#!/usr/bin/env python
# -*- encoding: utf-8 -*-

import cv2
import numpy as np
import matplotlib.pyplot as plt
scale = 1

img = cv2.imread('./auto.png')#要找的大图
img = cv2.resize(img, (0, 0), fx=scale, fy=scale)

template = cv2.imread('./image/water.png')#图中的小图
template = cv2.resize(template, (0, 0), fx=scale, fy=scale)
template_size= template.shape[:2]

#找图 返回最近似的点
def search_returnPoint(img,template,template_size):
    img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    template_ = cv2.cvtColor(template,cv2.COLOR_BGR2GRAY)
    result = cv2.matchTemplate(img_gray, template_,cv2.TM_CCOEFF_NORMED)
    threshold = 0.7
    # res大于70%
    loc = np.where(result >= threshold)
    # 使用灰度图像中的坐标对原始RGB图像进行标记
    point = ()
    for pt in zip(*loc[::-1]):
        cv2.rectangle(img, pt, (pt[0] + template_size[1], pt[1] + + template_size[0]), (7, 249, 151), 2)
        point = pt
    if point==():
        return None,None,None
    return img,point[0]+ template_size[1] /2,point[1]

img,x_,y_ = search_returnPoint(img,template,template_size)
if(img is None):
    print("没找到图片")
else:
    print("找到图片 位置:"+str(x_)+" " +str(y_))
    plt.figure()
    plt.imshow(img, animated=True)
    plt.show()