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).