OpenCV-python之单对象模板匹配_w, h = template.shape[::-1]

import cv2 as cv
import numpy as np
from matplotlib import pyplot as plt
img = cv.imread(‘xiaozhan1.jpg’,0)
img2 = img.copy()
template = cv.imread(‘xiaozhan.template.jpg’,0) #模板
w, h = template.shape[::-1] # w：宽度 h:高度 数字：代表颜色

列表中所有的6种比较方法

methods = [‘cv.TM_CCOEFF’, ‘cv.TM_CCOEFF_NORMED’, ‘cv.TM_CCORR’,
‘cv.TM_CCORR_NORMED’, ‘cv.TM_SQDIFF’, ‘cv.TM_SQDIFF_NORMED’]
for meth in methods:
img = img2.copy()
#eval 语句用来计算存储在字符串中的有效 Python 表达式
method = eval(meth) #eval():去掉参数最外侧引号并执行余下语句的函数
# 应用模板匹配
res = cv.matchTemplate(img,template,method)
min_val, max_val, min_loc, max_loc = cv.minMaxLoc(res) #相似度最大的位置中心坐标
# 如果方法是TM_SQDIFF或TM_SQDIFF_NORMED，则取最小值
if method in [cv.TM_SQDIFF, cv.TM_SQDIFF_NORMED]:
top_left = min_loc
else:
top_left = max_loc
bottom_right = (top_left[0] + w, top_left[1] + h)
cv.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.title()函数用于设置图像标题。
plt.subplot(122),plt.imshow(img,cmap = ‘gray’)
plt.title(‘Detected Point’), plt.xticks([]), plt.yticks([])
plt.suptitle(meth)
plt.show()