Python读取MNIST手写数据集生成图片

叁歲伎倆 2023-01-21 12:28 153阅读 0赞

## 一、[数据集官网链接][Link 1] ##

[本文章源码及数据集文件][Link 2]

## 二、数据集解析格式 ##

### 1. `train-labels-idx1-ubyte`与`t10k-labels-idx1-ubyte`为图片二进制数据文件 ###

头两个32bit数据不在标签范围，读取时需要舍去

### 2. `train-labels-idx1-ubyte`与`t10k-images-idx3-ubyte`为图片标签二进制数据文件 ###

头四个32bit数据不在图片范围，生成图片时需要舍去

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ0NTc1Nzg5_size_16_color_FFFFFF_t_70]

## 实现参考代码 ##

import numpy as np
    import cv2 as cv
    import os
    
    
    def mkdir_rsdir(path_root):
        """ :param path_root: 输出根路径 """
        path_t10k_images = path_root + '/t10k-images'
        path_train_images = path_root + '/train-images'
        if not os.path.exists(path_t10k_images):
            os.mkdir(path_t10k_images)
        if not os.path.exists(path_train_images):
            os.mkdir(path_train_images)
    
        for i in range(0, 10):
            if not os.path.exists(path_t10k_images + '/' + str(i)):
                os.mkdir(path_t10k_images + '/' + str(i))
            if not os.path.exists(path_train_images + '/' + str(i)):
                os.mkdir(path_train_images + '/' + str(i))
    
    
    def read_pic(idx3_ubyte_fp):
        """ 读取一张图片 :param idx3_ubyte_fp: 图片文件 :return: img """
        temp_image = []
        for i in range(0, 28 * 28):
            image_data = idx3_ubyte_fp.read(1)
            temp_image.append(int.from_bytes(image_data, byteorder='big', signed=False))
            # print(int.from_bytes(image_data, byteorder='big', signed=False), end=' ')
        return np.array(temp_image, dtype=np.uint8).reshape(28, 28)
    
    
    def read_lable(idx1_ubyte_fp):
        """ 读取一个标签 :param idx1_ubyte_fp: 标签文件 :return: 数字标签 """
        return int.from_bytes(idx1_ubyte_fp.read(1), byteorder='big', signed=False)
    
    
    if __name__ == '__main__':
        # 测试集
        t10k_idx3_ubyte_fp = open('t10k-images.idx3-ubyte', 'rb')
        # 舍去开头
        t10k_idx3_ubyte_fp.read(1 * 4 * 4)
        t10k_idx1_ubyte_fp = open('t10k-labels.idx1-ubyte', 'rb')
        # 舍去开头
        t10k_idx1_ubyte_fp.read(1 * 4 * 2)
        path_out_root = 'MNIST'
        mkdir_rsdir(path_out_root)
        t10k_all_pic = 0
        while t10k_idx1_ubyte_fp.tell() != os.path.getsize('t10k-labels.idx1-ubyte'):
            img = read_pic(t10k_idx3_ubyte_fp)
            lable = read_lable(t10k_idx1_ubyte_fp)
            cv.imwrite(
                path_out_root + '/t10k-images/' + str(lable) + '/' + str(lable) + ('_%d_10k_images.jpg' % t10k_all_pic),
                img)
            t10k_all_pic += 1
    
        t10k_idx3_ubyte_fp.close()
        t10k_idx1_ubyte_fp.close()
    
        # 训练集，与测试集一致，但懒得抽出函数
    
        train_idx3_ubyte_fp = open('train-images.idx3-ubyte', 'rb')
        # 舍去开头
        train_idx3_ubyte_fp.read(1 * 4 * 4)
        train_idx1_ubyte_fp = open('train-labels.idx1-ubyte', 'rb')
        # 舍去开头
        train_idx1_ubyte_fp.read(1 * 4 * 2)
        train_all_pic = 0
        while train_idx1_ubyte_fp.tell() != os.path.getsize('train-labels.idx1-ubyte'):
            img = read_pic(train_idx3_ubyte_fp)
            lable = read_lable(train_idx1_ubyte_fp)
            cv.imwrite(
                path_out_root + '/train-images/' + str(lable) + '/' + str(lable) + ('_%d_train_images.jpg' % train_all_pic),
                img)
            train_all_pic += 1
    
        train_idx3_ubyte_fp.close()
        train_idx1_ubyte_fp.close()

[原文][Link 3]：`https://www.blog.hiyj.cn/article/detail/4`

[Link 1]: http://yann.lecun.com/exdb/mnist/
[Link 2]: https://github.com/WindSnowLi/My-python-tools/tree/main/Read-MNIST
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ0NTc1Nzg5_size_16_color_FFFFFF_t_70]: /images/20221020/5975858ae0814157be289b6ae3b6749a.png
[Link 3]: https://www.blog.hiyj.cn/article/detail/4