Example #1
0
        private void button1_Click(object sender, EventArgs e)
        {
            cutter = new BoxCut2D(int.Parse(textBox1.Text),
                                  int.Parse(textBox2.Text),
                                  float.Parse(textBox3.Text),
                                  float.Parse(textBox4.Text),
                                  float.Parse(textBox5.Text),
                                  float.Parse(textBox6.Text),
                                  float.Parse(textBox7.Text),
                                  float.Parse(textBox8.Text));

            pictureBox1.Image = cutter.DrawRectangles(input, new Pen(Color.Green, 20));
        }
        private void button1_Click(object sender, EventArgs e)
        {
            if (openFileDialog1.ShowDialog() == DialogResult.OK)
            {
                Bitmap map = new Bitmap(openFileDialog1.FileName);

                BoxerDLL.BoxCut2D   cutter = new BoxCut2D(7, 10, 0.143f, 0.1f);
                List <Bitmap>       maps   = cutter.Cut(map);
                List <double[, , ]> rgbs   = new List <double[, , ]>();
                for (int i = 0; i < maps.Count; i++)
                {
                    maps[i] = new Bitmap(maps[i], new System.Drawing.Size(24, 12));
                    rgbs.Add(ImageDataConverter.GetRGBArray(maps[i]));
                }


                RectangleF[] rects = cutter.Rects1D(map.Width, map.Height);

                BitmapCatEnumerator enums   = new BitmapCatEnumerator("Sorted", new System.Drawing.Size(24, 12));
                BitmapCatEnumerator val     = new BitmapCatEnumerator("Val", new System.Drawing.Size(24, 12));
                Network             network = new Network();
                network.AddLayer(new Dropout(new Relu(), 0.05));
                network.AddLayer(new Conv2D(new Relu(), 7, 7, 32));
                network.AddLayer(new MaxPool2D(new Relu(), 2, 2));
                network.AddLayer(new Dropout(new Relu(), 0.05));

                network.AddLayer(new Conv2D(new Relu(), 3, 3, 64));
                network.AddLayer(new MaxPool2D(new Relu(), 2, 2));
                network.AddLayer(new Dropout(new Relu(), 0.05));

                network.AddLayer(new FullyConnLayar(new Sigmoid(), new NeuralNetwork.Size(1, 1, 256)));
                network.AddLayer(new FullyConnLayar(new Sigmoid(), new NeuralNetwork.Size(1, 1, 2)));

                network.Compile(new NeuralNetwork.Size(3, 12, 24), true);

                network.Normalization();

                pictureBox1.Image = map;

                MomentumParallel sgd = new MomentumParallel(network, 0.9, 1e-4);

                int last = 0;

                for (int i = 0; i < 1000; i++)
                {
                    var errors = sgd.TrainBatchPercent(enums, 32, 1);

                    if (errors.Last().Value > 90 || i - last > 20)
                    {
                        last = i;
                        Color[] colors = new Color[rects.Length];
                        Color   plus   = Color.FromArgb(100, Color.Red);
                        Color   minus  = Color.FromArgb(100, Color.Green);

                        for (int j = 0; j < maps.Count; j++)
                        {
                            double[,,] output = network.GetOutput(rgbs[j]);

                            colors[j] = output[0, 0, 0] > output[0, 0, 1] ? plus : minus;
                        }

                        pictureBox1.Image = DrawColoredRects(map, rects, colors);

                        var validation = network.GetError(val);
                        label2.Text = "Validation\nError: " + validation.Key + "\nPercent: " + validation.Value;
                    }
                    label1.Text = i + "\nError: " + errors.Last().Key + "\nPercent: " + errors.Last().Value;
                    Update();
                }
            }
        }