import pandas as pd
import numpy as np
import streamlit as st
import easyocr
from PIL import Image, ImageDraw
from streamlit_drawable_canvas import st_canvas

def rectangle(image, result):
    """Draw rectangles on the image based on predicted coordinates."""
    draw = ImageDraw.Draw(image)
    for res in result:
        top_left = tuple(res[0][0])
        bottom_right = tuple(res[0][2])
        draw.rectangle((top_left, bottom_right), outline="blue", width=2)
    st.image(image)

# Main title and markdowns
st.title("Get text from an image with EasyOCR")
st.markdown("## EasyOCR with Streamlit")
st.markdown("## Upload an Image or Draw")

# Column layout for uploader and canvas
col1, col2 = st.columns(2)

with col1:
    file = st.file_uploader("Upload Here", type=['png', 'jpg', 'jpeg'])

with col2:
    canvas_result = st_canvas(
        fill_color="rgba(255, 165, 0, 0.3)",
        stroke_width=3,
        stroke_color="#ffffff",
        background_color="#000000",
        background_image=None if file else st.session_state.get("background", None),
        update_streamlit=True,
        width=400,
        height=400,
        drawing_mode="freedraw",
        key="canvas",
    )

image = None

if file is not None:
    image = Image.open(file)
elif canvas_result.image_data is not None:
    # Convert canvas RGBA image to RGB
    canvas_image_data = canvas_result.image_data.astype(np.uint8)
    image = Image.fromarray(canvas_image_data, 'RGBA').convert('RGB')

if image is not None:
    st.image(image)

    reader = easyocr.Reader(['en', 'ja'], gpu=False)
    result = reader.readtext(np.array(image))

    for idx, res in enumerate(result):
        pred_text = res[1]
        st.write(pred_text)
    
    textdic_easyocr = {res[1]: {'pred_confidence': res[2]} for res in result}
    df = pd.DataFrame.from_dict(textdic_easyocr).T
    st.table(df)

    rectangle(image, result)
else:
    st.write("Please upload an image or use the canvas to draw.")