chore: new messages as info

app.py

@@ -87,24 +87,24 @@ with st.sidebar:
     if img_file_buffer:
         # To read image file buffer as a PIL Image:
         photo = Image.open(img_file_buffer)
-        print("picture taken!")
+        st.info("picture taken!")
         
 st.text(f'{information} mode is ON!\nTarget 🧾: {receipt}')  # \n(opening image @:./img/receipt-{receipt}.png)')
 
-if photo:
-    image = photo
-    print("photo loaded to image")
-elif image_upload:
-    image = image_upload
-else:
-    image = Image.open(f"./img/receipt-{receipt}.jpg")
-
 col1, col2 = st.columns(2)
 
-with col1:
-    st.image(image, caption='Your target receipt')
+with st.spinner('Loading image...'):
+    if photo:
+        image = photo
+        st.info("photo loaded to image")
+    elif image_upload:
+        image = image_upload
+    else:
+        image = Image.open(f"./img/receipt-{receipt}.jpg")
+    with col1:
+        st.image(image, caption='Your target receipt')
 
-st.text(f'baking the 🍩s...')
+st.info(f'baking the 🍩s...')
 
 if information == 'Receipt Summary':
     processor = DonutProcessor.from_pretrained("unstructuredio/donut-base-sroie")
@@ -130,7 +130,7 @@ else:
 
 with col2:
     if information == 'Extract all':
-        st.text(f'parsing 🧾 (extracting all)...')
+        st.info(f'parsing 🧾 (extracting all)...')
         pretrained_model, processor, task_prompt = pretrained_model_a, processor_a, f"<s>"
         pretrained_model.to(device)
         parsed_receipt_info_a, _ = run_prediction(image)
@@ -142,7 +142,7 @@ with col2:
         st.text(f'\nReceipt Menu Details:')
         st.json(parsed_receipt_info_b)
     else:
-        st.text(f'parsing 🧾...')
+        st.info(f'parsing 🧾...')
         parsed_receipt_info, _ = run_prediction(image)
         st.text(f'\n{information}')
         st.json(parsed_receipt_info)