Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,20 +1,75 @@
 import streamlit as st
 from PIL import Image
 import io
+import uuid
+import urllib.parse
+from ocr_engine import extract_weight_from_image  # your OCR function
 
-st.set_page_config(page_title="📁 Image Preview", layout="centered")
-st.title("🖼️ Image Uploader & Viewer")
+# Setup
+st.set_page_config(page_title="⚖️ Auto Weight Logger", layout="centered")
+st.title("⚖️ Auto Weight Logger")
 
-# Upload image
-uploaded_file = st.file_uploader("📁 Upload a JPG, JPEG, or PNG image", type=["jpg", "jpeg", "png"])
+# Camera refresh key
+if "camera_key" not in st.session_state:
+    st.session_state.camera_key = str(uuid.uuid4())
 
-# Show image
-if uploaded_file is not None:
+# Input selector
+input_mode = st.radio("📸 Select Input Method", ["Camera", "Upload"], horizontal=True)
+
+# Retake button
+if st.button("🔁 Clear / Retake"):
+    st.session_state.camera_key = str(uuid.uuid4())
+    st.experimental_rerun()
+
+# Variables
+image_bytes = None
+image = None
+
+# 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 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()
+
+# Show image and process
+if image_bytes:
     try:
-        image = Image.open(io.BytesIO(uploaded_file.read()))
-        st.image(image, caption="✅ Uploaded Image", use_column_width=True)
+        image = Image.open(io.BytesIO(image_bytes))
+        st.image(image, caption="📸 Preview", use_column_width=True)
+
+        if len(image_bytes) > 5 * 1024 * 1024:
+            st.error("❌ Image is too large (>5MB). Please use a smaller image.")
+            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.")
+        else:
+            st.success(f"✅ Detected Weight: {weight} g (Confidence: {int(confidence)}%)")
+
+            # Generate Salesforce URL
+            device_id = "BAL-001"
+            image_url = ""  # optional if image storage is needed
+
+            salesforce_url = (
+                "https://autoweightlogger-dev-ed.my.salesforce-sites.com/"
+                f"weight_logger_page?WeightInput={urllib.parse.quote(str(weight))}"
+                f"&DeviceID={urllib.parse.quote(device_id)}&ImageURL={urllib.parse.quote(image_url)}"
+            )
+
+            st.markdown("### 📤 Send to Salesforce")
+            st.markdown(f"[✅ Confirm and Log in Salesforce]({salesforce_url})", unsafe_allow_html=True)
+
     except Exception as e:
-        st.error("❌ Could not open image.")
+        st.error("❌ Error processing the image.")
         st.exception(e)
-else:
-    st.info("📌 Please upload an image to display it here.")