# 4.11 模板匹配

## 目标

• 使用模板匹配查找图像中的对象
• 你会学会这些函数：`cv2.matchTemplate()``cv2.minMaxLoc()`

## OpenCV中的模板匹配

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

img2 = img.copy()
w, h = template.shape[::-1]

# 所有6种比较方法的列表
methods = ['cv2.TM_CCOEFF', 'cv2.TM_CCOEFF_NORMED', 'cv2.TM_CCORR', 'cv2.TM_CCORR_NORMED', 'cv2.TM_SQDIFF', 'cv2.TM_SQDIFF_NORMED']

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

# 应用模版匹配
res = cv2.matchTemplate(img,template,method)
min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)
# 如果方法是 TM_SQDIFF或者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)

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([])
plt.suptitle(meth)

plt.show()``````

• `cv2.TM_CCOEFF`

• `cv2.TM_CCOEFF_NORMED`

• `cv2.TM_CCORR`

• `cv2.TM_CCORR_NORMED`

• `cv2.TM_SQDIFF`

• `cv2.TM_SQDIFF_NORMED`

## 与多个对象匹配的模板

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

img_gray = cv2.cvtColor(img_rgb, cv2.COLOR_BGR2GRAY)
w, h = template.shape[::-1]

res = cv2.matchTemplate(img_gray,template,cv2.TM_CCOEFF_NORMED)
threshold = 0.8
loc = np.where( res >= threshold)
for pt in zip(*loc[::-1]):
cv2.rectangle(img_rgb, pt, (pt[0] + w, pt[1] + h), (0,0,255), 2)

cv2.imwrite('res.png',img_rgb)``````