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深度学习训练营 - 21天实战

书名: 深度学习训练营 - 21天实战

基于Tensorflow + Keras + Scikit-learn框架编写而来的21个实战项目

Github地址:https://github.com/21-projects-for-deep-learning/MyBook

京东图书:深度学习训练营

本书所有的代码集合 (大约27MB)

链接: https://pan.baidu.com/s/1C6waPKRlRfQ_Dj8MDatdEg 提取码: eu3k

如果百度网盘不能下载,可以直接下载本项目,其中Python Code.zip就是所有的源代码

宋体的字体下载

链接:https://pan.baidu.com/s/1TThtFKeeGX6VjquwABQWOw 密码:y6u7



书中数据集和相关链接

1.1

数据集链接:https://www.cs.toronto.edu/~delve/data/boston/bostonDetail.html

6.3.4

plot()方法中的marker参数表示绘制的线的样式,全部的样式可以在以下链接查看:https://matplotlib.org/api/markers_api.html

8.1

平行语料库的数据集下载地址有以下两个

9.1

MNIST数据集下载:http://yann.lecun.com/exdb/mnist/

10.1

狗狗数据集:http://vision.stanford.edu/aditya86/ImageNetDogs/images.tar

10.4.1

下载狗狗的数据集

dataset_path = tf.keras.utils.get_file("Images", 
                  "http://vision.stanford.edu/aditya86/ImageNetDogs/images.tar", 
                  untar=True)

11.1

人脸数据集:http://vis-www.cs.umass.edu/lfw/lfw.tgz

# -O参数表示远程文件名,这里就是一个下载地址
$curl -O http://vis-www.cs.umass.edu/lfw/lfw.tgz

11.1.3

人脸检测模型,下载地址是:https://github.com/opencv/opencv/tree/master/data/haarcascades

11.2.1

下载代码仓库

git clone https://github.com/21-projects-for-deep-learning/facenet

预训练模型地址:https://pan.baidu.com/s/1mWyoy3AmwRaIuco6XlxWpQ

11.4.1

方式2安装,手动安装,所以要下载dlib的git仓库。

git clone https://github.com/davisking/dlib.git

13.1.2

下该TensorFlow的实现版本的代码库,代码如下:

git clone https://github.com/21-projects-for-deep-learning/tf-pose-estimation.git

13.2.2

Keras的多人姿态实时评估

git clone https://github.com/21-projects-for-deep-learning/keras_Realtime_Multi-Person_Pose_Estimation.git

14.1

病理图像数据集下载地址

https://challenge.kitware.com/#challenges

14.3.1

TensorFlow迁移学习实现分类

git clone https://github.com/21-projects-for-deep-learning/Simple_Transfer_Learning.git

15.3.1

1.下载tensorflow/models

git clone https://github.com/tensorflow/models.git

2.protoc下载地址:https://github.com/google/protobuf/releases。

16.1.2

本章所需要的代码库都在image2text的项目里,通过git clone可以将其克隆下来,代码如下:

git clone https://github.com/21-projects-for-deep-learning/image2text.git

image2text库的代码是从Google的models项目中迁移出来的,然后进行了一些本章讲解时的相应调整。 数据集是完整的取自val2017,然后拆分它为训练集和验证集。通过curl -O命令加上文件地址,就可以下载,命令如下:

curl -O http://images.cocodataset.org/zips/val2017.zip

解压val2017.zip文件通过unzip命令,如下:

unzip val2017.zip

下载标注文件(Annotations)也通过curl -O加上文件地址,命令如下:

curl -O http://images.cocodataset.org/annotations/annotations_trainval2017.zip

16.2.4

下载预训练模型Inception v3

curl -O http://download.tensorflow.org/models/inception_v3_2016_08_28.tar.gz

19.1.2

MNIST图像数据集下载 http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz

19.2.1

LFW(Labeled Faces in the Wild)官方网站上下载数据集 http://vis-www.cs.umass.edu/lfw/lfw.tgz

20.1.1

效果预览地址:http://waifu2x.udp.jp/

LFW数据集下载页面 http://vis-www.cs.umass.edu/lfw/

SRGAN预览效果页面地址 https://bigjpg.com/ https://waifu2x.me/

21.1.3

图片数据集 https://people.eecs.berkeley.edu/~taesung_park/CycleGAN/datasets/

21.4.1

下载dlib包:http://dlib.net/files/dlib-19.16.tar.bz2

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