merged

.hgtags

@@ -27,3 +27,4 @@ cae7fcc9e6a9b28b44a703e4598f44286fec734d v18.14
 feaff82884ded598bde93c635eb3ded9c0933a07 v18.15
 42a25c606cf924a8d41d2fc96b9c85f839d21a04 v18.16
 ce6f364987865b19bdb1b4730ac5403e2bb55dc4 v18.17
+7ae1775f61a44b7f07866050b50ad3ade581f019 v18.18

README.txt

 
+                              dlib C++ library
 
-See http://dlib.net for the main project documentation.
+Dlib is a modern C++ toolkit containing machine learning algorithms and tools
+for creating complex software in C++ to solve real world problems.  See
+http://dlib.net for the main project documentation and API reference.
 
 
 
-COMPILING DLIB EXAMPLE PROGRAMS
+COMPILING DLIB C++ EXAMPLE PROGRAMS
    Go into the examples folder and type:
        mkdir build; cd build; cmake .. ; cmake --build .
-
-   That will build all the examples.  There is nothing to install when using
-   dlib.  It's just a folder of source files.  
+   That will build all the examples.  If you have a CPU that supports AVX
+   instructions then turn them on like this:
+       mkdir build; cd build; cmake .. -DUSE_AVX_INSTRUCTIONS=1; cmake --build .
+   Doing so will make some things run faster.
+
+COMPILING DLIB Python API
+   Before you can run the Python example programs you must compile dlib. Type:
+       python setup.py install
+   or type
+       python setup.py install --yes USE_AVX_INSTRUCTIONS
+   if you have a CPU that supports AVX instructions, since this makes some
+   things run faster.  
 
 RUNNING THE UNIT TEST SUITE
    Type the following to compile and run the dlib unit test suite:
@@ -24,9 +36,12 @@ RUNNING THE UNIT TEST SUITE
    subfolder called Release.  If that's the case then you have to go to that
    folder before running the test.
 
-DOCUMENTATION
-   The source control repository doesn't contain finished documentation.  The
-   stuff in the docs folder is just a bunch of scripts and xml files used to
-   generate the documentation.  There is a readme in docs/README.txt which
-   discusses how to do this.  However, unless you are trying to modify the
-   documentation, you should just download a copy from http://dlib.net.  
+This library is licensed under the Boost Software License, which can be found
+in dlib/LICENSE.txt.  The long and short of the license is that you can use
+dlib however you like, even in closed source commercial software.
+
+Dlib Sponsors:
+  This code development was funded by the Office of the Director of National
+  Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA),
+  via IARPA R&D Contract No. 2014-14071600010
+

dlib/CMakeLists.txt

@@ -13,8 +13,8 @@ include(use_cpp_11.cmake)
 
 
 set(CPACK_PACKAGE_VERSION_MAJOR "18")
-set(CPACK_PACKAGE_VERSION_MINOR "17")
-set(CPACK_PACKAGE_VERSION_PATCH "100")
+set(CPACK_PACKAGE_VERSION_MINOR "18")
+set(CPACK_PACKAGE_VERSION_PATCH "99")
 set(VERSION ${CPACK_PACKAGE_VERSION_MAJOR}.${CPACK_PACKAGE_VERSION_MINOR}.${CPACK_PACKAGE_VERSION_PATCH})
 
 set(CMAKE_LEGACY_CYGWIN_WIN32 0) # Remove when CMake >= 2.8.4 is required

dlib/README.txt

- 
-                              dlib C++ library
-
-This project is a modern C++ library with a focus on portability and program
-correctness. It strives to be easy to use right and hard to use wrong. Thus, it
-comes with extensive documentation and thorough debugging modes. The library
-provides a platform abstraction layer for common tasks such as interfacing with
-network services, handling threads, or creating graphical user interfaces.
-Additionally, the library implements many useful algorithms such as data
-compression routines, linked lists, binary search trees, linear algebra and
-matrix utilities, machine learning algorithms, XML and text parsing, and many
-other general utilities.
-
-Documentation:  
-  There should be HTML documentation accompanying this library.  But if there
-  isn't you can download it from http://dlib.net
-
-Installation:
-  To use this library all you have to do is extract the library somewhere, make
-  sure the folder *containing* the dlib folder is in your include path, and
-  finally add dlib/all/source.cpp to your project.
-
-  An example makefile that uses this library can be found here:
-  dlib/test/makefile. It is the makefile used to build the regression test suite
-  for this library. There is also a CMake makefile that builds the regression
-  test suite at dlib/test/CMakeLists.txt and another CMake makefile that builds
-  all the example programs in the examples folder.
-
-  For further information see the accompanying HTML documentation or visit
-  http://dlib.net
-
-The license for this library can be found in LICENSE.txt.  But the long and
-short of the license is that you can use this code however you like, even in
-closed source commercial software.
-
-Dlib Sponsors:
-  This code development was funded by the Office of the Director of National
-  Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA),
-  via IARPA R&D Contract No. 2014-14071600010
-

dlib/test/cca.cpp

@@ -18,6 +18,7 @@ namespace
     dlib::rand rnd;
 // ----------------------------------------------------------------------------------------
 
+    /*
     std::vector<std::map<unsigned long, double> > make_really_big_test_matrix (
     )
     {
@@ -29,6 +30,7 @@ namespace
         }
         return temp;
     }
+    */
 
     template <typename T>
     std::vector<std::map<unsigned long, T> > mat_to_sparse (
@@ -60,6 +62,7 @@ namespace
 
 // ----------------------------------------------------------------------------------------
 
+    /*
     void check_correlation (
         matrix<double> L,
         matrix<double> R,
@@ -82,6 +85,7 @@ namespace
             cout << "error: "<< A(i) - correlations(i);
         }
     }
+    */
 
 // ----------------------------------------------------------------------------------------
 

dlib/test/multithreaded_object.cpp

@@ -183,7 +183,7 @@ namespace
             DLIB_TEST(is_running() == false);
         }
 
-        ~test4_c2()
+        ~test4_c2() throw (std::exception)
         {
             DLIB_TEST(number_of_threads_registered() == 2);
             DLIB_TEST(number_of_threads_alive() == 2);

docs/.logger_revnum

-ce6f36498786
+0e51b2aaee97

docs/docs/index.xml

@@ -9,16 +9,16 @@
 
       <p>
 
-      Dlib is a general purpose cross-platform C++ library designed using contract programming
-      and modern C++ techniques.  
+      Dlib is a modern C++ toolkit containing machine learning algorithms and tools
+      for creating complex software in C++ to solve real world problems.
 
       It is open source software and licensed
       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
-      started using the library.  However, if you have any questions, comments, or complaints feel free to 
-      <a href='mailto:davis@dlib.net'>email me</a><web> or post in the 
-      sourceforge <a href='http://sourceforge.net/p/dclib/discussion'>Forums</a></web>.
+      started using the library.  However, if after consulting the documentation, you have any questions, comments,
+      or complaints feel free to post in the  
+      <a href='http://sourceforge.net/p/dclib/discussion'>forums</a>.
 
       
       </p>
@@ -63,41 +63,37 @@
                      abstraction layers or is pure ISO standard C++.  </li>
                </ul>
             </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>
+            <li><b>Machine Learning Algorithms</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>
+                  <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>Numerical Algorithms</b>
                <ul>
                   <li>A fast <a href="linear_algebra.html#matrix">matrix</a> object implemented using the expression 
@@ -129,37 +125,6 @@
                </ul>
             </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>
                <ul>
                   <li><a href="bayes.html#bayesian_network_join_tree">Join tree</a> algorithm for exact inference in 
@@ -188,6 +153,41 @@
                </ul>
             </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>
                <ul>
                   <li>A <a href="algorithms.html#crc32">CRC 32</a> object</li>  

docs/docs/intro.xml

@@ -31,13 +31,16 @@
             software components, each accompanied by extensive documentation and thorough debugging modes. 
          </p>
 
+      
         <p>
-           Since development began in 2002, dlib has grown to include a wide
-           variety of tools.  In particular, it now contains software components 
-           for dealing with networking, threads, graphical interfaces, complex
-           data structures, linear algebra, statistical machine learning, image
-           processing, data mining, XML and text parsing, numerical
-           optimization, Bayesian networks, and numerous other tasks.  In
+           <a href='mailto:davis@dlib.net'>Davis King</a> has been the primary
+           author of dlib since development began in 2002.  In that time
+           dlib has grown to include a wide variety of tools.  In particular,
+           it now contains software components for dealing with networking,
+           threads, graphical interfaces, complex data structures, linear
+           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 
            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
@@ -45,7 +48,7 @@
         </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
          to be as portable as possible and similarly to not require a user to
          configure or install anything.  To help achieve this, all platform

docs/docs/main_menu.xml

@@ -91,6 +91,7 @@
                <name>Home</name>
                <link>http://dlib.net</link>
             </item>
+         </web>
          <item>
             <name>Dlib Blog</name>
             <link>http://blog.dlib.net</link>
@@ -103,7 +104,6 @@
             <name>Who uses dlib?</name>
             <link>http://sourceforge.net/p/dclib/wiki/Known_users/</link>
          </item>
-         </web>
 
          <item>
             <name>Introduction</name>

docs/makedocs

@@ -142,7 +142,6 @@ makedocs ()
     hg archive docs/cache || report_failure
     # Don't need the docs folder in the cache, moreover, deleting it here avoids letting the makerel script include it in the dlib tar balls.
     rm -rf docs/cache/docs
-    rm docs/cache/README.txt
 
     echo "#ifndef DLIB_REVISION_H"           > docs/cache/dlib/revision.h
     echo "// Version: " $RELEASE            >> docs/cache/dlib/revision.h

docs/makerel

@@ -52,9 +52,9 @@ mkdir $RELDIR
 cd $RELDIR || report_failure
 cp -r ../../docs/cache/* . || report_failure
 
-echo Version: $RELEASE >> dlib/README.txt
-echo "Date:    `date`" >> dlib/README.txt
-echo Mercurial Revision ID: $CHANGESET_ID >> dlib/README.txt
+echo Version: $RELEASE >> README.txt
+echo "Date:    `date`" >> README.txt
+echo Mercurial Revision ID: $CHANGESET_ID >> README.txt
 
 
 

setup.py

@@ -556,7 +556,7 @@ setup(
     version=read_version(),
     keywords=['dlib', 'Computer Vision', 'Machine Learning'],
     description='A toolkit for making real world machine learning and data analysis applications',
-    long_description=readme('dlib/README.txt'),
+    long_description=readme('README.txt'),
     author='Davis King',
     author_email='davis@dlib.net',
     url='https://github.com/davisking/dlib',