Update app.py

app.py

@@ -85,16 +85,11 @@ def extract_features_single(cnn_model, image_tensor):
     """Extract features from a single image using CNN for Random Forest"""
     cnn_model.eval()
     with torch.no_grad():
-        # Get features from the layer before final classification
+        # Extract raw 1280-dim features (matching how the RF model was trained)
         features = cnn_model.features(image_tensor)
         features = cnn_model.avgpool(features)
         features = torch.flatten(features, 1)
         
-        # Pass through the first part of classifier (before final layer)
-        if hasattr(cnn_model.classifier, '__iter__'):
-            for i, layer in enumerate(cnn_model.classifier[:-1]):  # Exclude final classification layer
-                features = layer(features)
-        
         return features.cpu().numpy()
 
 # Preprocess image for CNN