NICE_SemSeg/semseg/SemSegTools.h

/**
* @file SemSegTools.h
* @brief tools for semantic segmentation
* @author Erik Rodner
* @date 03/19/2009

*/
#ifndef SEMSEGTOOLSINCLUDE
#define SEMSEGTOOLSINCLUDE

#include "core/basics/Config.h"
#include "core/basics/ResourceStatistics.h"
#include "vislearning/cbaselib/MultiDataset.h"
#include "vislearning/cbaselib/Example.h"
#include "vislearning/cbaselib/CachedExample.h"


namespace OBJREC
{

/** tools for semantic segmentation */
class SemSegTools
{

  protected:

  public:

    /**
     * @brief produce an image with segmentation result as overlay
     * @param orig original input image
     * @param segment segmentation result
     * @param result overlay image
     */
    static void segmentToOverlay (
            const NICE::Image * orig,
            const NICE::ColorImage & segment,
            NICE::ColorImage & result );

    /**
     * @brief update confusion matrix with results of current image
     * @param img segmentation result
     * @param gt ground truth data
     * @param M confusion matrix
     * @param forbidden_classes set of classes, that should be ignored
     * @param classMapping mapping for a subset of classes
     */
    static void updateConfusionMatrix (
            const NICE::ImageT<int> & img,
            const NICE::ImageT<int> & gt,
            NICE::Matrix & M,
            const std::set<int> & forbiddenClasses,
            std::map<int,int> & classMapping );

    /**
     * @brief compute typical classification statistics using confusion matrix
     * @param confMat confusion matrix
     * @param classNames class names object
     * @param forbidden_classes set of classes, that should be ignored
     * @param classMappingInv mapping for a subset of classes
     */
    static void computeClassificationStatistics (
            NICE::Matrix & confMat,
            const OBJREC::ClassNames & classNames,
            const std::set<int> & forbiddenClasses,
            std::map<int,int> & classMappingInv );

    /**
     * @brief compute some resource statistics
     * @param rs resource statistics object
     */
    static void computeResourceStatistics (
            NICE::ResourceStatistics & rs );

    /**
     * @brief save results to image file
     * @param conf Config file
     * @param section section in config file
     * @param orig input image
     * @param gtruth ground truth data
     * @param segment segmentation result
     */
    static void saveResultsToImageFile (
            const NICE::Config * conf,
            const std::string & section,
            const NICE::ColorImage & orig,
            const NICE::ColorImage & gtruth,
            const NICE::ColorImage & segment,
            const std::string & file,
            std::string & outStr );

    /**
     * @brief Collect information about the depth of 3d images
     * @author Sven Sickert
     * @param Files a labeled set of data
     * @param depthVec output of depth values
     * @param run3dseg whether slice counting is necessary or not
     */
    static void getDepthVector (
            const LabeledSet *Files,
            std::vector<int> & depthVec,
            const bool run3dseg );

    /** collect pixel-wise training examples
        from a set of images
        @param conf includes settings about grid size etc.
        @param section section of the config
        @param train set of training images with localization information
        @param cn classNames object
        @param examples resulting pixel-wise examples
        @param imgexamples image based caching structure referenced by pixel-wise examples
        @param run3Dseg whether to run in 3D segmentation mode or not
    */
    static void collectTrainingExamples (
            const NICE::Config * conf,
            const std::string & section,
            const LabeledSet & train,
            const ClassNames & cn,
            Examples & examples,
            std::vector<CachedExample *> & imgexamples,
            const bool run3Dseg = false );
};


} // namespace

#endif