import logging
import pytesseract
from PIL import Image
import os
import streamlit as st

# Configure logging to display debug information
logging.basicConfig(level=logging.DEBUG)

# Function to extract text from an image
def extract_text_from_image(image):
    try:
        logging.info("Starting text extraction from image...")

        # Verify the image is not corrupted
        image.verify()  # Verifies the image is not corrupted
        logging.info("Image opened and verified successfully.")

        # Resize the image to improve performance (optional)
        image = image.resize((image.width // 2, image.height // 2))  # Resize image to 50% of the original size
        
        # Extract text using pytesseract
        text = pytesseract.image_to_string(image)
        
        logging.info("Text extraction completed successfully.")
        return text

    except Exception as e:
        logging.error(f"An error occurred while processing the image: {str(e)}")
        return f"Error: {str(e)}"

# Streamlit web application
def main():
    st.title("Lab Report Analyzer")

    st.markdown("Upload an image file to extract text from it.")

    # File uploader widget
    uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "png", "jpeg"])

    if uploaded_file is not None:
        # Save the uploaded file temporarily
        with open("temp_image.jpg", "wb") as f:
            f.write(uploaded_file.getbuffer())
        
        # Open the image file
        image = Image.open("temp_image.jpg")
        
        # Extract text from the uploaded image
        extracted_text = extract_text_from_image(image)

        # Display extracted text
        st.subheader("Extracted Text")
        st.text(extracted_text)

        # Optionally, delete the temporary file after processing
        os.remove("temp_image.jpg")

if __name__ == "__main__":
    main()