import streamlit as st from PIL import Image from ocr_engine import extract_weight_from_image import urllib.parse import uuid st.set_page_config(page_title="⚖️ Auto Weight Logger", layout="centered") st.title("⚖️ Auto Weight Logger") # Session state if "image_data" not in st.session_state: st.session_state.image_data = None if "camera_key" not in st.session_state: st.session_state.camera_key = str(uuid.uuid4()) # Clear / Retake if st.button("🔁 Clear / Retake Photo"): st.session_state.image_data = None st.session_state.camera_key = str(uuid.uuid4()) # new key to force reload # Show camera if st.session_state.image_data is None: img_data = st.camera_input("📷 Capture the weight display", key=st.session_state.camera_key) if img_data: st.session_state.image_data = img_data # Process image if st.session_state.image_data: st.success("✅ Image captured successfully!") image = Image.open(st.session_state.image_data) st.image(image, caption="📸 Snapshot", use_column_width=True) if len(st.session_state.image_data.getvalue()) > 5 * 1024 * 1024: st.error("❌ Image too large (>5MB). Please try again.") st.stop() with st.spinner("🔍 Extracting weight..."): weight, confidence = extract_weight_from_image(image) st.write(f"🛠️ DEBUG: weight = {weight}, confidence = {confidence}") if not weight or confidence < 80: st.error(f"⚠️ OCR confidence too low ({int(confidence)}%). Please retake the photo.") else: st.success(f"✅ Detected Weight: {weight} g (Confidence: {int(confidence)}%)") device_id = "BAL-001" image_url = "" 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"[✅ Click here to confirm and log in Salesforce]({salesforce_url})", unsafe_allow_html=True) if st.button("🔁 Retake Photo"): st.session_state.image_data = None st.session_state.camera_key = str(uuid.uuid4())