mirror of https://github.com/davisking/dlib.git
Davis King
11 years ago
parent
f3dc3c0e9e
commit
43ce7908b9
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<?xml version="1.0" encoding="ISO-8859-1" ?>
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<xsl:stylesheet version="1.0" xmlns:xsl="http://www.w3.org/1999/XSL/Transform">
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<xsl:output method='html' version='1.0' encoding='UTF-8' indent='yes' />
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<!-- ************************************************************************* -->
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<xsl:variable name="max_images_displayed">30</xsl:variable>
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<!-- ************************************************************************* -->
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<xsl:template match="/dataset">
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<html>
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<head>
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<style type="text/css">
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div#box{
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position: absolute;
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border-style:solid;
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border-width:1px;
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border-color:red;
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}
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div#circle{
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position: absolute;
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border-style:solid;
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border-width:1px;
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border-color:red;
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border-radius:7px;
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width:14px;
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height: 14px;
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}
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div#label{
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position: absolute;
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color: red;
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}
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div#img{
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position: relative;
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margin-bottom:2em;
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}
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pre {
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color: black;
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margin: 1em 0.25in;
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padding: 0.5em;
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background: rgb(240,240,240);
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border-top: black dotted 1px;
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border-left: black dotted 1px;
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border-right: black solid 2px;
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border-bottom: black solid 2px;
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}
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</style>
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</head>
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<body>
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Dataset name: <b><xsl:value-of select='/dataset/name'/></b> <br/>
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Dataset comment: <pre><xsl:value-of select='/dataset/comment'/></pre> <br/>
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Number of images: <xsl:value-of select="count(images/image)"/> <br/>
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Number of boxes: <xsl:value-of select="count(images/image/box)"/> <br/>
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<br/>
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<hr/>
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<!-- Show a warning if we aren't going to show all the images -->
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<xsl:if test="count(images/image) > $max_images_displayed">
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<h2>Only displaying the first <xsl:value-of select="$max_images_displayed"/> images.</h2>
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<hr/>
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</xsl:if>
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<xsl:for-each select="images/image">
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<!-- Don't try to display too many images. It makes your browser hang -->
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<xsl:if test="position() <= $max_images_displayed">
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<b><xsl:value-of select="@file"/></b> (Number of boxes: <xsl:value-of select="count(box)"/>)
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<div id="img">
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<img src="{@file}"/>
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<xsl:for-each select="box">
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<div id="box" style="top: {@top}px; left: {@left}px; width: {@width}px; height: {@height}px;"></div>
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<!-- If there is a label then display it in the lower right corner. -->
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<xsl:if test="label">
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<div id="label" style="top: {@top+@height}px; left: {@left+@width}px;">
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<xsl:value-of select="label"/>
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</div>
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</xsl:if>
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<xsl:for-each select="part">
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<div id="label" style="top: {@y+7}px; left: {@x}px;">
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<xsl:value-of select="@name"/>
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</div>
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<div id="circle" style="top: {(@y)-7}px; left: {(@x)-7}px; "></div>
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</xsl:for-each>
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</xsl:for-each>
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</div>
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</xsl:if>
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</xsl:for-each>
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</body>
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</html>
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</xsl:template>
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<!-- ************************************************************************* -->
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</xsl:stylesheet>
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@ -0,0 +1,43 @@
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<?xml version='1.0' encoding='ISO-8859-1'?>
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<?xml-stylesheet type='text/xsl' href='image_metadata_stylesheet.xsl'?>
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<dataset>
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<name>imglab dataset</name>
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<comment>Created by imglab tool.</comment>
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<images>
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<image file='2008_002470.jpg'>
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<box top='181' left='274' width='52' height='53'/>
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<box top='156' left='55' width='44' height='44'/>
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<box top='166' left='146' width='37' height='37'/>
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<box top='55' left='329' width='44' height='44'/>
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<box top='74' left='233' width='44' height='44'/>
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<box top='86' left='178' width='37' height='37'/>
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</image>
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<image file='2008_002506.jpg'>
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<box top='78' left='329' width='109' height='109'/>
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<box top='95' left='224' width='91' height='91'/>
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<box top='65' left='125' width='90' height='91'/>
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</image>
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<image file='2008_004176.jpg'>
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<box top='230' left='206' width='37' height='37'/>
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<box top='118' left='162' width='37' height='37'/>
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<box top='82' left='190' width='37' height='37'/>
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<box top='78' left='326' width='37' height='37'/>
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<box top='98' left='222' width='37' height='37'/>
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<box top='86' left='110' width='37' height='37'/>
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<box top='102' left='282' width='37' height='37'/>
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</image>
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<image file='2008_007676.jpg'>
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<box top='62' left='226' width='37' height='37'/>
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<box top='113' left='194' width='44' height='44'/>
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<box top='130' left='262' width='37' height='37'/>
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<box top='134' left='366' width='37' height='37'/>
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<box top='122' left='314' width='37' height='37'/>
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<box top='141' left='107' width='52' height='53'/>
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<box top='84' left='137' width='44' height='44'/>
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</image>
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<image file='2009_004587.jpg'>
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<box top='46' left='154' width='75' height='76'/>
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<box top='280' left='266' width='63' height='63'/>
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</image>
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</images>
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</dataset>
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@ -0,0 +1,34 @@
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<?xml version='1.0' encoding='ISO-8859-1'?>
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<?xml-stylesheet type='text/xsl' href='image_metadata_stylesheet.xsl'?>
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<dataset>
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<name>imglab dataset</name>
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<comment>Created by imglab tool.</comment>
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<images>
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<image file='2007_007763.jpg'>
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<box top='90' left='194' width='37' height='37'/>
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<box top='114' left='158' width='37' height='37'/>
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<box top='89' left='381' width='45' height='44'/>
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<box top='198' left='94' width='37' height='37'/>
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<box top='214' left='178' width='37' height='37'/>
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<box top='86' left='294' width='37' height='37'/>
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<box top='233' left='309' width='45' height='44'/>
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</image>
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<image file='2008_002079.jpg'>
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<box top='166' left='406' width='37' height='37'/>
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<box top='134' left='122' width='37' height='37'/>
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<box top='138' left='346' width='37' height='37'/>
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<box top='175' left='439' width='44' height='44'/>
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<box top='134' left='62' width='37' height='37'/>
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<box top='194' left='41' width='44' height='44'/>
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</image>
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<image file='2008_001009.jpg'>
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<box top='79' left='145' width='76' height='76'/>
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<box top='214' left='125' width='90' height='91'/>
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</image>
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<image file='2008_001322.jpg'>
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<box top='162' left='104' width='76' height='76'/>
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<box top='218' left='232' width='63' height='63'/>
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<box top='155' left='344' width='90' height='90'/>
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</image>
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</images>
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</dataset>
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@ -0,0 +1,116 @@
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// The contents of this file are in the public domain. See LICENSE_FOR_EXAMPLE_PROGRAMS.txt
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/*
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This is an example illustrating the use of the dlib tools for
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detecting objects in images. In this example we will create
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three simple images, each containing some white squares. We
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will then use the sliding window classifier tools to learn to
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detect these squares.
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*/
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#include <dlib/time_this.h>
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#include <dlib/image_processing/frontal_face_detector.h>
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#include <dlib/svm_threaded.h>
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#include <dlib/gui_widgets.h>
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#include <dlib/array.h>
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#include <dlib/array2d.h>
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#include <dlib/image_keypoint.h>
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#include <dlib/image_processing.h>
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#include <dlib/data_io.h>
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#include <iostream>
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#include <fstream>
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using namespace std;
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using namespace dlib;
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// ----------------------------------------------------------------------------------------
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int main()
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{
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/*
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NOTES
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- explain the concepts of ignore boxes
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*/
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try
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{
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dlib::array<array2d<unsigned char> > images, images_test;
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std::vector<std::vector<rectangle> > object_locations, object_locations_test;
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load_image_dataset(images, object_locations, "../faces/training.xml");
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upsample_image_dataset<pyramid_down<2> >(images, object_locations);
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load_image_dataset(images_test, object_locations_test, "../faces/testing.xml");
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upsample_image_dataset<pyramid_down<2> >(images_test, object_locations_test);
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add_image_left_right_flips(images, object_locations);
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cout << "num training images: " << images.size() << endl;
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cout << "num testing images: " << images_test.size() << endl;
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typedef scan_fhog_pyramid<pyramid_down<6> > image_scanner_type;
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image_scanner_type scanner;
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scanner.set_detection_window_size(80, 80); // faces
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//scanner.set_nuclear_norm_regularization_strength(1.0);
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structural_object_detection_trainer<image_scanner_type> trainer(scanner);
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trainer.set_num_threads(6); // Set this to the number of processing cores on your machine.
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trainer.set_c(1);
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//trainer.set_c(10);
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trainer.be_verbose();
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trainer.set_epsilon(0.01);
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// TODO, talk about this option
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//remove_unobtainable_rectangles(trainer, images, object_locations);
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object_detector<image_scanner_type> detector = trainer.train(images, object_locations);
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cout << "num filters 0.0: "<< num_separable_filters(detector) << endl;
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cout << "training results 0.0: " << test_object_detection_function(detector, images, object_locations) << endl;
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cout << "testing results 0.0: " << test_object_detection_function(detector, images_test, object_locations_test) << endl;
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detector = threshold_filter_singular_values(detector,0.01);
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cout << "num filters 0.01: "<< num_separable_filters(detector) << endl;
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cout << "testing results 0.01: " << test_object_detection_function(detector, images_test, object_locations_test) << endl;
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detector = threshold_filter_singular_values(detector,0.1);
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cout << "num filters 0.1: "<< num_separable_filters(detector) << endl;
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cout << "testing results 0.1: " << test_object_detection_function(detector, images_test, object_locations_test) << endl;
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image_window win, hogwin(draw_fhog(detector));
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for (unsigned long i = 0; i < images_test.size(); ++i)
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{
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std::vector<rectangle> dets;
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TIME_THIS(
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dets = detector(images_test[i]);
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);
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win.clear_overlay();
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win.set_image(images_test[i]);
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win.add_overlay(dets, rgb_pixel(255,0,0));
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cin.get();
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}
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ofstream fout("face_detector.svm", ios::binary);
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serialize(detector, fout);
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}
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catch (exception& e)
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{
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cout << "\nexception thrown!" << endl;
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cout << e.what() << endl;
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}
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}
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// ----------------------------------------------------------------------------------------
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