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钟尚武
dlib
Commits
eacfe67b
Commit
eacfe67b
authored
Oct 28, 2015
by
Davis King
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index.xml
docs/docs/index.xml
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docs/docs/intro.xml
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docs/docs/index.xml
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eacfe67b
...
@@ -9,16 +9,16 @@
...
@@ -9,16 +9,16 @@
<p>
<p>
Dlib is a
general purpose cross-platform C++ library designed using contract programming
Dlib is a
modern C++ toolkit containing machine learning algorithms and tools
and modern C++ techniques.
for creating complex software in C++ to solve real world problems.
It is open source software and licensed
It is open source software and licensed
under the
<a
href=
"license.html"
>
Boost Software License
</a>
.
under the
<a
href=
"license.html"
>
Boost Software License
</a>
.
The
<a
href=
"intro.html"
>
introduction
</a>
contains everything you need to know to get
The
<a
href=
"intro.html"
>
introduction
</a>
contains everything you need to know to get
started using the library. However, if
you have any questions, comments, or complaints feel free to
started using the library. However, if
after consulting the documentation, you have any questions, comments,
<a
href=
'mailto:davis@dlib.net'
>
email me
</a><web>
or post in the
or complaints feel free to post in the
sourceforge
<a
href=
'http://sourceforge.net/p/dclib/discussion'
>
Forums
</a></web
>
.
<a
href=
'http://sourceforge.net/p/dclib/discussion'
>
forums
</a
>
.
</p>
</p>
...
@@ -63,41 +63,37 @@
...
@@ -63,41 +63,37 @@
abstraction layers or is pure ISO standard C++.
</li>
abstraction layers or is pure ISO standard C++.
</li>
</ul>
</ul>
</li>
</li>
<li><b>
Threading
</b>
<li><b>
Machine Learning Algorithms
</b>
<ul>
<li>
The library provides a portable and simple
<a
href=
"api.html#threads"
>
threading API
</a></li>
<li>
A message passing
<a
href=
"other.html#pipe"
>
pipe
</a>
for inter-thread and
<a
href=
"network.html#bridge"
>
inter-process
</a>
communication
</li>
<li>
A
<a
href=
"other.html#timer"
>
timer
</a>
object capable of generating events that are regularly spaced in time
</li>
<li><a
href=
"api.html#threaded_object"
>
Threaded objects
</a></li>
<li><a
href=
"api.html#thread_function"
>
Threaded functions
</a></li>
<li><a
href=
"api.html#parallel_for"
>
Parallel for loops
</a></li>
<li>
A
<a
href=
"api.html#thread_pool"
>
thread_pool
</a>
with support for futures
</li>
</ul>
</li>
<li><b>
Networking
</b>
<ul>
<li>
The library provides a portable and simple
<a
href=
"api.html#sockets"
>
TCP sockets API
</a></li>
<li>
An object to help you make TCP based
<a
href=
"network.html#server"
>
servers
</a></li>
<li><a
href=
"network.html#iosockstream"
>
iostream
</a>
and
<a
href=
"network.html#sockstreambuf"
>
streambuf
</a>
objects that enables TCP sockets to interoperate with the C++ iostreams library
</li>
<li>
A simple
<a
href=
"network.html#server_http"
>
HTTP server
</a>
object you can use to embed a
web server into your applications
</li>
<li>
A message passing
<a
href=
"other.html#pipe"
>
pipe
</a>
for inter-thread and
<a
href=
"network.html#bridge"
>
inter-process
</a>
communication
</li>
<li>
A tool used to implement algorithms using the
<a
href=
"network.html#bsp_context"
>
Bulk Synchronous Parallel (BSP)
</a>
computing model
</li>
</ul>
</li>
<li><b>
Graphical User Interfaces
</b>
<ul>
<ul>
<li>
The library provides a portable and simple core
<a
href=
"api.html#gui_core"
>
GUI API
</a></li>
<li>
Conventional SMO based Support Vector Machines for
<a
href=
"ml.html#svm_nu_trainer"
>
classification
</a>
<li>
Implemented on top of the core GUI API are numerous
<a
href=
"api.html#gui_widgets"
>
widgets
</a></li>
and
<a
href=
"ml.html#svr_trainer"
>
regression
</a>
</li>
<li>
Unlike many other GUI toolkits, the entire dlib GUI toolkit is threadsafe
</li>
<li>
Reduced-rank methods for large-scale
<a
href=
"ml.html#svm_c_ekm_trainer"
>
classification
</a>
and
<a
href=
"ml.html#krr_trainer"
>
regression
</a></li>
<li>
Relevance vector machines for
<a
href=
"ml.html#rvm_trainer"
>
classification
</a>
and
<a
href=
"ml.html#rvm_regression_trainer"
>
regression
</a>
</li>
<li>
General purpose
<a
href=
"ml.html#one_vs_one_trainer"
>
multiclass classification
</a>
tools
</li>
<li>
A
<a
href=
"ml.html#svm_multiclass_linear_trainer"
>
Multiclass SVM
</a></li>
<li>
A tool for solving the optimization problem associated with
<a
href=
"ml.html#structural_svm_problem"
>
structural support vector machines
</a>
.
</li>
<li>
Structural SVM tools for
<a
href=
"ml.html#structural_sequence_labeling_trainer"
>
sequence labeling
</a>
</li>
<li>
Structural SVM tools for solving
<a
href=
"ml.html#structural_assignment_trainer"
>
assignment problems
</a>
</li>
<li>
Structural SVM tools for
<a
href=
"ml.html#structural_object_detection_trainer"
>
object detection
</a>
in images
</li>
<li>
Structural SVM tools for
<a
href=
"ml.html#structural_graph_labeling_trainer"
>
labeling nodes
</a>
in graphs
</li>
<li>
A large-scale
<a
href=
"ml.html#svm_rank_trainer"
>
SVM-Rank
</a>
implementation
</li>
<li>
An online
<a
href=
"ml.html#krls"
>
kernel RLS regression
</a>
algorithm
</li>
<li>
An online
<a
href=
"ml.html#svm_pegasos"
>
SVM classification
</a>
algorithm
</li>
<li><a
href=
"ml.html#vector_normalizer_frobmetric"
>
Semidefinite Metric Learning
</a></li>
<li>
An online kernelized
<a
href=
"ml.html#kcentroid"
>
centroid estimator
</a>
/novelty detector and
offline support vector
<a
href=
"ml.html#svm_one_class_trainer"
>
one-class classification
</a></li>
<li>
Clustering algorithms:
<a
href=
"ml.html#find_clusters_using_kmeans"
>
linear
</a>
or
<a
href=
"ml.html#kkmeans"
>
kernel k-means
</a>
,
<a
href=
"ml.html#chinese_whispers"
>
Chinese Whispers
</a>
, and
<a
href=
"ml.html#newman_cluster"
>
Newman clustering
</a>
.
</li>
<li><a
href=
"ml.html#rbf_network_trainer"
>
Radial Basis Function Networks
</a></li>
<li><a
href=
"ml.html#mlp"
>
Multi layer perceptrons
</a>
</li>
</ul>
</ul>
</li>
</li>
<li><b>
Numerical Algorithms
</b>
<li><b>
Numerical Algorithms
</b>
<ul>
<ul>
<li>
A fast
<a
href=
"linear_algebra.html#matrix"
>
matrix
</a>
object implemented using the expression
<li>
A fast
<a
href=
"linear_algebra.html#matrix"
>
matrix
</a>
object implemented using the expression
...
@@ -129,37 +125,6 @@
...
@@ -129,37 +125,6 @@
</ul>
</ul>
</li>
</li>
<li><b>
Machine Learning Algorithms
</b>
<ul>
<li>
Conventional SMO based Support Vector Machines for
<a
href=
"ml.html#svm_nu_trainer"
>
classification
</a>
and
<a
href=
"ml.html#svr_trainer"
>
regression
</a>
</li>
<li>
Reduced-rank methods for large-scale
<a
href=
"ml.html#svm_c_ekm_trainer"
>
classification
</a>
and
<a
href=
"ml.html#krr_trainer"
>
regression
</a></li>
<li>
Relevance vector machines for
<a
href=
"ml.html#rvm_trainer"
>
classification
</a>
and
<a
href=
"ml.html#rvm_regression_trainer"
>
regression
</a>
</li>
<li>
General purpose
<a
href=
"ml.html#one_vs_one_trainer"
>
multiclass classification
</a>
tools
</li>
<li>
A
<a
href=
"ml.html#svm_multiclass_linear_trainer"
>
Multiclass SVM
</a></li>
<li>
A tool for solving the optimization problem associated with
<a
href=
"ml.html#structural_svm_problem"
>
structural support vector machines
</a>
.
</li>
<li>
Structural SVM tools for
<a
href=
"ml.html#structural_sequence_labeling_trainer"
>
sequence labeling
</a>
</li>
<li>
Structural SVM tools for solving
<a
href=
"ml.html#structural_assignment_trainer"
>
assignment problems
</a>
</li>
<li>
Structural SVM tools for
<a
href=
"ml.html#structural_object_detection_trainer"
>
object detection
</a>
in images
</li>
<li>
Structural SVM tools for
<a
href=
"ml.html#structural_graph_labeling_trainer"
>
labeling nodes
</a>
in graphs
</li>
<li>
A large-scale
<a
href=
"ml.html#svm_rank_trainer"
>
SVM-Rank
</a>
implementation
</li>
<li>
An online
<a
href=
"ml.html#krls"
>
kernel RLS regression
</a>
algorithm
</li>
<li>
An online
<a
href=
"ml.html#svm_pegasos"
>
SVM classification
</a>
algorithm
</li>
<li><a
href=
"ml.html#vector_normalizer_frobmetric"
>
Semidefinite Metric Learning
</a></li>
<li>
An online kernelized
<a
href=
"ml.html#kcentroid"
>
centroid estimator
</a>
/novelty detector and
offline support vector
<a
href=
"ml.html#svm_one_class_trainer"
>
one-class classification
</a></li>
<li>
Clustering algorithms:
<a
href=
"ml.html#find_clusters_using_kmeans"
>
linear
</a>
or
<a
href=
"ml.html#kkmeans"
>
kernel k-means
</a>
,
<a
href=
"ml.html#chinese_whispers"
>
Chinese Whispers
</a>
, and
<a
href=
"ml.html#newman_cluster"
>
Newman clustering
</a>
.
</li>
<li><a
href=
"ml.html#rbf_network_trainer"
>
Radial Basis Function Networks
</a></li>
<li><a
href=
"ml.html#mlp"
>
Multi layer perceptrons
</a>
</li>
</ul>
</li>
<li><b>
Graphical Model Inference Algorithms
</b>
<li><b>
Graphical Model Inference Algorithms
</b>
<ul>
<ul>
<li><a
href=
"bayes.html#bayesian_network_join_tree"
>
Join tree
</a>
algorithm for exact inference in
<li><a
href=
"bayes.html#bayesian_network_join_tree"
>
Join tree
</a>
algorithm for exact inference in
...
@@ -188,6 +153,41 @@
...
@@ -188,6 +153,41 @@
</ul>
</ul>
</li>
</li>
<li><b>
Threading
</b>
<ul>
<li>
The library provides a portable and simple
<a
href=
"api.html#threads"
>
threading API
</a></li>
<li>
A message passing
<a
href=
"other.html#pipe"
>
pipe
</a>
for inter-thread and
<a
href=
"network.html#bridge"
>
inter-process
</a>
communication
</li>
<li>
A
<a
href=
"other.html#timer"
>
timer
</a>
object capable of generating events that are regularly spaced in time
</li>
<li><a
href=
"api.html#threaded_object"
>
Threaded objects
</a></li>
<li><a
href=
"api.html#thread_function"
>
Threaded functions
</a></li>
<li><a
href=
"api.html#parallel_for"
>
Parallel for loops
</a></li>
<li>
A
<a
href=
"api.html#thread_pool"
>
thread_pool
</a>
with support for futures
</li>
</ul>
</li>
<li><b>
Networking
</b>
<ul>
<li>
The library provides a portable and simple
<a
href=
"api.html#sockets"
>
TCP sockets API
</a></li>
<li>
An object to help you make TCP based
<a
href=
"network.html#server"
>
servers
</a></li>
<li><a
href=
"network.html#iosockstream"
>
iostream
</a>
and
<a
href=
"network.html#sockstreambuf"
>
streambuf
</a>
objects that enables TCP sockets to interoperate with the C++ iostreams library
</li>
<li>
A simple
<a
href=
"network.html#server_http"
>
HTTP server
</a>
object you can use to embed a
web server into your applications
</li>
<li>
A message passing
<a
href=
"other.html#pipe"
>
pipe
</a>
for inter-thread and
<a
href=
"network.html#bridge"
>
inter-process
</a>
communication
</li>
<li>
A tool used to implement algorithms using the
<a
href=
"network.html#bsp_context"
>
Bulk Synchronous Parallel (BSP)
</a>
computing model
</li>
</ul>
</li>
<li><b>
Graphical User Interfaces
</b>
<ul>
<li>
The library provides a portable and simple core
<a
href=
"api.html#gui_core"
>
GUI API
</a></li>
<li>
Implemented on top of the core GUI API are numerous
<a
href=
"api.html#gui_widgets"
>
widgets
</a></li>
<li>
Unlike many other GUI toolkits, the entire dlib GUI toolkit is threadsafe
</li>
</ul>
</li>
<li><b>
Data Compression and Integrity Algorithms
</b>
<li><b>
Data Compression and Integrity Algorithms
</b>
<ul>
<ul>
<li>
A
<a
href=
"algorithms.html#crc32"
>
CRC 32
</a>
object
</li>
<li>
A
<a
href=
"algorithms.html#crc32"
>
CRC 32
</a>
object
</li>
...
...
docs/docs/intro.xml
View file @
eacfe67b
...
@@ -31,13 +31,16 @@
...
@@ -31,13 +31,16 @@
software components, each accompanied by extensive documentation and thorough debugging modes.
software components, each accompanied by extensive documentation and thorough debugging modes.
</p>
</p>
<p>
<p>
Since development began in 2002, dlib has grown to include a wide
<a
href=
'mailto:davis@dlib.net'
>
Davis King
</a>
has been the primary
variety of tools. In particular, it now contains software components
author of dlib since development began in 2002. In that time
for dealing with networking, threads, graphical interfaces, complex
dlib has grown to include a wide variety of tools. In particular,
data structures, linear algebra, statistical machine learning, image
it now contains software components for dealing with networking,
processing, data mining, XML and text parsing, numerical
threads, graphical interfaces, complex data structures, linear
optimization, Bayesian networks, and numerous other tasks. In
algebra, statistical machine learning, image processing, data
mining, XML and text parsing, numerical optimization, Bayesian
networks, and numerous other tasks. In
recent years, much of the development has been focused on creating
recent years, much of the development has been focused on creating
a broad set of statistical machine learning tools. However, dlib
a broad set of statistical machine learning tools. However, dlib
remains a general purpose library and
<a
href=
"howto_contribute.html"
>
welcomes contributions
</a>
of high
remains a general purpose library and
<a
href=
"howto_contribute.html"
>
welcomes contributions
</a>
of high
...
@@ -45,7 +48,7 @@
...
@@ -45,7 +48,7 @@
</p>
</p>
<p>
<p>
Part of
the development philosophy of dlib is a dedication to
Core to
the development philosophy of dlib is a dedication to
portability and ease of use. Therefore, all code in dlib is designed
portability and ease of use. Therefore, all code in dlib is designed
to be as portable as possible and similarly to not require a user to
to be as portable as possible and similarly to not require a user to
configure or install anything. To help achieve this, all platform
configure or install anything. To help achieve this, all platform
...
...
docs/docs/main_menu.xml
View file @
eacfe67b
...
@@ -91,6 +91,7 @@
...
@@ -91,6 +91,7 @@
<name>
Home
</name>
<name>
Home
</name>
<link>
http://dlib.net
</link>
<link>
http://dlib.net
</link>
</item>
</item>
</web>
<item>
<item>
<name>
Dlib Blog
</name>
<name>
Dlib Blog
</name>
<link>
http://blog.dlib.net
</link>
<link>
http://blog.dlib.net
</link>
...
@@ -103,7 +104,6 @@
...
@@ -103,7 +104,6 @@
<name>
Who uses dlib?
</name>
<name>
Who uses dlib?
</name>
<link>
http://sourceforge.net/p/dclib/wiki/Known_users/
</link>
<link>
http://sourceforge.net/p/dclib/wiki/Known_users/
</link>
</item>
</item>
</web>
<item>
<item>
<name>
Introduction
</name>
<name>
Introduction
</name>
...
...
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