该代码用于在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。出于某种原因,错误在knnMatch中我们处理捕获的图像。附加的图像链接显示错误导致行。如果有人能为这个问题提供一些解决方案会很棒,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()
答案 0 :(得分:2)
聚会晚了一点,但我猜你是在说knnMatch而不是knnMatches。