python - 在 Python 中将 knnMatch 与 opencv 一起使用时出错

Question

我正在尝试在实时视频源中使用 SIFT 执行对象检测，并且正在围绕感兴趣的对象绘制轮廓该程序有时运行良好，但我经常遇到以下错误:-

Traceback (most recent call last):
  File "/home/user/adam/modify.py", line 19, in <module>
    matches=flann.knnMatch(des_img,des_query,k=2)
error: /io/opencv/modules/flann/src/miniflann.cpp:315: error: (-210) type=0
 in function buildIndex_

是什么原因造成的，我该如何解决。

这是我的代码

import cv2
import numpy as np

cap=cv2.VideoCapture(0)
img = cv2.imread("/home/user/Desktop/gre2.jpg",0)
sift=cv2.xfeatures2d.SIFT_create()
kp_img,des_img=sift.detectAndCompute(img,None)



index_params = dict(algorithm = 0 ,trees = 5)
search_params=dict()
flann = cv2.FlannBasedMatcher(index_params,search_params)

while True:
    _,frame=cap.read()
    grayframe=cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)
    kp_query,des_query=sift.detectAndCompute(grayframe,None)
    *matches=flann.knnMatch(des_img,des_query,k=2)*
    good_points = []
    for m,n in matches:
        if m.distance < 0.6*n.distance:
            good_points.append(m)

    if len(good_points)> 10:
        query_pts=np.float32([kp_img[m.queryIdx].pt for m in good_points]).reshape(-1,1,2)
        train_pts=np.float32([kp_query[m.trainIdx].pt for m in good_points]).reshape(-1,1,2)
        matrix,mask = cv2.findHomography(query_pts,train_pts,cv2.RANSAC,5.0)
        matches_mask=mask.ravel().tolist()
        h,w=img.shape
        pts=np.float32([[0,0],[0,h],[w,h],[w,0]]).reshape(-1,1,2)
        dst=cv2.perspectiveTransform(pts,matrix)

        homography = cv2.polylines(frame,[np.int32(dst)],True,(255,0,0),3)
        cv2.imshow("grayframe",homography)
    else:
        cv2.imshow("grayframe",frame)



    k =cv2.waitKey(1)
    if k ==27:
        break
cap.release()
cv2.destroyAllWindows()

Answer 1

问题是每当屏幕变黑或太暗时 des_query 返回 None 类型，所以我试了一下，除了解决我的错误，这里是工作代码:

import cv2
import numpy as np
cap=cv2.VideoCapture(0)
img = cv2.imread("/home/keshav/Desktop/gre2.jpg",0)
sift=cv2.xfeatures2d.SIFT_create()
kp_img,des_img=sift.detectAndCompute(img,None)
index_params = dict(algorithm = 2 ,trees = 5)
search_params=dict()
flann = cv2.FlannBasedMatcher(index_params,search_params

while True:
    _,frame=cap.read()
    grayframe=cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)
    kp_query,des_query=sift.detectAndCompute(grayframe,None)
    try:
        if(des_query==None):
            pass
    except:
        matches=flann.knnMatch(des_img,des_query,k=2)
        good_points = []
        for m,n in matches:
            if m.distance < 0.6*n.distance:
                good_points.append(m)
        if len(good_points)> 10:
            query_pts=np.float32([kp_img[m.queryIdx].pt for m in good_points]).reshape(-1,1,2)
            train_pts=np.float32([kp_query[m.trainIdx].pt for m in good_points]).reshape(-1,1,2)
            matrix,mask = cv2.findHomography(query_pts,train_pts,cv2.RANSAC,5.0)
            matches_mask=mask.ravel().tolist()
            h,w=img.shape
            pts=np.float32([[0,0],[0,h],[w,h],[w,0]]).reshape(-1,1,2)
            print(pts)
            dst=cv2.perspectiveTransform(pts,matrix)

            homography = cv2.polylines(frame,[np.int32(dst)],True,(255,0,0),3)
            cv2.imshow("grayframe",homography)
        else:
            cv2.imshow("grayframe",frame)


        k =cv2.waitKey(1)
        if k ==27:
            break
cap.release()
cv2.destroyAllWindows()