chore: style refactor

app.py

@@ -93,40 +93,38 @@ st.text(f'{information} mode is ON!\nTarget 🧾: {receipt}')  # \n(opening imag
 
 col1, col2 = st.columns(2)
 
-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.info(f'baking the 🍩s...')
-
-if information == 'Receipt Summary':
-    processor = DonutProcessor.from_pretrained("unstructuredio/donut-base-sroie")
-    pretrained_model = VisionEncoderDecoderModel.from_pretrained("unstructuredio/donut-base-sroie")
-    task_prompt = f"<s>"
-    device = "cuda" if torch.cuda.is_available() else "cpu"
-    pretrained_model.to(device)
-
-elif information == 'Receipt Menu Details':
-    processor = DonutProcessor.from_pretrained("naver-clova-ix/donut-base-finetuned-cord-v2")
-    pretrained_model = VisionEncoderDecoderModel.from_pretrained("naver-clova-ix/donut-base-finetuned-cord-v2")
-    task_prompt = f"<s_cord-v2>"
-    device = "cuda" if torch.cuda.is_available() else "cpu"
-    pretrained_model.to(device)
-    
+if photo:
+    image = photo
+    st.info("photo loaded to image")
+elif image_upload:
+    image = image_upload
 else:
-    processor_a = DonutProcessor.from_pretrained("unstructuredio/donut-base-sroie")
-    processor_b = DonutProcessor.from_pretrained("naver-clova-ix/donut-base-finetuned-cord-v2")
-    pretrained_model_a = VisionEncoderDecoderModel.from_pretrained("unstructuredio/donut-base-sroie")
-    pretrained_model_b = VisionEncoderDecoderModel.from_pretrained("naver-clova-ix/donut-base-finetuned-cord-v2")
+    image = Image.open(f"./img/receipt-{receipt}.jpg")
+with col1:
+    st.image(image, caption='Your target receipt')
+
+with st.spinner(f'baking the 🍩s...'):
+    if information == 'Receipt Summary':
+        processor = DonutProcessor.from_pretrained("unstructuredio/donut-base-sroie")
+        pretrained_model = VisionEncoderDecoderModel.from_pretrained("unstructuredio/donut-base-sroie")
+        task_prompt = f"<s>"
+        device = "cuda" if torch.cuda.is_available() else "cpu"
+        pretrained_model.to(device)
     
-    device = "cuda" if torch.cuda.is_available() else "cpu"
+    elif information == 'Receipt Menu Details':
+        processor = DonutProcessor.from_pretrained("naver-clova-ix/donut-base-finetuned-cord-v2")
+        pretrained_model = VisionEncoderDecoderModel.from_pretrained("naver-clova-ix/donut-base-finetuned-cord-v2")
+        task_prompt = f"<s_cord-v2>"
+        device = "cuda" if torch.cuda.is_available() else "cpu"
+        pretrained_model.to(device)
+        
+    else:
+        processor_a = DonutProcessor.from_pretrained("unstructuredio/donut-base-sroie")
+        processor_b = DonutProcessor.from_pretrained("naver-clova-ix/donut-base-finetuned-cord-v2")
+        pretrained_model_a = VisionEncoderDecoderModel.from_pretrained("unstructuredio/donut-base-sroie")
+        pretrained_model_b = VisionEncoderDecoderModel.from_pretrained("naver-clova-ix/donut-base-finetuned-cord-v2")
+        
+        device = "cuda" if torch.cuda.is_available() else "cpu"
 
 with col2:
     if information == 'Extract all':