mirror of
https://github.com/jomjol/AI-on-the-edge-device.git
synced 2025-12-08 12:36:52 +03:00
Waitmissing for missing memory
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@@ -116,7 +116,7 @@ string ClassFlowAlignment::getHTMLSingleStep(string host)
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bool ClassFlowAlignment::doFlow(string time)
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{
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if (!ImageTMP)
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ImageTMP = new CImageBasis(ImageBasis);
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ImageTMP = new CImageBasis(ImageBasis, 5);
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if (AlignAndCutImage)
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delete AlignAndCutImage;
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@@ -23,7 +23,7 @@ void ClassFlowAnalog::SetInitialParameter(void)
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modelysize = 1;
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ListFlowControll = NULL;
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previousElement = NULL;
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SaveAllFiles = true;
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SaveAllFiles = false;
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}
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ClassFlowAnalog::ClassFlowAnalog(std::vector<ClassFlow*>* lfc) : ClassFlowImage(lfc, TAG)
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@@ -202,15 +202,11 @@ bool ClassFlowControll::doFlow(string time)
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/////////////////////////////////////////////////////
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int aInternalFreeHeapSizeAtEnd, aInternalFreeHeapSizeAtStart;
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aInternalFreeHeapSizeAtStart = getInternalESPHeapSize();
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if (flowcontrolldebugdetail){
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std::string aStartEspInfoStr = "ClassFlowAnalog::doFlow - Start: " + getESPHeapInfo();
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LogFile.WriteToFile(aStartEspInfoStr);
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}
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aInternalFreeHeapSizeAtEnd = getInternalESPHeapSize();
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if (flowcontrolldebugdetail){
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std::string aStartEspInfoStr = "ClassFlowAnalog::doFlow - Now : " + getESPHeapInfo();
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LogFile.WriteToFile(aStartEspInfoStr);
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@@ -241,7 +237,6 @@ bool ClassFlowControll::doFlow(string time)
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result = true;
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}
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aInternalFreeHeapSizeAtEnd = getInternalESPHeapSize();
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if (flowcontrolldebugdetail){
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std::string aStartEspInfoStr = "ClassFlowAnalog::doFlow - Now : " + getESPHeapInfo();
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LogFile.WriteToFile(aStartEspInfoStr);
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@@ -24,7 +24,7 @@ void ClassFlowDigit::SetInitialParameter(void)
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modelysize = 1;
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ListFlowControll = NULL;
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previousElement = NULL;
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SaveAllFiles = true;
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SaveAllFiles = false;
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}
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ClassFlowDigit::ClassFlowDigit() : ClassFlowImage(TAG)
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@@ -283,7 +283,7 @@ void CImageBasis::LoadFromMemory(stbi_uc *_buffer, int len)
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}
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CImageBasis::CImageBasis(CImageBasis *_copyfrom)
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CImageBasis::CImageBasis(CImageBasis *_copyfrom, int _anzrepeat)
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{
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externalImage = false;
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channels = _copyfrom->channels;
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@@ -293,6 +293,18 @@ CImageBasis::CImageBasis(CImageBasis *_copyfrom)
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int memsize = width * height * channels;
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rgb_image = (unsigned char*)GET_MEMORY(memsize);
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int anz = 1;
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TickType_t xDelay;
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while (!rgb_image && (anz < _anzrepeat))
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{
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printf("Create Image from Copy - Speicher ist voll - Versuche es erneut: %d.\n", anz);
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xDelay = 1000 / portTICK_PERIOD_MS;
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rgb_image = (unsigned char*) malloc(memsize);
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anz++;
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}
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if (!rgb_image)
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{
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printf(getESPHeapInfo().c_str());
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@@ -65,7 +65,7 @@ class CImageBasis
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CImageBasis(std::string _image);
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CImageBasis(uint8_t* _rgb_image, int _channels, int _width, int _height, int _bpp);
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CImageBasis(int _width, int _height, int _channels);
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CImageBasis(CImageBasis *_copyfrom);
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CImageBasis(CImageBasis *_copyfrom, int _anzrepeat = 0);
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void Resize(int _new_dx, int _new_dy);
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void Resize(int _new_dx, int _new_dy, CImageBasis *_target);
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@@ -1,9 +1,8 @@
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#include "CTfLiteClass.h"
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#include "bitmap_image.hpp"
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// #include "bitmap_image.hpp"
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#include "ClassLogFile.h"
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#include "Helper.h"
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#include <sys/stat.h>
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@@ -33,20 +32,6 @@ int CTfLiteClass::GetClassFromImageBasis(CImageBasis *rs)
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return GetOutClassification();
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}
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int CTfLiteClass::GetClassFromImage(std::string _fn)
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{
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// printf("Before Load image %s\n", _fn.c_str());
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if (!LoadInputImage(_fn))
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return -1000;
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// printf("After Load image %s\n", _fn.c_str());
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Invoke();
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printf("After Invoke %s\n", _fn.c_str());
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return GetOutClassification();
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}
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int CTfLiteClass::GetOutClassification()
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{
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TfLiteTensor* output2 = interpreter->output(0);
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@@ -128,13 +113,10 @@ void CTfLiteClass::Invoke()
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bool CTfLiteClass::LoadInputImageBasis(CImageBasis *rs)
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{
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std::string zw = "ClassFlowAnalog::doNeuralNetwork nach LoadInputResizeImage: ";
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// LogFile.WriteToFile(zw);
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unsigned int w = rs->width;
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unsigned int h = rs->height;
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unsigned char red, green, blue;
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// printf("Image: %s size: %d x %d\n", _fn.c_str(), w, h);
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input_i = 0;
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@@ -152,49 +134,6 @@ bool CTfLiteClass::LoadInputImageBasis(CImageBasis *rs)
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input_data_ptr++;
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*(input_data_ptr) = (float) blue;
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input_data_ptr++;
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// printf("BMP: %f %f %f\n", (float) red, (float) green, (float) blue);
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}
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if (debugdetailtflite) LogFile.WriteToFile("Nach dem Laden in input");
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return true;
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}
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bool CTfLiteClass::LoadInputImage(std::string _fn)
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{
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std::string zw = "ClassFlowAnalog::doNeuralNetwork nach Load Image: " + _fn;
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// LogFile.WriteToFile(zw);
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bitmap_image image(_fn);
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if (debugdetailtflite) LogFile.WriteToFile(zw);
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unsigned int w = image.width();
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unsigned int h = image.height();
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unsigned char red, green, blue;
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// printf("Image: %s size: %d x %d\n", _fn.c_str(), w, h);
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input_i = 0;
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float* input_data_ptr = (interpreter->input(0))->data.f;
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for (int y = 0; y < h; ++y)
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for (int x = 0; x < w; ++x)
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{
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red = image.red_channel(x, y);
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green = image.green_channel(x, y);
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blue = image.blue_channel(x, y);
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*(input_data_ptr) = (float) red;
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input_data_ptr++;
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*(input_data_ptr) = (float) green;
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input_data_ptr++;
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*(input_data_ptr) = (float) blue;
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input_data_ptr++;
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// printf("BMP: %f %f %f\n", (float) red, (float) green, (float) blue);
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}
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if (debugdetailtflite) LogFile.WriteToFile("Nach dem Laden in input");
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@@ -205,7 +144,6 @@ bool CTfLiteClass::LoadInputImage(std::string _fn)
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void CTfLiteClass::MakeAllocate()
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{
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// static tflite::ops::micro::AllOpsResolver resolver;
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static tflite::AllOpsResolver resolver;
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this->interpreter = new tflite::MicroInterpreter(this->model, resolver, this->tensor_arena, this->kTensorArenaSize, this->error_reporter);
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@@ -215,7 +153,6 @@ void CTfLiteClass::MakeAllocate()
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this->GetInputDimension();
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return;
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}
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// printf("Allocate Done.\n");
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}
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@@ -223,8 +160,6 @@ void CTfLiteClass::GetInputTensorSize(){
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float *zw = this->input;
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int test = sizeof(zw);
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printf("Input Tensor Dimension: %d\n", test);
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printf("Input Tensor Dimension: %d\n", test);
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}
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long CTfLiteClass::GetFileSize(std::string filename)
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@@ -239,7 +174,7 @@ unsigned char* CTfLiteClass::ReadFileToCharArray(std::string _fn)
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{
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long size;
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size = this->GetFileSize(_fn);
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size = GetFileSize(_fn);
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if (size == -1)
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{
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@@ -247,16 +182,25 @@ unsigned char* CTfLiteClass::ReadFileToCharArray(std::string _fn)
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return NULL;
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}
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unsigned char *result = (unsigned char*) malloc(size);
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int anz = 1;
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TickType_t xDelay;
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while (!result && (anz < 6)) // maximal 5x versuchen (= 5s)
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{
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printf("Speicher ist voll - Versuche es erneut: %d.\n", anz);
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xDelay = 1000 / portTICK_PERIOD_MS;
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result = (unsigned char*) malloc(size);
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anz++;
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}
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if(result != NULL) {
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if(result != NULL) {
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// printf("\nSpeicher ist reserviert\n");
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FILE* f = OpenFileAndWait(_fn.c_str(), "rb"); // vorher nur "r"
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fread(result, 1, size, f);
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fclose(f);
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}else {
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printf("\nKein freier Speicher vorhanden.\n");
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}else {
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printf("\nKein freier Speicher vorhanden.\n");
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}
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@@ -272,14 +216,11 @@ void CTfLiteClass::LoadModel(std::string _fn){
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#endif
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unsigned char *rd;
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rd = this->ReadFileToCharArray(_fn.c_str());
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// printf("loadedfile: %d", (int) rd);
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rd = ReadFileToCharArray(_fn.c_str());
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this->model = tflite::GetModel(rd);
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free(rd);
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TFLITE_MINIMAL_CHECK(model != nullptr);
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// printf("tfile Loaded.\n");
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}
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@@ -308,6 +249,6 @@ namespace tflite {
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return 0;
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}
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} // namespace tflite
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}
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@@ -41,7 +41,6 @@ class CTfLiteClass
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const tflite::Model* model;
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tflite::MicroInterpreter* interpreter;
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TfLiteTensor* output = nullptr;
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// static tflite::ops::micro::AllOpsResolver *resolver;
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static tflite::AllOpsResolver resolver;
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int kTensorArenaSize;
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@@ -60,12 +59,10 @@ class CTfLiteClass
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void LoadModel(std::string _fn);
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void MakeAllocate();
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void GetInputTensorSize();
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bool LoadInputImage(std::string _fn);
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bool LoadInputImageBasis(CImageBasis *rs);
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void Invoke();
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void GetOutPut();
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int GetOutClassification();
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int GetClassFromImage(std::string _fn);
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int GetClassFromImageBasis(CImageBasis *rs);
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float GetOutputValue(int nr);
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