Update 101234444_aml_assignment_1.py

101234444_aml_assignment_1.py

@@ -32,6 +32,8 @@ model = tf.keras.models.load_model("final_model.h5")
 index_to_class = {v: k for k, v in class_indices.items()}
 
 def classify_image(image: PIL.Image.Image):
+    if image is None:
+        return "Invalid or empty image provided."
     try:
         # Ensure the input is a PIL Image, resize it, and then convert it to a NumPy array
         if not isinstance(image, PIL.Image.Image):
@@ -48,7 +50,7 @@ def classify_image(image: PIL.Image.Image):
         predicted_class_idx = np.argmax(predictions)  # Get the predicted class index
 
         # Map index to label using index_to_class
-        predicted_class_label = index_to_class[predicted_class_idx]
+        predicted_class_label = index_to_class[predicted_class_idx].replace('_', ' ')
         return predicted_class_label
 
     except Exception as e: