public async System.Threading.Tasks.Task <IActionResult> PostAsync([FromForm] IFormFile image, [FromForm] string scale)
{
MLSharpPython ml = new MLSharpPython();
if (System.IO.File.Exists(Constants.InputImage))
{
System.IO.File.Delete(Constants.InputImage);
}
using (var fileStream = new FileStream(Constants.InputImage, FileMode.Create))
{
await image.CopyToAsync(fileStream);
}
string error = string.Empty;
ml.ExecutePythonScript("../../super_resolution/super_resolve.py " +
$"--model_pth \"{Constants.ModelBasic}\" " +
$"--input_image \"{Constants.InputImage}\" " +
$"--output_image \"{Constants.OutputImage}\" "
+ $"--scale {scale}"
, out error);
Console.WriteLine(error);
return(this.Ok());
}
private void btnSubmit_Click(object sender, EventArgs e)
{
string scriptAndArgs = scriptDir + "savesommatrix.py";
scriptAndArgs += " " + scriptDir + "params.json";
// Load values from the form
string[] dataColumns = new string[lstColumns.Items.Count];
for (int i = 0; i < lstColumns.Items.Count; i++)
{
dataColumns[i] = lstColumns.Items[i].Text;
}
Dictionary <string, string> data = new Dictionary <string, string>();
data.Add("trainingData", inputDir + txtInputFile.Text);
data.Add("colsToLoad", JsonConvert.SerializeObject(dataColumns));
data.Add("indexCol", ((int)nudIDColumn.Value).ToString());
data.Add("matrixFile", outputDir + txtOutputFile.Text);
data.Add("mapWidth", ((int)nudMapWidth.Value).ToString());
data.Add("mapHeight", ((int)nudMapHeight.Value).ToString());
data.Add("iterLim", ((int)nudIterLim.Value).ToString());
data.Add("initLR", ((float)nudLearnRate.Value).ToString());
data.Add("initRad", ((float)nudRadius.Value).ToString());
// Save parameters to the params.json file for the Python script to see
string json = JsonConvert.SerializeObject(data);
File.WriteAllText(scriptDir + "params.json", json);
MLSharpPython scriptRunner = new MLSharpPython(pythonExe);
scriptRunner.ExecutePythonScript(scriptAndArgs, out string stdError1);
/*scriptRunner.ExecutePythonScript(@"D:\Matt\Documents\GitRepos\Dataset-Visualisation-Dissertation\python\Kohonen\savecoords.py" +
* @" D:\Matt\Documents\GitRepos\Dataset-Visualisation-Dissertation\python\Kohonen\params.json",
* out string stdError2);*/
}
public ActionResult Home()
{
var filePythonNamePath = @"C:\Users\tejoh\python\Face_Registration.py";
var filePythonExePath = @"C:\Users\tejoh\AppData\Local\Programs\Python\Python38\python.exe";
var filename1 = @"C:\Users\tejoh\python\john1.jpg";
var filename2 = @"C:\Users\tejoh\python\john2.jpg";
byte[] imageArray = System.IO.File.ReadAllBytes(filename1);
string base64ImageRepresentation = Convert.ToBase64String(imageArray);
string outputText, standardError;
// Instantiate Machine Learning C# - Python class object
IMLSharpPython mlSharpPython = new MLSharpPython(filePythonExePath);
// Define Python script file and input parameter name
string fileNameParameter = $"{filePythonNamePath}" /*{filePythonParameterName} {imagePathName}*/;
string arguments = $"{base64ImageRepresentation}" /*{filePythonParameterName} {imagePathName}*/;
// Execute the python script file
outputText = mlSharpPython.ExecutePythonScript(fileNameParameter, arguments, out standardError);
if (string.IsNullOrEmpty(standardError))
{
}
else
{
Console.WriteLine(standardError);
}
Console.ReadKey();
return(Ok("Testing page"));
}
//private static string filePythonParameterName = Properties.Settings.Default.FilePythonParameterName;
static void Main()
{
string outputText, standardError;
// Instantiate Machine Learning C# - Python class object
IMLSharpPython mlSharpPython = new MLSharpPython(filePythonExePath);
// Define Python script file and input parameter name
string fileNameParameter = $"{filePythonNamePath} {$"sth"}";
// Execute the python script file
outputText = mlSharpPython.ExecutePythonScript(fileNameParameter, out standardError);
if (string.IsNullOrEmpty(standardError))
{
//if there aren't some execptions in python and c#
Console.WriteLine(outputText);
}
else
{
//if there are some execption in python and c#
Console.WriteLine(standardError);
}
Console.ReadKey();
}