PointManifold_dy/Dataset_LLE.py

#!/usr/bin/env python
# coding: utf-8
"""
@Author: Dinghao Yang
@Contact: dinghaoyang@gmail,cin
@Time: 2020/9/28 7:29 PM

"""


import os
import glob
import h5py
import numpy as np
from sklearn import manifold

# In[3]:

def load_data(partition):
    DATA_DIR = './data'
    all_data = []
    all_label = []
    for h5_name in glob.glob(os.path.join(DATA_DIR, 'modelnet40*hdf5_2048', '*%s*.h5'%partition)):
        f = h5py.File(h5_name, 'r+')
        data = f['data'][:].astype('float32')
        label = f['label'][:].astype('int64')
        f.close()
        all_data.append(data)
        all_label.append(label)
    all_data = np.concatenate(all_data, axis=0)
    all_label = np.concatenate(all_label, axis=0)
    return all_data, all_label


# In[4]:


train_data, train_label = load_data('train')



train_data_lle = []
for i,x in enumerate(train_data):
    print('Processing sample%d'%i)
    x_lle, err =  manifold.locally_linear_embedding(x, n_neighbors=12,
                                             n_components=2)
    x_new = np.concatenate((x, x_lle),axis=1)
    train_data_lle.append(x_new)
print('Finish LLE!')

train_data_lle = np.array(train_data_lle)

f = h5py.File('./data/modelnet40_train_add_lle.h5','w')
f['data'] = train_data_lle
f['label'] = train_label
f.close()



# Test data
test_data, test_label = load_data('test')

# In[52]:


test_data_lle = []
for i,x in enumerate(test_data):
    print('Processing sample%d'%i)
    x_lle, err =  manifold.locally_linear_embedding(x, n_neighbors=12,
                                             n_components=2)
    x_new = np.concatenate((x, x_lle),axis=1)
    test_data_lle.append(x_new)
print('Finish LLE!')


# In[53]:


test_data_lle = np.array(test_data_lle)



f = h5py.File('./data/modelnet40_test_add_lle.h5','w')
f['data'] = test_data_lle
f['label'] = test_label
f.close()