Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,50 +1,52 @@
 import streamlit as st
 from PIL import Image
-from ocr_engine import extract_weight_from_image
-import urllib.parse
-import uuid
 import io
+import uuid
+import urllib.parse
+from ocr_engine import extract_weight_from_image  # Your OCR logic
 
 st.set_page_config(page_title="⚖️ Auto Weight Logger", layout="centered")
 st.title("⚖️ Auto Weight Logger")
 
-# Session state for camera reload
+# Unique key for camera input refresh
 if "camera_key" not in st.session_state:
     st.session_state.camera_key = str(uuid.uuid4())
 
-# Input method selector
-input_method = st.radio("📸 Select Input Method", ["Camera", "Upload"], horizontal=True)
+# UI - Input type selector
+input_method = st.radio("📸 Choose Input Method", ["Camera", "Upload"], horizontal=True)
 
-# Clear button
+# UI - Clear/reset
 if st.button("🔁 Clear / Retake"):
     st.session_state.camera_key = str(uuid.uuid4())
     st.experimental_rerun()
 
+# Initialize variables
 image_bytes = None
 image = None
 
-# ----- CAMERA INPUT -----
+# ----------------- CAMERA -----------------
 if input_method == "Camera":
-    camera_image = st.camera_input("📷 Capture the weight display", key=st.session_state.camera_key)
-    if camera_image is not None:
-        image_bytes = camera_image.getvalue()
+    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()
 
-# ----- FILE UPLOAD INPUT -----
+# ----------------- UPLOAD -----------------
 elif input_method == "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()
+    uploaded_image = st.file_uploader("📁 Upload image (JPG, PNG)", type=["jpg", "jpeg", "png"])
+    if uploaded_image is not None:
+        image_bytes = uploaded_image.read()
 
-# ----- IMAGE PROCESSING -----
+# ----------------- PROCESS IMAGE -----------------
 if image_bytes:
     try:
         image = Image.open(io.BytesIO(image_bytes))
         st.image(image, caption="📸 Snapshot", use_column_width=True)
 
         if len(image_bytes) > 5 * 1024 * 1024:
-            st.error("❌ Image too large (>5MB). Please use a smaller one.")
+            st.error("❌ Image too large (>5MB). Try a smaller file.")
             st.stop()
 
+        # OCR
         with st.spinner("🔍 Extracting weight..."):
             weight, confidence = extract_weight_from_image(image)
 
@@ -55,9 +57,9 @@ if image_bytes:
         else:
             st.success(f"✅ Detected Weight: {weight} g (Confidence: {int(confidence)}%)")
 
-            # Salesforce redirect link
+            # Salesforce link
             device_id = "BAL-001"
-            image_url = ""  # Optional
+            image_url = ""  # Optional if you host it
 
             salesforce_url = (
                 "https://autoweightlogger-dev-ed.my.salesforce-sites.com/"
@@ -69,5 +71,5 @@ if image_bytes:
             st.markdown(f"[✅ Click here to confirm and log in Salesforce]({salesforce_url})", unsafe_allow_html=True)
 
     except Exception as e:
-        st.error("❌ Failed to load or process the image.")
+        st.error("❌ Failed to read/process the image.")
         st.exception(e)