mirror of
https://github.com/jomjol/AI-on-the-edge-device.git
synced 2025-12-08 04:26:58 +03:00
Merge branch 'rolling' of https://github.com/jomjol/AI-on-the-edge-device into rolling
This commit is contained in:
Zwer2k
@@ -1,350 +0,0 @@
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#include "ClassFlowAnalog.h"
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#include <math.h>
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#include <iomanip>
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#include <sys/types.h>
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#include <sstream> // std::stringstream
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// #define OHNETFLITE
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#ifndef OHNETFLITE
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#include "CTfLiteClass.h"
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#endif
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#include "ClassLogFile.h"
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static const char* TAG = "flow_analog";
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bool debugdetailanalog = false;
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void ClassFlowAnalog::SetInitialParameter(void)
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{
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string cnnmodelfile = "";
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modelxsize = 1;
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modelysize = 1;
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ListFlowControll = NULL;
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previousElement = NULL;
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SaveAllFiles = false;
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disabled = false;
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extendedResolution = false;
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}
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ClassFlowAnalog::ClassFlowAnalog(std::vector<ClassFlow*>* lfc) : ClassFlowImage(lfc, TAG)
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{
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SetInitialParameter();
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ListFlowControll = lfc;
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for (int i = 0; i < ListFlowControll->size(); ++i)
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{
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if (((*ListFlowControll)[i])->name().compare("ClassFlowAlignment") == 0)
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{
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flowpostalignment = (ClassFlowAlignment*) (*ListFlowControll)[i];
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}
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}
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}
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int ClassFlowAnalog::AnzahlROIs()
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{
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int zw = ROI.size();
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if (extendedResolution)
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zw++;
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return zw;
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}
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string ClassFlowAnalog::getReadout()
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{
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string result = "";
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if (ROI.size() == 0)
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return result;
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float zahl = ROI[ROI.size() - 1]->result;
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int ergebnis_nachkomma = ((int) floor(zahl * 10)) % 10;
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int prev = -1;
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prev = ZeigerEval(ROI[ROI.size() - 1]->result, prev);
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result = std::to_string(prev);
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if (extendedResolution)
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result = result + std::to_string(ergebnis_nachkomma);
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for (int i = ROI.size() - 2; i >= 0; --i)
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{
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prev = ZeigerEval(ROI[i]->result, prev);
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result = std::to_string(prev) + result;
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}
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return result;
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}
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int ClassFlowAnalog::ZeigerEval(float zahl, int ziffer_vorgaenger)
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{
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int ergebnis_nachkomma = ((int) floor(zahl * 10)) % 10;
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int ergebnis_vorkomma = ((int) floor(zahl)) % 10;
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int ergebnis, ergebnis_rating;
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if (ziffer_vorgaenger == -1)
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return ergebnis_vorkomma % 10;
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ergebnis_rating = ergebnis_nachkomma - ziffer_vorgaenger;
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if (ergebnis_nachkomma >= 5)
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ergebnis_rating-=5;
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else
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ergebnis_rating+=5;
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ergebnis = (int) round(zahl);
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if (ergebnis_rating < 0)
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ergebnis-=1;
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if (ergebnis == -1)
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ergebnis+=10;
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ergebnis = ergebnis % 10;
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return ergebnis;
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}
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bool ClassFlowAnalog::ReadParameter(FILE* pfile, string& aktparamgraph)
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{
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std::vector<string> zerlegt;
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aktparamgraph = trim(aktparamgraph);
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if (aktparamgraph.size() == 0)
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if (!this->GetNextParagraph(pfile, aktparamgraph))
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return false;
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if ((aktparamgraph.compare("[Analog]") != 0) && (aktparamgraph.compare(";[Analog]") != 0)) // Paragraph passt nich zu MakeImage
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return false;
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if (aktparamgraph[0] == ';')
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{
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disabled = true;
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while (getNextLine(pfile, &aktparamgraph) && !isNewParagraph(aktparamgraph));
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printf("[Analog] is disabled !!!\n");
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return true;
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}
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while (this->getNextLine(pfile, &aktparamgraph) && !this->isNewParagraph(aktparamgraph))
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{
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zerlegt = this->ZerlegeZeile(aktparamgraph);
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if ((zerlegt[0] == "LogImageLocation") && (zerlegt.size() > 1))
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{
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this->LogImageLocation = "/sdcard" + zerlegt[1];
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this->isLogImage = true;
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}
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if ((toUpper(zerlegt[0]) == "LOGFILERETENTIONINDAYS") && (zerlegt.size() > 1))
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{
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this->logfileRetentionInDays = std::stoi(zerlegt[1]);
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}
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if ((zerlegt[0] == "Model") && (zerlegt.size() > 1))
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{
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this->cnnmodelfile = zerlegt[1];
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}
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if ((zerlegt[0] == "ModelInputSize") && (zerlegt.size() > 2))
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{
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this->modelxsize = std::stoi(zerlegt[1]);
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this->modelysize = std::stoi(zerlegt[2]);
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}
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if (zerlegt.size() >= 5)
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{
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roianalog* neuroi = new roianalog;
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neuroi->name = zerlegt[0];
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neuroi->posx = std::stoi(zerlegt[1]);
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neuroi->posy = std::stoi(zerlegt[2]);
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neuroi->deltax = std::stoi(zerlegt[3]);
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neuroi->deltay = std::stoi(zerlegt[4]);
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neuroi->result = -1;
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neuroi->image = NULL;
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neuroi->image_org = NULL;
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ROI.push_back(neuroi);
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}
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if ((toUpper(zerlegt[0]) == "SAVEALLFILES") && (zerlegt.size() > 1))
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{
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if (toUpper(zerlegt[1]) == "TRUE")
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SaveAllFiles = true;
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}
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if ((toUpper(zerlegt[0]) == "EXTENDEDRESOLUTION") && (zerlegt.size() > 1))
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{
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if (toUpper(zerlegt[1]) == "TRUE")
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extendedResolution = true;
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}
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}
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for (int i = 0; i < ROI.size(); ++i)
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{
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ROI[i]->image = new CImageBasis(modelxsize, modelysize, 3);
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ROI[i]->image_org = new CImageBasis(ROI[i]->deltax, ROI[i]->deltay, 3);
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}
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return true;
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}
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string ClassFlowAnalog::getHTMLSingleStep(string host)
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{
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string result, zw;
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std::vector<HTMLInfo*> htmlinfo;
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result = "<p>Found ROIs: </p> <p><img src=\"" + host + "/img_tmp/alg_roi.jpg\"></p>\n";
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result = result + "Analog Pointers: <p> ";
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htmlinfo = GetHTMLInfo();
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for (int i = 0; i < htmlinfo.size(); ++i)
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{
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std::stringstream stream;
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stream << std::fixed << std::setprecision(1) << htmlinfo[i]->val;
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zw = stream.str();
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result = result + "<img src=\"" + host + "/img_tmp/" + htmlinfo[i]->filename + "\"> " + zw;
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delete htmlinfo[i];
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}
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htmlinfo.clear();
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return result;
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}
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bool ClassFlowAnalog::doFlow(string time)
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{
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if (disabled)
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return true;
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if (!doAlignAndCut(time)){
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return false;
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};
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if (debugdetailanalog) LogFile.WriteToFile("ClassFlowAnalog::doFlow nach Alignment");
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doNeuralNetwork(time);
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RemoveOldLogs();
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return true;
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}
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bool ClassFlowAnalog::doAlignAndCut(string time)
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{
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if (disabled)
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return true;
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CAlignAndCutImage *caic = flowpostalignment->GetAlignAndCutImage();
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for (int i = 0; i < ROI.size(); ++i)
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{
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printf("Analog %d - Align&Cut\n", i);
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caic->CutAndSave(ROI[i]->posx, ROI[i]->posy, ROI[i]->deltax, ROI[i]->deltay, ROI[i]->image_org);
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if (SaveAllFiles) ROI[i]->image_org->SaveToFile(FormatFileName("/sdcard/img_tmp/" + ROI[i]->name + ".jpg"));
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ROI[i]->image_org->Resize(modelxsize, modelysize, ROI[i]->image);
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if (SaveAllFiles) ROI[i]->image->SaveToFile(FormatFileName("/sdcard/img_tmp/" + ROI[i]->name + ".bmp"));
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}
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return true;
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}
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void ClassFlowAnalog::DrawROI(CImageBasis *_zw)
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{
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int r = 0;
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int g = 255;
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int b = 0;
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for (int i = 0; i < ROI.size(); ++i)
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{
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_zw->drawRect(ROI[i]->posx, ROI[i]->posy, ROI[i]->deltax, ROI[i]->deltay, r, g, b, 1);
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_zw->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);
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_zw->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);
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_zw->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);
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}
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}
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bool ClassFlowAnalog::doNeuralNetwork(string time)
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{
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if (disabled)
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return true;
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string logPath = CreateLogFolder(time);
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string input = "/sdcard/img_tmp/alg.jpg";
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string ioresize = "/sdcard/img_tmp/resize.bmp";
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string output;
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input = FormatFileName(input);
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#ifndef OHNETFLITE
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CTfLiteClass *tflite = new CTfLiteClass;
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string zwcnn = "/sdcard" + cnnmodelfile;
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zwcnn = FormatFileName(zwcnn);
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printf(zwcnn.c_str());printf("\n");
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tflite->LoadModel(zwcnn);
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tflite->MakeAllocate();
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#endif
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for (int i = 0; i < ROI.size(); ++i)
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{
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printf("Analog %d - TfLite\n", i);
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ioresize = "/sdcard/img_tmp/ra" + std::to_string(i) + ".bmp";
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ioresize = FormatFileName(ioresize);
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float f1, f2;
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f1 = 0; f2 = 0;
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#ifndef OHNETFLITE
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// LogFile.WriteToFile("ClassFlowAnalog::doNeuralNetwork vor CNN tflite->LoadInputImage(ioresize)");
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// tflite->LoadInputImage(ioresize);
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tflite->LoadInputImageBasis(ROI[i]->image);
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tflite->Invoke();
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if (debugdetailanalog) LogFile.WriteToFile("Nach Invoke");
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f1 = tflite->GetOutputValue(0);
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f2 = tflite->GetOutputValue(1);
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#endif
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float result = fmod(atan2(f1, f2) / (M_PI * 2) + 2, 1);
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// printf("Result sin, cos, ziffer: %f, %f, %f\n", f1, f2, result);
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ROI[i]->result = result * 10;
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printf("Result Analog%i: %f\n", i, ROI[i]->result);
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if (isLogImage)
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{
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LogImage(logPath, ROI[i]->name, &ROI[i]->result, NULL, time, ROI[i]->image_org);
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}
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}
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#ifndef OHNETFLITE
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delete tflite;
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#endif
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return true;
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}
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std::vector<HTMLInfo*> ClassFlowAnalog::GetHTMLInfo()
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{
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std::vector<HTMLInfo*> result;
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for (int i = 0; i < ROI.size(); ++i)
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{
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HTMLInfo *zw = new HTMLInfo;
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zw->filename = ROI[i]->name + ".bmp";
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zw->filename_org = ROI[i]->name + ".jpg";
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zw->val = ROI[i]->result;
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zw->image = ROI[i]->image;
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zw->image_org = ROI[i]->image_org;
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result.push_back(zw);
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}
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return result;
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}
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@@ -1,48 +0,0 @@
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#pragma once
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#include "ClassFlowImage.h"
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#include "ClassFlowAlignment.h"
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// #include "CTfLiteClass.h"
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struct roianalog {
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int posx, posy, deltax, deltay;
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float result;
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CImageBasis *image, *image_org;
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string name;
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};
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class ClassFlowAnalog :
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public ClassFlowImage
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{
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protected:
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std::vector<roianalog*> ROI;
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string cnnmodelfile;
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int modelxsize, modelysize;
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int ZeigerEval(float zahl, int ziffer_vorgaenger);
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bool SaveAllFiles;
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ClassFlowAlignment* flowpostalignment;
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void SetInitialParameter(void);
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public:
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bool extendedResolution;
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ClassFlowAnalog(std::vector<ClassFlow*>* lfc);
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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();
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void DrawROI(CImageBasis *_zw);
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bool doNeuralNetwork(string time);
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bool doAlignAndCut(string time);
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std::vector<HTMLInfo*> GetHTMLInfo();
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int AnzahlROIs();
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string name(){return "ClassFlowAnalog";};
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};
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@@ -174,6 +174,15 @@ bool ClassFlowMQTT::doFlow(string zwtime)
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zw = namenumber + "timestamp";
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MQTTPublish(zw, resulttimestamp);
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std::string json="{\"value\":"+result;
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json += ",\"error\":\""+resulterror;
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json += "\",\"rate\":"+resultrate;
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json += ",\"timestamp\":\""+resulttimestamp+"\"}";
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zw = namenumber + "json";
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MQTTPublish(zw, json);
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}
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}
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else
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Reference in New Issue
Block a user