OpenFace自建CNN模型
OpenFace自建CNN模型
1. OpenFace Home:
https://cmusatyalab.github.io/openface/
Setup: (This is not working for myenvironment. View on 2016/8/23)
https://cmusatyalab.github.io/openface/setup/
2. Environment(环境）：
Ubuntu16.04
Nvidia 940M
Cuda8.0
3. Required Liabrary(必须环境）：
Opencv2.4.11与cuda8.0具有一定的冲突性，可以安装opencv2.4.13，本机安装的是opencv3.10.
Opencv2.4.13官方安装（未测试）：
http://docs.opencv.org/2.4/doc/tutorials/introduction/linux_install/linux_install.html
[compiler] sudo apt-get installbuild-essential
[required] sudo apt-get install cmake gitlibgtk2.0-dev pkg-config libavcodec-dev libavformat-dev libswscale-dev
[optional] sudo apt-get install python-devpython-numpy libtbb2 libtbb-dev libjpeg-dev libpng-dev libtiff-devlibjasper-dev libdc1394-22-dev
cd ~/opencv
mkdir release
cd release
cmake -D CMAKE_BUILD_TYPE=RELEASE -DCMAKE_INSTALL_PREFIX=/usr/local ..
make
sudo make install
4. Dlib库以及torch的安装此处略过，查看之前的内容
5. Openface的安装：
安装比较简单：
sudo python2 setup.py install
sh models/get-models.sh
配置好就可以跑一些简单的demo了(相关web的demo都没跑，感觉有点麻烦，～～）：
跑demo运行
demo2:
./demos/compare.pyimages/examples/{lennon*,clapton*}
运行demo3：
./demos/classifier.py infermodels/openface/celeb-classifier.nn4.small2.v1.pkl ./images/examples/carell.jpg：
注意：官网的很多命令不带有前标，如python2，th等。
6. 训练DNN模型：
数据预处理：
for N in {1..8}; do ./util/align-dlib.pydata/casia-facescrub/raw align outerEyesAndNose data/casia-facescrub/dlib-affine-sz:96--size 96 & done
python2 ./util/prune-dataset.pydata/casia-facescrub/dlib-affine-sz:96 --numImagesThreshold 3
Train之前需要做的处理：
train.lua:
修正module和OpenFaceOptim模块：
local models = require 'model'
local openFaceOptim = require 'OpenFaceOptim'
改为
local models = require './model.lua'
local openFaceOptim = require'./OpenFaceOptim.lua'
由官网所知opt.lua为训练的参数，其中需要更改两个参数，减少对GPU的要求（容易out of memory)：
cmd:option('-peoplePerBatch', 15, 'Number of people to sample in eachmini-batch.')
cmd:option('-imagesPerPerson',20, 'Number of images to sample per person in each mini-batch.')
改为：
cmd:option('-peoplePerBatch', 1, 'Number of people to sample in eachmini-batch.')
cmd:option('-imagesPerPerson', 2, 'Number of images to sample per personin each mini-batch.')
test.lua:运行时发生错误找不到文件，直接改成绝对目录了：
local batchRepresent ="../batch-represent/main.lua"
local lfwEval ="../evaluation/lfw.py"
改为：
local batchRepresent = "～/openface/batch-represent/main.lua"
local lfwEval = "~/openface/evaluation/lfw.py"
找不到/data/lfw/aligned文件：
修改opt.lua:
cmd:option('-lfwDir','../data/lfw/aligned', 'LFW aligned image directory for testing.')
改为：
cmd:option('-lfwDir', '~/openface/data/lfw/aligned','LFW aligned image directory for testing.')
改过之后，开始训练和测试的时候，还是溢出了，再改：
cmd:option('-testBatchSize', 800,'Batch size for testing.')
改成
cmd:option('-testBatchSize', 80, 'Batch size for testing.')
「必须！」为了要testing，改变在opts.lua中的lfwDir
cmd:option('-lfwDir','/media/tsunyi/0EF057F8F057E50D/codeDemo/openface-master/data/lfw/dlib-affine-sz:96','LFW aligned image directory for testing.'
更改openface/batch-represent下面的batch-represent和opts以减少GPU
更改/openface/evaluation下的lfw.py，相关文件路径