view transform/FeatureExtractionModelTransformer.h @ 875:3e6ed8a8577b tonioni

Use a sparse time-value model only for outputs with fixed bin count of 1, not for those with unknown bin count.
(Precursor to using more than one model for outputs with unknown bin count)

/* -*- c-basic-offset: 4 indent-tabs-mode: nil -*-  vi:set ts=8 sts=4 sw=4: */

/*
    Sonic Visualiser
    An audio file viewer and annotation editor.
    Centre for Digital Music, Queen Mary, University of London.
    This file copyright 2006 Chris Cannam and QMUL.
    
    This program is free software; you can redistribute it and/or
    modify it under the terms of the GNU General Public License as
    published by the Free Software Foundation; either version 2 of the
    License, or (at your option) any later version.  See the file
    COPYING included with this distribution for more information.
*/

#ifndef _FEATURE_EXTRACTION_MODEL_TRANSFORMER_H_
#define _FEATURE_EXTRACTION_MODEL_TRANSFORMER_H_

#include "ModelTransformer.h"

#include <QString>

#include <vamp-hostsdk/Plugin.h>

#include <iostream>

class DenseTimeValueModel;

class FeatureExtractionModelTransformer : public ModelTransformer
{
    Q_OBJECT

public:
    FeatureExtractionModelTransformer(Input input,
                                      const Transform &transform);

    // Obtain outputs for a set of transforms that all use the same
    // plugin and input (but with different outputs). i.e. run the
    // plugin once only and collect more than one output from it.
    FeatureExtractionModelTransformer(Input input,
                                      const Transforms &relatedTransforms);

    virtual ~FeatureExtractionModelTransformer();

protected:
    bool initialise();

    virtual void run();

    Vamp::Plugin *m_plugin;
    std::vector<Vamp::Plugin::OutputDescriptor *> m_descriptors; // per transform
    std::vector<int> m_fixedRateFeatureNos; // to assign times to FixedSampleRate features
    std::vector<int> m_outputNos;

    void createOutputModel(int n);

    void addFeature(int n,
                    size_t blockFrame,
		    const Vamp::Plugin::Feature &feature);

    void setCompletion(int, int);

    void getFrames(int channelCount, long startFrame, long size,
                   float **buffer);

    // just casts

    DenseTimeValueModel *getConformingInput();

    template <typename ModelClass> bool isOutput(int n) {
        return dynamic_cast<ModelClass *>(m_outputs[n]) != 0;
    }

    template <typename ModelClass> ModelClass *getConformingOutput(int n) {
        if ((int)m_outputs.size() > n) {
            ModelClass *mc = dynamic_cast<ModelClass *>(m_outputs[n]);
            if (!mc) {
                std::cerr << "FeatureExtractionModelTransformer::getOutput: Output model not conformable" << std::endl;
            }
            return mc;
        } else {
            std::cerr << "FeatureExtractionModelTransformer::getOutput: No such output number " << n << std::endl;
            return 0;
        }
    }
};

#endif