X-Git-Url: http://git.maemo.org/git/?p=opencv;a=blobdiff_plain;f=debian%2Fopencv-performance.1;fp=debian%2Fopencv-performance.1;h=e21ab01f77036183332aa6a4fc1fb59522209b1b;hp=0000000000000000000000000000000000000000;hb=e4c14cdbdf2fe805e79cd96ded236f57e7b89060;hpb=454138ff8a20f6edb9b65a910101403d8b520643 diff --git a/debian/opencv-performance.1 b/debian/opencv-performance.1 new file mode 100644 index 0000000..e21ab01 --- /dev/null +++ b/debian/opencv-performance.1 @@ -0,0 +1,125 @@ +.TH "OPENCV\-PERFORMANCE" "1" "May 2008" "OpenCV" "User Commands" + + +.SH NAME +opencv-performance \- evaluate the performance of the classifier + + +.SH SYNOPSIS +.B opencv\-performance [options] + + +.SH DESCRIPTION +.PP +.B 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. +.PP +When there is no such collection available test samples may be created from single +object image by the +.BR opencv\-createsamples (1) +utility. The scheme of test samples creation in this case is similar to training samples +.PP +In the output, the table should be read: +.TP +.RB \(aq Hits \(aq +shows the number of correctly found objects +.TP +.RB \(aq Missed \(aq +shows the number of missed objects (must exist but are not found, also known +as false negatives) +.TP +.RB \(aq False \(aq +shows the number of false alarms (must not exist but are found, also known +as false positives) + + +.SH OPTIONS +.PP +.B opencv\-performance +supports the following options: + +.PP + +.TP +.BI "\-data " classifier_directory_name +The directory, in which the classifier can be found. + +.TP +.BI "\-info " collection_file_name +File with test samples description. + +.TP +.BI "\-maxSizeDiff " max_size_difference +Determine the size criterion of reference and detected coincidence. +The default is +.IR 1.500000 . + +.TP +.BI "\-maxPosDiff " max_position_difference +Determine the position criterion of reference and detected coincidence. +The default is +.IR 0.300000 . + +.TP +.BI "\-sf " scale_factor +Scale the detection window in each iteration. The default is +.IR 1.200000 . + +.TP +.B \-ni +Don't save detection result to an image. This could be useful, if +.I collection_file_name +contains paths. + +.TP +.BI "\-nos " number_of_stages +Number of stages to use. The default is +.I \-1 +(all stages are used). + +.TP +.BI "\-rs " roc_size +The default is +.IR \40 . + +.TP +.BI "\-h " sample_height +The sample height (must have the same value as used during creation). +The default is +.IR 24 . + +.TP +.BI "\-w " sample_width +The sample width (must have the same value as used during creation). +The default is +.IR 24 . + +.PP +The same information is shown, if +.B opencv\-performance +is called without any arguments/options. + + +.SH EXAMPLES +.PP +To create training samples from one image applying distortions and show the +results: +.IP +.B opencv\-performance -data trainout -info tests.dat + + +.SH SEE ALSO +.PP +.BR opencv\-createsamples (1), +.BR opencv\-haartraing (1) +.PP +More information and examples can be found in the OpenCV documentation. + + +.SH AUTHORS +.PP +This manual page was written by \fBDaniel Leidert\fR <\&daniel.leidert@wgdd.de\&> +for the Debian project (but may be used by others).