Rolling 20210910

code/components/jomjol_tfliteclass/CTfLiteClass.cpp

@@ -28,6 +28,48 @@ int CTfLiteClass::GetClassFromImageBasis(CImageBasis *rs)
     return GetOutClassification();
 }
 
+
+int CTfLiteClass::GetOutClassification(int _von, int _bis)
+{
+  TfLiteTensor* output2 = interpreter->output(0);
+
+  float zw_max;
+  float zw;
+  int zw_class;
+
+  if (output2 == NULL)
+    return -1;
+
+  int numeroutput = output2->dims->data[1];
+  //printf("\n number output neurons: %d\n\n", numeroutput);
+
+  if (_bis == -1)
+    _bis = numeroutput;
+
+  if (_von == -1)
+    _von = 0;
+
+  if (_bis > numeroutput)
+  {
+    printf("ANZAHL OUTPUT NEURONS passt nicht zu geforderter Classifizierung!");
+    return -1;
+  }
+
+  zw_max = output2->data.f[_von];
+  zw_class = _von;
+  for (int i = _von+1; i <= _bis; ++i)
+  {
+    zw = output2->data.f[i];
+    if (zw > zw_max)
+    {
+        zw_max = zw;
+        zw_class = i;
+    }
+  }
+  return (zw_class - _von);
+}
+
+/*
 int CTfLiteClass::GetOutClassification()
 {
   TfLiteTensor* output2 = interpreter->output(0);
@@ -51,6 +93,7 @@ int CTfLiteClass::GetOutClassification()
   }
   return zw_class;
 }
+*/
 
 void CTfLiteClass::GetInputDimension(bool silent = false)
 {
@@ -71,18 +114,18 @@ void CTfLiteClass::GetInputDimension(bool silent = false)
 }
 
 
-void CTfLiteClass::GetOutPut()
+int CTfLiteClass::GetAnzOutPut(bool silent)
 {
   TfLiteTensor* output2 = this->interpreter->output(0);
 
   int numdim = output2->dims->size;
-  printf("NumDimension: %d\n", numdim);  
+  if (!silent) printf("NumDimension: %d\n", numdim);  
 
   int sizeofdim;
   for (int j = 0; j < numdim; ++j)
   {
     sizeofdim = output2->dims->data[j];
-    printf("SizeOfDimension %d: %d\n", j, sizeofdim);  
+    if (!silent) printf("SizeOfDimension %d: %d\n", j, sizeofdim);  
   }
 
 
@@ -93,8 +136,9 @@ void CTfLiteClass::GetOutPut()
   for (int i = 0; i < numeroutput; ++i)
   {
    fo = output2->data.f[i];
-    printf("Result %d: %f\n", i, fo);  
+    if (!silent) printf("Result %d: %f\n", i, fo);  
   }
+  return numeroutput;
 }
 
 void CTfLiteClass::Invoke()
@@ -107,7 +151,7 @@ void CTfLiteClass::Invoke()
 
 bool CTfLiteClass::LoadInputImageBasis(CImageBasis *rs)
 {
-    std::string zw = "ClassFlowAnalog::doNeuralNetwork nach LoadInputResizeImage: ";
+    std::string zw = "ClassFlowCNNGeneral::doNeuralNetwork nach LoadInputResizeImage: ";
 
     unsigned int w = rs->width;
     unsigned int h = rs->height;

code/components/jomjol_tfliteclass/CTfLiteClass.h

@@ -61,8 +61,11 @@ class CTfLiteClass
         void GetInputTensorSize();
         bool LoadInputImageBasis(CImageBasis *rs);
         void Invoke();
-        void GetOutPut();
-        int GetOutClassification();
+        int GetAnzOutPut(bool silent = true);        
+//        void GetOutPut();
+//        int GetOutClassification();
+        int GetOutClassification(int _von = -1, int _bis = -1);
+
         int GetClassFromImageBasis(CImageBasis *rs);
         std::string GetStatusFlow();
 

code/components/jomjol_tfliteclass/server_tflite.cpp

@@ -284,16 +284,27 @@ esp_err_t handler_wasserzaehler(httpd_req_t *req)
         httpd_resp_sendstr_chunk(req, txt.c_str()); 
         
         std::vector<HTMLInfo*> htmlinfo;
-        htmlinfo = tfliteflow.GetAllDigital();
+        htmlinfo = tfliteflow.GetAllDigital();  
+        printf("Size of htmlinfo: %i\n", htmlinfo.size());
         for (int i = 0; i < htmlinfo.size(); ++i)
         {
-            if (htmlinfo[i]->val == 10)
-                zw = "NaN";
+            if (tfliteflow.GetTypeDigital() == Digital)
+            {
+                if (htmlinfo[i]->val == 10)
+                    zw = "NaN";
+                else
+                    zw = to_string((int) htmlinfo[i]->val);
+
+                txt = "<img src=\"/img_tmp/" +  htmlinfo[i]->filename + "\"> " + zw;
+            }
             else
             {
-                zw = to_string((int) htmlinfo[i]->val);
+                std::stringstream stream;
+                stream << std::fixed << std::setprecision(1) << htmlinfo[i]->val;
+                zw = stream.str();
+
+                txt = "<img src=\"/img_tmp/" +  htmlinfo[i]->filename + "\"> " + zw;
             }
-            txt = "<img src=\"/img_tmp/" +  htmlinfo[i]->filename + "\"> " + zw;
             httpd_resp_sendstr_chunk(req, txt.c_str()); 
             delete htmlinfo[i];
         }
@@ -493,7 +504,9 @@ esp_err_t handler_editflow(httpd_req_t *req)
 //        string zwzw = "Do " + _task + " start\n"; printf(zwzw.c_str());
         std::string zw = tfliteflow.doSingleStep("[Alignment]", _host);
         httpd_resp_sendstr_chunk(req, zw.c_str()); 
-    }  
+    }
+
+/*      
     if (_task.compare("test_analog") == 0)
     {
         std::string _host = "";
@@ -504,7 +517,9 @@ esp_err_t handler_editflow(httpd_req_t *req)
 //        string zwzw = "Do " + _task + " start\n"; printf(zwzw.c_str());
         std::string zw = tfliteflow.doSingleStep("[Analog]", _host);
         httpd_resp_sendstr_chunk(req, zw.c_str()); 
-    }  
+    }
+*/  
+/*    
     if (_task.compare("test_digits") == 0)
     {
         std::string _host = "";
@@ -517,6 +532,7 @@ esp_err_t handler_editflow(httpd_req_t *req)
         std::string zw = tfliteflow.doSingleStep("[Digits]", _host);
         httpd_resp_sendstr_chunk(req, zw.c_str()); 
     } 
+*/
 
 
     /* Respond with an empty chunk to signal HTTP response completion */