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import streamlit as st
from ocr_processor import extract_info
from api_client import fetch_product
def main():
st.title("🛒 Advanced OCR Product Scanner")
uploaded_file = st.file_uploader("Upload product image", type=["jpg", "png", "jpeg"])
if uploaded_file:
# saving the img and process further
with open("temp_img.jpg", "wb") as f:
f.write(uploaded_file.getbuffer())
# Extract information
info = extract_info("temp_img.jpg")
# Display extraction results
st.subheader("🔍 Extracted Information")
st.info(f"**Raw OCR Text:** {info['raw_text']}")
st.success(f"**Cleaned Text:** {info['clean_text']}")
st.write(f"**Detected Brand:** {info['brand']}")
st.write(f"**Detected Product Name:** {info['product_name']}")
st.write(f"**Barcodes:** {info['barcodes'] or 'None'}")
# Fetch product data
product_data = fetch_product(info)
display_product_info(product_data)
def display_product_info(product):
if not product:
st.error("Product not found in database")
st.markdown("**Tip:** Try a clearer image or different product")
st.markdown("Contribute to Open Food Facts: [Add Product](https://world.openfoodfacts.org/add-product)")
return
# Handle missing datas
st.subheader("📦 Product Information")
st.write(f"**Name:** {product.get('product_name', 'N/A')}")
st.write(f"**Brand:** {product.get('brands', 'N/A')}")
st.write(f"**Ingredients:** {product.get('ingredients_text', 'N/A')[:300]}...")
if 'nutriments' in product:
st.write("**Nutrition Facts (per 100g):**")
nutrients = product['nutriments']
st.write(f"- Calories: {nutrients.get('energy-kcal_100g', 'N/A')} kcal")
st.write(f"- Fat: {nutrients.get('fat_100g', 'N/A')}g")
st.write(f"- Carbs: {nutrients.get('carbohydrates_100g', 'N/A')}g")
st.write(f"- Protein: {nutrients.get('proteins_100g', 'N/A')}g")
st.write(f"**Categories:** {product.get('categories', 'N/A')}")
if __name__ == "__main__":
main() |