mirror of
https://github.com/jomjol/AI-on-the-edge-device.git
synced 2025-12-07 12:06:58 +03:00
@@ -19,7 +19,7 @@ A 3d-printable housing can be found here: https://www.thingiverse.com/thing:4571
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### Known Issues
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* reboot on extensive web access due to the limits of the internal web server
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* Reboot on extensive web access due to the limits of the internal web server
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------
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@@ -1,39 +0,0 @@
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This directory is intended for project header files.
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A header file is a file containing C declarations and macro definitions
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to be shared between several project source files. You request the use of a
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header file in your project source file (C, C++, etc) located in `src` folder
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by including it, with the C preprocessing directive `#include'.
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```src/main.c
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#include "header.h"
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int main (void)
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{
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...
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}
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```
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Including a header file produces the same results as copying the header file
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into each source file that needs it. Such copying would be time-consuming
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and error-prone. With a header file, the related declarations appear
|
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in only one place. If they need to be changed, they can be changed in one
|
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place, and programs that include the header file will automatically use the
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new version when next recompiled. The header file eliminates the labor of
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finding and changing all the copies as well as the risk that a failure to
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find one copy will result in inconsistencies within a program.
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In C, the usual convention is to give header files names that end with `.h'.
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It is most portable to use only letters, digits, dashes, and underscores in
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header file names, and at most one dot.
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Read more about using header files in official GCC documentation:
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* Include Syntax
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* Include Operation
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* Once-Only Headers
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* Computed Includes
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https://gcc.gnu.org/onlinedocs/cpp/Header-Files.html
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254
code/lib/jomjol_tfliteclass/CTfLiteClass._cpp_old
Normal file
254
code/lib/jomjol_tfliteclass/CTfLiteClass._cpp_old
Normal file
@@ -0,0 +1,254 @@
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#include "CTfLiteClass.h"
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#include "bitmap_image.hpp"
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#include <sys/stat.h>
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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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int numeroutput = output2->dims->data[1];
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if ((nr+1) > numeroutput)
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return -1000;
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return output2->data.f[nr];
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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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// return 0;
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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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float zw_max = 0;
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float zw;
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int zw_class = -1;
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if (output2 == NULL)
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return -1;
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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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void CTfLiteClass::GetInputDimension(bool silent = false)
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{
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TfLiteTensor* input2 = this->interpreter->input(0);
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int numdim = input2->dims->size;
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if (!silent) printf("NumDimension: %d\n", numdim);
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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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void CTfLiteClass::GetOutPut()
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{
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TfLiteTensor* output2 = this->interpreter->output(0);
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int numdim = output2->dims->size;
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printf("NumDimension: %d\n", numdim);
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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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float fo;
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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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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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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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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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return true;
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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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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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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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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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printf("Allocate Done.\n");
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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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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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{
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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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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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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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unsigned char *result = (unsigned char*) malloc(size);
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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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return result;
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}
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void CTfLiteClass::LoadModel(std::string _fn){
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this->error_reporter = new tflite::MicroErrorReporter;
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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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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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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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// 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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CTfLiteClass::~CTfLiteClass()
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{
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delete this->tensor_arena;
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}
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72
code/lib/jomjol_tfliteclass/CTfLiteClass._h_old
Normal file
72
code/lib/jomjol_tfliteclass/CTfLiteClass._h_old
Normal file
@@ -0,0 +1,72 @@
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#pragma once
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#ifndef __CFINDTEMPLATE
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#define __CFINGTEMPLATE
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#define TFLITE_MINIMAL_CHECK(x) \
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if (!(x)) { \
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fprintf(stderr, "Error at %s:%d\n", __FILE__, __LINE__); \
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exit(1); \
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}
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//#include "CAccessSD.h"
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#include "CFindTemplate.h"
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#include "tensorflow/lite/micro/kernels/all_ops_resolver.h"
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#include "tensorflow/lite/micro/micro_error_reporter.h"
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#include "tensorflow/lite/micro/micro_interpreter.h"
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#include "tensorflow/lite/schema/schema_generated.h"
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#include "tensorflow/lite/version.h"
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#include "tensorflow/lite/micro/kernels/micro_ops.h"
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#include "esp_err.h"
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#include "esp_log.h"
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//extern CAccessSDClass accessSD;
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class CTfLiteClass
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{
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protected:
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// CAccessSDClass *accessSD;
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tflite::ErrorReporter* error_reporter;
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const tflite::Model* model;
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tflite::MicroInterpreter* interpreter;
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// TfLiteTensor* input = nullptr;
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TfLiteTensor* output = nullptr;
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static tflite::ops::micro::AllOpsResolver *resolver;
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tflite::MicroOpResolver<5> micro_op_resolver;
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int kTensorArenaSize;
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uint8_t *tensor_arena;
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float* input;
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int input_i;
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|
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int im_height, im_width, im_channel;
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|
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long GetFileSize(std::string filename);
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unsigned char* ReadFileToCharArray(std::string _fn);
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|
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public:
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// CTfLiteClass(CAccessSDClass *_accessSD);
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CTfLiteClass();
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~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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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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float GetOutputValue(int nr);
|
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void GetInputDimension(bool silent);
|
||||
|
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};
|
||||
|
||||
|
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#endif
|
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@@ -1,4 +1,4 @@
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const char* GIT_REV="707472b";
|
||||
const char* GIT_REV="de772d7";
|
||||
const char* GIT_TAG="";
|
||||
const char* GIT_BRANCH="rolling";
|
||||
const char* BUILD_TIME="2020-11-15 11:59";
|
||||
const char* BUILD_TIME="2020-11-15 12:29";
|
||||
@@ -13,7 +13,7 @@ extern "C"
|
||||
#include "Helper.h"
|
||||
#include <fstream>
|
||||
|
||||
const char* GIT_BASE_BRANCH = "master - v4.0.0 - 2020-11-15";
|
||||
const char* GIT_BASE_BRANCH = "master - v3.1.0 - 2020-10-26";
|
||||
|
||||
|
||||
const char* git_base_branch(void)
|
||||
|
||||
0
code/src/zip._c
Normal file
0
code/src/zip._c
Normal file
@@ -1,4 +1,4 @@
|
||||
const char* GIT_REV="707472b";
|
||||
const char* GIT_REV="de772d7";
|
||||
const char* GIT_TAG="";
|
||||
const char* GIT_BRANCH="rolling";
|
||||
const char* BUILD_TIME="2020-11-15 11:59";
|
||||
const char* BUILD_TIME="2020-11-15 12:29";
|
||||
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Reference in New Issue
Block a user