文件名称:trainHOG-master
介绍说明－－下载内容均来自于网络，请自行研究使用
Read positive and negative training sample image files specified directories
Calculate their HOG features and keep track of their classes (pos, neg)
Save the feature map (vector of vectors/matrix) to file system
Read in and pass the features and their classes to a machine learning algorithm, e.g. SVMlight
Train the machine learning algorithm using the specified parameters
Use the calculated support vectors and SVM model to calculate a single detecting descr iptor vector
Dry-run the newly trained custom HOG descr iptor against training set and against camera images, if available-Read positive and negative training sample image files specified directories
Calculate their HOG features and keep track of their classes (pos, neg)
Save the feature map (vector of vectors/matrix) to file system
Read in and pass the features and their classes to a machine learning algorithm, e.g. SVMlight
Train the machine learning algorithm using the specified parameters
Use the calculated support vectors and SVM model to calculate a single detecting descr iptor vector
Dry-run the newly trained custom HOG descr iptor against training set and against camera images, if available
Calculate their HOG features and keep track of their classes (pos, neg)
Save the feature map (vector of vectors/matrix) to file system
Read in and pass the features and their classes to a machine learning algorithm, e.g. SVMlight
Train the machine learning algorithm using the specified parameters
Use the calculated support vectors and SVM model to calculate a single detecting descr iptor vector
Dry-run the newly trained custom HOG descr iptor against training set and against camera images, if available-Read positive and negative training sample image files specified directories
Calculate their HOG features and keep track of their classes (pos, neg)
Save the feature map (vector of vectors/matrix) to file system
Read in and pass the features and their classes to a machine learning algorithm, e.g. SVMlight
Train the machine learning algorithm using the specified parameters
Use the calculated support vectors and SVM model to calculate a single detecting descr iptor vector
Dry-run the newly trained custom HOG descr iptor against training set and against camera images, if available
(系统自动生成,下载前可以参看下载内容)
下载文件列表
trainHOG-master
...............\.gitignore
...............\ApacheLicense2.txt
...............\Makefile
...............\Readme.md
...............\genfiles
...............\........\.gitignore
...............\libsvm
...............\......\libsvm.h
...............\main.cpp
...............\nbproject
...............\.........\Makefile-Debug.mk
...............\.........\Makefile-Release.mk
...............\.........\Makefile-impl.mk
...............\.........\Makefile-variables.mk
...............\.........\Package-Debug.bash
...............\.........\Package-Release.bash
...............\.........\configurations.xml
...............\.........\private
...............\.........\.......\Makefile-variables.mk
...............\.........\.......\configurations.xml
...............\.........\project.xml
...............\neg
...............\...\.gitignore
...............\pos
...............\...\.gitignore
...............\sidefiles
...............\.........\IDEView.png
...............\.........\fileStructureSVMlight.png
...............\svmlight
...............\........\svmlight.h