Refactor prediction function: update data logging, reshape input handling, and simplify sketchpad configuration

app.py

@@ -28,16 +28,12 @@ model = tf.keras.models.load_model("./sketch_recognition_numbers_model.h5")
 
 # Prediction function for sketch recognition
 def predict(data):
-    print(data)
-    # ValueError: cannot reshape array of size 1 into shape (1,28,28,1)
-
+    print(data.shape)
     # Reshape image to 28x28
     img = np.reshape(data['composite'], (1, img_size, img_size, 1))
     # Make prediction
     pred = model.predict(img)
     # Get top class
-    top_class = np.argmax
-    # Get top 3 classes
     top_3_classes = np.argsort(pred[0])[-3:][::-1]
     # Get top 3 probabilities
     top_3_probs = pred[0][top_3_classes]
@@ -52,7 +48,7 @@ label = gr.Label(num_top_classes=3)
 # Open Gradio interface for sketch recognition
 interface = gr.Interface(
     fn=predict,
-    inputs=gr.Sketchpad(crop_size=(28,28), type='numpy', image_mode='L', brush=gr.Brush()),
+    inputs=gr.Sketchpad(type='numpy'),
     outputs=label,
     title=title,
     description=head,