Update app.py

app.py

@@ -64,22 +64,22 @@ class NumpyEncoder(json.JSONEncoder):
 device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
 
 # Model paths and class names (copied from app_mcp.py)
+# MODEL_PATHS (model_4 removed)
 MODEL_PATHS = {
     "model_1": "LPX55/detection-model-1-ONNX",
     "model_2": "LPX55/detection-model-2-ONNX",
     "model_3": "LPX55/detection-model-3-ONNX",
-    "model_4": "cmckinle/sdxl-flux-detector_v1.1",
     "model_5": "LPX55/detection-model-5-ONNX",
     "model_6": "LPX55/detection-model-6-ONNX",
     "model_7": "LPX55/detection-model-7-ONNX",
     "model_8": "aiwithoutborders-xyz/CommunityForensics-DeepfakeDet-ViT"
 }
 
+# CLASS_NAMES (model_4 removed)
 CLASS_NAMES = {
     "model_1": ['artificial', 'real'],
     "model_2": ['AI Image', 'Real Image'],
     "model_3": ['artificial', 'human'],
-    "model_4": ['AI', 'Real'],
     "model_5": ['Realism', 'Deepfake'],
     "model_6": ['ai_gen', 'human'],
     "model_7": ['Fake', 'Real'],
@@ -87,8 +87,6 @@ CLASS_NAMES = {
 }
 
 
-
-
 def register_model_with_metadata(model_id, model, preprocess, postprocess, class_names, display_name, contributor, model_path, architecture=None, dataset=None):
     entry = ModelEntry(model, preprocess, postprocess, class_names, display_name=display_name, contributor=contributor, model_path=model_path, architecture=architecture, dataset=dataset)
     MODEL_REGISTRY[model_id] = entry