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import streamlit as st
from PIL import Image
import io
import numpy as np
# Import our custom modules
from utils.image_preprocessing import preprocess_image
from models.document_ai import extract_text_and_layout
from models.text_processor import process_menu_text
# App title and description
st.title("Menu to Braille Converter")
st.write("Upload a menu image to convert it to Braille text")
# Sidebar for model settings
st.sidebar.header("Settings")
use_llm = st.sidebar.checkbox("Use LLM for text processing", value=True)
# Add information about the application
st.sidebar.markdown("---")
st.sidebar.subheader("About")
st.sidebar.info(
"This application converts menu images to Braille text using AI. "
"It extracts text from images using document AI, processes the text with LLMs, "
"and will convert to Braille in future versions."
)
# File uploader
uploaded_file = st.file_uploader("Choose a menu image...", type=["jpg", "jpeg", "png"])
# Display uploaded image and process it
if uploaded_file is not None:
# Load and display image
image = Image.open(uploaded_file)
st.image(image, caption="Uploaded Menu", use_column_width=True)
# Add a button to process the image
if st.button("Process Menu"):
with st.spinner("Processing image..."):
# Preprocess the image
preprocessed_img = preprocess_image(image)
# Extract text using LayoutLMv2
try:
result = extract_text_and_layout(preprocessed_img)
# Display extracted words
if result['words']:
raw_text = ' '.join(result['words'])
# Show raw text in an expandable section
with st.expander("Raw Extracted Text"):
st.text_area("Raw OCR Output", raw_text, height=150)
# Process text with LLM if enabled
if use_llm:
st.subheader("Processed Menu Text")
with st.spinner("Enhancing text with AI..."):
processed_result = process_menu_text(raw_text)
if processed_result['success']:
st.text_area("Structured Menu Text",
processed_result['structured_text'],
height=300)
# Store the processed result for later use
st.session_state.processed_text = processed_result['structured_text']
st.session_state.menu_data = processed_result.get('menu_data', {})
else:
st.warning(f"AI processing failed: {processed_result.get('error', 'Unknown error')}")
st.text_area("Text Output", raw_text, height=300)
st.session_state.processed_text = raw_text
else:
# Just use the raw text
st.subheader("Extracted Text")
st.text_area("Text Output", raw_text, height=300)
st.session_state.processed_text = raw_text
else:
st.warning("No text was extracted from the image.")
except Exception as e:
st.error(f"Error processing image: {str(e)}")
# Placeholders for future functionality
st.subheader("Braille Translation")
st.info("Braille translation will be implemented in Phase 4")
st.subheader("Download Options")
st.info("PDF download will be implemented in Phase 5")
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