Update app.py

app.py

@@ -27,6 +27,8 @@ model=load_model('best_model.h5')
 #   return result 
 
 
+
+
 def classify_image(inp):
     np.random.seed(143)
     labels = {'Burger King': 0, 'KFC': 1, 'McDonalds': 2, 'Other': 3, 'Starbucks': 4, 'Subway': 5}
@@ -36,20 +38,17 @@ def classify_image(inp):
     prediction = model.predict(inp)
     predicted_class_indices = np.argmax(prediction, axis=1)
     result = {}
-    # for i in range(len(predicted_class_indices)):
-    #     if predicted_class_indices[i] < NUM_CLASSES:
-    #         try:
-    #             label = labels[predicted_class_indices[i]]
-    #             result[label] = float(predicted_class_indices[i])
-    #         except KeyError:
-    #             print(f"KeyError: Label not found for index {predicted_class_indices[i]}")
+
     label_order = ["Burger King", "KFC", "McDonalds", "Other", "Starbucks", "Subway"]
 
-    # Assuming prediction is a dictionary with label keys
-    # result = [f"{label}: {prediction[label]:.2f}" for label in label_order]
-    # return ", ".join(result)
-    result = [f"{label}: {prediction[label]:.2f}" for label in labels]
-    return ", ".join(result)
+    # Create a dictionary to hold the results
+    result = {label: f"{prediction[labels[label]]:.2f}" for label in label_order}
+
+    # Convert the dictionary to a string
+    result_str = ", ".join([f"{label}: {value}" for label, value in result.items()])
+
+    return result_str
+