Update models.py

models.py

@@ -59,70 +59,12 @@ def download_model_with_retry(repo_id, filename, max_retries=None):
 
 
 def load_face_analysis():
-    """Load face analysis model with intelligent provider selection."""
-    print("Loading face analysis model...")
-    
-    # Determine provider preference from config
-    prefer_cpu = FACE_DETECTION_CONFIG.get('prefer_cpu', True)
-    
-    if prefer_cpu:
-        # CPU-first configuration for memory efficiency
-        provider_configs = [
-            (['CPUExecutionProvider'], -1, "CPU (memory efficient)"),
-            (['CUDAExecutionProvider', 'CPUExecutionProvider'], 0, "GPU with CPU fallback"),
-            (None, 0, "auto-detect")
-        ]
-    else:
-        # GPU-first configuration for speed
-        provider_configs = [
-            (['CUDAExecutionProvider', 'CPUExecutionProvider'], 0, "GPU with CPU fallback"),
-            (['CPUExecutionProvider'], -1, "CPU only"),
-            (None, 0, "auto-detect")
-        ]
-    
-    print(f"  Provider preference: {'CPU (memory efficient)' if prefer_cpu else 'GPU (faster)'}")
-    
-    for providers, ctx_id, provider_desc in provider_configs:
-        try:
-            print(f"  Attempting with {provider_desc}...")
-            
-            if providers:
-                face_app = FaceAnalysis(
-                    name=FACE_DETECTION_CONFIG['model_name'],
-                    root='./models/insightface',
-                    providers=providers
-                )
-            else:
-                # Let InsightFace choose providers automatically
-                face_app = FaceAnalysis(
-                    name=FACE_DETECTION_CONFIG['model_name'],
-                    root='./models/insightface'
-                )
-            
-            face_app.prepare(
-                ctx_id=ctx_id,
-                det_size=FACE_DETECTION_CONFIG['det_size']
-            )
-            
-            # Test the model to ensure it works
-            import numpy as np
-            test_img = np.zeros((640, 640, 3), dtype=np.uint8)
-            _ = face_app.get(test_img)
-            
-            print(f"  [OK] Face analysis model loaded with {provider_desc}")
-            return face_app, True
-            
-        except Exception as e:
-            error_msg = str(e)[:200] if str(e) else "Unknown error"
-            print(f"  [INFO] {provider_desc} failed: {error_msg}")
-            continue
-    
-    # All attempts failed
-    print("  [WARNING] Face detection not available - all providers failed")
-    print("  [INFO] Generation will continue without face preservation")
-    print("  [TIP] Check that onnxruntime or onnxruntime-gpu is properly installed")
-    return None, False
 
+    antelope_download = snapshot_download(repo_id="DIAMONIK7777/antelopev2", local_dir="/data/models/antelopev2")
+    face_app = FaceAnalysis(name='antelopev2', root='/data', providers=['CPUExecutionProvider'])
+    face_app.prepare(ctx_id=0, det_size=(640, 640))
+    
+    return face_app, True
 
 def load_depth_detector():
     """Load Zoe Depth detector with optimized memory management."""