Update app.py

app.py

@@ -26,7 +26,6 @@ def extract_resnet_features(image_data):
     x = image.img_to_array(img)
     x = np.expand_dims(x, axis=0)
     x = preprocess_input(x)
-    
     # Extract features using ResNet50
     features = base_model.predict(x)
     features_flattened = features.flatten()
@@ -39,7 +38,7 @@ def predict(image):
     features = extract_resnet_features(image)
     
     # Make prediction using Random Forest classifier
-    predicted_index = rf_classifier.predict([features_flattened])[0]
+    predicted_index = rf_classifier.predict([features])[0]
     
     # Decode predicted class using the class labels obtained from the Random Forest classifier
     predicted_class = class_labels[predicted_index]