Skip to content

Commit

Permalink
update images (PaddlePaddle/book#946)
Browse files Browse the repository at this point in the history
  • Loading branch information
@TCChenlong @wadefelix
TCChenlong authored and wadefelix committed Jul 30, 2021
1 parent a788823 commit bff6db6
Show file tree
Hide file tree
Showing 5 changed files with 32 additions and 82 deletions.
114 changes: 32 additions & 82 deletions paddle2.0_docs/dcgan_face/dcgan_face.ipynb
View file
Original file line number Diff line number Diff line change
Expand Up @@ -2,9 +2,7 @@
"cells": [
{
"cell_type": "markdown",
"metadata": {
"collapsed": false
},
"metadata": {},
"source": [
"# 通过DCGAN实现人脸图像生成\n",
"\n",
Expand All @@ -16,9 +14,7 @@
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": false
},
"metadata": {},
"source": [
"## 1 简介\n",
"本项目基于paddlepaddle，结合生成对抗网络（DCGAN）,通过弱监督学习的方式，训练生成真实人脸照片\n",
Expand Down Expand Up @@ -57,9 +53,7 @@
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": false
},
"metadata": {},
"source": [
"## 2 环境设置及数据集\n",
"\n",
Expand All @@ -80,9 +74,7 @@
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": false
},
"metadata": {},
"source": [
"### 2.1 数据集预处理\n",
"多线程处理，以裁切坐标(0,10)和(64,74)，将输入网络的图片裁切到64*64。"
Expand All @@ -91,9 +83,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [],
"source": [
"from PIL import Image\n",
Expand Down Expand Up @@ -189,9 +179,7 @@
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": false
},
"metadata": {},
"source": [
"## 3 模型组网\n",
"### 3.1 定义数据预处理工具-Paddle.io.Dataset\n",
Expand All @@ -201,9 +189,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [],
"source": [
"import os\n",
Expand Down Expand Up @@ -261,19 +247,15 @@
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": false
},
"metadata": {},
"source": [
"### 3.2 测试Paddle.io.DataLoader并输出图片"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [],
"source": [
"\n",
Expand Down Expand Up @@ -311,9 +293,7 @@
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": false
},
"metadata": {},
"source": [
"### 3.3 权重初始化\n",
"在 DCGAN 论文中，作者指定所有模型权重应从均值为0、标准差为0.02的正态分布中随机初始化。 \n",
Expand All @@ -323,9 +303,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [],
"source": [
"conv_initializer=paddle.nn.initializer.Normal(mean=0.0, std=0.02)\n",
Expand All @@ -334,9 +312,7 @@
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": false
},
"metadata": {},
"source": [
"### 3.4 判别器\n",
"如上文所述，生成器$D$是一个二进制分类网络，它以图像作为输入，输出图像是真实的（相对应$G$生成的假样本）的概率。输入$Shape$为[3,64,64]的RGB图像，通过一系列的$Conv2d$，$BatchNorm2d$和$LeakyReLU$层对其进行处理，然后通过全连接层输出的神经元个数为2，对应两个标签的预测概率。\n",
Expand All @@ -351,9 +327,7 @@
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [],
"source": [
"import paddle\n",
Expand Down Expand Up @@ -415,15 +389,13 @@
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": false
},
"metadata": {},
"source": [
"### 3.5 生成器\n",
"生成器$G$旨在映射潜在空间矢量$z$到数据空间。由于我们的数据是图像，因此转换$z$到数据空间意味着最终创建具有与训练图像相同大小[3,64,64]的RGB图像。在网络设计中，这是通过一系列二维卷积转置层来完成的，每个层都与$BatchNorm$层和$ReLu$激活函数。生成器的输出通过$tanh$函数输出，以使其返回到输入数据范围[−1,1]。值得注意的是，在卷积转置层之后存在$BatchNorm$函数，因为这是DCGAN论文的关键改进。这些层有助于训练过程中的梯度更好地流动。 \n",
"\n",
"**生成器网络结构** \n",
"![](https://ai-studio-static-online.cdn.bcebos.com/ca0434dd681849338b1c0c46285616f72add01ab894b4e95848daecd5a72e3cb)\n",
"![models](./images/models.png)\n",
"\n",
"* 将$BatchNorm$批归一化中$momentum$参数设置为0.5\n",
"\n",
Expand All @@ -434,9 +406,7 @@
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [],
"source": [
"\n",
Expand Down Expand Up @@ -501,9 +471,7 @@
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": false
},
"metadata": {},
"source": [
"### 3.6 损失函数\n",
"选用BCELoss,公式如下:\n",
Expand All @@ -515,9 +483,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [],
"source": [
"###损失函数\n",
Expand All @@ -526,9 +492,7 @@
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": false
},
"metadata": {},
"source": [
"## 4 模型训练\n",
" 设置的超参数为：\n",
Expand All @@ -545,9 +509,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [],
"source": [
"import IPython.display as display\n",
Expand Down Expand Up @@ -650,9 +612,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [],
"source": [
"plt.figure(figsize=(15, 6))\n",
Expand All @@ -668,26 +628,22 @@
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": false
},
"metadata": {},
"source": [
"## 5 模型评估\n",
"### 生成器$G$和判别器$D$的损失与迭代变化图\n",
"![](https://ai-studio-static-online.cdn.bcebos.com/0c8cff8bf3a540bcb601bd24012f67dda622b0391f1d412ea2372693b67b4541)\n",
"![loss](./images/loss.png)\n",
"\n",
"### 对比真实人脸图像（图一）和生成人脸图像（图二）\n",
"#### 图一\n",
"![](https://ai-studio-static-online.cdn.bcebos.com/622fff7b67a240ff8a1fceb209fc27445c929099365c44e8bd006569bf26e0a6)\n",
"![face_image1](./images/face_image1.jpeg)\n",
"### 图二\n",
"![](https://ai-studio-static-online.cdn.bcebos.com/ed33cf82762d4ae79feef82b77604273303cc38b8f5d4728a632b492f2665ed4)\n"
"![face_image2](./images/face_image2.jpeg)\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": false
},
"metadata": {},
"source": [
"## 6 模型预测\n",
"### 输入随机数让生成器$G$生成随机人脸\n",
Expand All @@ -697,9 +653,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [],
"source": [
"device = paddle.set_device('gpu')\n",
Expand All @@ -726,9 +680,7 @@
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": false
},
"metadata": {},
"source": [
"## 7 项目总结\n",
"简单介绍了一下DCGAN的原理，通过对原项目的改进和优化，一步一步依次对生成器和判别器以及训练过程进行介绍。\n",
Expand All @@ -737,9 +689,7 @@
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": false
},
"metadata": {},
"source": [
"## 8 参考文献\n",
"[1] Goodfellow, Ian J.; Pouget-Abadie, Jean; Mirza, Mehdi; Xu, Bing; Warde-Farley, David; Ozair, Sherjil; Courville, Aaron; Bengio, Yoshua. Generative Adversarial Networks. 2014. arXiv:1406.2661 [stat.ML].\n",
Expand All @@ -756,9 +706,9 @@
],
"metadata": {
"kernelspec": {
"display_name": "PaddlePaddle 2.0.0b0 (Python 3.5)",
"display_name": "Python 3",
"language": "python",
"name": "py35-paddle1.2.0"
"name": "python3"
},
"language_info": {
"codemirror_mode": {
Expand All @@ -770,7 +720,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.4"
"version": "3.8.2"
}
},
"nbformat": 4,
Expand Down
Binary file added paddle2.0_docs/dcgan_face/images/face_image1.jpeg
View file
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
Binary file added paddle2.0_docs/dcgan_face/images/face_image2.jpeg
View file
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
Binary file added paddle2.0_docs/dcgan_face/images/loss.png
View file
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
Binary file added paddle2.0_docs/dcgan_face/images/models.png
View file
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.

0 comments on commit bff6db6

Please sign in to comment.