Update models.py

models.py

@@ -13,7 +13,7 @@ from diffusers import (
 from diffusers.models.attention_processor import AttnProcessor2_0
 from transformers import CLIPVisionModelWithProjection
 from insightface.app import FaceAnalysis
-from controlnet_aux import ZoeDetector, OpenposeDetector  # <-- NEW
+from controlnet_aux import ZoeDetector, OpenposeDetector, LeresDetector, MidasDetector, MediapipeFaceDetector
 from huggingface_hub import hf_hub_download
 from compel import Compel, ReturnedEmbeddingsType
 
@@ -82,16 +82,44 @@ def load_face_analysis():
 
 
 def load_depth_detector():
-    """Load Zoe Depth detector."""
-    print("Loading Zoe Depth detector...")
+    """
+    Load depth detector with fallback hierarchy: Leres → Zoe → Midas.
+    Returns (detector, detector_type, success).
+    """
+    print("Loading depth detector with fallback hierarchy...")
+    
+    # Try LeresDetector first (best quality)
     try:
+        print("  Attempting LeresDetector (highest quality)...")
+        leres_depth = LeresDetector.from_pretrained("lllyasviel/Annotators")
+        leres_depth.to(device)
+        print("  [OK] LeresDetector loaded successfully")
+        return leres_depth, 'leres', True
+    except Exception as e:
+        print(f"  [INFO] LeresDetector not available: {e}")
+    
+    # Fallback to ZoeDetector
+    try:
+        print("  Attempting ZoeDetector (fallback #1)...")
         zoe_depth = ZoeDetector.from_pretrained("lllyasviel/Annotators")
         zoe_depth.to(device)
-        print("  [OK] Zoe Depth loaded successfully")
-        return zoe_depth, True
+        print("  [OK] ZoeDetector loaded successfully")
+        return zoe_depth, 'zoe', True
     except Exception as e:
-        print(f"  [WARNING] Zoe Depth not available: {e}")
-        return None, False
+        print(f"  [INFO] ZoeDetector not available: {e}")
+    
+    # Final fallback to MidasDetector
+    try:
+        print("  Attempting MidasDetector (fallback #2)...")
+        midas_depth = MidasDetector.from_pretrained("lllyasviel/Annotators")
+        midas_depth.to(device)
+        print("  [OK] MidasDetector loaded successfully")
+        return midas_depth, 'midas', True
+    except Exception as e:
+        print(f"  [WARNING] MidasDetector not available: {e}")
+    
+    print("  [ERROR] No depth detector available")
+    return None, None, False
 
 # --- NEW FUNCTION ---
 def load_openpose_detector():
@@ -107,6 +135,19 @@ def load_openpose_detector():
         return None, False
 # --- END NEW FUNCTION ---
 
+# --- NEW FUNCTION ---
+def load_mediapipe_face_detector():
+    """Load MediapipeFaceDetector for advanced face detection."""
+    print("Loading MediapipeFaceDetector...")
+    try:
+        face_detector = MediapipeFaceDetector()
+        print("  [OK] MediapipeFaceDetector loaded successfully")
+        return face_detector, True
+    except Exception as e:
+        print(f"  [WARNING] MediapipeFaceDetector not available: {e}")
+        return None, False
+# --- END NEW FUNCTION ---
+
 def load_controlnets():
     """Load ControlNet models."""
     print("Loading ControlNet Zoe Depth model...")
@@ -187,17 +228,37 @@ def load_sdxl_pipeline(controlnets):
         return pipe, False
 
 
-def load_lora(pipe):
-    """Load LORA from HuggingFace Hub."""
-    print("Loading LORA (retroart) from HuggingFace Hub...")
-    try:
-        lora_path = download_model_with_retry(MODEL_REPO, MODEL_FILES['lora'])
-        pipe.load_lora_weights(lora_path, adapter_name="retroart")
-        print(f"  [OK] LORA loaded successfully")
-        return True
-    except Exception as e:
-        print(f"  [WARNING] Could not load LORA: {e}")
-        return False
+def load_loras(pipe):
+    """Load all LORAs from HuggingFace Hub."""
+    print("Loading all LORAs from HuggingFace Hub...")
+    loaded_loras = {}
+    
+    lora_files = {
+        "retroart": MODEL_FILES.get("lora_retroart"),
+        "vga": MODEL_FILES.get("lora_vga"),
+        "lucasart": MODEL_FILES.get("lora_lucasart")
+    }
+
+    for adapter_name, filename in lora_files.items():
+        if not filename:
+            print(f"  [INFO] No file specified for LORA '{adapter_name}', skipping.")
+            loaded_loras[adapter_name] = False
+            continue
+            
+        try:
+            lora_path = download_model_with_retry(MODEL_REPO, filename)
+            pipe.load_lora_weights(lora_path, adapter_name=adapter_name)
+            print(f"  [OK] LORA loaded successfully: {filename} as '{adapter_name}'")
+            loaded_loras[adapter_name] = True
+        except Exception as e:
+            print(f"  [WARNING] Could not load LORA {filename}: {e}")
+            loaded_loras[adapter_name] = False
+            
+    success = any(loaded_loras.values())
+    if not success:
+        print("  [WARNING] No LORAs were loaded successfully.")
+        
+    return loaded_loras, success
 
 
 def setup_ip_adapter(pipe, image_encoder):