Update models.py

models.py

@@ -67,49 +67,12 @@ def load_face_analysis():
     Downloads from DIAMONIK7777/antelopev2 which has the correct model structure.
     """
     print("Loading face analysis model...")
-    
-    # Use a persistent location for models
-    local_model_root = '/data/models' if os.path.exists('/data') else './models'
-    model_name = 'antelopev2'
-    
-    # This is the directory where the .onnx files must be
-    local_model_path = os.path.join(local_model_root, model_name)
-    
+
     try:
-        # Download from DIAMONIK7777/antelopev2 repo (correct structure)
-        print(f"  Downloading antelopev2 models to {local_model_path}...")
-        
-        from huggingface_hub import snapshot_download
-        
-        # Download entire repo
-        snapshot_kwargs = {
-            "repo_id": "DIAMONIK7777/antelopev2",
-            "local_dir": local_model_path,
-            "local_dir_use_symlinks": False,
-            "repo_type": "model"
-        }
-        if HUGGINGFACE_TOKEN:
-            snapshot_kwargs["token"] = HUGGINGFACE_TOKEN
-        
-        antelope_download = snapshot_download(**snapshot_kwargs)
-        print(f"  [OK] Models downloaded to: {antelope_download}")
-        
-        # Initialize FaceAnalysis with correct paths
-        # Note: root should be the PARENT of the model directory
-        face_app = FaceAnalysis(
-            name=model_name,
-            root=local_model_root,  # Parent directory
-            providers=['CUDAExecutionProvider', 'CPUExecutionProvider']
-        )
-        
-        face_app.prepare(
-            ctx_id=FACE_DETECTION_CONFIG['ctx_id'], 
-            det_size=FACE_DETECTION_CONFIG['det_size']
-        )
-        
-        print("  [OK] Face analysis model loaded successfully")
-        print(f"  [OK] Using providers: {face_app.det_model.providers}")
-        return face_app, True
+        antelope_download = snapshot_download(repo_id="DIAMONIK7777/antelopev2", local_dir="/data/models/antelopev2")
+        face_app = FaceAnalysis(name='antelopev2', root='/data', providers=['CUDAExecutionProvider', 'CPUExecutionProvider'])
+        face_app.prepare(ctx_id=0, det_size=(640, 640))
+            return face_app, True
         
     except Exception as e:
         print(f"  [ERROR] Face detection not available: {e}")