Files
AI-on-the-edge-device/code/components/jomjol_flowcontroll/ClassFlowAnalog.cpp
2020-11-20 19:34:55 +01:00

309 lines
8.3 KiB
C++

#include "ClassFlowAnalog.h"
#include <math.h>
#include <iomanip>
#include <sys/types.h>
// #define OHNETFLITE
#ifndef OHNETFLITE
#include "CTfLiteClass.h"
#endif
#include "ClassLogFile.h"
static const char* TAG = "flow_analog";
bool debugdetailanalog = false;
ClassFlowAnalog::ClassFlowAnalog() : ClassFlowImage(TAG)
{
string cnnmodelfile = "";
modelxsize = 1;
modelysize = 1;
ListFlowControll = NULL;
}
ClassFlowAnalog::ClassFlowAnalog(std::vector<ClassFlow*>* lfc) : ClassFlowImage(lfc, TAG)
{
string cnnmodelfile = "";
modelxsize = 1;
modelysize = 1;
}
string ClassFlowAnalog::getReadout()
{
int prev = -1;
string result = "";
for (int i = ROI.size() - 1; i >= 0; --i)
{
prev = ZeigerEval(ROI[i]->result, prev);
result = std::to_string(prev) + result;
}
return result;
}
int ClassFlowAnalog::ZeigerEval(float zahl, int ziffer_vorgaenger)
{
int ergebnis_nachkomma = ((int) floor(zahl * 10)) % 10;
int ergebnis_vorkomma = ((int) floor(zahl)) % 10;
int ergebnis, ergebnis_rating;
if (ziffer_vorgaenger == -1)
return ergebnis_vorkomma % 10;
ergebnis_rating = ergebnis_nachkomma - ziffer_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;
return ergebnis;
}
bool ClassFlowAnalog::ReadParameter(FILE* pfile, string& aktparamgraph)
{
std::vector<string> zerlegt;
aktparamgraph = trim(aktparamgraph);
if (aktparamgraph.size() == 0)
if (!this->GetNextParagraph(pfile, aktparamgraph))
return false;
if (aktparamgraph.compare("[Analog]") != 0) // Paragraph passt nich zu MakeImage
return false;
while (this->getNextLine(pfile, &aktparamgraph) && !this->isNewParagraph(aktparamgraph))
{
zerlegt = this->ZerlegeZeile(aktparamgraph);
if ((zerlegt[0] == "LogImageLocation") && (zerlegt.size() > 1))
{
this->LogImageLocation = "/sdcard" + zerlegt[1];
this->isLogImage = true;
}
if ((toUpper(zerlegt[0]) == "LOGFILERETENTIONINDAYS") && (zerlegt.size() > 1))
{
this->logfileRetentionInDays = std::stoi(zerlegt[1]);
}
if ((zerlegt[0] == "Model") && (zerlegt.size() > 1))
{
this->cnnmodelfile = zerlegt[1];
}
if ((zerlegt[0] == "ModelInputSize") && (zerlegt.size() > 2))
{
this->modelxsize = std::stoi(zerlegt[1]);
this->modelysize = std::stoi(zerlegt[2]);
}
if (zerlegt.size() >= 5)
{
roianalog* neuroi = new roianalog;
neuroi->name = zerlegt[0];
neuroi->posx = std::stoi(zerlegt[1]);
neuroi->posy = std::stoi(zerlegt[2]);
neuroi->deltax = std::stoi(zerlegt[3]);
neuroi->deltay = std::stoi(zerlegt[4]);
neuroi->result = -1;
ROI.push_back(neuroi);
}
}
return true;
}
string ClassFlowAnalog::getHTMLSingleStep(string host)
{
string result, zw;
std::vector<HTMLInfo*> htmlinfo;
result = "<p>Found ROIs: </p> <p><img src=\"" + host + "/img_tmp/alg_roi.jpg\"></p>\n";
result = result + "Analog Pointers: <p> ";
htmlinfo = GetHTMLInfo();
for (int i = 0; i < htmlinfo.size(); ++i)
{
std::stringstream stream;
stream << std::fixed << std::setprecision(1) << htmlinfo[i]->val;
zw = stream.str();
result = result + "<img src=\"" + host + "/img_tmp/" + htmlinfo[i]->filename + "\"> " + zw;
delete htmlinfo[i];
}
htmlinfo.clear();
return result;
}
bool ClassFlowAnalog::doFlow(string time)
{
if (!doAlignAndCut(time)){
return false;
};
if (debugdetailanalog) LogFile.WriteToFile("ClassFlowAnalog::doFlow nach Alignment");
doNeuralNetwork(time);
RemoveOldLogs();
return true;
}
bool ClassFlowAnalog::doAlignAndCut(string time)
{
string input = "/sdcard/img_tmp/alg.jpg";
string input_roi = "/sdcard/img_tmp/alg_roi.jpg";
string ioresize = "/sdcard/img_tmp/resize.bmp";
string output;
string nm;
input = FormatFileName(input);
input_roi = FormatFileName(input_roi);
CResizeImage *rs;
CImageBasis *img_roi = NULL;
CAlignAndCutImage *caic = new CAlignAndCutImage(input);
if (!caic->ImageOkay()){
if (debugdetailanalog) LogFile.WriteToFile("ClassFlowAnalog::doAlignAndCut not okay!");
delete caic;
return false;
}
if (input_roi.length() > 0){
img_roi = new CImageBasis(input_roi);
if (!img_roi->ImageOkay()){
if (debugdetailanalog) LogFile.WriteToFile("ClassFlowAnalog::doAlignAndCut ImageRoi not okay!");
delete caic;
delete img_roi;
return false;
}
}
for (int i = 0; i < ROI.size(); ++i)
{
printf("Analog %d - Align&Cut\n", i);
output = "/sdcard/img_tmp/" + ROI[i]->name + ".jpg";
output = FormatFileName(output);
caic->CutAndSave(output, ROI[i]->posx, ROI[i]->posy, ROI[i]->deltax, ROI[i]->deltay);
rs = new CResizeImage(output);
if (!rs->ImageOkay()){
if (debugdetailanalog) LogFile.WriteToFile("ClassFlowAnalog::doAlignAndCut CResizeImage(output);!");
delete caic;
delete rs;
return false;
}
rs->Resize(modelxsize, modelysize);
ioresize = "/sdcard/img_tmp/ra" + std::to_string(i) + ".bmp";
ioresize = FormatFileName(ioresize);
rs->SaveToFile(ioresize);
delete rs;
if (img_roi)
{
int r = 0;
int g = 255;
int b = 0;
img_roi->drawRect(ROI[i]->posx, ROI[i]->posy, ROI[i]->deltax, ROI[i]->deltay, r, g, b, 1);
img_roi->drawCircle((int) (ROI[i]->posx + ROI[i]->deltax/2), (int) (ROI[i]->posy + ROI[i]->deltay/2), (int) (ROI[i]->deltax/2), r, g, b, 2);
img_roi->drawLine((int) (ROI[i]->posx + ROI[i]->deltax/2), (int) ROI[i]->posy, (int) (ROI[i]->posx + ROI[i]->deltax/2), (int) (ROI[i]->posy + ROI[i]->deltay), r, g, b, 2);
img_roi->drawLine((int) ROI[i]->posx, (int) (ROI[i]->posy + ROI[i]->deltay/2), (int) ROI[i]->posx + ROI[i]->deltax, (int) (ROI[i]->posy + ROI[i]->deltay/2), r, g, b, 2);
}
}
delete caic;
if (img_roi)
{
img_roi->SaveToFile(input_roi);
delete img_roi;
}
return true;
}
bool ClassFlowAnalog::doNeuralNetwork(string time)
{
string logPath = CreateLogFolder(time);
string input = "/sdcard/img_tmp/alg.jpg";
string ioresize = "/sdcard/img_tmp/resize.bmp";
string output;
input = FormatFileName(input);
#ifndef OHNETFLITE
CTfLiteClass *tflite = new CTfLiteClass;
string zwcnn = "/sdcard" + cnnmodelfile;
zwcnn = FormatFileName(zwcnn);
printf(zwcnn.c_str());printf("\n");
tflite->LoadModel(zwcnn);
tflite->MakeAllocate();
#endif
for (int i = 0; i < ROI.size(); ++i)
{
printf("Analog %d - TfLite\n", i);
ioresize = "/sdcard/img_tmp/ra" + std::to_string(i) + ".bmp";
ioresize = FormatFileName(ioresize);
float f1, f2;
f1 = 0; f2 = 0;
#ifndef OHNETFLITE
// LogFile.WriteToFile("ClassFlowAnalog::doNeuralNetwork vor CNN tflite->LoadInputImage(ioresize)");
tflite->LoadInputImage(ioresize);
tflite->Invoke();
if (debugdetailanalog) LogFile.WriteToFile("Nach Invoke");
f1 = tflite->GetOutputValue(0);
f2 = tflite->GetOutputValue(1);
#endif
float result = fmod(atan2(f1, f2) / (M_PI * 2) + 2, 1);
// printf("Result sin, cos, ziffer: %f, %f, %f\n", f1, f2, result);
ROI[i]->result = result * 10;
printf("Result Analog%i: %f\n", i, ROI[i]->result);
LogImage(logPath, ROI[i]->name, &ROI[i]->result, NULL, time);
}
#ifndef OHNETFLITE
delete tflite;
#endif
return true;
}
std::vector<HTMLInfo*> ClassFlowAnalog::GetHTMLInfo()
{
std::vector<HTMLInfo*> result;
for (int i = 0; i < ROI.size(); ++i)
{
HTMLInfo *zw = new HTMLInfo;
zw->filename = ROI[i]->name + ".jpg";
zw->val = ROI[i]->result;
result.push_back(zw);
}
return result;
}