EBarCodeReader::Learn

Learns the best options to use to read the given Images/ROIs. The EBarCodeReader::MinModuleSize is modified as well as the scales at which we detect barcodes. The other options (symbologies, checksum verification, max number of codes, ...) must be set by the user so that the codes are read correctly.

Namespace: Euresys::Open_eVision::EasyBarCode2

[C++]

float Learn(
   const std::vector<Euresys::Open_eVision::EROIBW8>& rois,
   bool keepDefaultScales,
   bool addAllScales
)

float Learn(
   const std::vector<Euresys::Open_eVision::EImageBW8>& images,
   bool keepDefaultScales,
   bool addAllScales
)

Parameters

rois

ROIs in which to find the barcodes.

keepDefaultScales

if true, Learning does not remove the scales used by default even if they are useless for the given images. Default: true

addAllScales

if true, Learning adds all of the scales at which a code is detected. Otherwise, the smallest number of scales required to read all of the images is added. Default: true

images

Images in which to find the barcodes.

Remarks

Adding more scales does not necessarily makes the reading slower, as processing stops as soon as we find the required number of codes. On the other hand, having too few scales can make the reading fail. The is why the default scales are kept and all the interesting scales are added by default.

EBarCodeReader.Learn

Namespace: Euresys.Open_eVision.EasyBarCode2

[C#]

float Learn(
   Euresys.Open_eVision.EROIBW8[] rois,
   bool keepDefaultScales,
   bool addAllScales
)

float Learn(
   Euresys.Open_eVision.EImageBW8[] images,
   bool keepDefaultScales,
   bool addAllScales
)