使用CNN对cifar-10数据集进行读取和分类

这篇博客介绍了作者在WEEK2中使用CNN对cifar-10数据集进行分类的实践。内容包括数据来源、数据集展示(5000万张训练集,1000张测试集,每张图片32x32像素),CNN网络结构,测试集达到0.78的精度,文件结构,代码实现(数据读取和CNN训练)以及BN层和conv层same padding的重要性探讨。

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WEEK2报告

数据来源

cifar-10数据集说明和下载地址

数据集展示

整体结构:5000万张训练集,1000张测试集
在这里插入图片描述
单个图片size:32323
在这里插入图片描述

CNN网络结构

在这里插入图片描述

分类结果

测试集精度:0.78
7)(https://imgchr.com/i/eJC75V)]

read data_batch_1
has trained 1000 datas, accuracy = 0.21
has trained 2000 datas, accuracy = 0.27
has trained 3000 datas, accuracy = 0.27
has trained 4000 datas, accuracy = 0.37
has trained 5000 datas, accuracy = 0.34
has trained 6000 datas, accuracy = 0.4
has trained 7000 datas, accuracy = 0.38
has trained 8000 datas, accuracy = 0.37
has trained 9000 datas, accuracy = 0.46
has trained 10000 datas, accuracy = 0.47
read data_batch_2
has trained 11000 datas, accuracy = 0.46
has trained 12000 datas, accuracy = 0.44
has trained 13000 datas, accuracy = 0.44
has trained 14000 datas, accuracy = 0.5
has trained 15000 datas, accuracy = 0.49
has trained 16000 datas, accuracy = 0.45
has trained 17000 datas, accuracy = 0.41
has trained 18000 datas, accuracy = 0.47
has trained 19000 datas, accuracy = 0.64
has trained 20000 datas, accuracy = 0.46
read data_batch_3
has trained 21000 datas, accuracy = 0.53
has trained 22000 datas, accuracy = 0.63
has trained 23000 datas, accuracy = 0.54
has trained 24000 datas, accuracy = 0.54
has trained 25000 datas, accuracy = 0.51
has trained 26000 datas, accuracy = 0.6
has trained 27000 datas, accuracy = 0.54
has trained 28000 datas, accuracy = 0.57
has trained 29000 datas, accuracy = 0.52
has trained 30000 datas, accuracy = 0.57
read data_batch_4
has trained 31000 datas, accuracy = 0.5
has trained 32000 datas, accuracy = 0.56
has trained 33000 datas, accuracy = 0.59
has trained 34000 datas, accuracy = 0.54
has trained 35000 datas, accuracy = 0.57
has trained 36000 datas, accuracy = 0.59
has trained 37000 datas, accuracy = 0.59
has trained 38000 datas, accuracy = 0.59
has trained 39000 datas, accuracy = 0.54
has trained 40000 datas, accuracy = 0.69
read data_batch_5
has trained 41000 datas, accuracy = 0.62
has trained 42000 datas, accuracy = 0.57
has trained 43000 datas, accuracy = 0.58
has trained 44000 datas, accuracy = 0.53
has trained 45000 datas, accuracy = 0.62
has trained 46000 datas, accuracy = 0.58
has trained 47000 datas, accuracy = 0.53
has trained 48000 datas, accuracy = 0.66
has trained 49000 datas, accuracy = 0.54
has trained 50000 datas, accuracy = 0.67
training complicated!
test data accuracy = 0.78
runing time:  387.4479079246521

文件结构

在这里插入图片描述

代码

功能:
读取,格式化数据集

# -*- coding: utf-8 -*-
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