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https://github.com/jomjol/AI-on-the-edge-device.git
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73 lines
1.8 KiB
C++
73 lines
1.8 KiB
C++
#ifndef __CLASSCNNGENERAL__
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#define __CLASSCNNGENERAL__
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#include"ClassFlowDefineTypes.h"
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#include "ClassFlowAlignment.h"
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// #include "ClassFlowPostProcessing.h"
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enum t_CNNType {
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AutoDetect,
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Analogue,
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Digital,
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DigitalHyprid,
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None
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};
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class ClassFlowCNNGeneral :
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public ClassFlowImage
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{
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protected:
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t_CNNType CNNType;
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std::vector<general*> GENERAL;
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string cnnmodelfile;
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int modelxsize, modelysize;
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bool isLogImageSelect;
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string LogImageSelect;
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ClassFlowAlignment* flowpostalignment;
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// ClassFlowPostProcessing *flowpostprocessing = NULL;
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bool SaveAllFiles;
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// bool extendedResolution;
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int ZeigerEval(float zahl, int ziffer_vorgaenger);
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int ZeigerEvalHybrid(float zahl, float zahl_vorgaenger, int eval_vorgaenger);
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bool doNeuralNetwork(string time);
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bool doAlignAndCut(string time);
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public:
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ClassFlowCNNGeneral(ClassFlowAlignment *_flowalign, t_CNNType _cnntype = AutoDetect);
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bool ReadParameter(FILE* pfile, string& aktparamgraph);
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bool doFlow(string time);
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string getHTMLSingleStep(string host);
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string getReadout(int _analog, bool _extendedResolution);
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void DrawROI(CImageBasis *_zw);
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std::vector<HTMLInfo*> GetHTMLInfo();
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// int AnzahlROIs(int _analog);
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int getAnzahlGENERAL();
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general* GetGENERAL(int _analog);
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general* GetGENERAL(string _name, bool _create);
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general* FindGENERAL(string _name_number);
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string getNameGENERAL(int _analog);
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bool isExtendedResolution(int _number = 0);
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// void setPostprocessing(ClassFlowPostProcessing *_fpp){flowpostprocessing = _fpp;};
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void UpdateNameNumbers(std::vector<std::string> *_name_numbers);
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t_CNNType getCNNType(){return CNNType;};
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string name(){return "ClassFlowCNNGeneral";};
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};
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#endif
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