V0

.gradio/cached_examples/40/log.csv

@@ -0,0 +1,27 @@
+Analysis Result,Detection Results,component 2,timestamp
+"{""path"": "".gradio/cached_examples/40/Analysis Result/3d8a35a089e8760701a4/image.webp"", ""url"": ""/gradio_api/file=/tmp/gradio/7eafcfaf41f08c2049e53e8648b2ef8dd2cc81e0378baec560a71bd1b7c3927f/image.webp"", ""size"": null, ""orig_name"": ""image.webp"", ""mime_type"": null, ""is_stream"": false, ""meta"": {""_type"": ""gradio.FileData""}}","Usage: 1/3
+ERROR: Deepfake model not found at ./output/vit_deepfake_best.pth
+Using device: cpu
+Setting up damage detector...
+✅ Damage detector initialized
+Setting up deepfake detector...
+❌ Failed to initialize deepfake detector
+Detecting damaged regions...
+Found 2 damage regions in 12.47 seconds
+
+✅ VERDICT: All damage appears REAL
+
+Remaining tries: 2",,2025-04-23 10:58:28.544329
+"{""path"": "".gradio/cached_examples/40/Analysis Result/100109825f2cbc19dd76/image.webp"", ""url"": ""/gradio_api/file=/tmp/gradio/888cd0407f045b7ed2d283b3ce82dc55329fb70f258b11a6baf0650ceffd35cc/image.webp"", ""size"": null, ""orig_name"": ""image.webp"", ""mime_type"": null, ""is_stream"": false, ""meta"": {""_type"": ""gradio.FileData""}}","Usage: 1/3
+ERROR: Deepfake model not found at ./output/vit_deepfake_best.pth
+Using device: cpu
+Setting up damage detector...
+✅ Damage detector initialized
+Setting up deepfake detector...
+❌ Failed to initialize deepfake detector
+Detecting damaged regions...
+Found 2 damage regions in 14.81 seconds
+
+✅ VERDICT: All damage appears REAL
+
+Remaining tries: 2",,2025-04-23 10:58:44.809650

app.py

@@ -139,12 +139,12 @@ def load_vit_deepfake_model(model_path, device):
     try:
      
         # Import AutoAdapterModel from adapter_transformers
-        from adapters import AutoAdapterModel
+        from transformers import AutoModelForImageClassification
+
         
         # Create model from pretrained base
         print(f"Loading AutoAdapter model for deepfake detection...")
-        model = AutoAdapterModel.from_pretrained("undefined")
-        model.load_adapter("Askhedi/Car_fraud_damage_detector", set_active=True)
+        model = AutoModelForImageClassification.from_pretrained("Askhedi/Car_fraud_damage_detector")
         
         # Move model to device and set to evaluation mode
         model = model.to(device)