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

import cv2
# 讀取圖片
img = cv2.imread("girl.jpg", 0)
print(img.shape)  # (1280, 1920)
# 讀取模板
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
# 讀取圖片
img = cv2.imread("girl.jpg", 0)
# 讀取模板
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']
# 循環(huán)
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或歸一化平方差匹配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)
 # 畫(huà)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()