python - ORB Detector 如何与不同的匹配器（FlannBased、BruteForce、...）一起工作？

Question

我正在尝试实现一个程序来检测和跟踪玩家，并且我一直在使用这些匹配器测试 ORB 检测器：FlannBased、BFMatcher。我什至用 SIFT Detector 试过这些匹配器，但我得到的结果都是一样的。这张图片基本上显示了我得到的内容： ORB With FlannBased Matcher

如您所见，这两个图像之间的匹配主要集中在舞台的结构上，而不是在球员身上。不知道有没有办法让探测器只关注人。我愿意接受建议！！另外，我想知道图像质量是否有某种限制

这是我用来获取上图的代码

#FLANN based Matcher With  ORB Descriptors
import numpy as np
import cv2
from matplotlib import pyplot as plt

img1 = cv2.imread('Imag-Prueba.png',0)   # queryImage
img2 = cv2.imread('Imag-Prueba-2.jpg',0) # trainImage

# Initiate ORB detector
orb = cv2.ORB_create(nfeatures=10000, scoreType=cv2.ORB_FAST_SCORE)

# find the keypoints and descriptors with ORB
kp1, des1 = orb.detectAndCompute(img1,None)
kp2, des2 = orb.detectAndCompute(img2,None)

# FLANN parameters
FLANN_INDEX_LSH = 6
index_params= dict(algorithm = FLANN_INDEX_LSH,
                   table_number = 12, # 12
                   key_size = 12,     # 20
                   multi_probe_level = 2) #2

search_params = dict(checks=100)   # or pass empty dictionary
flann = cv2.FlannBasedMatcher(index_params,search_params)
matches = flann.knnMatch(des1, des2, k=2)

# Need to draw only good matches, so create a mask
matchesMask = [[0,0] for i in range(len(matches))]

# ratio test as per Lowe's paper
for i, m_n in enumerate(matches):
  if len(m_n) != 2:
    continue
  elif m_n[0].distance < 0.80*m_n[1].distance:
    matchesMask[i]=[1,0]

draw_params = dict(matchColor = (0,255,0),
                   singlePointColor = (255,0,0),
                   matchesMask = matchesMask,
                   flags = 0)

img3 = cv2.drawMatchesKnn(img1,kp1,img2,kp2,matches,None,**draw_params)
cv2.imwrite('ORB-FLANNMatcher-0.8.jpg',img3)

标签： pythonopencvorbflann