completed - Building Your Own Custom Object Detector

Building Your Own Custom Object Detector/README.md

@@ -0,0 +1,13 @@
+# Building Your Own Custom Object Detector
+
+- template_matching
+- object_detection_made_easy
+- image-pyramids
+- sliding_windows
+- preparing_experiment
+- hog_feature_extraction
+- initial_training_phase
+- nms (non-maxima suppression)
+- hard_negative_mining
+- retraining_classifier
+- dlib_custom

Building Your Own Custom Object Detector/dlib_custom/face_detector/faces_annotations.xml

@@ -0,0 +1,198 @@
+<?xml version='1.0' encoding='ISO-8859-1'?>
+<?xml-stylesheet type='text/xsl' href='image_metadata_stylesheet.xsl'?>
+<dataset>
+<name>imglab dataset</name>
+<comment>Created by imglab tool.</comment>
+<images>
+  <image file='faces/faces_001.jpg'>
+    <box top='487' left='60' width='72' height='76'/>
+    <box top='368' left='122' width='82' height='106'/>
+    <box top='154' left='309' width='73' height='85'/>
+    <box top='129' left='409' width='84' height='85'/>
+    <box top='72' left='701' width='80' height='84'/>
+    <box top='387' left='649' width='57' height='54'/>
+    <box top='542' left='729' width='65' height='75'/>
+  </image>
+  <image file='faces/faces_002.jpg'>
+    <box top='76' left='103' width='143' height='133'/>
+  </image>
+  <image file='faces/faces_003.jpg'>
+    <box top='107' left='22' width='220' height='213'/>
+  </image>
+  <image file='faces/faces_004.jpg'>
+    <box top='30' left='118' width='56' height='55'/>
+  </image>
+  <image file='faces/faces_005.jpg'>
+    <box top='69' left='143' width='118' height='115'/>
+  </image>
+  <image file='faces/faces_006.jpg'>
+    <box top='92' left='208' width='133' height='144'/>
+  </image>
+  <image file='faces/faces_007.jpg'>
+    <box top='20' left='50' width='71' height='67'/>
+    <box top='86' left='138' width='46' height='61'/>
+    <box top='103' left='207' width='53' height='48'/>
+    <box top='45' left='323' width='55' height='56'/>
+    <box top='68' left='447' width='55' height='53'/>
+    <box top='120' left='508' width='61' height='59'/>
+  </image>
+  <image file='faces/faces_008.jpg'>
+    <box top='31' left='36' width='95' height='104'/>
+  </image>
+  <image file='faces/faces_009.jpg'>
+    <box top='94' left='171' width='96' height='98'/>
+  </image>
+  <image file='faces/faces_010.jpg'>
+    <box top='53' left='63' width='66' height='61'/>
+    <box top='48' left='131' width='57' height='64'/>
+  </image>
+  <image file='faces/faces_011.jpg'>
+    <box top='68' left='115' width='33' height='28'/>
+    <box top='52' left='155' width='31' height='32'/>
+    <box top='62' left='191' width='33' height='37'/>
+    <box top='118' left='205' width='29' height='29'/>
+    <box top='125' left='158' width='38' height='35'/>
+    <box top='120' left='122' width='26' height='28'/>
+  </image>
+  <image file='faces/faces_012.jpg'>
+    <box top='79' left='88' width='104' height='99'/>
+  </image>
+  <image file='faces/faces_013.jpg'>
+    <box top='21' left='8' width='41' height='44'/>
+    <box top='27' left='64' width='57' height='68'/>
+  </image>
+  <image file='faces/faces_014.jpg'>
+    <box top='61' left='170' width='62' height='65'/>
+  </image>
+  <image file='faces/faces_015.jpg'>
+    <box top='153' left='212' width='112' height='110'/>
+  </image>
+  <image file='faces/faces_016.jpg'>
+    <box top='111' left='58' width='171' height='163'/>
+  </image>
+  <image file='faces/faces_017.jpg'>
+    <box top='36' left='177' width='63' height='59'/>
+    <box top='193' left='74' width='61' height='63'/>
+  </image>
+  <image file='faces/faces_018.jpg'>
+    <box top='111' left='67' width='34' height='37'/>
+    <box top='100' left='105' width='36' height='39'/>
+    <box top='213' left='92' width='38' height='38'/>
+    <box top='148' left='126' width='41' height='39'/>
+    <box top='133' left='173' width='35' height='31'/>
+    <box top='92' left='215' width='32' height='44'/>
+    <box top='144' left='258' width='36' height='35'/>
+    <box top='148' left='320' width='43' height='41'/>
+    <box top='107' left='375' width='37' height='43'/>
+  </image>
+  <image file='faces/faces_019.jpg'>
+    <box top='89' left='42' width='51' height='58'/>
+    <box top='118' left='105' width='49' height='61'/>
+    <box top='108' left='165' width='61' height='64'/>
+    <box top='129' left='237' width='65' height='70'/>
+  </image>
+  <image file='faces/faces_020.jpg'>
+    <box top='295' left='249' width='175' height='145'/>
+  </image>
+  <image file='faces/faces_021.jpg'>
+    <box top='271' left='193' width='57' height='55'/>
+    <box top='275' left='385' width='57' height='57'/>
+  </image>
+  <image file='faces/faces_022.jpg'>
+    <box top='92' left='26' width='59' height='51'/>
+    <box top='36' left='156' width='58' height='55'/>
+    <box top='50' left='284' width='53' height='50'/>
+  </image>
+  <image file='faces/faces_023.jpg'>
+    <box top='291' left='522' width='153' height='143'/>
+  </image>
+  <image file='faces/faces_024.jpg'>
+    <box top='141' left='172' width='145' height='123'/>
+  </image>
+  <image file='faces/faces_025.jpg'>
+    <box top='131' left='48' width='473' height='418'/>
+  </image>
+  <image file='faces/faces_026.jpg'>
+    <box top='114' left='52' width='70' height='64'/>
+    <box top='263' left='79' width='75' height='74'/>
+    <box top='159' left='126' width='56' height='63'/>
+    <box top='178' left='208' width='59' height='63'/>
+    <box top='82' left='223' width='61' height='60'/>
+    <box top='122' left='303' width='63' height='67'/>
+    <box top='256' left='304' width='61' height='64'/>
+    <box top='197' left='375' width='82' height='73'/>
+  </image>
+  <image file='faces/faces_027.jpg'>
+    <box top='28' left='106' width='68' height='71'/>
+  </image>
+  <image file='faces/faces_028.jpg'>
+    <box top='219' left='129' width='82' height='81'/>
+    <box top='228' left='224' width='82' height='75'/>
+    <box top='219' left='333' width='83' height='82'/>
+  </image>
+  <image file='faces/faces_029.jpg'>
+    <box top='91' left='111' width='42' height='35'/>
+    <box top='159' left='153' width='38' height='38'/>
+    <box top='82' left='213' width='37' height='31'/>
+    <box top='71' left='284' width='40' height='37'/>
+    <box top='120' left='292' width='33' height='36'/>
+    <box top='84' left='348' width='33' height='39'/>
+    <box top='91' left='405' width='35' height='39'/>
+  </image>
+  <image file='faces/faces_030.jpg'>
+    <box top='35' left='22' width='440' height='421'/>
+  </image>
+  <image file='faces/faces_031.jpg'>
+    <box top='93' left='59' width='205' height='202'/>
+  </image>
+  <image file='faces/faces_032.jpg'>
+    <box top='33' left='84' width='54' height='53'/>
+    <box top='56' left='155' width='40' height='40'/>
+    <box top='50' left='234' width='36' height='41'/>
+    <box top='42' left='320' width='46' height='48'/>
+  </image>
+  <image file='faces/faces_033.jpg'>
+    <box top='37' left='27' width='44' height='43'/>
+  </image>
+  <image file='faces/faces_034.jpg'>
+    <box top='134' left='128' width='99' height='103'/>
+  </image>
+  <image file='faces/faces_035.jpg'>
+    <box top='108' left='162' width='219' height='197'/>
+  </image>
+  <image file='faces/faces_036.jpg'>
+    <box top='29' left='176' width='82' height='87'/>
+  </image>
+  <image file='faces/faces_037.jpg'>
+    <box top='78' left='110' width='68' height='68'/>
+    <box top='56' left='244' width='53' height='57'/>
+  </image>
+  <image file='faces/faces_038.jpg'>
+    <box top='37' left='112' width='41' height='48'/>
+    <box top='38' left='204' width='45' height='46'/>
+  </image>
+  <image file='faces/faces_039.jpg'>
+    <box top='25' left='35' width='39' height='39'/>
+  </image>
+  <image file='faces/faces_040.jpg'>
+    <box top='62' left='58' width='77' height='85'/>
+  </image>
+  <image file='faces/faces_041.jpg'>
+    <box top='84' left='115' width='155' height='161'/>
+  </image>
+  <image file='faces/faces_042.jpg'>
+    <box top='353' left='159' width='326' height='322'/>
+  </image>
+  <image file='faces/faces_043.jpg'>
+    <box top='189' left='271' width='52' height='43'/>
+  </image>
+  <image file='faces/faces_044.jpg'>
+    <box top='133' left='65' width='34' height='35'/>
+    <box top='54' left='114' width='39' height='38'/>
+    <box top='260' left='135' width='43' height='42'/>
+    <box top='233' left='260' width='29' height='37'/>
+    <box top='42' left='337' width='37' height='36'/>
+    <box top='95' left='399' width='44' height='43'/>
+  </image>
+</images>
+</dataset>

Building Your Own Custom Object Detector/dlib_custom/face_detector/image_metadata_stylesheet.xsl

@@ -0,0 +1,109 @@
+<?xml version="1.0" encoding="ISO-8859-1" ?>
+
+<xsl:stylesheet version="1.0" xmlns:xsl="http://www.w3.org/1999/XSL/Transform">
+<xsl:output method='html' version='1.0' encoding='UTF-8' indent='yes' />
+
+<!-- ************************************************************************* -->
+
+   <xsl:variable name="max_images_displayed">30</xsl:variable>
+
+<!-- ************************************************************************* -->
+
+   <xsl:template match="/dataset">
+      <html>
+         <head>
+
+            <style type="text/css">
+               div#box{
+                  position: absolute; 
+                  border-style:solid; 
+                  border-width:1px; 
+                  border-color:red;
+               }
+
+               div#circle{
+                  position: absolute; 
+                  border-style:solid; 
+                  border-width:1px; 
+                  border-color:red;
+                  border-radius:7px;
+                  width:1px; 
+                  height: 1px;
+               }
+
+               div#label{
+                  position: absolute; 
+                  color: red;
+               }
+
+               div#img{
+                  position: relative;
+                  margin-bottom:2em;
+               }
+
+
+               pre {
+                  color: black;
+                  margin: 1em 0.25in;
+                  padding: 0.5em;
+                  background: rgb(240,240,240);
+                  border-top: black dotted 1px;
+                  border-left: black dotted 1px;
+                  border-right: black solid 2px;
+                  border-bottom: black solid 2px;
+               }
+
+            </style>
+
+         </head>
+
+         <body>
+            Dataset name: <b><xsl:value-of select='/dataset/name'/></b> <br/>
+            Dataset comment: <pre><xsl:value-of select='/dataset/comment'/></pre> <br/> 
+            Number of images: <xsl:value-of select="count(images/image)"/> <br/>
+            Number of boxes: <xsl:value-of select="count(images/image/box)"/> <br/>
+            <br/>
+            <hr/>
+
+            <!-- Show a warning if we aren't going to show all the images -->
+            <xsl:if test="count(images/image) &gt; $max_images_displayed">
+               <h2>Only displaying the first <xsl:value-of select="$max_images_displayed"/> images.</h2>
+               <hr/>
+            </xsl:if>
+
+
+            <xsl:for-each select="images/image">
+               <!-- Don't try to display too many images.  It makes your browser hang -->
+               <xsl:if test="position() &lt;= $max_images_displayed">
+                  <b><xsl:value-of select="@file"/></b> (Number of boxes: <xsl:value-of select="count(box)"/>) 
+                  <div id="img">
+                     <img src="{@file}"/>
+                     <xsl:for-each select="box">
+                        <div id="box" style="top: {@top}px; left: {@left}px; width: {@width}px; height: {@height}px;"></div>
+
+                        <!-- If there is a label then display it in the lower right corner. -->
+                        <xsl:if test="label">
+                           <div id="label" style="top: {@top+@height}px; left: {@left+@width}px;">
+                              <xsl:value-of select="label"/>
+                           </div>
+                        </xsl:if>
+
+                        <xsl:for-each select="part">
+                           <!--
+                           <div id="label" style="top: {@y+7}px; left: {@x}px;">
+                              <xsl:value-of select="@name"/>
+                           </div>
+                           -->
+                           <div id="circle" style="top: {(@y)}px; left: {(@x)}px; "></div>
+                        </xsl:for-each>
+                     </xsl:for-each>
+                  </div>
+               </xsl:if>
+            </xsl:for-each>
+         </body>
+      </html>
+   </xsl:template>
+
+   <!-- ************************************************************************* -->
+
+</xsl:stylesheet>

Building Your Own Custom Object Detector/dlib_custom/test_detector.py

@@ -0,0 +1,32 @@
+# USAGE
+# python test_detector.py --detector face_detector/detector.svm --testing face_detector/testing
+
+# import the necessary packages
+from imutils import paths
+import argparse
+import dlib
+import cv2
+
+# construct the argument parse and parse the arguments
+ap = argparse.ArgumentParser()
+ap.add_argument("-d", "--detector", required=True, help="Path to trained object detector")
+ap.add_argument("-t", "--testing", required=True, help="Path to directory of testing images")
+args = vars(ap.parse_args())
+
+# load the detector
+detector = dlib.simple_object_detector(args["detector"])
+
+# loop over the testing images
+for testingPath in paths.list_images(args["testing"]):
+	# load the image and make predictions
+	image = cv2.imread(testingPath)
+	boxes = detector(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
+
+	# loop over the bounding boxes and draw them
+	for b in boxes:
+		(x, y, w, h) = (b.left(), b.top(), b.right(), b.bottom())
+		cv2.rectangle(image, (x, y), (w, h), (0, 255, 0), 2)
+
+	# show the image
+	cv2.imshow("Image", image)
+	cv2.waitKey(0)

Building Your Own Custom Object Detector/dlib_custom/train_detector.py

@@ -0,0 +1,32 @@
+# USAGE
+# python train_detector.py --xml face_detector/faces_annotations.xml --detector face_detector/detector.svm
+
+# import the necessary packages
+from __future__ import print_function
+import argparse
+import dlib
+
+# construct the argument parse and parse the arguments
+ap = argparse.ArgumentParser()
+ap.add_argument("-x", "--xml", required=True, help="path to input XML file")
+ap.add_argument("-d", "--detector", required=True, help="path to output director")
+args = vars(ap.parse_args())
+
+# grab the default training options for the HOG + Linear SVM detector, then
+# train the detector -- in practice, the `C` parameter should be cross-validated
+print("[INFO] training detector...")
+options = dlib.simple_object_detector_training_options()
+options.C = 1.0
+options.num_threads = 4
+options.be_verbose = True
+dlib.train_simple_object_detector(args["xml"], args["detector"], options)
+
+# show the training accuracy
+print("[INFO] training accuracy: {}".format(
+	dlib.test_simple_object_detector(args["xml"], args["detector"])))
+
+# load the detector and visualize the HOG filter
+detector = dlib.simple_object_detector(args["detector"])
+win = dlib.image_window()
+win.set_image(detector)
+dlib.hit_enter_to_continue()