app.py

import streamlit as st
import numpy as np
from PIL import Image
import time
import utlis
import easyocr
import cv2
import os

#@st.cache
def get_image(img):
    image = Image.open(img)
    return np.asarray(image)

@st.cache
def get_reader_lang(lang='ar'):
    reader = easyocr.Reader([lang])
    return reader

@st.cache
def get_result(image, lang='ar'):
    reader = get_reader_lang(lang)
    result = reader.readtext(image)
    return result 
        
def main():
    st.markdown("<h1 style='text-align: center;position:static; top:-50 ;color: rgb(65, 59, 59);font-size:300%;'>Arabic OCR</h1>",
                unsafe_allow_html=True)
    side_bar = st.sidebar
    image_file = side_bar.file_uploader('',type=['png', 'jpg', 'jpeg'])
    col1, col2 = st.columns(2)
    
    if image_file is not None:
        image= get_image(image_file)
        start_btn = side_bar.button('Start OCR')
        
        if start_btn:
            animation_placeholder = st.empty()
            animation_placeholder.markdown(utlis.read_custum_html('animation_style.html'), unsafe_allow_html=True)
            t1 = time.time()
            result = get_result(image)
            animation_placeholder.empty()
            annoted_image = utlis.annotate_image(image, result)
            annoted_image = Image.fromarray(annoted_image)
            col1.text('Image')
            col1.image( annoted_image, use_column_width=True)
            extracted_text = utlis.get_raw_text(result)
            col2.text('Extracted text')
            col2.write(extracted_text,  use_column_width=True)
            t2 = time.time()
            print(f'The task done in {t2-t1} sec')

    
if __name__ == "__main__":
    main()