Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,75 +1,20 @@
 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
 
-# Setup
-st.set_page_config(page_title="⚖️ Auto Weight Logger", layout="centered")
-st.title("⚖️ Auto Weight Logger")
+st.set_page_config(page_title="📁 Image Preview", layout="centered")
+st.title("🖼️ Image Uploader & Viewer")
 
-# Camera refresh key
-if "camera_key" not in st.session_state:
-    st.session_state.camera_key = str(uuid.uuid4())
+# Upload image
+uploaded_file = st.file_uploader("📁 Upload a JPG, JPEG, or PNG image", type=["jpg", "jpeg", "png"])
 
-# 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:
+# Show image
+if uploaded_file is not None:
     try:
-        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)
-
+        image = Image.open(io.BytesIO(uploaded_file.read()))
+        st.image(image, caption="✅ Uploaded Image", use_column_width=True)
     except Exception as e:
-        st.error("❌ Error processing the image.")
+        st.error("❌ Could not open image.")
         st.exception(e)
+else:
+    st.info("📌 Please upload an image to display it here.")