Question

我无法看到我出错的地方。我有python代码使用OpenCV2来计算2个图像的特征，然后匹配并绘制最相似的点。如果我运行单独的代码，它可以工作，我可以更改第二个图像文件的名称，当我尝试自动化它循环通过图像目录与第一个图像进行比较我在Ubuntu 14.04，OpenCV 3.10上得到以下错误

除了我的代码粗糙之外，任何人都会看到为什么循环错误，但个别比较没有？

opencv / modules / core / src / stat.cpp：3749：错误：（-215）type == src2.type（）＆amp;＆amp; src1.cols == src2.cols＆amp;＆amp; （函数batchDistance

中的（type == CV_32F || type == CV_8U）

个人代码

import sys
import cv2
import os
import numpy as np
from matplotlib import pyplot as plt

#Load the crest and create a grey version
crest = cv2.imread('Crest.png')
greyCrest = cv2.cvtColor(crest,cv2.COLOR_BGR2GRAY)

#Create the ORB Object and BruteForce
orb=cv2.ORB_create()
#Use Hamming Distance as its ORD (other algorithms would use a different distance measure)
BruteForceMatch = cv2.BFMatcher(cv2.NORM_HAMMING,crossCheck=True)
#Calculate the keypoints and descriptors for the crest
Crestkeypoints,Crestdescriptor = orb.detectAndCompute(greyCrest,None)

#
testimage = cv2.imread('OtherImage.jpg')
testkeypoints, testdescriptors = orb.detectAndCompute(testimage,None)

#Basic Idea
matches = BruteForceMatch.match(Crestdescriptor,testdescriptors)
#Sort the matches so the strongest are at the top
matches = sorted(matches, key = lambda x:x.distance)
Title = "Total Matched " + str(len(matches)) +" Plotting Top 40"
#display the top 40 matches on the plot
MatchImage = cv2.drawMatches(greyCrest,Crestkeypoints,testimage,testkeypoints,matches[:40],testimage,flags=2)
#This gets rid of the blue tint to the end image when plotting OpenCV image in Matplotlib because of the RGB ,BGR difference
plt.imshow(cv2.cvtColor(MatchImage, cv2.COLOR_BGR2RGB))
plt.title(Title)
plt.show()
#Pause for 10 Seconds so you can see the plot
plt.pause(10)
#Have to close as for some reason the figures weren't plotting correctly when I ran the code the 2nd time
plt.close('all')

循环代码

下面是遍历目录的代码，将图像加载到OpenCV中，计算图像的关键点和特征，并在获得匹配数量和绘制前40个匹配项之前将其与搜索图像进行比较

#Load the crest and create a grey version
import cv2
import os
import numpy as np
from matplotlib import pyplot as plt
    crest = cv2.imread('Crest.png')
    greyCrest = cv2.cvtColor(crest,cv2.COLOR_BGR2GRAY)

    #Create the ORB Object and BruteForce
    orb2=cv2.ORB_create()
    #Use Hamming Distance as its ORD (other algorithms would use a different distance measure)
    BruteForceMatch = cv2.BFMatcher(cv2.NORM_HAMMING,crossCheck=True)
    #Calculate the keypoints and descriptors for the crest
    Crestkeypoints,Crestdescriptor = orb2.detectAndCompute(greyCrest,None)


    #Get the folder of Images to be matched with ORB 1 by 1 against the Search Image
    for ImageToProcess in os.listdir('/MatchWithORB'):
        print "Processing Image", ImageToProcess
        #Load the current Image as greyscale and calculate the keypoints, descriptors
        CurrentImage = cv2.imread(ImageToProcess,cv2.IMREAD_GRAYSCALE)
        currImageKeyPoints, currImageDescriptors = orb2.detectAndCompute(CurrentImage,None)
        #Get the matches between the current image and the crest
        matches = BruteForceMatch.match(Crestdescriptor,currImageDescriptors)
        Title = "Crest Total Matched " + str(len(matches)) +" Plotting Top 40 " +ImageToProcess
        # Sort them so the top matches are higher
        matches = sorted(matches, key = lambda x:x.distance)
        MatchImage = cv2.drawMatches(greyCrest,Crestkeypoints,CurrentImage,currImageKeyPoints,matches[:40],CurrentImage,flags=2)
        plt.imshow(MatchImage)
        plt.draw()
        plt.pause(10)
        #tidyup
        BruteForceMatch.clear
    print"Looping"

Answer 1

一个古老的问题，但是答案是，如果未检测到任何功能，detectAndCompute将返回“ None”而不是一个空列表。然后，随着代码继续匹配，它将尝试将功能列表与None类型匹配，从而为您提供所描述的错误。简便的检查方法：

    if des1 is None or des2 is None:
    print(des1)
    print(des2)
    pdb.set_trace()

他们可能会是无

个别比较正常工作时循环浏览图像时OpenCV2 BatchDistance错误-215

1 个答案: