NAME
opencv_performance - evaluate the performance of the classifier
SYNOPSIS
opencv_performance [options]
DESCRIPTION
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)
OPTIONS
opencv_performance supports the following options:
-data classifier_directory_name
The directory, in which the classifier can be found.
-info collection_file_name
File with test samples description.
-maxSizeDiff max_size_difference
Determine the size criterion of reference and detected
coincidence. The default is 1.500000.
-maxPosDiff max_position_difference
Determine the position criterion of reference and detected
coincidence. The default is 0.300000.
-sf scale_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.
-nos number_of_stages
Number of stages to use. The default is -1 (all stages are
used).
-rs roc_size
The default is 40.
-h sample_height
The sample height (must have the same value as used during
creation). The default is 24.
-w sample_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.
EXAMPLES
To create training samples from one image applying distortions and show
the results:
opencv_performance -data trainout -info tests.dat
SEE ALSO
opencv_createsamples(1), opencv_haartraing(1)
More information and examples can be found in the OpenCV documentation.
AUTHORS
This manual page was written by Daniel Leidert <daniel.leidert@wgdd.de>
and Nobuhiro Iwamatsu <iwamatsu@debian.org> for the Debian project (but
may be used by others).