模板匹配

demo1

# 单模板匹配

import cv2

img = cv2.imread("./rh.png")
template = cv2.imread("./template.png")
img = cv2.resize(img, None, None, 0.5, 0.5)
height, width, c = template.shape

# 按照标准平方差方式匹配
result = cv2.matchTemplate(img, template, cv2.TM_SQDIFF_NORMED)

# 获取匹配结果中最小值，最大值，最小值坐标和最大值坐标
minValue, maxValue, minLoc, maxLoc = cv2.minMaxLoc(result)
resultPoint1 = minLoc
# 计算出最佳匹配区域的右下角点坐标
resultPoint2 = (resultPoint1[0] + width, resultPoint1[1] + height)

# 在最佳匹配区域位置绘制红色方框
cv2.rectangle(img, resultPoint1, resultPoint2, (0, 0, 255), 2)
cv2.imshow("img", img)
cv2.waitKey()
cv2.destroyAllWindows()

demo2

# 寻找文件夹中重复的文件
import cv2
import os
import sys

PIC_PATH = "./"

width, height = 100, 100
pic_file = os.listdir(PIC_PATH)

same_pic_index = []
imgs = []
has_same = set()
count = len(pic_file)
# 如果图片的数量为0
if count == 0:
    print("没有图像")
    # 退出程序
    sys.exit(0)
# 遍历照片文件
for file_name in pic_file:
    # 拼接完整文件名
    file_name = PIC_PATH + file_name
    # 创建文件的图像
    img = cv2.imread(file_name)
    # 缩放成统一大小
    img = cv2.resize(img, (width, height))
    imgs.append(img)

# 遍历所有图像文件不遍历最后一个图像
for i in range(0, count - 1):
    # 如果此图像已经找到相同的图像
    if i in has_same:
        continue
    # 取出模板图像
    templ = imgs[i]
    # 与templ内容相同的图像索引列表
    same = [i]
    # 从templ的下一个位置开始遍历
    for j in range(0 + i + 1, count):
        # 如果此图像已经找到相同的图像
        if j in has_same:
            continue
        pic = imgs[j]
        result = cv2.matchTemplate(pic, templ, cv2.TM_SQDIFF_NORMED)
        if result > 0.9:
            same.append(j)
            has_same.add(i)
            has_same.add(j)
    if len(same) > 1:
        same_pic_index.append(same)
for same_list in same_pic_index:
    text = "相同的照片"
    for same in same_list:
        text += str(pic_file[same]) + ","
    print(text)

demo3

# 多模板匹配
import cv2
# 读取原始图像
img = cv2.imread("./orig/hz.jpg")
img = cv2.resize(img, None, None, 0.2, 0.2)
# cv2.imwrite("./orig/hz.jpg", img)
# 读取模板图像
rh = cv2.imread("./template/rh.png")

height, width, c = rh.shape
# 按照标准相关系数匹配
result = cv2.matchTemplate(img, rh, cv2.TM_CCORR_NORMED)

for y in range(len(result)):
    for x in range(len(result[y])):
        if result[y][x] > 0.85:
            cv2.rectangle(img, (x, y), (x + width, y + height), (0, 0, 255), 2)


cv2.imshow("img", img)
cv2.waitKey()
cv2.destroyAllWindows()

demo4

import cv2
# 多模板匹配

def myMatchTemplate(img, templ):
    height, width, c = templ.shape
    results = cv2.matchTemplate(img, templ, cv2.TM_CCORR_NORMED)

    loc = list()
    for i in range(len(results)):
        for j in range(len(results[i])):
            if results[i][j] > 0.92:
                loc.append((j, i, j + width, i + height))

    return loc

img = cv2.imread("./orig/hz.jpg")

templs = list()

templs.append(cv2.imread("./template/phl.png"))
templs.append(cv2.imread("./template/rh.png"))
templs.append(cv2.imread("./template/shy.png"))

loc = list()

for t in templs:
    loc += myMatchTemplate(img, t)

for i in loc:
    cv2.rectangle(img, (i[0], i[1]), (i[2], i[3]), (0, 0, 255), 2)

cv2.imshow("img", img)
cv2.waitKey()
cv2.destroyAllWindows()