ValueError:无法将大小为2的序列复制到维度为4的数组轴 [英] ValueError: cannot copy sequence with size 2 to array axis with dimension 4

问题描述

任何人都可以向我解释此错误是从哪里来的吗?这是什么意思?以及我该如何解决? 也许我的问题太笼统了！对不起，但我不知道该在这里多放些什么！ :P

Can any one explain to me where is this error come from? and what does it mean? and how can I fix that? Maybe my question is so general! sorry but I don't know what should I put more here! :P

错误:

    Traceback (most recent call last):
  File "C:\test\7.4.3.bench.py", line 9, in <module>
    print imagesearch.compute_ukbench_score(src,imlist[:100])
  File "C:\test\imagesearch.py", line 168, in compute_ukbench_score
    pos[i] = [w[1]-1 for w in src.query(imlist[i])[:4]]
  File "C:\test\imagesearch.py", line 128, in query
    h = self.get_imhistogram(imname)
  File "C:\test\imagesearch.py", line 91, in get_imhistogram
    "select rowid from imlist where filename='%s'" % imname).fetchone()
ValueError: cannot copy sequence with size 2 to array axis with dimension 4

这是imagesearch.py​​:

Here is imagesearch.py:

from numpy import *
import pickle
from pysqlite2 import dbapi2 as sqlite


class Indexer(object):

    def __init__(self,db,voc):
        """ Initialize with the name of the database 
            and a vocabulary object. """

        self.con = sqlite.connect(db)
        self.voc = voc

    def __del__(self):
        self.con.close()

    def db_commit(self):
        self.con.commit()

    def get_id(self,imname):
        """ Get an entry id and add if not present. """

        cur = self.con.execute(
        "select rowid from imlist where filename='%s'" % imname)
        res=cur.fetchone()
        if res==None:
            cur = self.con.execute(
            "insert into imlist(filename) values ('%s')" % imname)
            return cur.lastrowid
        else:
            return res[0] 

    def is_indexed(self,imname):
        """ Returns True if imname has been indexed. """

        im = self.con.execute("select rowid from imlist where filename='%s'" % imname).fetchone()
        return im != None

    def add_to_index(self,imname,descr):
        """ Take an image with feature descriptors, 
            project on vocabulary and add to database. """

        if self.is_indexed(imname): return
        print 'indexing', imname

        # get the imid
        imid = self.get_id(imname)

        # get the words
        imwords = self.voc.project(descr)
        nbr_words = imwords.shape[0]

        # link each word to image
        for i in range(nbr_words):
            word = imwords[i]
            # wordid is the word number itself
            self.con.execute("insert into imwords(imid,wordid,vocname) values (?,?,?)", (imid,word,self.voc.name))

        # store word histogram for image
        # use pickle to encode NumPy arrays as strings
        self.con.execute("insert into imhistograms(imid,histogram,vocname) values (?,?,?)", (imid,pickle.dumps(imwords),self.voc.name))

    def create_tables(self): 
        """ Create the database tables. """

        self.con.execute('create table imlist(filename)')
        self.con.execute('create table imwords(imid,wordid,vocname)')
        self.con.execute('create table imhistograms(imid,histogram,vocname)')        
        self.con.execute('create index im_idx on imlist(filename)')
        self.con.execute('create index wordid_idx on imwords(wordid)')
        self.con.execute('create index imid_idx on imwords(imid)')
        self.con.execute('create index imidhist_idx on imhistograms(imid)')
        self.db_commit()


class Searcher(object):

    def __init__(self,db,voc):
        """ Initialize with the name of the database. """
        self.con = sqlite.connect(db)
        self.voc = voc

    def __del__(self):
        self.con.close()

    def get_imhistogram(self,imname):
        """ Return the word histogram for an image. """

        im_id = self.con.execute(
            "select rowid from imlist where filename='%s'" % imname).fetchone()
        s = self.con.execute(
            "select histogram from imhistograms where rowid='%d'" % im_id).fetchone()

        # use pickle to decode NumPy arrays from string
         return pickle.loads(str(s[0]))

     def candidates_from_word(self,imword):
        """ Get list of images containing imword. """

        im_ids = self.con.execute(
            "select distinct imid from imwords where wordid=%d" % imword).fetchall()
         return [i[0] for i in im_ids]

    def candidates_from_histogram(self,imwords):
        """ Get list of images with similar words. """

        # get the word ids
        words = imwords.nonzero()[0]

        # find candidates
        candidates = []
        for word in words:
            c = self.candidates_from_word(word)
            candidates+=c

        # take all unique words and reverse sort on occurrence 
        tmp = [(w,candidates.count(w)) for w in set(candidates)]
        tmp.sort(cmp=lambda x,y:cmp(x[1],y[1]))
        tmp.reverse()

        # return sorted list, best matches first    
        return [w[0] for w in tmp] 

    def query(self,imname):
        """ Find a list of matching images for imname. """

        h = self.get_imhistogram(imname)
        candidates = self.candidates_from_histogram(h)

        matchscores = []
        for imid in candidates:
            # get the name
            cand_name = self.con.execute(
                "select filename from imlist where rowid=%d" % imid).fetchone()
            cand_h = self.get_imhistogram(cand_name)
            cand_dist = sqrt( sum( self.voc.idf*(h-cand_h)**2 ) )
            matchscores.append( (cand_dist,imid) )

        # return a sorted list of distances and database ids
        matchscores.sort()
        return matchscores

    def get_filename(self,imid):
        """ Return the filename for an image id. """

        s = self.con.execute(
            "select filename from imlist where rowid='%d'" % imid).fetchone()
        return s[0]


def tf_idf_dist(voc,v1,v2):

    v1 /= sum(v1)
    v2 /= sum(v2)

    return sqrt( sum( voc.idf*(v1-v2)**2 ) )


def compute_ukbench_score(src,imlist):
    """ Returns the average number of correct
        images on the top four results of queries. """

    nbr_images = len(imlist)
    pos = zeros((nbr_images,4))
    # get first four results for each image
    for i in range(nbr_images):
        pos[i] = [w[1]-1 for w in src.query(imlist[i])[:4]]

    # compute score and return average
    score = array([ (pos[i]//4)==(i//4) for i in range(nbr_images)])*1.0
    return sum(score) / (nbr_images)


# import PIL and pylab for plotting        
from PIL import Image
from pylab import *

def plot_results(src,res):
    """ Show images in result list 'res'. """

   figure()
   nbr_results = len(res)
   for i in range(nbr_results):
        imname = src.get_filename(res[i])
        subplot(1,nbr_results,i+1)
        imshow(array(Image.open(imname)))
        axis('off')
    show()

推荐答案

imagesearch.py​​中的第168行看起来有问题:

line 168 in imagesearch.py looks problematic:

    pos[i] = [  w[1]-1 for w in src.query(imlist[i]) [:4] ]

这里可能发生的情况是您的数据库查询返回的行少于4个.然后，在列表理解中，您尝试将其插入到具有4列的pos行中(因此需要4项，而这些项不存在).因此出现错误:"ValueError:无法将大小为2的序列复制到维度为4的数组轴上"

What is possibly happening here is that your db query is returning a row with less than 4 items. And then in your list comprehension you are trying to insert that into a row of pos which has 4 columns (and so needs 4 items, which are not there). Hence the error: "ValueError: cannot copy sequence with size 2 to array axis with dimension 4"

通过打印查询语句的o/p来检验该假设.看看它是否真的有4个项目.

Test this hypothesis by printing the o/p of the query statement. See whether it really has 4 items or not.

如果它出现两个项目，那么要避免分配给pos，请执行以下操作:

And if it turns up two items then to avoid the assignment to pos do:

l = [  w[1]-1 for w in src.query(imlist[i]) [:4] ]
if len(l) == 4:
    pos[i] = l

这篇关于ValueError:无法将大小为2的序列复制到维度为4的数组轴的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！