cv2.matchTemplate(image, templ, method, result=None, mask=None)

import cv2

# 读取图片
img = cv2.imread("girl.jpg", 0)
print(img.shape)  # (1280, 1920)

# 读取模板
template = cv2.imread("face.jpg", 0)
h, w = template.shape
print(template.shape)  # (510, 518)

# 模板匹配
result = cv2.matchTemplate(img, template, cv2.TM_SQDIFF)

import cv2
from matplotlib import pyplot as plt

# 读取图片
img = cv2.imread("girl.jpg", 0)

# 读取模板
template = cv2.imread("face.jpg", 0)
h, w = template.shape

# 模式
methods = ['cv2.TM_SQDIFF', 'cv2.TM_SQDIFF_NORMED', 'cv2.TM_CCORR',
           'cv2.TM_CCORR_NORMED', 'cv2.TM_CCOEFF', 'cv2.TM_CCOEFF_NORMED']

# 循环
for meth in methods:
    img2 = img.copy()

    # 匹配方法的真值
    method = eval(meth)
    print("method:", method)
    res = cv2.matchTemplate(img, template, method)
    min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)

    # 如果是平方差匹配TM_SQDIFF或归一化平方差匹配TM_SQDIFF_NORMED，取最小值
    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)

    # 画矩形
    cv2.rectangle(img2, top_left, bottom_right, 255, 2)

    # 展示
    f, ax = plt.subplots(1, 2, figsize=(16, 8))
    ax[0].imshow(img2, cmap='gray')
    ax[1].imshow(res, cmap='gray')
    plt.suptitle(meth)

    plt.show()