br.cs

namespace koh
{
    using AForge;
    using AForge.Imaging;
    using AForge.Imaging.Filters;
    //using koh;
    using System;
    using System.Collections.Generic;
    using System.Drawing;
    using System.IO;
    using System.Linq;
    using System.Runtime.Serialization.Formatters.Binary;

    internal class Program
    {
        private static bool CheckArg(string arg)
        {
            try
            {
                FileInfo info = new FileInfo(arg);
                return (info.Exists && (info.Length < 0x800000L));
            }
            catch (Exception)
            {
                return false;
            }
        }

        private static List<byte> ConvertImage(Bitmap img)
        {
            List<byte> list = new List<byte>();
            using (UnmanagedImage image = UnmanagedImage.FromManagedImage(img))
            {
                List<IntPoint> points = new List<IntPoint>();
                for (int i = 0; i < image.Width; i++)
                {
                    for (int j = 0; j < image.Height; j++)
                    {
                        points.Add(new IntPoint(i, j));
                        Console.Write(i+","+j+":");
                    }
                }
                byte[] collection = image.Collect8bppPixelValues(points);
                Console.Write(collection + ":");

                list.AddRange(collection);
            }
            return list;
        }

        private static Bitmap LoadImage(string arg)
        {
            return AForge.Imaging.Image.FromFile(arg);
        }

        private static void Main(string[] args)
        {
           /* if ((args.Length != 1) || !CheckArg(args[0]))
            {
                Usage();
            }
            else
            {
            * */
              //  string arg = args[0];
                string arg = "C:\\Users\\Administrator\\Desktop\\baltctf\\braaainz\\out.bmp";
                Bitmap img = ProcessImage(LoadImage(arg));
                List<byte> source = ConvertImage(img);
                img.Save("out.jpg");
                BinaryFormatter formatter = new BinaryFormatter();
                FileStream serializationStream = File.OpenRead("pinky.brain");
                KohonenLayer layer = (KohonenLayer) formatter.Deserialize(serializationStream);

                Console.WriteLine(layer.Neurons.Count);
                Console.WriteLine(layer.PrevLayer.Count);

            /*
                for (int j = 0; j < layer.Neurons.Count; j++)
                {
                    Console.WriteLine(layer.Neurons[j]);
                    Console.WriteLine(((Neuron)layer.Neurons[j]).Data);

                    foreach (Link link in (((Neuron)layer.Neurons[j]).IngoingLinks))
                    {
                        Console.Write(link.Data);
                    }
                    foreach (Link link in (((Neuron)layer.Neurons[j]).OutgoingLinks))
                    {
                        Console.Write(link.Data);
                    }
                }
            */
            Console.WriteLine("######################################");
            Console.WriteLine(layer.PrevLayer.Count);
            
                for (int j = 0; j < layer.PrevLayer.Count; j++)
                {
                    //Console.Write(layer.PrevLayer[j]);

                    foreach (Link link in layer.PrevLayer[j].IngoingLinks)
                    {
                        //Console.Write(link.Data);
                      //  Console.WriteLine(link.Weight);
                    }

                    foreach (Link link in layer.PrevLayer[j].OutgoingLinks)
                    {
                        //Console.Write(link.Data);
                      //  Console.WriteLine(link.Weight);
                    }

                  
                }
                double minValue = double.MinValue;
                int num2 = 0;//让1号神经元的SUM最大。625个点指向10个神经元

                List<double> aa = source.Select<byte, double>(new Func<byte, double>(Convert.ToDouble)).ToList<double>();
            /////////////////////////////////////////


                for (int i = 0; i < aa.Count; i++)
                {
                    foreach (Link link in layer.PrevLayer[i].OutgoingLinks)
                    {
                        link.Data = aa[i];
                    }
                }

                Console.WriteLine("layer.Neurons.Count:"+layer.Neurons.Count);
                for (int j = 0; j < layer.Neurons.Count; j++)
                {
                    double num5 = ((Neuron)layer.Neurons[j]).Activate();
                    Console.WriteLine(num5);
                    if (num5 > minValue)
                    {
                        minValue = num5;
                        num2 = j;
                    }
                }
                Console.WriteLine("CQ:"+num2);



            //source: 255---->aa:255.0
                
                Console.WriteLine(layer.Activate(aa));
                
            //}
        }

        private static Bitmap ProcessImage(Bitmap img)
        {
            img = new ResizeBicubic(0x19, 0x19).Apply(img);
            //http://www.aforgenet.com/framework/docs/html/1371dd12-7dbd-2a0e-a0d7-32d8c28d73eb.htm
            img = new GrayscaleRMY().Apply(img);
            //http://www.aforgenet.com/framework/docs/html/1100c0be-7a9f-490e-b49c-a2f3cc681a01.htm
            img = new OtsuThreshold().Apply(img);
            //http://www.aforgenet.com/framework/docs/html/b2bd54da-46c2-cb64-3577-0962d8f56554.htm
            return img;
        }

        private static void Usage()
        {
            Console.WriteLine("Provide path to image");
        }
    }
}