kmeans:必需参数未找到“标志”（位置6）

Question

我想用kmeans计算lbp的集群。 首先，我计算每幅图像大小为8*8的lbp值。 然后我用cv2.kmeans，但它不能工作 这个错误：必需参数未找到“标志”（位置6） 代码：

# -*- coding: utf-8 -*- """ Spyder Editor This temporary script file is located here: /home/nel/.spyder2/.temp.py """ from skimage.feature import local_binary_pattern from skimage import io from skimage.color import rgb2gray import numpy as np import cv2 def loadImages(path): import os imagePaths = map(lambda a:os.path.join(path,a),os.listdir(path)) images = map(io.imread,imagePaths) return imagePaths,images def lbpdesc(imagename): radius = 1 n_points = 8 METHOD = 'nri_uniform' imagename = io.imread('/home/nel/project/pictest/1.jpg') gray_image = rgb2gray(imagename) lbp_height,lbp_width = gray_image.shape grid_rows = 8 grid_cols = 8 py = int(np.floor(lbp_height/grid_rows)) px = int(np.floor(lbp_width/grid_cols)) E = np.zeros((py*px,64)) i = 0 for row in range(0,py): for col in range(0,px): block =gray_image[row*grid_rows:(row+1)*grid_rows,col*grid_cols:(col+1)*grid_cols] H = local_binary_pattern(block,n_points,radius,METHOD) E[i,:] = H.ravel() i+=1 return E if __name__ =="__main__": images = {} imagePath,imagesed = loadImages("/home/nel/project/pictest") for i in range(len(imagePath)): images[imagePath[i]] = imagesed[i] features = {} for d,x in images.items(): features[d] = lbpdesc(x) featureall = np.float32(np.vstack(features.values())) codebookSize = 40 iterMax = 100 term_crit = (cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT,10,1) retval,bestLabels,codebook = cv2.kmeans(featureall,codebookSize,term_crit,iterMax,cv2.KMEANS_RANDOM_CENTERS)