Update app.py

app.py

@@ -9,8 +9,27 @@ def main():
     tabs = st.tabs(["Intro", "find order"])
 
     with tabs[0]:
-        st.write('## Intro')
-        st.write('This is the introduction tab')
+        col1, col2 = st.columns([1, 2])
+        with col1:
+            st.image("image.jpg", use_column_width=True)
+        with col2:
+            st.markdown(
+            """
+            <h3 style='text-align: center;'>Lorem ipsum dolor sit amet!</h3>
+            
+            <p>Lorem ipsum dolor sit amet, consectetur adipiscing elit. Nam hendrerit nisi sed sollicitudin pellentesque.</p>            
+            <p>Lorem ipsum dolor sit amet, consectetur adipiscing elit. Nam hendrerit nisi sed sollicitudin pellentesque.</p>            
+            """,
+            unsafe_allow_html=True)
+        st.markdown(
+            """
+            <div style='text-align: center;'>
+                <h3 style='text-align: center;'>About the demo</h3>
+                <p>Lorem ipsum dolor sit amet, consectetur adipiscing elit. Nam hendrerit nisi sed sollicitudin pellentesque.</p>
+            
+            </div>
+            """, 
+            unsafe_allow_html=True)
 
     with tabs[1]:
         st.write('## Find Order')
@@ -20,9 +39,10 @@ def main():
             st.write('## Input')
             uploaded_file = st.file_uploader('Upload the image file (PNG or JPG)', type=['png', 'jpg'], help='help')
             input_file = st.file_uploader('Upload the input file (TXT)', type=['txt'], help='help')
-            ocre = st.selectbox('OCR Engine', ['Hive', 'Tesseract'])
-            img_processing = st.selectbox('Image preprocessing', ['Gray Scaling', 'Thresholding, Denoising, Binarization, Skew Correction', 'Adaptive Thresholding, Morphological Operations, CCA'])
-            cnn_model = st.selectbox('Neural Network Model', ['CNN-MaxPool-Dense-Dropout', 'BatchNorm-CNN-MaxPool-Dense-Dropout'])
+            with st.expander('Settings'):
+                ocre = st.selectbox('OCR Engine', ['Hive', 'Tesseract'])
+                img_processing = st.selectbox('Image preprocessing', ['Gray Scaling', 'Thresholding, Denoising, Binarization, Skew Correction', 'Adaptive Thresholding, Morphological Operations, CCA'])
+                cnn_model = st.selectbox('Neural Network Model', ['CNN-MaxPool-Dense-Dropout', 'BatchNorm-CNN-MaxPool-Dense-Dropout'])
     
         if st.button('Find Order ID') and uploaded_file and input_file:
             st.write('## Output')