# -*- coding: utf-8 -*-
import base64,re
import time, os,datetime, sched
import cv2
from io import BytesIO
from PIL import Image, ImageDraw, ImageFont
import requests,re
import numpy as np


class quekou():
    def __init__(self):
        self.t = int(time.time() * 1000)
        pass
    def save_png(self,path,con):
        with open(path, "wb") as fp:
            fp.write(con)

    def get_distance2(self,bg,tp):

        bg = base64.b64decode(bg)  # base64转二进制

        tp = base64.b64decode(tp)  # base64转二进制

        res = self.det.slide_match(tp, bg, simple_target=True)
        res=res['target'][0]

        return res

    def get_distance(self, bg, tp):

        bg = base64.b64decode(bg)  # base64转二进制

        tp = base64.b64decode(tp)  # base64转二进制
        ''' bg: 背景图片 tp: 缺口图片 out:输出图片 '''
        # 读取背景图片和缺口图片
        bg_img = Image.open(BytesIO(bg))  # 背景图片
        tp_img = Image.open(BytesIO(tp))  # 缺口图片
        bg_edge = cv2.Canny(np.array(bg_img), 100, 200)
        tp_edge = cv2.Canny(np.array(tp_img), 100, 200)
        # 转换图片格式
        bg_pic = cv2.cvtColor(bg_edge, cv2.COLOR_GRAY2RGB)
        tp_pic = cv2.cvtColor(tp_edge, cv2.COLOR_GRAY2RGB)
        # 缺口匹配
        res = cv2.matchTemplate(bg_pic, tp_pic, cv2.TM_CCOEFF_NORMED)
        min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)  # 寻找最优匹配
        # 绘制方框
        tl = max_loc  # 左上角点的坐标
        return tl[0]