Update src/streamlit_app.py

src/streamlit_app.py

@@ -5,9 +5,9 @@ import uuid
 import urllib.parse
 from datetime import datetime
 import pytz
-from ocr_engine import extract_weight_from_image  # Ensure this function returns (weight, confidence)
+from ocr_engine import extract_weight_from_image  # This must return (weight, confidence)
 
-# Set up page
+# Setup
 st.set_page_config(page_title="⚖️ Auto Weight Logger", layout="centered")
 st.title("⚖️ Auto Weight Logger")
 
@@ -19,12 +19,12 @@ if "captured_time" not in st.session_state:
 if "image_bytes" not in st.session_state:
     st.session_state.image_bytes = None
 
-# Get IST time
+# Function to get IST time
 def get_current_ist_time():
     ist = pytz.timezone("Asia/Kolkata")
     return datetime.now(ist).strftime("%Y-%m-%d %I:%M:%S %p")
 
-# Input method
+# Input selection
 input_mode = st.radio("📸 Select Input Method", ["Camera", "Upload"], horizontal=True)
 
 # Retake button
@@ -47,19 +47,20 @@ elif input_mode == "Upload":
         st.session_state.image_bytes = uploaded_file.read()
         st.session_state.captured_time = get_current_ist_time()
 
-# Process and Display (if image is available)
+# Process image
 if st.session_state.image_bytes:
     try:
         image = Image.open(io.BytesIO(st.session_state.image_bytes))
 
-        # 1. Show captured time
-        st.markdown(f"### 🕒 Captured At (IST): `{st.session_state.captured_time}`")
+        # Display bullet-point summary
+        st.markdown("### 📋 Captured Information")
 
-        # 2. Show image
-        st.markdown("### 🖼️ Snapshot Image")
+        st.markdown(f"""
+        - 🕒 **Captured At (IST):** `{st.session_state.captured_time}`
+        - 🖼️ **Snapshot Image:**  
+        """)
         st.image(image, use_column_width=True)
 
-        # 3. OCR processing
         if len(st.session_state.image_bytes) > 5 * 1024 * 1024:
             st.error("❌ Image too large (>5MB). Please upload a smaller image.")
             st.stop()
@@ -67,18 +68,16 @@ if st.session_state.image_bytes:
         with st.spinner("🔍 Extracting weight using OCR..."):
             weight, confidence = extract_weight_from_image(image)
 
-        # 4. Display OCR result
-        st.markdown("### ⚖️ Captured Weight & OCR Confidence")
         if not weight or confidence < 80:
-            st.error(f"⚠️ Low OCR Confidence ({int(confidence)}%). Please retake or upload a clearer image.")
-            st.markdown("**Detected Weight:** Not reliable")
+            st.markdown(f"- ⚠️ **Low OCR Confidence:** `{int(confidence)}%` — Please retake or upload a clearer image.")
+            st.markdown("- ⚖️ **Detected Weight:** Not reliable")
         else:
-            st.success(f"✅ Detected Weight: `{weight} g`")
-            st.markdown(f"**Confidence:** `{int(confidence)}%`")
+            st.markdown(f"- ⚖️ **Detected Weight:** `{weight} g`")
+            st.markdown(f"- 📊 **OCR Confidence:** `{int(confidence)}%`")
 
-        # 5. Send to Salesforce
+        # Salesforce link
         device_id = "BAL-001"
-        image_url = ""  # optional
+        image_url = ""  # Optional
 
         salesforce_url = (
             "https://autoweightlogger-dev-ed.my.salesforce-sites.com/"
@@ -109,5 +108,5 @@ if st.session_state.image_bytes:
     except UnidentifiedImageError:
         st.error("❌ Unable to process image. Please upload a valid JPG or PNG.")
     except Exception as e:
-        st.error("❌ Unexpected error.")
+        st.error("❌ Unexpected error occurred.")
         st.exception(e)