ValueError：查询数据维必须与训练数据维匹配

Question

当我尝试使用KNN模型和gabor描述符进行图像分类时，总是出现此错误。我认为这与y_hat和Ytest之间的尺寸不匹配有关。

有人可以帮助我纠正此错误吗？

这是代码：

def build_filters3():
    filters = []
    ksize = 9
    for theta in np.arange(0, np.pi, np.pi/12):
        for lamda in np.arange(0.5, 4, 0.3) :
            kern = cv2.getGaborKernel((ksize, ksize), 1.0, theta, lamda, 0.5, 0, ktype=cv2.CV_32F)
            kern/= 1.5*kern.sum()
            filters.append(kern)
    return filters

def process(img, filters):
    accum = np.zeros_like(img)
    for kern in filters:
        fimg = cv2.filter2D(img, cv2.CV_8UC3, kern)
        np.maximum(accum, fimg, accum)
    return accum



def gaborfiltersapp(f, Path):
    imgg = cv2.imread(Path, 0)
    feat = []
    # calculating the local energy for each convolved image
    for j in range(f.shape[0]):
        res = process(imgg, f[j])
        temp = 0
        for p in range(128):
            for q in range(128):
                temp = temp + res[p][q] * res[p][q]
        feat.append(temp)
    # calculating the mean amplitude for each convolved image
    for j in range(f.shape[0]):
        res = process(imgg, f[j])
        temp = 0
        for p in range(128):
            for q in range(128):
                temp = temp + abs(res[p][q])
        feat.append(temp)
    return np.ravel(feat)


filters3 = []
filters3 = build_filters3()
filters3 = np.asarray(filters3)
nbClass = 2
Xtrain = []
Ytrain = []
Xtest = []
Ytest = []
y_hat = []
def getTrainTest(nbClass) :
    Xtrain = []
    Ytrain = []
    Xtest = []
    Ytest = []
    compteur = 0
    for i in range(nbClass):
        print('le nombre i est :'+ str(i))
        cible = zeros(nbClass)
        cible[i] = 1
        X = []
        Y = []
        for j in range(2):
            ch = path+ 'ps' + str(i)+'/'+'ps'+str(i)+'_img'+str(j)+'.jpg'
            GaborImage = gaborfiltersapp(filters3, ch) 
            Xtrain.append(GaborImage)
            Ytrain.append(cible)
            print('element ajoutee au data train') 
        GaborImageTest = gaborfiltersapp(filters3, pathtest+'ps'+str(i)+'/'+'ps'+str(i)+'_img.jpg') 
        Xtest.append(GaborImageTest)
        Ytest.append(cible)
        print('element ajoutee au data test') 

    return Xtrain,Ytrain,Xtest,Ytest
Xtrain,Ytrain,Xtest,Ytest = getTrainTest(nbClass)
clf = KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski', metric_params=None, n_jobs=1, n_neighbors=1, p=2, weights='uniform')
clf.fit(Xtrain, Ytrain) 
y_hat = clf.predict(Xtest)
print('accuracy :' + str(clf.score(Ytest , y_hat)))

这是我从上一条指令中得到的错误：

  

ValueError：查询数据维必须与训练数据维匹配