Update src/streamlit_app.py

src/streamlit_app.py

@@ -3,6 +3,7 @@ from PIL import Image
 from ocr_engine import extract_weight_from_image
 import urllib.parse
 import uuid
+import io
 
 st.set_page_config(page_title="⚖️ Auto Weight Logger", layout="centered")
 st.title("⚖️ Auto Weight Logger")
@@ -15,35 +16,46 @@ if "input_mode" not in st.session_state:
 if "camera_key" not in st.session_state:
     st.session_state.camera_key = str(uuid.uuid4())
 
-# Choose input mode
+# Choose input method
 st.radio("📸 Select Image Input Method:", ["Camera", "Upload"], key="input_mode", horizontal=True)
 
-# Reset image
+# Clear/reset image
 if st.button("🔁 Clear / Retake Photo"):
     st.session_state.image_data = None
-    st.session_state.camera_key = str(uuid.uuid4())  # Reload webcam
+    st.session_state.camera_key = str(uuid.uuid4())
+
+# Get image input
+uploaded_image = None
 
-# Input section
 if st.session_state.image_data is None:
     if st.session_state.input_mode == "Camera":
-        img_data = st.camera_input("📷 Capture the weight display", key=st.session_state.camera_key)
+        uploaded_image = st.camera_input("📷 Capture the weight display", key=st.session_state.camera_key)
     else:
-        img_data = st.file_uploader("📁 Upload an image of the weight display", type=["jpg", "jpeg", "png"])
+        uploaded_image = st.file_uploader("📁 Upload an image of the weight display", type=["jpg", "jpeg", "png"])
 
-    if img_data:
-        st.session_state.image_data = img_data
+    if uploaded_image:
+        st.session_state.image_data = uploaded_image
 
-# OCR and Display
+# Process image
 if st.session_state.image_data:
     st.success("✅ Image received successfully!")
-    image = Image.open(st.session_state.image_data)
+
+    # Convert to PIL image
+    try:
+        image_bytes = st.session_state.image_data.read() if hasattr(st.session_state.image_data, 'read') else st.session_state.image_data.getvalue()
+        image = Image.open(io.BytesIO(image_bytes))
+    except Exception as e:
+        st.error("❌ Failed to load image.")
+        st.stop()
+
     st.image(image, caption="📸 Snapshot", use_column_width=True)
 
-    # Check image size
-    if len(st.session_state.image_data.getvalue()) > 5 * 1024 * 1024:
-        st.error("❌ Image too large (>5MB). Please try a smaller file.")
+    # Size check
+    if len(image_bytes) > 5 * 1024 * 1024:
+        st.error("❌ Image too large (>5MB). Please upload a smaller image.")
         st.stop()
 
+    # OCR Extraction
     with st.spinner("🔍 Extracting weight..."):
         weight, confidence = extract_weight_from_image(image)
 
@@ -54,8 +66,9 @@ if st.session_state.image_data:
     else:
         st.success(f"✅ Detected Weight: {weight} g (Confidence: {int(confidence)}%)")
 
+        # Generate Salesforce URL
         device_id = "BAL-001"
-        image_url = ""  # Placeholder for now
+        image_url = ""  # You can upload to S3 or Salesforce Files if needed
 
         salesforce_url = (
             "https://autoweightlogger-dev-ed.my.salesforce-sites.com/"
@@ -66,6 +79,7 @@ if st.session_state.image_data:
         st.markdown("### 📤 Send to Salesforce")
         st.markdown(f"[✅ Click here to confirm and log in Salesforce]({salesforce_url})", unsafe_allow_html=True)
 
+    # Retake or upload another
     if st.button("🔁 Retake / Upload Another"):
         st.session_state.image_data = None
         st.session_state.camera_key = str(uuid.uuid4())