Я неправильно использую LMDB? Он говорит, что предел размера карты среды достигнут после 0 вставок

Я пытаюсь создать базу данных LMDB для моего проекта машинного обучения Caffe. Но LMDB выдает ошибку при первой попытке вставить точку данных, говоря, что размер карты среды заполнен.

Вот код, который пытается заполнить базу данных:

import numpy as np
from PIL import Image
import os
import lmdb
import random
# my data structure for holding image/label pairs
from serialization import DataPoint

class LoadImages(object):
    def __init__(self, image_data_path):
        self.image_data_path = image_data_path
        self.dirlist = os.listdir(image_data_path)

        # find the number of images that are to be read from disk
        # in this case there are 370 images.
        num = len(self.dirlist)

        # shuffle the list of image files so that they are read in a random order
        random.shuffle(self.dirlist)

        map_size = num*10

        j=0

        # load images from disk
        for image_filename in os.listdir(image_data_path):
            # check that every image belongs to either category _D_ or _P_
            assert (image_filename[:3] == '_D_' or image_filename[:3] == '_P_'), "ERROR: unknown category"

            # set up the LMDB datbase object
            env = lmdb.open('image_lmdb', map_size=map_size)
            with env.begin(write=True) as txn:

                # iterate over (shuffled) list of image files
                for image_filename in self.dirlist:
                    print "Loading " + str(j) + "th image from disk - percentage complete:  " + str((float(j)/num) * 100) + " %"

                    # open the image
                    with open(str(image_data_path + "/" + image_filename), 'rb') as f:
                        image = Image.open(f)
                        npimage = np.asarray(image, dtype=np.float64)

                    # discard alpha channel, if necessary
                    if npimage.shape[2] == 4:
                        npimage = npimage[:,:,:3]
                        print image_filename + " had its alpha channel removed."

                    # get category
                    if image_filename[:3] == '_D_':
                        category = 0
                    elif image_filename[:3] == '_P_':
                        category = 1

                    # wrap image data and label into a serializable data structure
                    datapoint = DataPoint(npimage, category)
                    serialized_datapoint = datapoint.serialize()

                    # a database key
                    str_id = '{:08}'.format(j)

                    # put the data point in the LMDB
                    txn.put(str_id.encode('ascii'), serialized_datapoint)

                j+=1

Я также создал небольшую структуру данных для хранения изображений и меток и их сериализации, которая использовалась выше:

import numpy as np

class DataPoint(object):
    def __init__(self, image=None, label=None, dtype=np.float64):
        self.image = image
        if self.image is not None:
            self.image = self.image.astype(dtype)
        self.label = label

    def serialize(self):
        image_string = self.image.tobytes()
        label_string = chr(self.label)
        datum_string = label_string + image_string
        return datum_string

    def deserialize(self, string):
        image_string = string[1:]
        label_string = string[:1]
        image = np.fromstring(image_string, dtype=np.float64)
        label = ord(label_string)
        return DataPoint(image, label)

Вот ошибка:

/usr/bin/python2.7 /home/hal9000/PycharmProjects/Caffe_Experiments_0.6/gather_images.py
Loading 0th image from disk - percentage complete:  0.0 %
Traceback (most recent call last):
  File "/home/hal9000/PycharmProjects/Caffe_Experiments_0.6/gather_images.py", line 69, in <module>
    g = LoadImages(path)
  File "/home/hal9000/PycharmProjects/Caffe_Experiments_0.6/gather_images.py", line 62, in __init__
    txn.put(str_id.encode('ascii'), serialized_datapoint)
lmdb.MapFullError: mdb_put: MDB_MAP_FULL: Environment mapsize limit reached