mnistのデータを numpy と pillow for python で pngへ変換

# coding: utf-8

from PIL import Image
import sys, os
import urllib.request
import gzip
import numpy as np


def main():
    mymnist = MyMnist()
    (x_train, t_train, x_test, t_test) = mymnist.load_mnist()

    i = 0
    while i < 10:
        img = Image.fromarray(np.uint8( x_train[i].reshape(28,28) ) )
        img.save("x_train_%d.png" % (i))
        i += 1

class MyMnist:
    def __init__(self):
        pass

    def load_mnist(self,flatten=True):
        data_files = self.download_mnist()
        # convert numpy
        dataset = {}
        dataset['train_img']   = self.load_img(  data_files['train_img'] )
        dataset['train_label'] = self.load_label(data_files['train_label'])
        dataset['test_img']    = self.load_img(  data_files['test_img']  )
        dataset['test_label']  = self.load_label(data_files['test_label'])

        # for key in ('train_img', 'test_img'):
        #     dataset[key] = dataset[key].astype(np.float32)
        #     dataset[key] /= 255.0

        for key in ('train_label','test_label'):
            dataset[key]=self.change_one_hot_label( dataset[key] )

        # 画像を一次元配列(平)にしない場合
        if not flatten:
             for key in ('train_img', 'test_img'):
                dataset[key] = dataset[key].reshape(-1, 1, 28, 28)
                
        return (dataset['train_img'],
                dataset['train_label'],
                dataset['test_img'],
                dataset['test_label'] )

    def change_one_hot_label(self,X):
        T = np.zeros((X.size, 10))
        for idx, row in enumerate(T):
            row[X[idx]] = 1
        return T
    
    def download_mnist(self):
        url_base = 'http://yann.lecun.com/exdb/mnist/'
        key_file = {'train_img'  :'train-images-idx3-ubyte.gz',
                    'train_label':'train-labels-idx1-ubyte.gz',
                    'test_img'   :'t10k-images-idx3-ubyte.gz',
                    'test_label' :'t10k-labels-idx1-ubyte.gz' }
        data_files = {}
        dataset_dir = os.path.dirname(os.path.abspath(__file__))
        
        for data_name, file_name in key_file.items():
            req_url   = url_base+file_name
            file_path = dataset_dir + "/" + file_name

            request  = urllib.request.Request( req_url )
            response = urllib.request.urlopen(request).read()
            with open(file_path, mode='wb') as f:
                f.write(response)
                
            data_files[data_name] = file_path
        return data_files

    def load_img( self,file_path):
        img_size    = 784 # = 28*28
        
        with gzip.open(file_path, 'rb') as f:
            data = np.frombuffer(f.read(), np.uint8, offset=16)
        data = data.reshape(-1, img_size)
        return data
    
    def load_label(self,file_path):
        with gzip.open(file_path, 'rb') as f:
            labels = np.frombuffer(f.read(), np.uint8, offset=8)
        return labels

if __name__ == '__main__':
    main()

↑こう書くと、↓こう変換できます