Mirror/AI-on-the-edge-device
1
0
Fork 0
mirror of https://github.com/jomjol/AI-on-the-edge-device.git synced 2026-01-27 12:50:39 +03:00
Code Issues Packages Projects Releases Wiki Activity

Rolling 20210420

Browse Source
This commit is contained in:
jomjol
2021-04-20 19:44:16 +02:00
parent 520f818adc
commit ea2305de47
156 changed files with 11095 additions and 8601 deletions
Download Patch File Download Diff File Expand all files Collapse all files

45
code/components/jomjol_tfliteclass/CTfLiteClass.cpp
View File

@@ -6,9 +6,13 @@
// #define DEBUG_DETAIL_ON
//#define GET_MEMORY(X) malloc(X)
#define GET_MEMORY(X) heap_caps_malloc(X, MALLOC_CAP_SPIRAM)
float CTfLiteClass::GetOutputValue(int nr)
{
TfLiteTensor* output2 = this->interpreter->output(0);
TfLiteTensor* output2 = interpreter->output(0);
int numeroutput = output2->dims->data[1];
if ((nr+1) > numeroutput)
@@ -53,7 +57,7 @@ int CTfLiteClass::GetOutClassification()
void CTfLiteClass::GetInputDimension(bool silent = false)
{
TfLiteTensor* input2 = this->interpreter->input(0);
TfLiteTensor* input2 = interpreter->input(0);
int numdim = input2->dims->size;
if (!silent) printf("NumDimension: %d\n", numdim);
@@ -72,7 +76,7 @@ void CTfLiteClass::GetInputDimension(bool silent = false)
void CTfLiteClass::GetOutPut()
{
TfLiteTensor* output2 = this->interpreter->output(0);
TfLiteTensor* output2 = interpreter->output(0);
int numdim = output2->dims->size;
printf("NumDimension: %d\n", numdim);
@@ -142,20 +146,20 @@ void CTfLiteClass::MakeAllocate()
static tflite::AllOpsResolver resolver;
// printf(LogFile.getESPHeapInfo().c_str()); printf("\n");
this->interpreter = new tflite::MicroInterpreter(this->model, resolver, this->tensor_arena, this->kTensorArenaSize, this->error_reporter);
interpreter = new tflite::MicroInterpreter(model, resolver, tensor_arena, kTensorArenaSize, error_reporter);
// printf(LogFile.getESPHeapInfo().c_str()); printf("\n");
TfLiteStatus allocate_status = this->interpreter->AllocateTensors();
TfLiteStatus allocate_status = interpreter->AllocateTensors();
if (allocate_status != kTfLiteOk) {
TF_LITE_REPORT_ERROR(error_reporter, "AllocateTensors() failed");
this->GetInputDimension();
GetInputDimension();
return;
}
// printf("Allocate Done.\n");
}
void CTfLiteClass::GetInputTensorSize(){
float *zw = this->input;
float *zw = input;
int test = sizeof(zw);
#ifdef DEBUG_DETAIL_ON
printf("Input Tensor Dimension: %d\n", test);
@@ -211,36 +215,39 @@ unsigned char* CTfLiteClass::ReadFileToCharArray(std::string _fn)
void CTfLiteClass::LoadModel(std::string _fn){
#ifdef SUPRESS_TFLITE_ERRORS
this->error_reporter = new tflite::OwnMicroErrorReporter;
error_reporter = new tflite::OwnMicroErrorReporter;
#else
this->error_reporter = new tflite::MicroErrorReporter;
error_reporter = new tflite::MicroErrorReporter;
#endif
unsigned char *rd;
rd = ReadFileToCharArray(_fn.c_str());
this->model = tflite::GetModel(rd);
model = tflite::GetModel(rd);
free(rd);
TFLITE_MINIMAL_CHECK(model != nullptr);
MakeAllocate();
}
CTfLiteClass::CTfLiteClass()
{
this->model = nullptr;
this->interpreter = nullptr;
this->input = nullptr;
this->output = nullptr;
this->kTensorArenaSize = 200 * 1024; /// laut testfile: 108000 - bisher 600
this->tensor_arena = new uint8_t[kTensorArenaSize];
model = nullptr;
interpreter = nullptr;
input = nullptr;
output = nullptr;
kTensorArenaSize = 200 * 1024; /// laut testfile: 108000 - bisher 600
tensor_arena = (uint8_t*) GET_MEMORY(kTensorArenaSize);
// tensor_arena = new uint8_t[kTensorArenaSize];
}
CTfLiteClass::~CTfLiteClass()
{
delete this->tensor_arena;
delete this->interpreter;
delete this->error_reporter;
delete tensor_arena;
delete interpreter;
delete error_reporter;
}