Update app.py

app.py

@@ -102,16 +102,16 @@ with tab1:
             st.info("Please upload an image to classify.")
     else:
         st.info("Using Pretrained model")
-        # model = tf.keras.models.load_model("./models/medical_classifier.h5")
-        model = TFAutoModel.from_pretrained('./models/medical_classifier')
-        config = model.config
-        if 'batch_shape' in config:
-            config['input_shape'] = config.pop('batch_shape')[1:]  # Remove batch size
+        model = tf.keras.models.load_model("./models/medical_classifier.h5")
+        # model = TFAutoModel.from_pretrained('./models/medical_classifier')
+        # config = model.config
+        # if 'batch_shape' in config:
+        #     config['input_shape'] = config.pop('batch_shape')[1:]  # Remove batch size
             
-        # Create the input layer with the corrected configuration
-        input_layer = InputLayer(**model.config)
-        # Rebuild the model (if necessary)
-        model.build(input_shape=model.config['input_shape'])
+        # # Create the input layer with the corrected configuration
+        # input_layer = InputLayer(**model.config)
+        # # Rebuild the model (if necessary)
+        # model.build(input_shape=model.config['input_shape'])
 
         if image_file is not None:
             predict_class = Analysing_image(st, model, image_file)