import os
import re
import sys
from glob import glob
import cv2
import numpy as np
import tensorflow as tf
sys.path.append(os.path.dirname(os.path.abspath(__file__)) + "/../")
from model import crnn_ctc_equation, ctc_decode, crnn_ctc_equation_large
from utils import pil_resize, add_contrast

package_dir = os.path.abspath(os.path.dirname(__file__))
image_shape = (32, 192, 1)
model_path = package_dir + "/models/e55-loss0.14-equation.h5"

with open(package_dir + "/equation.txt", 'r', encoding='utf-8') as f:
    char_list = f.readlines()
char_str = "".join(char_list)
char_str = re.sub("\n", "", char_str)


def recognize(image_np, model=None, sess=None):
    if sess is None:
        sess = tf.compat.v1.Session(graph=tf.Graph())

    if model is None:
        with sess.as_default():
            with sess.graph.as_default():
                model = crnn_ctc_equation_large(input_shape=image_shape, class_num=35+2, is_train=False)
                model.load_weights(model_path)

    img = image_np
    img = pil_resize(img, image_shape[0], image_shape[1])
    if img.shape[2] == 3:
        img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
        img = np.expand_dims(img, axis=-1)
    img = add_contrast(img)
    # cv2.imshow("contrast", img)

    X = []
    img = img / 255.
    X.append(img)
    X = np.array(X)
    with sess.as_default():
        with sess.graph.as_default():
            pred = ctc_decode(X, model)

    result_list = []
    for index in pred:
        index = int(index-1)
        if index < 0:
            continue
        result_list.append(char_str[index])
        # print(char_str[index])
    # cv2.waitKey(0)
    print("cer result", result_list)
    return calculate(result_list)


def calculate(_list):
    char_dict = {
        "1": 1,
        "2": 2,
        "3": 3,
        "4": 4,
        "5": 5,
        "6": 6,
        "7": 7,
        "8": 8,
        "9": 9,
        "0": 0,
        "一": 1,
        "二": 2,
        "三": 3,
        "四": 4,
        "五": 5,
        "六": 6,
        "七": 7,
        "八": 8,
        "九": 9,
        "零": 0,
        "加": "加",
        "减": "减",
        "乘": "乘",
        "除": "除",
        "+": "加",
        "-": "减",
        "*": "乘",
        "×": "乘",
        "/": "除",
        "÷": "除",
        "=": "",
        "?": "",
        "上": "",
        "去": "",
        "以": "",
    }
    equation_str = ""
    for c in _list:
        equation_str += str(char_dict.get(c))
    op = re.findall("加|减|乘|除", equation_str)
    op = list(set(op))
    if len(op) != 1:
        return None
    nums = re.split("加|减|乘|除", equation_str)
    if len(nums) != 2:
        return None
    try:
        num1 = int(nums[0])
        num2 = int(nums[1])
    except:
        print("非数字！")
        return None

    op = op[0]
    if op == "加":
        result = num1 + num2
    elif op == '减':
        result = num1 - num2
    elif op == '乘':
        result = num1 * num2
    elif op == '除':
        result = int(num1 / max(num2, 1))
    return result


if __name__ == "__main__":
    # _path = "../data/test/char_9.jpg"
    # _path = "../data/equation/38376_减_1_问_加_4_除.jpg"
    _paths = glob("../data/test/FileInfo1021/*")
    for _path in _paths:
        recognize(_path)