


import cv2
import numpy as np
import time
from matplotlib import pyplot as plt

x = 0
y = 0


def makematchpicture(Grayurl):
    img = cv2.imread(Grayurl, 0)
    img2 = img.copy()
    template = cv2.imread('test.png', 0)
    w, h = template.shape[::-1]

    methods = ['cv2.TM_SQDIFF']

    for meth in methods:
        img = img2.copy()
        method = eval(meth)

        # Apply template Matching
        res = cv2.matchTemplate(img, template, method)
        min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)

        # If the method is TM_SQDIFF or TM_SQDIFF_NORMED, take minimum
        if method in [cv2.TM_SQDIFF, cv2.TM_SQDIFF_NORMED]:
            top_left = min_loc
        else:
            top_left = max_loc
        bottom_right = (top_left[0] + w, top_left[1] + h)
        print("模板匹配：",int(top_left[0] + w / 2), int(top_left[1] + h / 2))
        cv2.rectangle(img, top_left, bottom_right, 255, 2)
        plt.figure()
        plt.subplot(121), plt.imshow(res, cmap='gray')
        plt.title('Matching Result'), plt.xticks([]), plt.yticks([])
        plt.subplot(122), plt.imshow(img, cmap='gray')
        plt.title('Detected Point'), plt.xticks([]), plt.yticks([])
        plt.suptitle(meth)
        global x
        global y
        x = int(top_left[0] + w / 2)
        y = int(top_left[1] + h / 2)
