app.py

import streamlit as st
import pandas as pd
from pdf2image import convert_from_bytes
import pytesseract
from pytesseract import Output
from io import BytesIO
import base64

# Set up the Streamlit app
st.title("PDF to Excel Converter with OCR")

combined_data = pd.DataFrame()

# Upload the PDF file
uploaded_file = st.file_uploader("Upload a PDF file", type=["pdf"])

# Convert the PDF to images and use OCR to extract the text
if uploaded_file is not None:
    with st.spinner("Converting PDF to images..."):
        images = convert_from_bytes(uploaded_file.read())

    st.success("PDF converted to images successfully!")

    with st.spinner("Extracting text from images using OCR..."):
        data = []
        for i, img in enumerate(images):
            text = pytesseract.image_to_data(img, output_type=Output.DICT)
            data.append(pd.DataFrame(text))

        combined_data = pd.concat(data, ignore_index=True)
        st.success("Text extracted successfully!")

# Display the extracted text and create a download button for the Excel file
st.write(combined_data)

def to_excel(df):
    output = BytesIO()
    writer = pd.ExcelWriter(output, engine='openpyxl')
    df.to_excel(writer, index=False, sheet_name='Sheet1')
    writer.close()
    processed_data = output.getvalue()
    return processed_data

def get_table_download_link(df):
    val = to_excel(df)
    b64 = base64.b64encode(val)
    return f'<a href="data:application/octet-stream;base64,{b64.decode()}" download="output.xlsx">Download Excel file</a>'

st.markdown(get_table_download_link(combined_data), unsafe_allow_html=True)