import argparse
import cv2
import os
import sys
import re
import warnings
import pytesseract
import numpy as np
from PIL import Image


def img_to_products(img: Image) -> list:
    img_postproc = preprocessor(img)
    ocr_text = get_text(img_postproc)
    list_out = get_products(ocr_text)
    return list_out


def img_to_products_debug(img: Image) -> (list, str, Image):
    img_postproc = preprocessor(img)
    ocr_text = get_text(img_postproc)
    list_out = get_products(ocr_text)
    return list_out, ocr_text, img_postproc


def recognize(img: Image, debug: bool = False) -> Image:
    processed_img = preprocessor(img)
    pass


def preprocessor(img: Image, debug: bool = False) -> Image:
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    gray = cv2.GaussianBlur(gray, (5, 5), 0)
    edged = cv2.Canny(gray, 75, 200)
    contours, hierarchy = cv2.findContours(edged.copy(),
                                       cv2.RETR_LIST,
                                       cv2.CHAIN_APPROX_SIMPLE)
    max_area_contour = max(contours, key=cv2.contourArea)
    x, y, w, h = cv2.boundingRect(max_area_contour)
    if debug:
        box_img = img.copy()
        cv2.rectangle(box_img, (x,y), (x+w, y+h), (0, 0, 255), thickness=2, lineType=8)
        cv2.imshow("MARK CROP", box_img)
    img_cut = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)[y:y+h, x:x+w]
    img_out = cv2.cvtColor(img_cut, cv2.COLOR_BGR2RGB)
    if debug:
        cv2.imshow("CROPPED", img_out)
    return img_out


def get_text(img: Image,  debug: bool = False) -> str:
    text = pytesseract.image_to_string(Image.fromarray(img), config="-l pol")
    return text


def get_products(ocr_text,  debug: bool = False) -> list:
    out_list = []
    text_lines = ocr_text.split('\n')
    index_start = 0
    index_stop = len(text_lines) - 1
    for i in range(len(text_lines) - 1):
        if(re.compile('PARAGON.*FISKALNY.*').match(text_lines[i])):
            index_start = i
        if(re.compile('SPRZEDA.*').match(text_lines[i])):
            index_stop = i

    for item_line in text_lines[index_start + 1: index_stop - 2]:
        # print(item_line)
        regex = re.compile("([ A-Za-ząćęłśźż]+).*(\d{1,3},\d{2})[A-E]$")
        m = regex.match(item_line)
        if m:
            out_list.append((item_line, m.group(1), m.group(2)))
            # print(item_line, "===>", m.group(1), m.group(2))
        else:
            print("skipped!")

    return out_list


if __name__ == "__main__":
    ap = argparse.ArgumentParser()
    ap.add_argument("-i", "--image", required=True, help="Path to the image")
    ap.add_argument("-s", "--show-steps", required=False, help="Display image on every step", action='store_true')
    args = vars(ap.parse_args())

    if (not os.path.isfile(args["image"])):
        print(f"Could not find an image '{args['image']}'")
        sys.exit(-1)

    DEBUG = args["show_steps"]

    img = cv2.imread(args["image"])
    img_postproc = preprocessor(img, debug=DEBUG)
    ocr_text = get_text(img_postproc, debug=DEBUG)
    product_list = get_products(ocr_text, debug=DEBUG)
    # print(product_list)
    if(DEBUG):
        cv2.waitKey(0)
        cv2.destroyAllWindows()

    # out_img = img.copy()
    # gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    # gray = cv2.GaussianBlur(gray, (5, 5), 0)
    # edged = cv2.Canny(gray, 75, 200)

    # contours, hierarchy = cv2.findContours(edged.copy(),
    #                                    cv2.RETR_LIST,
    #                                    cv2.CHAIN_APPROX_SIMPLE)

    # max_area_contour = max(contours, key=cv2.contourArea)
    # x, y, w, h = cv2.boundingRect(max_area_contour)
    # # out_img = gray[y:y+h, x:x+w]
    # # ret, out_img = cv2.threshold(gray[y:y+h, x:x+w], 155, 255, cv2.THRESH_TOZERO)
    # img_cut = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)[y:y+h, x:x+w]
    # img_out = cv2.cvtColor(img_cut, cv2.COLOR_BGR2RGB)

    
    # text = pytesseract.image_to_string(Image.fromarray(img_out), config="-l pol")
    # text_lines = text.split('\n')
    # index_start = 0
    # index_stop = len(text_lines) - 1
    # for i in range(len(text_lines) - 1):
    #     if(re.compile('PARAGON.*FISKALNY.*').match(text_lines[i])):
    #         index_start = i
    #     if(re.compile('SPRZEDA.*').match(text_lines[i])):
    #         index_stop = i

    # for item_line in text_lines[index_start + 1: index_stop - 2]:
    #     print(item_line)

    
    # regex = re.compile("([ A-Za-ząćęłśźż]+).*(\d{1,3},\d{2})[A-E]$")
    # m = regex.match(item_line)
    # if m:
    #     print(item_line, "===>", m.group(1), m.group(2))
    # else:
    #     print("skipped!")

# # cv2.drawContours(out_img, contours, -1, (0, 255, 0), 3)
# # cv2.rectangle(out_img, (x, y), (x+w, y+h), (0, 0, 255), 2)
# cv2.imshow("cropped", img_out)
# # cv2.imshow("Edged", edged)
# cv2.waitKey(0)
# cv2.destroyAllWindows()