//This method return the training accuracy for each of the parameters for the model by running the python script : train.py with these paramters
private double TrainModelAndReturnAccuracy(double layers, double steps, double learningRate)
{
var pythones = new PythonExecutionService().GetAccuracy(layers, steps, learningRate);
//Call the python function and get the accuracy
return(pythones);
}
public async Task <HttpResponseMessage> TestUserImage()
{
Dictionary <string, object> dict = new Dictionary <string, object>();
try
{
ModelService modelService = new ModelService();
var httpRequest = HttpContext.Current.Request;
//Getting the GUID from the request
var guid = httpRequest.Params["guid"];
var image = new MLApiImage();
try
{
if (!modelService.IsValidModelId(Guid.Parse(guid)))
{
var message = string.Format("The model is not available in the datamodel");
dict.Add("status", "failure");
dict.Add("error", message);
return(Request.CreateResponse(HttpStatusCode.NotFound, dict));
}
image.ModelId = Guid.Parse(guid);
}
catch (Exception ex)
{
var message = string.Format("The GUID format is incorrect");
dict.Add("status", "failure");
dict.Add("error", message);
return(Request.CreateResponse(HttpStatusCode.BadRequest, dict));
}
foreach (string file in httpRequest.Files)
{
HttpResponseMessage response = Request.CreateResponse(HttpStatusCode.Created);
var postedFile = httpRequest.Files[file];
if (postedFile != null && postedFile.ContentLength > 0)
{
int MaxContentLength = 1024 * 1024 * 1; //Size = 1 MB
IList <string> AllowedFileExtensions = new List <string> {
".jpg", ".png"
};
var ext = postedFile.FileName.Substring(postedFile.FileName.LastIndexOf('.'));
var extension = ext.ToLower();
//Checking for the compatible extensions
if (!AllowedFileExtensions.Contains(extension))
{
var message = string.Format("Please Upload image of type .jpg,.png.");
dict.Add("status", "failure");
dict.Add("error", message);
return(Request.CreateResponse(HttpStatusCode.BadRequest, dict));
}
else if (postedFile.ContentLength > MaxContentLength)
{
var message = string.Format("Please Upload a file of size upto 1 mb.");
dict.Add("status", "failure");
dict.Add("error", message);
return(Request.CreateResponse(HttpStatusCode.BadRequest, dict));
}
else
{
string pathToCreate = "~/Userimages/";
if (!Directory.Exists(HttpContext.Current.Server.MapPath(pathToCreate)))
{
//Now you know it is ok, create it
Directory.CreateDirectory(HttpContext.Current.Server.MapPath(pathToCreate));
}
var filePath = HttpContext.Current.Server.MapPath("~/Userimages/" + postedFile.FileName + extension);
postedFile.SaveAs(filePath);
image.ImagePath = filePath;
}
}
var result = SaveImage(image);
if (result.IsSuccessStatusCode)
{
var pythones = new PythonExecutionService().GetAccuracyForModel(image.ModelId ?? Guid.Empty);
//Call the python function and get the accuracy
dict.Clear();
dict.Add("status", "success");
dict.Add("message", new { Accuracy = pythones });
return(Request.CreateResponse(HttpStatusCode.OK, dict));;
}
else
{
return(result);
}
}
var res = string.Format("No image found , please upload an image.");
dict.Add("status", "failure");
dict.Add("error", res);
return(Request.CreateResponse(HttpStatusCode.NotFound, dict));
}
catch (Exception ex)
{
var res = string.Format($"Error Occurred in saving image {ex.Message}");
dict.Add("status", "failure");
dict.Add("error", res);
return(Request.CreateResponse(HttpStatusCode.NotFound, dict));
}
}
