = os.path.join("./models", ip_adapter_filename)
 
@@ -130,8 +128,7 @@ class ModelHandler:
         
         # The custom pipeline has this method, now pass the LOCAL FILE PATH
         print(f"Loading IP-Adapter from local file: {ip_adapter_local_path}")
-        self.pipeline.load_ip_adapter_instantid(ip_adapter_local_path) # <-- Pass local path
-        # --- END FIX ---
+        self.pipeline.load_ip_adapter_instantid(ip_adapter_local_path) # Pass local path
         
         self.pipeline.load_lora_weights(Config.REPO_ID, weight_name=Config.LORA_FILENAME)
         self.pipeline.fuse_lora(lora_scale=1.0) 
@@ -150,7 +147,9 @@ class ModelHandler:
             
         try:
             # Convert PIL to CV2
-            cv2_img = cv2.cvtColor(np.array(image), cv2.COLOR_RGB_BGR) 
+            # --- START FIX ---
+            cv2_img = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR) # <-- Corrected typo
+            # --- END FIX ---
             faces = self.app.get(cv2_img)
             
             if len(faces) == 0: