python opencv如何匹配具有不同颜色和亮度的相同形状的模板

Question

我使用匹配模板来检测黑暗背景下的2x2平方米。用我的代码，它检测大多数方块没有任何问题，但它失败了，当颜色的方块是黑暗和黑色。我试过在opencv中规范化，但效果不太好。也试过使用口罩，但也不起作用(也许我用错了口罩功能？)因为我对图像预处理和opencv缺乏了解。我相信有那么多东西我错过了，但我只是不知道我错过了什么。如果有人能帮我，我会很感激的

import cv2
import numpy as np
import time
import win32gui, win32ui, win32con

    
def imagesearch(per):



    img = cv2.imread('target.png', cv2.IMREAD_GRAYSCALE)
    img1 = cv2.imread('target.png')

    template = cv2.imread('./map/monster.png', cv2.IMREAD_GRAYSCALE)
    w, h = template.shape[::-1]

    meth = [cv2.TM_CCOEFF, cv2.TM_CCOEFF_NORMED, cv2.TM_CCORR, cv2.TM_CCORR_NORMED, cv2.TM_SQDIFF, cv2.TM_SQDIFF_NORMED]

    res = cv2.matchTemplate(img, template, meth[3])


    threshold = per 
    loc = np.where(res>=threshold) 


    if loc[0].any():


        for pt in zip(*loc[::-1]):
            cv2.rectangle(img1, pt, (pt[0] + w, pt[1] + h), (0,0,255), 1) 


            
    cv2.imshow("dst", img1)
    cv2.waitKey(0)
    cv2.destroyAllWindows()


imagesearch(0.8)

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模板

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图像

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结果

Answer 1

你面临的问题是，你想要检测的部分方块不遵循“比背景轻”和“比背景暗”的规则。解决此问题的方法是使用带有反向颜色的模板图像：

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^--反转模板

import cv2
import numpy as np
import time
    
def imagesearch(per):

    img  = cv2.imread('openCV_squareDetection.png', cv2.IMREAD_GRAYSCALE)
    img1 = cv2.imread('openCV_squareDetection.png')

    template_inversed = cv2.imread('openCV_squareDetection_template_inversed.png', cv2.IMREAD_GRAYSCALE)
    template          = cv2.imread('openCV_squareDetection_template.png',          cv2.IMREAD_GRAYSCALE)
    w, h = template.shape[::-1]

    meth = [cv2.TM_CCOEFF, cv2.TM_CCOEFF_NORMED, cv2.TM_CCORR, cv2.TM_CCORR_NORMED, cv2.TM_SQDIFF, cv2.TM_SQDIFF_NORMED]

    res          = cv2.matchTemplate(img, template         , meth[1])
    res_inversed = cv2.matchTemplate(img, template_inversed, meth[1])
    threshold = per 

    loc          = np.where(res         >=threshold) 
    loc_inversed = np.where(res_inversed>=threshold) 

    if loc[         0].any():
        for pt in zip(*loc[::-1]):
            cv2.rectangle(img1, pt, (pt[0] + w, pt[1] + h), (0,0,255), 1) 
    if loc_inversed[0].any():
        for pt in zip(*loc_inversed[::-1]):
            cv2.rectangle(img1, pt, (pt[0] + w, pt[1] + h), (0,0,255), 1) 

    cv2.imshow("dst", img1)
    cv2.waitKey(0)
    cv2.destroyAllWindows()

imagesearch(0.95)

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