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import streamlit as st
from PIL import Image, UnidentifiedImageError
import io
import uuid
import urllib.parse
from datetime import datetime
import pytz
from ocr_engine import extract_weight_from_image # Make sure this returns (weight, confidence)
# Set up page
st.set_page_config(page_title="⚖️ Auto Weight Logger", layout="centered")
st.title("⚖️ Auto Weight Logger")
# Session state keys
if "camera_key" not in st.session_state:
st.session_state.camera_key = str(uuid.uuid4())
if "captured_time" not in st.session_state:
st.session_state.captured_time = ""
# Get IST time
def get_current_ist_time():
ist = pytz.timezone("Asia/Kolkata")
return datetime.now(ist).strftime("%Y-%m-%d %I:%M:%S %p")
# Input selection
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.session_state.captured_time = ""
st.rerun()
# Image handling
image_bytes = None
image = None
# Webcam input
if input_mode == "Camera":
cam_photo = st.camera_input("📷 Capture Weight Display", key=st.session_state.camera_key)
if cam_photo:
image_bytes = cam_photo.getvalue()
st.session_state.captured_time = get_current_ist_time()
# File upload
elif input_mode == "Upload":
uploaded_file = st.file_uploader("📁 Upload an image (JPG/PNG)", type=["jpg", "jpeg", "png"])
if uploaded_file:
image_bytes = uploaded_file.read()
st.session_state.captured_time = get_current_ist_time()
# Process and display
if image_bytes:
try:
image = Image.open(io.BytesIO(image_bytes))
# 1. Show Captured At
st.markdown(f"### 🕒 Captured At (IST): `{st.session_state.captured_time}`")
# 2. Show Snapshot Image
st.markdown("### 🖼️ Snapshot Image")
st.image(image, use_column_width=True)
# 3. Extract OCR and show result
if len(image_bytes) > 5 * 1024 * 1024:
st.error("❌ Image too large (>5MB). Please upload a smaller image.")
st.stop()
with st.spinner("🔍 Extracting weight using OCR..."):
weight, confidence = extract_weight_from_image(image)
st.markdown("### ⚖️ Captured Weight & OCR Confidence")
if not weight or confidence < 80:
st.error(f"⚠️ Low OCR Confidence ({int(confidence)}%). Please retake or upload a clearer image.")
st.markdown("**Detected Weight:** Not reliable")
else:
st.success(f"✅ Detected Weight: `{weight} g`")
st.markdown(f"**Confidence:** `{int(confidence)}%`")
# 4. Send to Salesforce
device_id = "BAL-001"
image_url = "" # optional
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 to Log Weight in Salesforce]({salesforce_url})", unsafe_allow_html=True)
except UnidentifiedImageError:
st.error("❌ Unable to process image. Please upload a valid JPG or PNG.")
except Exception as e:
st.error("❌ Unexpected error.")
st.exception(e)
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