Update app.py

app.py

@@ -32,26 +32,49 @@ def transcribe_handwriting(image):
 
 # Set Streamlit page configuration
 st.set_page_config(
-    page_title="Prescription Reader",
+    page_title="AI and ML Handwriting Reader",
     page_icon="💊",
     layout="centered",
 )
 
+# Function to display extracted text in a fancy div
+def display_extracted_text(extracted_text):
+    # Custom HTML and CSS for styling
+    fancy_div = f"""
+    <div style="
+        border: 2px solid #128c7E; 
+        border-radius: 10px; 
+        padding: 20px; 
+        background-color: #f0f0f0; 
+        box-shadow: 0 4px 10px rgba(0, 0, 0, 0.1); 
+        font-family: 'Arial', sans-serif; 
+        color: #333;">
+        <h2 style="color: #128c7E;">Transcribed Text from Image:</h2>
+        <p style="font-size: 16px;">{extracted_text}</p>
+    </div>
+    """
+    st.markdown(fancy_div, unsafe_allow_html=True)
+    
 # Header
-st.title("Doctor's Prescription Reader 💊")
+st.title("AI and ML based Handwriting Reader")
 
 # Upload prescription image
-uploaded_file = st.file_uploader("Upload Prescription Image", type=["jpg", "jpeg", "png"])
+uploaded_file = st.file_uploader("Upload Handwriting Image", type=["jpg", "jpeg", "png"])
 
 if uploaded_file is not None:
     # Open the image using PIL
     image = Image.open(uploaded_file)
 
     # Display uploaded image
-    st.image(image, caption="Uploaded Prescription", use_column_width=True)
+    st.image(image, caption="Uploaded Handwriting Image", width="400")
 
     with st.spinner("Transcribing handwriting..."):
         # Transcribe handwritten notes
         extracted_text = transcribe_handwriting(image)
         st.subheader("Transcribed Text from Prescription:")
-        st.text(extracted_text)
+        display_extracted_text(extracted_text)
+
+
+
+
+