Update app.py

app.py

@@ -20,9 +20,6 @@ output_module1 = gr.outputs.Textbox(label = "Predicted Digit")
 output_module2 = gr.outputs.Image(label = "Predicted Probability per class")
 
 def image_classification(input1, input2):
-    print(input1.shape)
-    print(input2)
-
     image = input1.reshape(1, 28 *28)
     X_train = x_train.reshape(60000, 28*28)
     X_test = x_test.reshape(10000, 28*28)
@@ -32,8 +29,8 @@ def image_classification(input1, input2):
     
     y_test_predicted_label = kNN_classifier.predict(image)
 
-    output1 = y_test_predicted_label# text output example
-    output2 = np.random.rand(2,2) # image-like array output example
+    output1 = y_test_predicted_label[0]# text output example
+    output2 = y_test_predicted_label[1:5] # image-like array output example
     return output1,output2
 
 # Step 6.4: Put all three component together into the gradio's interface function