private void button2_Click(object sender, EventArgs e)
{
if (threadCnn != null && threadCnn.ThreadState == ThreadState.Running)
{
return;
}
threadCnn = new Thread(() =>
{
CnnHelper.SumCount = 0;
CnnHelper.TrueCount = 0;
#region LFW人脸集
foreach (var file in Directory.GetFiles("img2", "*.jpg"))
{
using (Bitmap img = new Bitmap(file))
{
byte label = Convert.ToByte(file.Substring(file.LastIndexOf('\\') + 1, 1));
Image <Bgr, float> trainingData = new Image <Bgr, float>(img);;
double[,] input = new double[img.Width, img.Height];
for (int w = 0; w < img.Width; w++)
{
for (int h = 0; h < img.Height; h++)
{
input[w, h] = Color.FromArgb(0,
(int)trainingData.Data[h, w, 2],
(int)trainingData.Data[h, w, 1],
(int)trainingData.Data[h, w, 0]
).ToArgb() / (double)0xFFFFFF;
}
}
input = CnnHelper.MatrixExpand(input, 2, 2, 0);
double[] labels = cnn.Predict(input);
double[] labelsTrue = new double[10];
double maxtype = labels[0], max = 0;
for (int n = 0; n < 10; n++)
{
if (maxtype < labels[n])
{
max = n;
maxtype = labels[n];
}
if (label == n)
{
labelsTrue[n] = 1;
}
}
//Console.WriteLine(i + ":" + label + "," + max);
CnnHelper.ShowChange(labels, labelsTrue, 10000);
this.Invoke(new Action(() =>
{
lblInfo.Text = String.Format("识别次数:{0}/{1} 正确率:{2:00.####%}", CnnHelper.TrueCount, CnnHelper.SumCount, CnnHelper.TrueCount / (double)CnnHelper.SumCount);
lblResult.Text = CnnHelper.LabelsNum + " " + CnnHelper.ResultNum;
pbImage1.Image = new Bitmap(img);
}));
}
}
#endregion
});
threadCnn.Start();
}
private Rectangle[] PredictBP(Bitmap img)
{
Rectangle[] tmpR = new Rectangle[] { };
Bitmap tmpImg = ZoomImg(img, bpWidth, bpHeight, ref tmpR);
List <Rectangle> retRects = new List <Rectangle>();
Image <Bgr, float> trainingData = new Image <Bgr, float>(tmpImg);
double[,] input = new double[bpWidth, bpHeight];
for (int i = 0; i < bpWidth; i++)
{
for (int j = 0; j < bpHeight; j++)
{
input[i, j] = Color.FromArgb(
(int)trainingData.Data[j, i, 2],
(int)trainingData.Data[j, i, 1],
(int)trainingData.Data[j, i, 0]
).ToArgb() / (float)0xFFFFFF;
}
}
double[] output = cnn.Predict(input);
for (int i = 0; i < bpRectangleCount * 4; i += 4)
{
Rectangle r = new Rectangle();
r.X = (int)(output[i] * (float)bpWidth);
r.Y = (int)(output[i + 1] * (float)bpHeight);
r.Width = (int)(output[i + 2] * (float)bpWidth);
r.Height = (int)(output[i + 3] * (float)bpHeight);
if (r.X >= 0 && r.Y >= 0 && r.Width > 0 && r.Height > 0)
{
retRects.Add(r);
}
}
return(retRects.ToArray());
}
private void button2_Click(object sender, EventArgs e)
{
if (threadCnn != null && threadCnn.ThreadState == ThreadState.Running)
{
return;
}
threadCnn = new Thread(() =>
{
CnnHelper.SumCount = 0;
CnnHelper.TrueCount = 0;
if (!chkHandwritten.Checked)
{
#region MNIST库
using (FileStream fs = new FileStream("t10k-labels.idx1-ubyte", FileMode.Open))
{
using (FileStream fsImages = new FileStream("t10k-images.idx3-ubyte", FileMode.Open))
{
byte[] bytes4 = new byte[4];
fsImages.Seek(4, SeekOrigin.Current);
fs.Seek(8, SeekOrigin.Current);
fsImages.Read(bytes4, 0, 4);
int count = ToInt32(bytes4);
fsImages.Read(bytes4, 0, 4);
int height = ToInt32(bytes4);
fsImages.Read(bytes4, 0, 4);
int width = ToInt32(bytes4);
for (int i = 0; i < count; i++)
{
Bitmap img = GetImage(fsImages, width, height);
byte label = GetLable(fs);
Image <Bgr, float> trainingData = new Image <Bgr, float>(img);;
double[,] input = new double[width, height];
for (int w = 0; w < width; w++)
{
for (int h = 0; h < height; h++)
{
input[w, h] = Color.FromArgb(0,
(int)trainingData.Data[h, w, 2],
(int)trainingData.Data[h, w, 1],
(int)trainingData.Data[h, w, 0]
).ToArgb() / (double)0xFFFFFF;
}
}
input = CnnHelper.MatrixExpand(input, 2, 2, 0);
double[] labels = cnn.Predict(input);
double[] labelsTrue = new double[10];
double maxtype = labels[0], max = 0;
for (int n = 0; n < 10; n++)
{
if (maxtype < labels[n])
{
max = n;
maxtype = labels[n];
}
if (label == n)
{
labelsTrue[n] = 1;
}
}
//Console.WriteLine(i + ":" + label + "," + max);
CnnHelper.ShowChange(labels, labelsTrue, 10000);
this.Invoke(new Action(() =>
{
lblInfo.Text = String.Format("识别次数:{0}/{1} 正确率:{2:00.####%}", CnnHelper.TrueCount, CnnHelper.SumCount, CnnHelper.TrueCount / (double)CnnHelper.SumCount);
if (i % 20 == 0)
{
lblResult.Text = CnnHelper.LabelsNum + " " + CnnHelper.ResultNum;
pbImage.Image = img;
}
}));
//img.Save("imgs/" + i + "_" + label + ".jpg");
}
fsImages.Close();
fs.Close();
}
}
#endregion
}
else
{
#region 手写字体集
foreach (var file in Directory.GetFiles("img2", "*.jpg"))
{
using (Bitmap img = new Bitmap(file))
{
byte label = Convert.ToByte(file.Substring(file.LastIndexOf('\\') + 1, 1));
Image <Bgr, float> trainingData = new Image <Bgr, float>(img);;
double[,] input = new double[img.Width, img.Height];
for (int w = 0; w < img.Width; w++)
{
for (int h = 0; h < img.Height; h++)
{
input[w, h] = Color.FromArgb(0,
(int)trainingData.Data[h, w, 2],
(int)trainingData.Data[h, w, 1],
(int)trainingData.Data[h, w, 0]
).ToArgb() / (double)0xFFFFFF;
}
}
input = CnnHelper.MatrixExpand(input, 2, 2, 0);
double[] labels = cnn.Predict(input);
double[] labelsTrue = new double[10];
double maxtype = labels[0], max = 0;
for (int n = 0; n < 10; n++)
{
if (maxtype < labels[n])
{
max = n;
maxtype = labels[n];
}
if (label == n)
{
labelsTrue[n] = 1;
}
}
//Console.WriteLine(i + ":" + label + "," + max);
CnnHelper.ShowChange(labels, labelsTrue, 10000);
this.Invoke(new Action(() =>
{
lblInfo.Text = String.Format("识别次数:{0}/{1} 正确率:{2:00.####%}", CnnHelper.TrueCount, CnnHelper.SumCount, CnnHelper.TrueCount / (double)CnnHelper.SumCount);
lblResult.Text = CnnHelper.LabelsNum + " " + CnnHelper.ResultNum;
pbImage.Image = new Bitmap(img);
}));
}
}
#endregion
}
});
threadCnn.Start();
}
