app.py

import streamlit as st
from PIL import Image
from ocr_utils import extract_text

import numpy as np
# Streamlit application title
st.title("OCR and Keyword Search Application")
st.write("Upload an image containing Hindi and English text to extract and search within the text.")

# File uploader for image
uploaded_file = st.file_uploader("Upload Image", type=["jpg", "jpeg", "png"])

if uploaded_file is not None:
    # Open the uploaded image using PIL
    image = Image.open(uploaded_file)
    st.image(image, caption='Uploaded Image', use_column_width=True)

    # Convert the image to a NumPy array
    image_np = np.array(image)

    # Perform OCR on the uploaded image using the utility function
    full_text = extract_text(image_np)

    # Display the extracted text
    st.subheader("Extracted Text")
    st.write(full_text)

    # Text input for keyword search
    keyword = st.text_input("Enter Keyword to Search")

    #Highlight the keyword in the extracted text
    if keyword:
        if keyword in full_text:
            highlighted_text = full_text.replace(
                keyword, f"<mark style='background-color: yellow; color: black;'>{keyword}</mark>")
            st.subheader("Highlighted Search Results")
            st.markdown(highlighted_text, unsafe_allow_html=True)
        else:
            st.subheader("Highlighted Search Results")
            st.write(f"The keyword '{keyword}' was not found in the text.")
    else:
        st.subheader("Highlighted Search Results")
        st.write("No keyword entered for highlighting.")