This is the script which I wrote to convert the cifar10/100 (gcn,whitened) datasets from pylearn2 to lmdb.

CIFAR10_Pylearn2_To_LMDB_Convertor.py

#in the name of GOD
#pylearn2 cifar10 convertor to lmdb
#by:Seyyed Hossein Hasanpour
#[email protected] 
#2/14/2017
import numpy as np
import cPickle
import lmdb
import caffe
from caffe.proto import caffe_pb2

def unpickle(file):
    import cPickle
    fo = open(file,'rb')
    dict = cPickle.load(fo)
    fo.close()
    return dict
	
def writeToLMDB(data_set, name):
    
    data = data_set.get_data()[0]
    labels = data_set.get_data()[1]
    
    size = data.shape[0]
    
    lmdb_file = name + '_gcn_whitened'
    batch_size = size

    db = lmdb.open(lmdb_file, map_size=int(data.nbytes))
    batch = db.begin(write=True)
    datum = caffe_pb2.Datum()
    
    print 'size = ',size	
    print 'label[0] shape = ',labels[0].shape
    print 'data[0] shape = ',data[0].shape
    for i in range(size):
        if i % 1000 == 0:
            print i

        # save in datum
        datum = caffe.io.array_to_datum(data[i].reshape(3,32,32), int(labels[i]))
        keystr = '{:0>5d}'.format(i)
        batch.put( keystr, datum.SerializeToString() )

        # write batch
        if(i + 1) % batch_size == 0:
            batch.commit()
            batch=db.begin(write=True)
            print (i + 1)

    # write last batch
    if (i+1) % batch_size != 0:
        batch.commit()
        print 'last batch'
        print (i + 1)

    print('Successfullly created ', lmdb_file) 
    
    
		
testset = unpickle('./test.pkl')
trainingset = unpickle('./train.pkl')
writeToLMDB(testset,'cifar10_test_lmdb')
writeToLMDB(trainingset,'cifar10_train_lmdb')