模板与OpenCV和Python中的多个源图像匹配 [英] Template matching with multiple source images in OpenCV and Python

问题描述

以下是Python和OpenCV中使用模板匹配进行图像检测的代码

The following is the code in Python and OpenCV for image detection using template matching

import numpy as np
import cv2

image = cv2.imread('photo.jpg')

template = cv2.imread('template.jpg')

# resize images
image = cv2.resize(image, (0,0), fx=0.5, fy=0.5) 
template = cv2.resize(template, (0,0), fx=0.5, fy=0.5) 

# Convert to grayscale
imageGray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
templateGray = cv2.cvtColor(template, cv2.COLOR_BGR2GRAY)

# Find template
result = cv2.matchTemplate(imageGray,templateGray, cv2.TM_CCOEFF)
min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(result)
top_left = max_loc
h,w = templateGray.shape
bottom_right = (top_left[0] + w, top_left[1] + h)
cv2.rectangle(image,top_left, bottom_right,(0,0,255),4)

# Show result
cv2.imshow("Template", template)
cv2.imshow("Result", image)

cv2.moveWindow("Template", 10, 50);
cv2.moveWindow("Result", 150, 50);

cv2.waitKey(0)

我想知道如何对多个源图像执行该程序?

I want to know how to do the program with multiple source images?

推荐答案

假设您的意思是多个模板图像，这是我尝试过的.

Assuming that you mean multiple template images, here is something I tried.

import cv2
import numpy as np
import glob

#empty list to store template images
template_data=[]
#make a list of all template images from a directory
files1= glob.glob('your\\template images\\template*.png')

for myfile in files1:
    image = cv2.imread(myfile,0)
    template_data.append(image)

test_image=cv2.imread('you\\testimage\\testimage.png')
test_image= cv2.cvtColor(test_image, cv2.COLOR_BGR2GRAY)

#loop for matching
for tmp in template_data:
    (tH, tW) = tmp.shape[:2]
    cv2.imshow("Template", tmp)
    cv2.waitKey(1000)
    cv2.destroyAllWindows()
    result = cv2.matchTemplate(test_image, tmp, cv2.TM_CCOEFF)
    min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(result)
    top_left = max_loc
    bottom_right = (top_left[0] + tW, top_left[1] + tH)
    cv2.rectangle(test_image,top_left, bottom_right,255, 2)

cv2.imshow('Result',test_image)
cv2.waitKey(0)

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