“cv2.FlannBasedMatcher”对象没有属性“knnMatches”

Question

该代码用于在从网络摄像头捕获的图像上使用 FLANN 匹配器实现基于 SIFT 的算法。由于某种原因，错误出现在我们处理捕获图像的 knnMatch 中。附加的图像链接显示了导致错误的行。如果有人能为这个问题提供一些解决方案，那就太好了，请在下面评论具体细节。

    import cv2
import numpy as np

MIN_MATCH_COUNT = 30

detector = cv2.xfeatures2d.SIFT_create()
FLANN_INDEX_KDITREE = 0
flannParam = dict(algorithm=FLANN_INDEX_KDITREE,tree=5)
searchParam = dict(check = 50)
flann=cv2.FlannBasedMatcher(flannParam,searchParam)

trainImg=cv2.imread("E:\\EXCHANGE_Courses\\training_img1.jpg")
trainImg1 = cv2.cvtColor(trainImg,cv2.COLOR_BGR2GRAY)
trainKP,trainDecs = detector.detectAndCompute(trainImg1,None)

cam = cv2.VideoCapture(1)
print(cam.isOpened())

for i in range(1):
    return_value, image = cam.read()
    cv2.imwrite('capture'+str(i)+'.jpg', image)
del(cam)


while True:
   
   
    QImage = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)
  
    
    queryKP,queryDesc = detector.detectAndCompute(QImage,None)
   # Now match the key descriptions from the training image and the query image
    # np.asarray(des1,np.float32),np.asarray(des2,np.float32),k=2
     #   queryDesc,trainDecs, k=2
    matches=flann.knnMatches(queryDesc,trainDecs, k=2)
    print("upper part clear")
    # Filter the pool of keypoints as we need to collect the key points of interest only with the object in mind
    goodMatch=[]
    for m,n in matches:

        if(m.distance<0.75*n.distance):
            goodMatch.append(m)
            print("all ok here")
        
    if(len(goodMatch)>MIN_MATCH_COUNT):
            tp=[]
            qp=[]
            for m in goodMatch:
                tp.append(trainKP[m.trainIdx].pt)
                qp.append(queryKP[m.queryIdx].pt)
                tp,qp = np.float32((tp,qp))
                H,status = cv2.findHomography(tp,qp,cv2.RANSAC,3.0)
                h,w=trainImg.shape
                
                trainBorder = np.float32([[[0,0],[0,h-1],[w-1,h-1],[0,w-1]]])
                queryBorder = cv2.perspectiveTransform(trainBorder,H)
                # changed QImageBGR to image
                cv2.polylines(QImage,[np.uint8(queryBorder)],True,(0,255,0),3)
    else:
            print("Not enough matches - %d/%d" %len(goodMatch),MIN_MATCH_COUNT)
            cv2.imshow('results',QImage)
             #print ("Not enough matches are found - %d/%d" % (len(goodMatch),MIN_MATCH_COUNT))
             #matchesMask = None
             #draw_params = dict(matchColor = (0,255,0), # draw matches in green color
             #      singlePointColor = None,
                  # matchesMask = matchesMask, # draw only inliers
                  # flags = 2)

#img3 = cv2.drawMatches(trainImg1,trainKP,QImage,queryKP,goodMatch,None,**draw_params)

#plt.imshow(img3, 'gray'),plt.show()

            if cv2.waitKey(10)==ord('q'):
                break
#cam.release()
#cv2.destroyAllWindows()

Answer 1

聚会有点晚了，但我猜你的意思是 knnMatch 而不是 knnMatches。