public List <RecognitionContract> Post([FromBody] Dictionary <string, string> imgs)
{
List <RecognitionContract> predictionResults = new List <RecognitionContract>();
imgs.Values.ToArray();
model.MakePrediction(imgs);
lock (model.recognitionLibraryContext)
{
foreach (var i in imgs)
{
RecognitionInfo temp = new RecognitionInfo(i.Key, "", 0);
temp.Image = Convert.FromBase64String(i.Value);
var res = model.recognitionLibraryContext.FindOne(temp);
if (res == null)
{
Trace.WriteLine("Post null");
}
else
{
byte[] tmp1 = res.ImageDetails.Image;
var converted = Convert.ToBase64String(tmp1);
predictionResults.Add(new RecognitionContract(i.Key, res.Label.ToString(), res.Confidence, converted));
}
Trace.WriteLine("Post " + i.Key + " " + res.Label + res.Confidence);
}
}
return(predictionResults);
}
static void Main(string[] args)
{
//Console.WriteLine("If you want to stop recognition press ESС");
string img = Console.ReadLine();
string curDir = Directory.GetParent(Environment.CurrentDirectory).Parent.Parent.Parent.Parent.FullName;
NNModel Mnist = new NNModel(Path.Combine(curDir, "mnist-8.onnx"), Path.Combine(curDir, "classlabel.txt"));
Mnist.MessageToUser += PrintMessageToUser;
Mnist.OutputResult += PrintResult;
var t = Task.Run(() => { return(Mnist.MakePrediction()); }).Result;
}
public List <RecognitionInfo> Post([FromBody] string dir)
{
List <RecognitionInfo> predictionResults = new List <RecognitionInfo>();
model.MakePrediction(dir);
lock (model.recognitionLibraryContext)
{
foreach (var path in Directory.GetFiles(dir).Where(s => s.EndsWith(".png") || s.EndsWith(".jpg") || s.EndsWith(".bmp") || s.EndsWith(".gif")))
{
RecognitionInfo temp = new RecognitionInfo(path, "", 0);
var res = model.recognitionLibraryContext.FindOne(temp);
predictionResults.Add(new RecognitionInfo(path, res.Label.ToString(), res.Confidence));
}
}
return(predictionResults);
}