app.py

import streamlit as st
from streamlit_drawable_canvas import st_canvas
from PIL import Image
import pytesseract
import numpy as np

# Set the path to the Tesseract executable for Hugging Face Spaces
pytesseract.pytesseract.tesseract_cmd = '/usr/bin/tesseract'

st.title("Handwritten Text Recognition")

# Create a canvas component
canvas_result = st_canvas(
    fill_color="rgba(255, 165, 0, 0.3)",  # Fill color with some transparency
    stroke_width=2,
    stroke_color="#000000",
    background_color="#ffffff",
    update_streamlit=True,
    height=150,
    width=600,
    drawing_mode="freedraw",
    key="canvas"
)

# Process the canvas image
if canvas_result.image_data is not None:
    img = Image.fromarray(canvas_result.image_data.astype('uint8'), 'RGBA').convert('L')
    img = img.resize((img.width * 2, img.height * 2), Image.LANCZOS)  # Resize to improve OCR accuracy
    text = pytesseract.image_to_string(img, config='--psm 6')
    st.text_area("Recognized Text", text, height=100)