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jomjol
2020-12-22 08:08:07 +01:00
parent f5c28107d4
commit b418525b3b
39 changed files with 1173 additions and 501 deletions
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55
code/components/jomjol_tfliteclass/CTfLiteClass.cpp
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@@ -21,6 +21,18 @@ float CTfLiteClass::GetOutputValue(int nr)
return output2->data.f[nr];
}
int CTfLiteClass::GetClassFromImageBasis(CImageBasis *rs)
{
// printf("Before Load image %s\n", _fn.c_str());
if (!LoadInputImageBasis(rs))
return -1000;
Invoke();
printf("After Invoke \n");
return GetOutClassification();
}
int CTfLiteClass::GetClassFromImage(std::string _fn)
{
@@ -33,7 +45,6 @@ int CTfLiteClass::GetClassFromImage(std::string _fn)
printf("After Invoke %s\n", _fn.c_str());
return GetOutClassification();
// return 0;
}
int CTfLiteClass::GetOutClassification()
@@ -113,6 +124,46 @@ void CTfLiteClass::Invoke()
}
bool CTfLiteClass::LoadInputImageBasis(CImageBasis *rs)
{
std::string zw = "ClassFlowAnalog::doNeuralNetwork nach LoadInputResizeImage: ";
// LogFile.WriteToFile(zw);
unsigned int w = rs->width;
unsigned int h = rs->height;
unsigned char red, green, blue;
// printf("Image: %s size: %d x %d\n", _fn.c_str(), w, h);
input_i = 0;
float* input_data_ptr = (interpreter->input(0))->data.f;
for (int y = 0; y < h; ++y)
for (int x = 0; x < w; ++x)
{
red = rs->GetPixelColor(x, y, 0);
green = rs->GetPixelColor(x, y, 1);
blue = rs->GetPixelColor(x, y, 2);
*(input_data_ptr) = (float) red;
input_data_ptr++;
*(input_data_ptr) = (float) green;
input_data_ptr++;
*(input_data_ptr) = (float) blue;
input_data_ptr++;
// printf("BMP: %f %f %f\n", (float) red, (float) green, (float) blue);
}
if (debugdetailtflite) LogFile.WriteToFile("Nach dem Laden in input");
return true;
}
bool CTfLiteClass::LoadInputImage(std::string _fn)
{
std::string zw = "ClassFlowAnalog::doNeuralNetwork nach Load Image: " + _fn;
@@ -239,7 +290,7 @@ CTfLiteClass::CTfLiteClass()
this->interpreter = nullptr;
this->input = nullptr;
this->output = nullptr;
this->kTensorArenaSize = 600 * 1024;
this->kTensorArenaSize = 150 * 1024; /// laut testfile: 108000 - bisher 600
this->tensor_arena = new uint8_t[kTensorArenaSize];
}