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jomjol
2022-04-17 21:51:26 +02:00
parent ccb4bd595c
commit cce812ff11
23 changed files with 378 additions and 92 deletions
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155
code/components/jomjol_flowcontroll/ClassFlowCNNGeneral.cpp
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@@ -17,6 +17,7 @@ ClassFlowCNNGeneral::ClassFlowCNNGeneral(ClassFlowAlignment *_flowalign, t_CNNTy
string cnnmodelfile = "";
modelxsize = 1;
modelysize = 1;
CNNGoodThreshold = 0.9;
ListFlowControll = NULL;
previousElement = NULL;
SaveAllFiles = false;
@@ -27,7 +28,7 @@ ClassFlowCNNGeneral::ClassFlowCNNGeneral(ClassFlowAlignment *_flowalign, t_CNNTy
flowpostalignment = _flowalign;
}
string ClassFlowCNNGeneral::getReadout(int _analog = 0, bool _extendedResolution = false)
string ClassFlowCNNGeneral::getReadout(int _analog = 0, bool _extendedResolution, int prev)
{
string result = "";
if (GENERAL[_analog]->ROI.size() == 0)
@@ -38,8 +39,6 @@ string ClassFlowCNNGeneral::getReadout(int _analog = 0, bool _extendedResolution
float zahl = GENERAL[_analog]->ROI[GENERAL[_analog]->ROI.size() - 1]->result_float;
int ergebnis_nachkomma = ((int) floor(zahl * 10) + 10) % 10;
int prev = -1;
prev = ZeigerEval(GENERAL[_analog]->ROI[GENERAL[_analog]->ROI.size() - 1]->result_float, prev);
result = std::to_string(prev);
@@ -66,7 +65,51 @@ string ClassFlowCNNGeneral::getReadout(int _analog = 0, bool _extendedResolution
return result;
}
if (CNNType == DigitalHyprid)
if ((CNNType == DoubleHyprid10))
{
float zahl = GENERAL[_analog]->ROI[GENERAL[_analog]->ROI.size() - 1]->result_float;
if (zahl >= 0) // NaN?
{
if (_extendedResolution)
{
int ergebnis_nachkomma = ((int) floor(zahl * 10)) % 10;
int ergebnis_vorkomma = ((int) floor(zahl)) % 10;
result = std::to_string(ergebnis_vorkomma) + std::to_string(ergebnis_nachkomma);
prev = ergebnis_vorkomma;
}
else
{
prev = ZeigerEval(GENERAL[_analog]->ROI[GENERAL[_analog]->ROI.size() - 1]->result_float, prev);
// prev = ZeigerEvalHybrid(GENERAL[_analog]->ROI[GENERAL[_analog]->ROI.size() - 1]->result_float, prev, prev);
result = std::to_string(prev);
}
}
else
{
result = "N";
if (_extendedResolution && (CNNType != Digital))
result = "NN";
}
for (int i = GENERAL[_analog]->ROI.size() - 2; i >= 0; --i)
{
if (GENERAL[_analog]->ROI[i]->result_float >= 0)
{
prev = ZeigerEvalHybrid(GENERAL[_analog]->ROI[i]->result_float, GENERAL[_analog]->ROI[i+1]->result_float, prev);
result = std::to_string(prev) + result;
}
else
{
prev = -1;
result = "N" + result;
}
}
return result;
}
if ((CNNType == DigitalHyprid))
{
int zif_akt = -1;
@@ -110,6 +153,7 @@ string ClassFlowCNNGeneral::getReadout(int _analog = 0, bool _extendedResolution
return result;
}
return result;
}
@@ -153,6 +197,35 @@ int ClassFlowCNNGeneral::ZeigerEvalHybrid(float zahl, float zahl_vorgaenger, int
return ((int) trunc(zahl) + 10) % 10;
}
/*
int ClassFlowCNNGeneral::ZeigerEvalHybrid_NEU(float zahl, float zahl_vorgaenger)
{
int ergebnis_nachkomma = ((int) floor(zahl * 10) + 10) % 10;
int ergebnis_vorkomma = ((int) floor(zahl) + 10) % 10;
int ergebnis, ergebnis_rating;
if (zahl_vorgaenger < 0)
return ergebnis_vorkomma % 10;
ergebnis_rating = ergebnis_nachkomma - zahl_vorgaenger;
if (ergebnis_nachkomma >= 5)
ergebnis_rating-=5;
else
ergebnis_rating+=5;
ergebnis = (int) round(zahl);
if (ergebnis_rating < 0)
ergebnis-=1;
if (ergebnis == -1)
ergebnis+=10;
ergebnis = (ergebnis + 10) % 10;
return ergebnis;
}
*/
int ClassFlowCNNGeneral::ZeigerEval(float zahl, int ziffer_vorgaenger)
{
int ergebnis_nachkomma = ((int) floor(zahl * 10) + 10) % 10;
@@ -206,12 +279,12 @@ bool ClassFlowCNNGeneral::ReadParameter(FILE* pfile, string& aktparamgraph)
while (this->getNextLine(pfile, &aktparamgraph) && !this->isNewParagraph(aktparamgraph))
{
zerlegt = this->ZerlegeZeile(aktparamgraph);
if ((zerlegt[0] == "LogImageLocation") && (zerlegt.size() > 1))
if ((toUpper(zerlegt[0]) == "LOGIMAGELOCATION") && (zerlegt.size() > 1))
{
this->LogImageLocation = "/sdcard" + zerlegt[1];
this->isLogImage = true;
}
if ((zerlegt[0] == "LogImageSelect") && (zerlegt.size() > 1))
if ((toUpper(zerlegt[0]) == "LOGIMAGESELECT") && (zerlegt.size() > 1))
{
LogImageSelect = zerlegt[1];
isLogImageSelect = true;
@@ -227,11 +300,16 @@ bool ClassFlowCNNGeneral::ReadParameter(FILE* pfile, string& aktparamgraph)
CNNType = DigitalHyprid;
}
if ((zerlegt[0] == "Model") && (zerlegt.size() > 1))
if ((toUpper(zerlegt[0]) == "MODEL") && (zerlegt.size() > 1))
{
this->cnnmodelfile = zerlegt[1];
}
if ((zerlegt[0] == "ModelInputSize") && (zerlegt.size() > 2))
if ((toUpper(zerlegt[0]) == "CNNGOODTHRESHOLD") && (zerlegt.size() > 1))
{
CNNGoodThreshold = std::stof(zerlegt[1]);
}
if ((toUpper(zerlegt[0]) == "MODELINPUTSIZE") && (zerlegt.size() > 2))
{
this->modelxsize = std::stoi(zerlegt[1]);
this->modelysize = std::stoi(zerlegt[2]);
@@ -408,7 +486,6 @@ void ClassFlowCNNGeneral::DrawROI(CImageBasis *_zw)
for (int i = 0; i < GENERAL[_ana]->ROI.size(); ++i)
{
_zw->drawRect(GENERAL[_ana]->ROI[i]->posx, GENERAL[_ana]->ROI[i]->posy, GENERAL[_ana]->ROI[i]->deltax, GENERAL[_ana]->ROI[i]->deltay, r, g, b, 1);
// _zw->drawCircle((int) (GENERAL[_ana]->ROI[i]->posx + GENERAL[_ana]->ROI[i]->deltax/2), (int) (GENERAL[_ana]->ROI[i]->posy + GENERAL[_ana]->ROI[i]->deltay/2), (int) (GENERAL[_ana]->ROI[i]->deltax/2), r, g, b, 2);
_zw->drawEllipse( (int) (GENERAL[_ana]->ROI[i]->posx + GENERAL[_ana]->ROI[i]->deltax/2), (int) (GENERAL[_ana]->ROI[i]->posy + GENERAL[_ana]->ROI[i]->deltay/2), (int) (GENERAL[_ana]->ROI[i]->deltax/2), (int) (GENERAL[_ana]->ROI[i]->deltay/2), r, g, b, 2);
_zw->drawLine((int) (GENERAL[_ana]->ROI[i]->posx + GENERAL[_ana]->ROI[i]->deltax/2), (int) GENERAL[_ana]->ROI[i]->posy, (int) (GENERAL[_ana]->ROI[i]->posx + GENERAL[_ana]->ROI[i]->deltax/2), (int) (GENERAL[_ana]->ROI[i]->posy + GENERAL[_ana]->ROI[i]->deltay), r, g, b, 2);
_zw->drawLine((int) GENERAL[_ana]->ROI[i]->posx, (int) (GENERAL[_ana]->ROI[i]->posy + GENERAL[_ana]->ROI[i]->deltay/2), (int) GENERAL[_ana]->ROI[i]->posx + GENERAL[_ana]->ROI[i]->deltax, (int) (GENERAL[_ana]->ROI[i]->posy + GENERAL[_ana]->ROI[i]->deltay/2), r, g, b, 2);
@@ -451,6 +528,10 @@ bool ClassFlowCNNGeneral::doNeuralNetwork(string time)
CNNType = Analogue;
printf("TFlite-Type set to Analogue\n");
break;
case 10:
CNNType = DoubleHyprid10;
printf("TFlite-Type set to DoubleHyprid10\n");
break;
case 11:
CNNType = Digital;
printf("TFlite-Type set to Digital\n");
@@ -562,6 +643,62 @@ bool ClassFlowCNNGeneral::doNeuralNetwork(string time)
if (isLogImage)
LogImage(logPath, GENERAL[_ana]->ROI[i]->name, &GENERAL[_ana]->ROI[i]->result_float, NULL, time, GENERAL[_ana]->ROI[i]->image_org);
} break;
case DoubleHyprid10:
{
int _num, _numplus, _numminus;
float _val, _valplus, _valminus;
float _fit;
tflite->LoadInputImageBasis(GENERAL[_ana]->ROI[i]->image);
tflite->Invoke();
if (debugdetailgeneral) LogFile.WriteToFile("Nach Invoke");
_num = tflite->GetOutClassification(0, 9);
_numplus = (_num + 1) % 10;
_numminus = (_num - 1) % 10;
_val = tflite->GetOutputValue(_num);
_valplus = tflite->GetOutputValue(_numplus);
_valminus = tflite->GetOutputValue(_numminus);
float result = _num;
if (_valplus > _numminus)
{
result = result + _valplus / (_valplus + _val);
_fit = _val + _valplus;
}
else
{
result = result - _valminus / (_val + _valminus);
_fit = _val + _valminus;
}
if (result > 10)
result = result - 10;
if (result < 0)
result = result + 10;
if (_fit < CNNGoodThreshold)
{
GENERAL[_ana]->ROI[i]->isReject = true;
result = -1;
string zw = "Value Rejected due to Threshold (Fit: " + to_string(_fit) + "Threshold: " + to_string(CNNGoodThreshold);
printf("Value Rejected due to Threshold (Fit: %f, Threshold: %f\n", _fit, CNNGoodThreshold);
LogFile.WriteToFile(zw);
}
else
{
GENERAL[_ana]->ROI[i]->isReject = false;
}
GENERAL[_ana]->ROI[i]->result_float = result;
printf("Result General(Analog)%i: %f\n", i, GENERAL[_ana]->ROI[i]->result_float);
}
break;
default:
break;
}