opencv_performance - evaluate the performance of the classifier

       This  manual  page  was  written  by  DanielLeidert  <daniel.leidert@wgdd.de>  and  NobuhiroIwamatsu
       <iwamatsu@debian.org> for the Debian project (but may be used by others).

OpenCV                                              May 2010                               OPENCV_PERFORMANCE(1)

opencv_performance  evaluates  the performance of the classifier. It takes a collection of marked up test
       images, applies the classifier and outputs the performance, i.e.  number  of  found  objects,  number  of
       missed objects, number of false alarms and other information.

       When  there  is  no such collection available test samples may be created from single object image by the
       opencv_createsamples(1) utility. The scheme of test samples creation in this case is similar to  training
       samples

       In the output, the table should be read:

       'Hits' shows the number of correctly found objects

       'Missed'
              shows the number of missed objects (must exist but are not found, also known as false negatives)

       'False'
              shows the number of false alarms (must not exist but are found, also known as false positives)

       To create training samples from one image applying distortions and show the results:

              opencv_performance-datatrainout-infotests.dat

       opencv_performance - evaluate the performance of the classifier

opencv_performance supports the following options:

       -dataclassifier_directory_name
              The directory, in which the classifier can be found.

       -infocollection_file_name
              File with test samples description.

       -maxSizeDiffmax_size_difference
              Determine the size criterion of reference and detected coincidence.  The default is 1.500000.

       -maxPosDiffmax_position_difference
              Determine the position criterion of reference and detected coincidence.  The default is 0.300000.

       -sfscale_factor
              Scale the detection window in each iteration. The default is 1.200000.

       -ni    Don't  save  detection  result to an image. This could be useful, if collection_file_name contains
              paths.

       -nosnumber_of_stages
              Number of stages to use. The default is -1 (all stages are used).

       -rsroc_size
              The default is 40.

       -hsample_height
              The sample height (must have the same value as used during creation).  The default is 24.

       -wsample_width
              The sample width (must have the same value as used during creation).  The default is 24.

       The same information is shown, if opencv_performance is called without any arguments/options.

opencv_createsamples(1), opencv_haartraing(1)

       More information and examples can be found in the OpenCV documentation.

opencv_performance[options]