Update src/streamlit_app.py

src/streamlit_app.py

@@ -9,33 +9,27 @@ st.title("⚖️ Auto Weight Logger")
 img_data = st.camera_input("📷 Capture the weight display")
 
 if img_data:
-    # ✅ Check file size (BRD requirement)
     if len(img_data.getvalue()) > 5 * 1024 * 1024:
         st.error("❌ Image too large (>5MB). Please try again.")
         st.stop()
 
-    # ✅ Show the image to user
     image = Image.open(img_data)
     st.image(image, caption="📸 Snapshot", use_column_width=True)
 
-    # ✅ Run OCR to get weight and confidence
     with st.spinner("🔍 Extracting weight..."):
         weight, confidence = extract_weight_from_image(image)
 
-    # ✅ DEBUG: Uncomment this to see raw output
-    # st.write(f"DEBUG: weight = {weight}, confidence = {confidence}")
+    # ✅ Show debug info (you can delete this later)
+    st.write(f"🛠️ DEBUG: weight = {weight}, confidence = {confidence}")
 
-    # ✅ Handle OCR failure or low confidence
     if not weight or confidence < 80:
         st.error(f"⚠️ OCR confidence too low ({int(confidence)}%). Please retake the image.")
         if st.button("🔁 Try Again"):
             st.experimental_rerun()
         st.stop()
 
-    # ✅ Show success with weight and confidence
     st.success(f"✅ Detected Weight: {weight} g (Confidence: {int(confidence)}%)")
 
-    # ✅ Prepare Salesforce link
     device_id = "BAL-001"
     image_url = ""
 
@@ -48,6 +42,5 @@ if img_data:
         f"weight_logger_page?WeightInput={encoded_weight}&DeviceID={encoded_device}&ImageURL={encoded_image_url}"
     )
 
-    # ✅ Show Salesforce confirmation link
     st.markdown("### 📤 Send to Salesforce")
     st.markdown(f"[✅ Click here to confirm and log in Salesforce]({salesforce_url})", unsafe_allow_html=True)