具体描述
本书是一本深度学习的基础入门读物，对深度学习的基本理论进行了介绍，主要以Ubuntu系统为例搭建了三大主流框架——Caffe、TensorFlow、Torch，然后分别在3个框架下，通过3个实战项目掌握了框架的使用方法，并详细描述了生产流程，最后讲述了通过集群部署深度学习的项目以及如何进行运营维护的注意事项。
作者简介
唐宏
中国电信股份有限公司广州研究院数据通信研究所所长、高级工程师，中国电子学会云计算专家委员会委员，中国电信股份有限公司科技委员会数据组副组长，中国SDN产业联盟需求场景与网络架构组组长。主要从事IP承载网、下一代互联网、网络新技术方面的研发与管理工作。
目录信息
第 1 章 深度学习简介 ············································································ 1
1.1 深度学习的发展 ·······································································1
1.2 深度学习的应用及研究方向 ···················································3
1.3 深度学习工具介绍和对比 ·······················································4
1.3.1 Caffe·················································································4
1.3.2 TensorFlow ······································································5
1.3.3 Torch ················································································6
1.4 小结 ···························································································7
第 2 章 深度学习基本理论 ····································································9
2.1 深度学习的基本概念 ·······························································9
2.2 深度学习的训练过程 ·····························································13
2.3 深度学习的常用模型和方法 ·················································14
2.4 小结 ·························································································20
第 3 章 深度学习环境搭建 ································································· 23
3.1 Caffe 安装 ···············································································23
3.1.1 安装 Caffe 的相关依赖项·············································24
3.1.2 安装 NVIDIA 驱动 ·······················································24
3.1.3 安装 CUDA ···································································27
3.1.4 配置 cuDNN ··································································30
3.1.5 源代码编译安装 OpenCV ············································32
3.1.6 编译 Caffe，并配置 Python 接口 ································34
3.2 Caffe 框架下的 MNIST 数字识别问题···································41
3.3 TensorFlow 安装 ······································································42
3.3.1 基于 pip 安装·································································42
3.3.2 基于 Anaconda 安装 ······················································46
3.3.3 基于源代码安装····························································51
3.3.4 常见安装问题································································56
3.4 TensorFlow 框架下的 CIFAR 图像识别问题·························59
3.5 Torch 安装 ···············································································61
3.5.1 无 CUDA 的 Torch 7 安装 ·············································61
3.5.2 CUDA 的 Torch 7 安装 ··················································61
3.6 Torch 框架下 neural-style 图像合成问题······························62
3.7 小结 ·························································································74
第 4 章 人脸识别 ················································································· 75
4.1 人脸识别概述 ·········································································75
4.2 人脸识别系统设计 ·································································76
4.2.1 需求分析········································································76
4.2.2 功能设计········································································77
4.2.3 模块设计········································································78
4.3 系统生产环境部署及验证 ·····················································81
4.3.1 抽帧环境部署································································81
4.3.2 抽帧功能验证································································82
4.3.3 OpenFace 环境部署·······················································82
4.3.4 OpenFace 环境验证·······················································84
4.4 批量生产 ·················································································90
4.5 小结 ·······················································································102
第 5 章 车辆识别 ···············································································103
5.1 概述 ·······················································································103
5.2 系统设计 ···············································································104
5.2.1 需求分析······································································104
5.2.2 功能设计······································································104
5.2.3 模块设计······································································105
5.3 系统生产环境部署及验证 ···················································106
5.3.1 生产环境部署······························································106
5.3.2 项目部署······································································107
5.3.3 环境验证······································································108
5.4 批量生产 ···············································································109
5.5 小结 ·······················································································117
第 6 章 不良视频识别 ······································································· 119
6.1 概述 ·······················································································119
6.2 不良图片模型简介 ·······························································120
6.3 系统设计 ···············································································122
6.4 系统部署及系统测试验证 ···················································123
6.5 批量生产 ···············································································125
6.5.1 批量节目元数据信息检索与筛选······························125
6.5.2 基于 FFmpeg 的 SDK 抽取视频 I 帧 ··························126
6.5.3 基于肤色比例检测的快速筛查··································128
6.5.4 基于 Caffe 框架的不良图片检测································128
6.6 小结 ·······················································································129
第 7 章 集群部署与运营维护 ··························································· 131
7.1 认识 Docker···········································································131
7.2 基于 Docker 的 TensorFlow 实验环境··································134
7.3 运营维护 ···············································································137
7.4 小结 ·······················································································138
参考文献································································································139
· · · · · · (收起)
1.1 深度学习的发展 ·······································································1
1.2 深度学习的应用及研究方向 ···················································3
1.3 深度学习工具介绍和对比 ·······················································4
1.3.1 Caffe·················································································4
1.3.2 TensorFlow ······································································5
1.3.3 Torch ················································································6
1.4 小结 ···························································································7
第 2 章 深度学习基本理论 ····································································9
2.1 深度学习的基本概念 ·······························································9
2.2 深度学习的训练过程 ·····························································13
2.3 深度学习的常用模型和方法 ·················································14
2.4 小结 ·························································································20
第 3 章 深度学习环境搭建 ································································· 23
3.1 Caffe 安装 ···············································································23
3.1.1 安装 Caffe 的相关依赖项·············································24
3.1.2 安装 NVIDIA 驱动 ·······················································24
3.1.3 安装 CUDA ···································································27
3.1.4 配置 cuDNN ··································································30
3.1.5 源代码编译安装 OpenCV ············································32
3.1.6 编译 Caffe，并配置 Python 接口 ································34
3.2 Caffe 框架下的 MNIST 数字识别问题···································41
3.3 TensorFlow 安装 ······································································42
3.3.1 基于 pip 安装·································································42
3.3.2 基于 Anaconda 安装 ······················································46
3.3.3 基于源代码安装····························································51
3.3.4 常见安装问题································································56
3.4 TensorFlow 框架下的 CIFAR 图像识别问题·························59
3.5 Torch 安装 ···············································································61
3.5.1 无 CUDA 的 Torch 7 安装 ·············································61
3.5.2 CUDA 的 Torch 7 安装 ··················································61
3.6 Torch 框架下 neural-style 图像合成问题······························62
3.7 小结 ·························································································74
第 4 章 人脸识别 ················································································· 75
4.1 人脸识别概述 ·········································································75
4.2 人脸识别系统设计 ·································································76
4.2.1 需求分析········································································76
4.2.2 功能设计········································································77
4.2.3 模块设计········································································78
4.3 系统生产环境部署及验证 ·····················································81
4.3.1 抽帧环境部署································································81
4.3.2 抽帧功能验证································································82
4.3.3 OpenFace 环境部署·······················································82
4.3.4 OpenFace 环境验证·······················································84
4.4 批量生产 ·················································································90
4.5 小结 ·······················································································102
第 5 章 车辆识别 ···············································································103
5.1 概述 ·······················································································103
5.2 系统设计 ···············································································104
5.2.1 需求分析······································································104
5.2.2 功能设计······································································104
5.2.3 模块设计······································································105
5.3 系统生产环境部署及验证 ···················································106
5.3.1 生产环境部署······························································106
5.3.2 项目部署······································································107
5.3.3 环境验证······································································108
5.4 批量生产 ···············································································109
5.5 小结 ·······················································································117
第 6 章 不良视频识别 ······································································· 119
6.1 概述 ·······················································································119
6.2 不良图片模型简介 ·······························································120
6.3 系统设计 ···············································································122
6.4 系统部署及系统测试验证 ···················································123
6.5 批量生产 ···············································································125
6.5.1 批量节目元数据信息检索与筛选······························125
6.5.2 基于 FFmpeg 的 SDK 抽取视频 I 帧 ··························126
6.5.3 基于肤色比例检测的快速筛查··································128
6.5.4 基于 Caffe 框架的不良图片检测································128
6.6 小结 ·······················································································129
第 7 章 集群部署与运营维护 ··························································· 131
7.1 认识 Docker···········································································131
7.2 基于 Docker 的 TensorFlow 实验环境··································134
7.3 运营维护 ···············································································137
7.4 小结 ·······················································································138
参考文献································································································139
· · · · · · (收起)
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