added most accurate model

Author: sethjuarez

Digitz.sln

@@ -5,8 +5,6 @@ VisualStudioVersion = 15.0.27130.2010
 MinimumVisualStudioVersion = 10.0.40219.1
 Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "Digitz", "Digitz\Digitz.csproj", "{A5362F75-A802-4DFF-87FC-DBCCA0C5C36E}"
 EndProject
-Project("{888888A0-9F3D-457C-B088-3A5042F75D52}") = "LearnDigitz", "LearnDigitz\LearnDigitz.pyproj", "{AE6064DD-F103-41EF-98D8-97B6B0465B1D}"
-EndProject
 Global
 	GlobalSection(SolutionConfigurationPlatforms) = preSolution
 		Debug|Any CPU = Debug|Any CPU
@@ -35,14 +33,6 @@ Global
 		{A5362F75-A802-4DFF-87FC-DBCCA0C5C36E}.Release|x64.Build.0 = Release|Any CPU
 		{A5362F75-A802-4DFF-87FC-DBCCA0C5C36E}.Release|x86.ActiveCfg = Release|Any CPU
 		{A5362F75-A802-4DFF-87FC-DBCCA0C5C36E}.Release|x86.Build.0 = Release|Any CPU
-		{AE6064DD-F103-41EF-98D8-97B6B0465B1D}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
-		{AE6064DD-F103-41EF-98D8-97B6B0465B1D}.Debug|ARM.ActiveCfg = Debug|Any CPU
-		{AE6064DD-F103-41EF-98D8-97B6B0465B1D}.Debug|x64.ActiveCfg = Debug|Any CPU
-		{AE6064DD-F103-41EF-98D8-97B6B0465B1D}.Debug|x86.ActiveCfg = Debug|Any CPU
-		{AE6064DD-F103-41EF-98D8-97B6B0465B1D}.Release|Any CPU.ActiveCfg = Release|Any CPU
-		{AE6064DD-F103-41EF-98D8-97B6B0465B1D}.Release|ARM.ActiveCfg = Release|Any CPU
-		{AE6064DD-F103-41EF-98D8-97B6B0465B1D}.Release|x64.ActiveCfg = Release|Any CPU
-		{AE6064DD-F103-41EF-98D8-97B6B0465B1D}.Release|x86.ActiveCfg = Release|Any CPU
 	EndGlobalSection
 	GlobalSection(SolutionProperties) = preSolution
 		HideSolutionNode = FALSE

Digitz/MainWindow.xaml.cs

@@ -81,14 +81,15 @@ private TFTensor GetWrittenDigit(int size)
         private void recognizeButton_Click(object sender, RoutedEventArgs e)
         {
             var tensor = GetWrittenDigit(28);
-
+            const string input_node = "x";
+            const string output_node = "Model/prediction";
             using (var graph = new TFGraph())
             {
                 graph.Import(File.ReadAllBytes("digits.pb"));
                 var session = new TFSession(graph);
                 var runner = session.GetRunner();
-                runner.AddInput(graph["x"][0], tensor);
-                runner.Fetch(graph["Model/prediction"][0]);
+                runner.AddInput(graph[input_node][0], tensor);
+                runner.Fetch(graph[output_node][0]);
                 var output = runner.Run();
                 TFTensor result = output[0];
                 float[] p = ((float[][])result.GetValue(true))[0];