Update app.py

app.py

@@ -77,14 +77,23 @@ def predict(img_path):
     if pred_class.capitalize() in df["Makanan"].values:
         row = df.loc[df["Makanan"] == pred_class.capitalize()]
 
-        # Mengambil informasi gizi
-        calories = row["Kalori"].values[0]
-        protein = row["Protein"].values[0]
-        fat = row["Lemak"].values[0]
-        carbs = row["Karbohidrat"].values[0]
-        fiber = row["Serat"].values[0]
-        sugar = row["Gula"].values[0]
-        price = row["Harga (Rp)"].values[0]
+        # Convert int64 values to native Python data types
+        calories = int(row["Kalori"].values[0])
+        protein = int(row["Protein"].values[0])
+        fat = int(row["Lemak"].values[0])
+        carbs = int(row["Karbohidrat"].values[0])
+        fiber = int(row["Serat"].values[0])
+        sugar = int(row["Gula"].values[0])
+        price = int(row["Harga (Rp)"].values[0])
+
+        # # Mengambil informasi gizi
+        # calories = row["Kalori"].values[0]
+        # protein = row["Protein"].values[0]
+        # fat = row["Lemak"].values[0]
+        # carbs = row["Karbohidrat"].values[0]
+        # fiber = row["Serat"].values[0]
+        # sugar = row["Gula"].values[0]
+        # price = row["Harga (Rp)"].values[0]
 
         return pred_class, calories, protein, fat, carbs, fiber, sugar, price
     else: