Uncommented commented out app

app.py

@@ -118,25 +118,23 @@ def predict(image, reader, processor: LayoutLMv3Processor, model: LayoutLMv3ForS
         probabilities = F.softmax(logits, dim=-1).flatten().tolist()
         return predicted_class.detach().item(), probabilities
 
-st.markdown(f"Test")
-
-# reader = create_ocr_reader()
-# processor = create_processor()
-# model = create_model()
-
-# uploaded_file = st.file_uploader("Choose a JPG file", ["jpg", "png"])
-# if uploaded_file is not None:
-#     bytes_data = io.BytesIO(uploaded_file.read())    
-#     image = Image.open(bytes_data)
-#     st.image(image, caption="Uploaded Image", use_column_width=True)
-#     predicted, probabilities = predict(image, reader, processor, model)
-#     predicted_label = model.config.id2label[predicted]
-#     st.markdown(f"Predicted Label: {predicted_label}")
-
-#     df = pd.DataFrame({
-#         "Label": list(model.config.id2label.values()),
-#         "Probability": probabilities
-#     })
-#     fig = px.bar(df, x="Label", y="Probability")
-#     st.plotly_chart(fig, use_container_width=True)
+reader = create_ocr_reader()
+processor = create_processor()
+model = create_model()
+
+uploaded_file = st.file_uploader("Choose a JPG file", ["jpg", "png"])
+if uploaded_file is not None:
+    bytes_data = io.BytesIO(uploaded_file.read())    
+    image = Image.open(bytes_data)
+    st.image(image, caption="Uploaded Image", use_column_width=True)
+    predicted, probabilities = predict(image, reader, processor, model)
+    predicted_label = model.config.id2label[predicted]
+    st.markdown(f"Predicted Label: {predicted_label}")
+
+    df = pd.DataFrame({
+        "Label": list(model.config.id2label.values()),
+        "Probability": probabilities
+    })
+    fig = px.bar(df, x="Label", y="Probability")
+    st.plotly_chart(fig, use_container_width=True)