import os
import tkinter as tk

import pytesseract
import cv2
import pyperclip
import numpy as np
from pytesseract import Output
# import argparse
# import pyautogui as gui
# from threading import Thread, Event
# from PIL import Image, ImageOps, ImageEnhance
# from time import sleep

# thread = Thread(target=gui.prompt)
def thin_font(image):
    image = cv2.bitwise_not(image)
    kernel = np.ones((2, 2), np.uint8)
    image = cv2.erode(image, kernel, iterations=1)
    image = cv2.bitwise_not(image)
    return (image)

def thick_font(image):
    image = cv2.bitwise_not(image)
    kernel = np.ones((2, 2), np.uint8)
    image = cv2.dilate(image, kernel, iterations=1)
    image = cv2.bitwise_not(image)
    return (image)

def noise_removal(image):
    kernel = np.ones((1, 1), np.uint8)
    image = cv2.dilate(image, kernel, iterations=1)
    kernel = np.ones((1, 1), np.uint8)
    image = cv2.erode(image, kernel, iterations=1)
    image = cv2.morphologyEx(image, cv2.MORPH_CLOSE, kernel)
    image = cv2.medianBlur(image, 3)
    return (image)

def process_tess(file):
    image = cv2.imread(file)
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    # gray = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
    # gray = thin_font(gray)
    # _thresh, im_bw = cv2.threshold(gray, 210, 230, cv2.THRESH_BINARY)
    results = pytesseract.image_to_data(gray, output_type=Output.DICT)
    text = '\n'.join(results['text'])
    return text

def main_tess(ext='.png'):
    im_files = [f for f in os.listdir() if f.endswith(ext)]
    im_files.sort(key=lambda x: os.stat(os.path.join(x)).st_mtime, reverse=True)
    text = process_tess(im_files[0])
    pyperclip.copy(text)
    root = tk.Tk()
    T = tk.Text(root, height=10, width=50)
    T.pack()
    T.insert(tk.END, text)
    tk.mainloop()
    # os.remove(im_files[0])
    # gui.prompt(title='ocr', default=text)

# parser = argparse.ArgumentParser()
# parser.add_argument('-file', type=str, help='name of the scanned file to be converted',
#                     default=img_files[0])
# parser.add_argument('-p', '--preprocess', type=str, default='thresh',
#                     help='type of preprocessing to be done')
# args = parser.parse_args()
# image = cv2.imread(args.file)
# rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
# gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

# if args.preprocess == "thresh":
#     gray = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)[1]
# elif args.preprocess == "blur":
#     gray = cv2.medianBlur(gray, 3)

# cv2.imwrite('new_image.png', gray)
# print('tesseract version {}'.format(pytesseract.get_tesseract_version()))
# print('processing', args.file)
# results = pytesseract.image_to_data(gray, output_type=Output.DICT)
# text = ' '.join(results['text'])
# pyperclip.copy(text)
# gui.prompt(title='ocr', default=text)
# text = pytesseract.image_to_string(gray)


if __name__ == '__main__':
    main_tess()