import pytesseract
from PIL import Image
import pandas as pd
import os
import gradio as gr
import numpy as np
import gradio as gr


def ocr_df_using_pytesseract(image):
    #pytesseract.pytesseract.tesseract_cmd =r"C:\Users\amold\Desktop\Upwork\pdf to image and pytesseract\tesseact_exe\Tesseract-OCR\tesseract.exe"

    pytesseract.pytesseract.tesseract_cmd = r'/usr/bin/tesseract'
    #image = Image.open(example['image_path'])

    width, height = image.size

    # apply ocr to the image 
    ocr_df = pytesseract.image_to_data(image, output_type='data.frame')
    float_cols = ocr_df.select_dtypes('float').columns
    ocr_df = ocr_df.dropna().reset_index(drop=True)
    ocr_df[float_cols] = ocr_df[float_cols].round(0).astype(int)
    ocr_df = ocr_df.replace(r'^\s*$', np.nan, regex=True)
    ocr_df = ocr_df.dropna().reset_index(drop=True)

    ocr_df

    ocr_df['X1']=ocr_df['left']

    ocr_df['Y1']=ocr_df['top']

    ocr_df['X2']= ocr_df['left'] + ocr_df['width']

    ocr_df['Y2']= ocr_df['top'] + ocr_df['height']

    return ocr_df


def image_to_text(image):
    ocr_df= ocr_df_using_pytesseract(image)


    grouped_text = ocr_df.groupby(['block_num', 'line_num'])['text'].agg(' '.join).reset_index()

    # sort the text by line numbers within each block
    grouped_text = grouped_text.sort_values(['block_num', 'line_num'])

    # join the text by blocks and add newlines
    result = ''
    for i, row in grouped_text.iterrows():
        if i > 0 and row['block_num'] != grouped_text.loc[i-1, 'block_num']:
            result += '\n\n'
        result += row['text'].rstrip() + '\n'

    return result



demo = gr.Interface(fn=image_to_text, 
                    inputs= gr.Image(type="pil"), 
                    outputs=["text"],
                    title="Menu image to text",
                    description= "Upload Menu image here")
demo.launch(share=False)