Update app.py

app.py

@@ -4,7 +4,7 @@ import gradio as gr
 from sklearn.preprocessing import OneHotEncoder
 from sklearn.impute import SimpleImputer
 
-# Modeli, encoder'ı ve imputer'ı yükleme
+# Modeli, encoder'ı ve imputer'ı yükleme - IMPORT'lardan HEMEN SONRA
 logreg_model = joblib.load('logreg_model.pkl')
 rf_model = joblib.load('rf_model.pkl')
 encoder = joblib.load('encoder.pkl')
@@ -59,8 +59,24 @@ def fraud_detection(accountAgeDays, numItems, localTime, paymentMethod, paymentM
     rf_prediction = rf_model.predict(input_data)[0]
 
     # Sonuçları formatlama
-    logreg_result = "Sahtekarlık Değil" if logreg_prediction == 0 else "Sahtekarlık"
-    rf_result = "Sahtekarlık Değil" if rf_prediction == 0 else "Sahtekarlık"
+    logreg_result = "
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/67044b086fd3c9b6f6576f6d/Yk1ALS0QO0s48XbPO1Y_A.png)
+
+" if logreg_prediction == 0 else "
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/67044b086fd3c9b6f6576f6d/kn7rSJLyehM0BRq-BLGmf.png)
+
+"
+    rf_result = "
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/67044b086fd3c9b6f6576f6d/Wpa8dOnc9l1H-sz_U1YHy.png)
+
+" if rf_prediction == 0 else "
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/67044b086fd3c9b6f6576f6d/-P8PGOa8GqW9cC0gM5fWj.png)
+
+"
 
     return f"Logistic Regression: {logreg_result}\nRandom Forest: {rf_result}"