updated docs

docs/docs/imaging.xml

@@ -144,6 +144,11 @@
          <item>binned_vector_feature_image</item>
          <item>nearest_neighbor_feature_image</item>
          <item>randomly_sample_image_features</item> 
+
+         <item>make_uniform_lbp_image</item>
+         <item>extract_histogram_descriptors</item>
+         <item>extract_uniform_lbp_descriptors</item>
+         <item>extract_highdim_face_lbp_descriptors</item>
       </section>
 
 
@@ -2265,6 +2270,71 @@
          </description>
                                  
       </component>
+
+            
+   <!-- ************************************************************************* -->
+
+      <component>
+         <name>make_uniform_lbp_image</name>
+         <file>dlib/image_transforms.h</file>
+         <spec_file link="true">dlib/image_transforms/lbp_abstract.h</spec_file>
+         <description>
+              This function extracts the uniform local-binary-pattern feature at every pixel
+              of an image and stores the output in a new image object.  
+              We use the idea of uniform LBPs from the paper: 
+              <blockquote>
+                Face Description with Local Binary Patterns: Application to Face Recognition
+                by Ahonen, Hadid, and Pietikainen.
+              </blockquote>
+         </description>
+      </component>
+
+   <!-- ************************************************************************* -->
+
+      <component>
+         <name>extract_histogram_descriptors</name>
+         <file>dlib/image_transforms.h</file>
+         <spec_file link="true">dlib/image_transforms/lbp_abstract.h</spec_file>
+         <description>
+              This function extracts histograms of pixel values from a set of windows in an
+              image and returns the histograms.
+         </description>
+      </component>
+
+   <!-- ************************************************************************* -->
+
+      <component>
+         <name>extract_uniform_lbp_descriptors</name>
+         <file>dlib/image_transforms.h</file>
+         <spec_file link="true">dlib/image_transforms/lbp_abstract.h</spec_file>
+         <description>
+              Extracts histograms of uniform local-binary-patterns from an image.  The
+              histograms are from densely tiled windows that do not overlap and cover all
+              of the image.
+              We use the idea of uniform LBPs from the paper: 
+              <blockquote>
+                Face Description with Local Binary Patterns: Application to Face Recognition
+                by Ahonen, Hadid, and Pietikainen.
+              </blockquote>
+         </description>
+      </component>
+
+   <!-- ************************************************************************* -->
+
+      <component>
+         <name>extract_highdim_face_lbp_descriptors</name>
+         <file>dlib/image_transforms.h</file>
+         <spec_file link="true">dlib/image_transforms/lbp_abstract.h</spec_file>
+         <description>
+              This function extracts the high-dimensional LBP feature described in the
+              paper:
+              <blockquote>
+                Blessing of Dimensionality: High-dimensional Feature and Its Efficient
+                Compression for Face Verification by Dong Chen, Xudong Cao, Fang Wen, and
+                Jian Sun
+              </blockquote>
+         </description>
+      </component>
       
    <!-- ************************************************************************* -->
 

docs/docs/ml.xml

@@ -132,6 +132,7 @@ Davis E. King. <a href="http://jmlr.csail.mit.edu/papers/volume10/king09a/king09
          <item>linear_manifold_regularizer</item>
          <item>discriminant_pca</item> 
          <item>vector_normalizer_frobmetric</item> 
+         <item>compute_lda_transform</item> 
       </section>
       <section>
          <name>Feature Selection</name>
@@ -166,6 +167,7 @@ Davis E. King. <a href="http://jmlr.csail.mit.edu/papers/volume10/king09a/king09
          <item>test_ranking_function</item>
          <item>test_shape_predictor</item>
          <item>average_precision</item>
+         <item>equal_error_rate</item>
       </section>
 
       <section>
@@ -620,6 +622,20 @@ Davis E. King. <a href="http://jmlr.csail.mit.edu/papers/volume10/king09a/king09
          </description>
       </component>
       
+   <!-- ************************************************************************* -->
+      
+      <component>
+         <name>compute_lda_transform</name>
+         <file>dlib/statistics.h</file>
+         <spec_file link="true">dlib/statistics/lda_abstract.h</spec_file>
+         <description>
+            This function performs the dimensionality reducing version of linear
+            discriminant analysis.  That is, you give it a set of labeled vectors and it
+            returns a linear transform that maps the input vectors into a new space that
+            is good for distinguishing between the different classes. 
+         </description>
+      </component>
+      
    <!-- ************************************************************************* -->
       
       <component>
@@ -2693,6 +2709,19 @@ Davis E. King. <a href="http://jmlr.csail.mit.edu/papers/volume10/king09a/king09
          </description>
       </component>
       
+   <!-- ************************************************************************* -->
+      
+      <component>
+         <name>equal_error_rate</name>
+         <file>dlib/statistics.h</file>
+         <spec_file link="true">dlib/statistics/lda_abstract.h</spec_file>
+         <description>
+              This function finds a threshold that best separates the elements of two
+              vectors by selecting the threshold with equal error rate.  It also reports
+              the value of the equal error rate.
+         </description>
+      </component>
+      
    <!-- ************************************************************************* -->
       
       <component>

docs/docs/term_index.xml

@@ -351,6 +351,7 @@
          <term file="ml.html" name="is_ranking_problem"                             include="dlib/svm.h"/>
          <term file="ml.html" name="count_ranking_inversions"                       include="dlib/svm.h"/>
          <term file="ml.html" name="average_precision"                              include="dlib/statistics.h"/>
+         <term file="ml.html" name="equal_error_rate"                               include="dlib/statistics.h"/>
          <term file="ml.html" name="test_ranking_function"                          include="dlib/svm.h"/>
          <term file="ml.html" name="cross_validate_ranking_trainer"                 include="dlib/svm.h"/>
          <term file="ml.html" name="svm_c_ekm_trainer"                              include="dlib/svm.h"/>
@@ -398,6 +399,7 @@
          <term file="ml.html" name="rank_unlabeled_training_samples"                include="dlib/svm.h"/>
          <term file="ml.html" name="vector_normalizer"                              include="dlib/statistics.h"/>
          <term file="ml.html" name="vector_normalizer_frobmetric"                   include="dlib/statistics.h"/>
+         <term file="ml.html" name="compute_lda_transform"                          include="dlib/statistics.h"/>
          <term file="ml.html" name="frobmetric_training_sample"                     include="dlib/statistics.h"/>
          <term file="ml.html" name="vector_normalizer_pca"                          include="dlib/statistics.h"/>
          <term file="ml.html" name="discriminant_pca"                               include="dlib/statistics.h"/>
@@ -1256,6 +1258,7 @@
          <term file="dlib/image_transforms/interpolation_abstract.h.html" name="chip_details"           include="dlib/image_transforms.h"/>
          <term file="dlib/image_transforms/interpolation_abstract.h.html" name="get_face_chip_details"  include="dlib/image_transforms.h"/>
          <term file="dlib/image_transforms/interpolation_abstract.h.html" name="get_mapping_to_chip" include="dlib/image_transforms.h"/>
+         <term file="dlib/image_transforms/interpolation_abstract.h.html" name="map_det_to_chip" include="dlib/image_transforms.h"/>
          <term file="dlib/image_transforms/interpolation_abstract.h.html" name="chip_dims"      include="dlib/image_transforms.h"/>
          <term file="imaging.html" name="pyramid_up"              include="dlib/image_transforms.h"/>
          <term file="imaging.html" name="add_image_left_right_flips" include="dlib/image_transforms.h"/>
@@ -1269,6 +1272,11 @@
          <term file="dlib/image_transforms/interpolation_abstract.h.html" name="black_background" include="dlib/image_transforms.h"/>
          <term file="dlib/image_transforms/interpolation_abstract.h.html" name="white_background" include="dlib/image_transforms.h"/>
          <term file="dlib/image_transforms/interpolation_abstract.h.html" name="no_background"    include="dlib/image_transforms.h"/>
+         
+         <term file="imaging.html" name="make_uniform_lbp_image"                 include="dlib/image_transforms.h"/>
+         <term file="imaging.html" name="extract_histogram_descriptors"          include="dlib/image_transforms.h"/>
+         <term file="imaging.html" name="extract_uniform_lbp_descriptors"        include="dlib/image_transforms.h"/>
+         <term file="imaging.html" name="extract_highdim_face_lbp_descriptors"   include="dlib/image_transforms.h"/>
 
          <term file="imaging.html" name="integral_image"          include="dlib/image_transforms.h"/>
          <term file="imaging.html" name="integral_image_generic"  include="dlib/image_transforms.h"/>