Update src/streamlit_app.py

src/streamlit_app.py

@@ -3,63 +3,63 @@ from PIL import Image
 import io
 import uuid
 import urllib.parse
-from ocr_engine import extract_weight_from_image  # Your OCR logic
+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")
 
-# Unique key for camera input refresh
+# Camera refresh key
 if "camera_key" not in st.session_state:
     st.session_state.camera_key = str(uuid.uuid4())
 
-# UI - Input type selector
-input_method = st.radio("📸 Choose Input Method", ["Camera", "Upload"], horizontal=True)
+# Input selector
+input_mode = st.radio("📸 Select Input Method", ["Camera", "Upload"], horizontal=True)
 
-# UI - Clear/reset
+# Retake button
 if st.button("🔁 Clear / Retake"):
     st.session_state.camera_key = str(uuid.uuid4())
     st.experimental_rerun()
 
-# Initialize variables
+# Variables
 image_bytes = None
 image = None
 
-# ----------------- CAMERA -----------------
-if input_method == "Camera":
-    cam_image = st.camera_input("📷 Capture the weight display", key=st.session_state.camera_key)
-    if cam_image is not None:
-        image_bytes = cam_image.getvalue()
+# Camera mode
+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 -----------------
-elif input_method == "Upload":
-    uploaded_image = st.file_uploader("📁 Upload image (JPG, PNG)", type=["jpg", "jpeg", "png"])
-    if uploaded_image is not None:
-        image_bytes = uploaded_image.read()
+# Upload mode
+elif input_mode == "Upload":
+    uploaded_file = st.file_uploader("📁 Upload an image (JPG/PNG)", type=["jpg", "jpeg", "png"])
+    if uploaded_file is not None:
+        image_bytes = uploaded_file.read()
 
-# ----------------- PROCESS IMAGE -----------------
+# Show image and process
 if image_bytes:
     try:
         image = Image.open(io.BytesIO(image_bytes))
-        st.image(image, caption="📸 Snapshot", use_column_width=True)
+        st.image(image, caption="📸 Preview", use_column_width=True)
 
         if len(image_bytes) > 5 * 1024 * 1024:
-            st.error("❌ Image too large (>5MB). Try a smaller file.")
+            st.error("❌ Image is too large (>5MB). Please use a smaller image.")
             st.stop()
 
-        # OCR
-        with st.spinner("🔍 Extracting weight..."):
+        with st.spinner("🔍 Extracting weight using OCR..."):
             weight, confidence = extract_weight_from_image(image)
 
-        st.write(f"🛠️ DEBUG: weight = {weight}, confidence = {confidence}")
+        st.write(f"🛠️ DEBUG: Weight = {weight}, Confidence = {confidence}")
 
         if not weight or confidence < 80:
-            st.error(f"⚠️ OCR confidence too low ({int(confidence)}%). Please try again.")
+            st.error(f"⚠️ Low OCR confidence ({int(confidence)}%). Try again.")
         else:
             st.success(f"✅ Detected Weight: {weight} g (Confidence: {int(confidence)}%)")
 
-            # Salesforce link
+            # Generate Salesforce URL
             device_id = "BAL-001"
-            image_url = ""  # Optional if you host it
+            image_url = ""  # optional if image storage is needed
 
             salesforce_url = (
                 "https://autoweightlogger-dev-ed.my.salesforce-sites.com/"
@@ -68,8 +68,8 @@ if image_bytes:
             )
 
             st.markdown("### 📤 Send to Salesforce")
-            st.markdown(f"[✅ Click here to confirm and log in Salesforce]({salesforce_url})", unsafe_allow_html=True)
+            st.markdown(f"[✅ Confirm and Log in Salesforce]({salesforce_url})", unsafe_allow_html=True)
 
     except Exception as e:
-        st.error("❌ Failed to read/process the image.")
+        st.error("❌ Error processing the image.")
         st.exception(e)