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@@ -0,0 +1,254 @@
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+#include "CTfLiteClass.h"
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+
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+#include "bitmap_image.hpp"
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+
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+#include <sys/stat.h>
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+
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+float CTfLiteClass::GetOutputValue(int nr)
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+{
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+ TfLiteTensor* output2 = this->interpreter->output(0);
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+
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+ int numeroutput = output2->dims->data[1];
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+ if ((nr+1) > numeroutput)
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+ return -1000;
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+
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+ return output2->data.f[nr];
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+}
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+
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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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+
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+ Invoke();
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+ printf("After Invoke %s\n", _fn.c_str());
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+
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+ return GetOutClassification();
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+// return 0;
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+}
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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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+
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+ float zw_max = 0;
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+ float zw;
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+ int zw_class = -1;
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+
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+ if (output2 == NULL)
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+ return -1;
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+
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+ int numeroutput = output2->dims->data[1];
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+ for (int i = 0; i < numeroutput; ++i)
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+ {
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+ zw = output2->data.f[i];
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+ if (zw > zw_max)
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+ {
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+ zw_max = zw;
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+ zw_class = i;
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+ }
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+ }
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+// printf("Result Ziffer: %d\n", zw_class);
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+ return zw_class;
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+}
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+
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+void CTfLiteClass::GetInputDimension(bool silent = false)
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+{
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+ TfLiteTensor* input2 = this->interpreter->input(0);
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+
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+ int numdim = input2->dims->size;
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+ if (!silent) printf("NumDimension: %d\n", numdim);
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+
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+ int sizeofdim;
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+ for (int j = 0; j < numdim; ++j)
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+ {
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+ sizeofdim = input2->dims->data[j];
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+ if (!silent) printf("SizeOfDimension %d: %d\n", j, sizeofdim);
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+ if (j == 1) im_height = sizeofdim;
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+ if (j == 2) im_width = sizeofdim;
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+ if (j == 3) im_channel = sizeofdim;
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+ }
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+}
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+
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+
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+void CTfLiteClass::GetOutPut()
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+{
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+ TfLiteTensor* output2 = this->interpreter->output(0);
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+
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+ int numdim = output2->dims->size;
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+ printf("NumDimension: %d\n", numdim);
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+
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+ int sizeofdim;
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+ for (int j = 0; j < numdim; ++j)
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+ {
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+ sizeofdim = output2->dims->data[j];
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+ printf("SizeOfDimension %d: %d\n", j, sizeofdim);
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+ }
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+
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+
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+ float fo;
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+
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+ // Process the inference results.
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+ int numeroutput = output2->dims->data[1];
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+ for (int i = 0; i < numeroutput; ++i)
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+ {
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+ fo = output2->data.f[i];
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+ printf("Result %d: %f\n", i, fo);
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+ }
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+}
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+
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+void CTfLiteClass::Invoke()
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+{
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+ interpreter->Invoke();
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+// printf("Invoke Done.\n");
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+}
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+
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+
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+bool CTfLiteClass::LoadInputImage(std::string _fn)
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+{
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+ bitmap_image image(_fn);
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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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+
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+ input_i = 0;
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+ float* input_data_ptr = (interpreter->input(0))->data.f;
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+
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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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+
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+// printf("BMP: %f %f %f\n", (float) red, (float) green, (float) blue);
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+
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+ }
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+ return true;
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+}
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+
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+
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+void CTfLiteClass::MakeAllocate()
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+{
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+/*
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+ this->micro_op_resolver.AddBuiltin(
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+ tflite::BuiltinOperator_RESHAPE,
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+ tflite::ops::micro::Register_RESHAPE());
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+ this->micro_op_resolver.AddBuiltin(tflite::BuiltinOperator_CONV_2D,
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+ tflite::ops::micro::Register_CONV_2D());
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+ this->micro_op_resolver.AddBuiltin(tflite::BuiltinOperator_FULLY_CONNECTED,
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+ tflite::ops::micro::Register_FULLY_CONNECTED());
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+ this->micro_op_resolver.AddBuiltin(tflite::BuiltinOperator_SOFTMAX,
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+ tflite::ops::micro::Register_SOFTMAX());
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+ this->micro_op_resolver.AddBuiltin(tflite::BuiltinOperator_DEPTHWISE_CONV_2D,
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+ tflite::ops::micro::Register_DEPTHWISE_CONV_2D());
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+
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+
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+ this->interpreter = new tflite::MicroInterpreter(this->model, this->micro_op_resolver, this->tensor_arena, this->kTensorArenaSize, this->error_reporter);
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+*/
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+
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+
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+ static tflite::ops::micro::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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+
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+ TfLiteStatus allocate_status = this->interpreter->AllocateTensors();
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+ if (allocate_status != kTfLiteOk) {
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+ TF_LITE_REPORT_ERROR(error_reporter, "AllocateTensors() failed");
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+ this->GetInputDimension();
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+ return;
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+ }
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+
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+ printf("Allocate Done.\n");
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+}
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+
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+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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+
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+ printf("Input Tensor Dimension: %d\n", test);
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+}
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+
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+long CTfLiteClass::GetFileSize(std::string filename)
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+{
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+ struct stat stat_buf;
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+ long rc = stat(filename.c_str(), &stat_buf);
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+ return rc == 0 ? stat_buf.st_size : -1;
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+}
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+
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+
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+unsigned char* CTfLiteClass::ReadFileToCharArray(std::string _fn)
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+{
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+ long size;
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+
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+ size = this->GetFileSize(_fn);
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+
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+ if (size == -1)
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+ {
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+ printf("\nFile existiert nicht.\n");
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+ return NULL;
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+ }
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+
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+
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+ unsigned char *result = (unsigned char*) malloc(size);
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+
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+ if(result != NULL) {
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+// printf("\nSpeicher ist reserviert\n");
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+ FILE* f = fopen(_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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+ }
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+
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+
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+ return result;
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+}
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+
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+void CTfLiteClass::LoadModel(std::string _fn){
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+
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+
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+ this->error_reporter = new tflite::MicroErrorReporter;
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+
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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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+
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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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+}
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+
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+
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+
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+CTfLiteClass::CTfLiteClass()
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+{
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+// this->accessSD = _accessSD;
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+ this->model = nullptr;
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+ this->interpreter = nullptr;
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+ this->input = nullptr;
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+ this->output = nullptr;
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+ this->kTensorArenaSize = 600 * 1024;
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+ this->tensor_arena = new uint8_t[kTensorArenaSize];
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+
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+// micro_op_resolver.AddBuiltin(tflite::BuiltinOperator_CONV_2D,
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+// tflite::ops::micro::Register_CONV_2D());
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+}
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+
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+CTfLiteClass::~CTfLiteClass()
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+{
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+ delete this->tensor_arena;
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+}
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+
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+
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