Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,65 +1,76 @@
 import streamlit as st
-from PIL import Image
+from PIL import Image, UnidentifiedImageError
 import io
 import uuid
 import urllib.parse
+import pytz
+from datetime import datetime
 from ocr_engine import extract_weight_from_image  # your OCR function
 
 # Setup
 st.set_page_config(page_title="⚖️ Auto Weight Logger", layout="centered")
 st.title("⚖️ Auto Weight Logger")
 
-# Camera refresh key
+# IST timezone
+ist = pytz.timezone('Asia/Kolkata')
+
+# Session state
 if "camera_key" not in st.session_state:
     st.session_state.camera_key = str(uuid.uuid4())
 
-# Input selector
+# Input method
 input_mode = st.radio("📸 Select Input Method", ["Camera", "Upload"], horizontal=True)
 
-# Retake button
+# Reset
 if st.button("🔁 Clear / Retake"):
     st.session_state.camera_key = str(uuid.uuid4())
     st.experimental_rerun()
 
-# Variables
 image_bytes = None
 image = None
 
-# Camera mode
+# Camera input
 if input_mode == "Camera":
     cam_photo = st.camera_input("📷 Take a photo of the weight display", key=st.session_state.camera_key)
     if cam_photo is not None:
         image_bytes = cam_photo.getvalue()
 
-# Upload mode
+# Upload input
 elif input_mode == "Upload":
-    uploaded_file = st.file_uploader("📁 Upload an image (JPG/PNG)", type=["jpg", "jpeg", "png"])
+    uploaded_file = st.file_uploader("📁 Upload a JPG/PNG image", type=["jpg", "jpeg", "png"])
     if uploaded_file is not None:
-        image_bytes = uploaded_file.read()
+        try:
+            image_bytes = uploaded_file.read()
+        except Exception as e:
+            st.error("❌ Failed to read uploaded file.")
+            st.exception(e)
 
-# Show image and process
+# Image display and OCR
 if image_bytes:
     try:
         image = Image.open(io.BytesIO(image_bytes))
-        st.image(image, caption="📸 Preview", use_column_width=True)
+        st.image(image, caption="📸 Snapshot", use_column_width=True)
 
         if len(image_bytes) > 5 * 1024 * 1024:
-            st.error("❌ Image is too large (>5MB). Please use a smaller image.")
+            st.error("❌ Image too large (>5MB).")
             st.stop()
 
         with st.spinner("🔍 Extracting weight using OCR..."):
             weight, confidence = extract_weight_from_image(image)
 
-        st.write(f"🛠️ DEBUG: Weight = {weight}, Confidence = {confidence}")
-
         if not weight or confidence < 80:
-            st.error(f"⚠️ Low OCR confidence ({int(confidence)}%). Try again.")
+            st.error(f"⚠️ OCR Confidence too low ({int(confidence)}%). Try again.")
         else:
-            st.success(f"✅ Detected Weight: {weight} g (Confidence: {int(confidence)}%)")
+            # IST time
+            captured_time = datetime.now(ist).strftime("%Y-%m-%d %I:%M:%S %p")
+
+            st.success("✅ OCR Success")
+            st.markdown(f"### 📦 Captured Weight: `{weight} g`")
+            st.markdown(f"### 🕒 Captured At (IST): `{captured_time}`")
 
-            # Generate Salesforce URL
+            # Salesforce link
             device_id = "BAL-001"
-            image_url = ""  # optional if image storage is needed
+            image_url = ""  # optional if stored externally
 
             salesforce_url = (
                 "https://autoweightlogger-dev-ed.my.salesforce-sites.com/"
@@ -68,8 +79,10 @@ if image_bytes:
             )
 
             st.markdown("### 📤 Send to Salesforce")
-            st.markdown(f"[✅ Confirm and Log in Salesforce]({salesforce_url})", unsafe_allow_html=True)
+            st.markdown(f"[✅ Click to Log in Salesforce]({salesforce_url})", unsafe_allow_html=True)
 
+    except UnidentifiedImageError:
+        st.error("❌ Unsupported or invalid image format.")
     except Exception as e:
-        st.error("❌ Error processing the image.")
+        st.error("❌ Unexpected error processing image.")
         st.exception(e)