dvsq.py 文件源码

def initial_centers(self, img_output):
        C_init = np.zeros([self.subspace_num * self.subcenter_num, self.output_dim])
        print "#DVSQ train# initilizing Centers"
        all_output = img_output
        for i in xrange(self.subspace_num):
            kmeans = MiniBatchKMeans(n_clusters=self.subcenter_num).fit(all_output[:, i * self.output_dim / self.subspace_num: (i + 1) * self.output_dim / self.subspace_num])
            C_init[i * self.subcenter_num: (i + 1) * self.subcenter_num, i * self.output_dim / self.subspace_num: (i + 1) * self.output_dim / self.subspace_num] = kmeans.cluster_centers_
            print "step: ", i, " finish"
        return C_init