Beispiel #1
0
        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);
        }
Beispiel #2
0
        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);
        }