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

img = cv2.imread('img/123.jpeg',0)
img2 = img.copy()

template = cv2.imread('img/123_face.jpeg',0)
w,h = template.shape
print(w)

medthods = ['cv2.TM_CCOEFF', 'cv2.TM_CCOEFF_NORMED', 'cv2.TM_CCORR',
            'cv2.TM_CCORR_NORMED', 'cv2.TM_SQDIFF', 'cv2.TM_SQDIFF_NORMED']

for meth in medthods:
    img = img2.copy()

    medthod = eval(meth)

    res = cv2.matchTemplate(img, template, medthod)
    min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)

    if medthod 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)

    cv2.rectangle(img, top_left, bottom_right, 255, 2)

    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([])


# opencv 单一对象的模板匹配
