Update app.py

app.py

@@ -16,7 +16,8 @@ with gr.Blocks() as demo:
             gr.Markdown(
     """
     * uploading an image will engage the model in image classsification
-    * trained on the following image types: 'T-shirt/top', 'Trouser', 'Pullover', 'Dress', 'Coat','Sandal', 'Shirt', 'Sneaker', 'Bag', 'Ankle boot'
+    * trained on the following image types: 'T-shirt/top', 'Trouser', 'Pullover', 'Dress',
+                                                        'Coat','Sandal', 'Shirt', 'Sneaker', 'Bag', 'Ankle boot'
     """)
 
     # Train, evaluate and test a ML
@@ -59,7 +60,7 @@ with gr.Blocks() as demo:
     
     # train the model - 5 runs
     # evaluate the model on the test set
-    model.fit(x_train, y_train, epochs=5)
+    model.fit(x_train, y_train, epochs=5, validation_split=0.3)
     test_loss, test_acc = model.evaluate(x_test,  y_test, verbose=2)
     post_train_results = f"Test accuracy: {test_acc} Test Loss: {test_loss}"
     print(post_train_results)
@@ -68,10 +69,7 @@ with gr.Blocks() as demo:
     probability_model = tf.keras.Sequential([model, tf.keras.layers.Softmax()])
 
         
-    def classifyImage(img):
-        #global probability_model
-        #global class_names      
-        
+    def classifyImage(img):     
         # Normalize the pixel values
         img = np.array(img) / 255.0