public Tuple<string, int> Recognize(Image<Gray, byte> src)
{
var list = src.getEdge().Sample(100);
#region 计算形状上下文
int r = 15;
var scall = Jim.OCR.ShapeContext2D.ShapeContext.ComputeSC(list);
var scq = new double[r, 60];
for (int i = 0; i < r; ++i) {
int pos = rand.Next(list.Count);
for (int k = 0; k < 60; ++k) {
scq[i, k] = scall[pos, k];
}
}
#endregion
#region 计算距离
var dists = new ValueIndexPair<double>[SC.template_sc.Length];
for (int i = 0; i < SC.template_sc.Length; ++i) {
double[,] sci = SC.template_sc[i];
double[,] costmat = Jim.OCR.ShapeContext2D.ShapeContext.HistCost(scq, sci);
double cost = 0;
for (int j = 0; j < r; ++j) {
double min = double.MaxValue;
for (int u = 0; u < 100; ++u) {
double val = costmat[j, u];
if (val < min) min = val;
}
cost += min;
}
dists[i] = new ValueIndexPair<double> { Value = cost, Index = i };
}
#endregion
#region 对结果排序
var arr = dists
.OrderBy(p => p.Value)
.Select(p => new { Distance = p.Value, Char = SC.template_chars[p.Index] })
//.Where(p => "ABCDEFGHIJKLMNPQRSTUVWXYZ123456789".IndexOf(p.Char) != -1)
.Where(p => Filter.IndexOf(p.Char) != -1)
.ToArray();
Dictionary<string, int> matchcount = new Dictionary<string, int>();
foreach (var pair in arr.Take(Knn)) {
string ch = pair.Char;
matchcount[ch] = matchcount.ContainsKey(ch) ? matchcount[ch] + 1 : 1;
}
var match = matchcount.Select(pair => new { Count = pair.Value, Ch = pair.Key })
.Where(v => v.Count > 0)
.OrderByDescending(v => v.Count).ToArray();
//string result = "";
//foreach (var m in match.Take(3)) {
// result += String.Format("Char:'{0}',Accuracy:{1}/{2}\t", m.Ch, m.Count, knn);
//}
#endregion
return new Tuple<string, int> { First = match[0].Ch, Second = match[0].Count };
}
private void PrepareCalculate()
{
check = false;
int[] arrayInt;
int count = Convert.ToInt32(CountFindNumberTextBox.Text);
UseArray.Clear();
CalculateArray.Text = "";
if (EnterArrayTextBox.Text.Length != 0)
{
arrayInt = EnterArrayTextBox.Text.Split(' ').Take(Convert.ToInt32(SizeArrayTextBox.Text)).Select(x => int.Parse(x)).ToArray();
try
{
SortedSet <ValueIndexPair> sorted = new SortedSet <ValueIndexPair>(new ValueIndexCompare());
for (int i = 0; i < arrayInt.Length; i++)
{
var pair = new ValueIndexPair(arrayInt[i], i);
if (sorted.Count < count)
{
sorted.Add(pair);
}
else
{
if (sorted.Max.Value < arrayInt[i])
{
sorted.Remove(sorted.Max);
sorted.Add(pair);
}
}
}
foreach (var item in sorted)
{
CalculateArray.Text = CalculateArray.Text + " " + item.Value;
}
;
}
catch (Exception eEnterArrayTextBox)
{
MessageBoxResult message = MessageBox.Show(eEnterArrayTextBox.Message, "Error", MessageBoxButton.OK);
if (message == MessageBoxResult.OK)
{
check = true;
}
}
}
}
private static void fastPruningWithRSC()
{
int s = 100, r = 5;
MyTimer timer = new MyTimer();
string[] templatefiles = Directory.GetFiles(@"D:\Play Data\train_data\sc\", "*.sc")
.Take(1000).ToArray();
#region 打开模板
string templatepath = @"D:\Play Data\template\";
int templatecount = templatefiles.Length;
Debug("打开{0}个模板--------------------------------------------", templatecount);
double[][,] templates = new double[templatecount][,];
int[] templatenums = new int[templatecount];
timer.Restart();
for (int i = 0; i < templatefiles.Length; ++i) {
string file = templatefiles[i];
string filename = Path.GetFileNameWithoutExtension(file);
templatenums[i] = int.Parse(filename.Split('-')[1]);
templates[i] = new double[s, 60];
unsafe {
#region 指针也快不了多少
//byte[] data = File.ReadAllBytes(file);
//fixed (byte* ptr = data) {
// //using (var fs = new FileStream(file, FileMode.Open)) {
// // using (var br = new BinaryReader(fs)) {
// int offset = 0;
// for (int j = 0; j < s; ++j) {
// for (int k = 0; k < 60; ++k) {
// //templates[i][j, k] = br.ReadDouble();
// fixed (double* t = &templates[i][j, k]) {
// for (int p = 0; p < sizeof(double); ++p)
// *((byte*)t + p) = *(ptr + offset++);
// }
// }
// }
//}
#endregion
using (var fs = new FileStream(file, FileMode.Open)) {
using (var br = new BinaryReader(fs)) {
for (int j = 0; j < s; ++j) {
for (int k = 0; k < 60; ++k) {
templates[i][j, k] = br.ReadDouble();
}
}
}
}
}
if (i % 100 == 0)
Debug("已完成{0}个", i);
}
Debug("模板读取完成，用时{0}ms.", timer.Stop());
#endregion
string[] testfiles = Directory.GetFiles(@"D:\Play Data\test\", "*.bmp")
.Take(100).ToArray();
#region 测试
int testcase = testfiles.Length, acc = 0;
Debug("为{0}个对象寻找候选模板------------------------------------------", testcase);
foreach (var file in testfiles) {
timer.Restart();
string filenameext = Path.GetFileName(file);
string filename = Path.GetFileNameWithoutExtension(file);
int thisnum = int.Parse(filename.Split('-')[1]);
Image<Gray, Byte> img = new Image<Gray, byte>(file);
var list = getEdge(img.Resize(2.5, Emgu.CV.CvEnum.INTER.CV_INTER_LINEAR)).Sample(s);
var sc100 = Jim.OCR.ShapeContext2D.ShapeContext.ComputeSC(list);
double[,] scq = new double[r, 60];
for (int i = 0; i < 5; ++i) {
int pos = rand.Next(s);
for (int k = 0; k < 60; ++k) {
scq[i, k] = sc100[pos, k];
}
}
var arr = new ValueIndexPair<double>[templatecount];
for (int i = 0; i < templatecount; ++i) {
double[,] sci = templates[i];
double[,] costmat = Jim.OCR.ShapeContext2D.ShapeContext.HistCost(scq, sci);
double cost = 0;
for (int j = 0; j < 5; ++j) {
double min = double.MaxValue;
for (int u = 0; u < s; ++u) {
double val = costmat[j, u];
if (val < min) min = val;
}
cost += min;
}
arr[i] = new ValueIndexPair<double> { Value = cost, Index = i };
}
Array.Sort(arr, (a, b) => a.Value.CompareTo(b.Value));
int[] matchcount = new int[10];
double[] matchcost = new double[10];
int knn = 10;
foreach (var pair in arr.Take(knn)) {
int num = templatenums[pair.Index];
matchcount[num]++;
matchcost[num] += pair.Value;
}
var match = matchcount.Select((val, i) => new { Count = val, Num = i })
.Where(v => v.Count > 0)
.OrderByDescending(v => v.Count).ToArray();
//var match = matchcost.Select((val, i) => new { Cost = val / matchcount[i], Num = i })
// .Where(v => !double.IsNaN(v.Cost))
// .OrderBy(v => v.Cost).ToArray();
#region 进行精细匹配，效果一般
//double[] matchrate = new double[10];
//foreach (var m in match) {
// if (m.Count == 0) break;
// string template = Path.Combine(templatepath, m.Num + ".bmp");
// Jim.OCR.ShapeContext2D.ShapeContext sc = new Jim.OCR.ShapeContext2D.ShapeContext(file, template);
// sc.debug_flag = false;
// sc.timer_flag = false;
// sc.display_flag = false;
// sc.n_iter = 3;
// sc.matchScale = 2.5;
// sc.maxsamplecount = 100;
// matchrate[m.Num] = sc.MatchFile();
//}
//var bestmatches = matchrate.Select((val, i) => new { Cost = val, Num = i })
// .Where(m => m.Cost > 0)
// .OrderBy(m => m.Cost).ToArray();
//int firstmatch = bestmatches[0].Num;
#endregion
int firstmatch = match[0].Num;
var fc = Console.ForegroundColor;
Console.ForegroundColor = firstmatch == thisnum ? ConsoleColor.Green : ConsoleColor.Red;
string info = String.Format("{0} {1}ms - {2}\t", filename, timer.Stop(), (firstmatch == thisnum ? "Right" : "Wrong"));
//foreach (var m in bestmatches.Take(4)) {
foreach (var m in match) {
info += String.Format("{0}/{1}\t", m.Num, m.Count);
//info += String.Format("{0}/{1:F3}\t", m.Num, m.Cost);
//info += String.Format("{0}/{1:F3}\t", m.Num, m.Cost);
}
Debug(info);
Console.ForegroundColor = fc;
if (firstmatch == thisnum) {
++acc;
}
}
Debug("测试用例：{0}。正确率{1}。", testcase, acc);
#endregion
}
private static void testCluter()
{
int ss = 100, sq = 100, k = 10, m = 10; // 采样数，G取前k，S取前m
int randcount = 5, randtake = 10, randselect = 3;
var timer = new MyTimer();
var templatefiles = Directory.GetFiles(@"D:\Play Data\字符模板");
int templatecount = templatefiles.Length;
var templateChars = new string[templatecount];
var templatePoints = new Vector2[templatecount][];
//var templatesc = new double[templatecount][,];
var templatesc = new double[templatecount][][];
#region 计算模板的SC
for (int f = 0; f < templatecount; ++f) {
string file = templatefiles[f], filename = Path.GetFileNameWithoutExtension(file);
using (Image<Gray, Byte> img = new Image<Gray, byte>(file)) {
var samples = getEdge(img).Sample(ss);
templatesc[f] = Jim.OCR.ShapeContext2D.ShapeContext.ComputeSC2(samples);
templatePoints[f] = samples.Select(p => new Vector2(p.X, p.Y)).ToArray();
}
templateChars[f] = filename;
Console.Write(filename);
}
Console.WriteLine();
Debug("模板读取完成");
#endregion
#region 处理字符
foreach (string file in Directory.GetFiles(@"D:\Play Data\字符")) {
string filename = Path.GetFileNameWithoutExtension(file);
if (filename != "AB") continue;
timer.Restart();
Image<Bgr, Byte> img = new Image<Bgr, Byte>(file);
var samples = getEdge(img.Convert<Gray, Byte>()).Sample(sq);
//double[,] SCQ = Jim.OCR.ShapeContext2D.ShapeContext.ComputeSC(samples);
double[][] SCQ = Jim.OCR.ShapeContext2D.ShapeContext.ComputeSC2(samples);
var Q_Points = samples.Select(p => new Vector2(p.X, p.Y)).ToArray();
var mmg = img.Convert<Bgr, Byte>();
Graphics g = Graphics.FromImage(mmg.Bitmap);
Q_Points.ToList().ForEach(v => { mmg[(int)v.Y, (int)v.X] = new Bgr(0, 0, 255); });
var point_distance = new ValueIndexPair<double>[sq][];
#region 计算采样点之间的距离
for (int i = 0; i < sq; ++i) {
double xi = Q_Points[i].X, yi = Q_Points[i].Y;
point_distance[i] = new ValueIndexPair<double>[sq];
for (int j = 0; j < sq; ++j) {
double xj = Q_Points[j].X, yj = Q_Points[j].Y;
point_distance[i][j] = new ValueIndexPair<double> {
Value = Math.Sqrt((xi - xj) * (xi - xj) + (yi - yj) * (yi - yj)),
Index = j
};
}
Array.Sort(point_distance[i], (a, b) => a.Value.CompareTo(b.Value));
}
#endregion
var randpoints = new int[randcount][];
#region 随机取randcount个点，并在其周围randtake个点中取randselect个
for (int i = 0; i < randcount; ++i) {
int pi = rand.Next(Q_Points.Length);
var p = Q_Points[pi];
mmg.Draw(new CircleF(new PointF((float)p.X, (float)p.Y), 2), new Bgr(255, 0, 0), 1);
randpoints[i] = new int[randselect];
bool[] vi = Utils.InitArray<bool>(randtake, false);
for (int cnt = 0; cnt < randselect; ) {
int rnd = rand.Next(randtake);
if (!vi[rnd]) {
vi[rnd] = true;
randpoints[i][cnt++] = rnd;
}
}
for (int ppp = 0; ppp < randselect; ++ppp) {
var pt = Q_Points[point_distance[pi][randpoints[i][ppp]].Index];
//g.DrawString(i.ToString(), new Font("Arial", 7), new SolidBrush(Color.FromArgb(0, 128, 0)), new PointF((float)pt.X, (float)pt.Y));
}
}
#endregion
#region 为这randcount组RSC分别选最好的模板
var rscmatch = new Tuple<int, double, Vector2>[randcount]; // <Si, d, L>
for (int rc = 0; rc < randcount; ++rc) {
var rsc_matches = new Tuple<double, Vector2>[templatecount]; // <d, L>
for (int i = 0; i < templatecount; ++i) {
#region 拷贝出一个rsc来
var rsc = new double[randselect][];
for (int j = 0; j < randselect; ++j) {
rsc[j] = new double[60];
Array.Copy(SCQ[randpoints[rc][j]], rsc[j], 60);
}
#endregion
var costmat = Jim.OCR.ShapeContext2D.ShapeContext.HistCost2(rsc, templatesc[i]);
var matches = costmat.Select(
row => row.Select((d, c) => new ValueIndexPair<double> { Value = d, Index = c })
.OrderBy(d => d.Value).First()).ToArray();
Vector2 L = Vector2.Zero;
double M = 0;
for (int j = 0; j < randselect; ++j) {
int u = randpoints[rc][j], mu = matches[j].Index;
double d = matches[j].Value;
Vector2 pu = Q_Points[u], pmu = templatePoints[i][mu];
M += (1 - d);
L += (1 - d) * (pu - pmu);
}
L /= M;
rsc_matches[i] = new Tuple<double, Vector2> {
First = matches.Sum(r => r.Value),
Second = L
};
}
var best_template = rsc_matches.Select((mt, i) => new { Match = mt, i })
.OrderBy(t => t.Match.First)
.First();
rscmatch[rc] = new Tuple<int, double, Vector2> {
First = best_template.i,
Second = best_template.Match.First,
Third = best_template.Match.Second
};
string label = templateChars[best_template.i];
g.DrawString(label, new Font("Arial", 48), Brushes.Green,
new PointF((float)best_template.Match.Second.X, (float)best_template.Match.Second.Y));
}
#endregion
//Font f = new Font("Arial", 12);
//var G = new Tuple<int, int, double>[templatecount][]; // <u, m(u), d>
//#region 为每个Si挑选合适的Gi
//{
// var costmats = new double[templatecount][,];
// for (int i = 0; i < templatecount; ++i) {
// double[,] SCi = templatesc[i];
// costmats[i] = Jim.OCR.ShapeContext2D.ShapeContext.HistCost(SCQ, SCi);
// G[i] = new Tuple<int, int, double>[sq * ss];
// for (int u = 0; u < sq; ++u) {
// for (int j = 0; j < ss; ++j) {
// G[i][u * ss + j] = new Tuple<int, int, double> {
// First = u,
// Second = j,
// Third = costmats[i][u, j]
// };
// }
// }
// Array.Sort(G[i], (da, db) => da.Third.CompareTo(db.Third));
// }
//}
//#endregion
//var d_Q_S = new double[templatecount];
//#region 求出每个Si和Q的d(Q, Si)
//{
// for (int i = 0; i < templatecount; ++i) {
// var Gi = G[i].Take(k);
// foreach (var g in Gi) {
// int u = g.First, mu = g.Second;
// double d = g.Third;
// double Nu = G.Average(gi => gi.First(t => t.First == u).Third);
// d_Q_S[i] += d / Nu;
// }
// d_Q_S[i] /= k;
// }
//}
//#endregion
//var firstmG = new Tuple<Tuple<int, int, double>[], double, int>[m]; // <G, d, i> <=> <<u, m(u), d>[], d, i>
//#region 根据d(Q, Si)截取前20个最好的Gi
//{
// var firstmdQS = d_Q_S.Select((d, i) => new ValueIndexPair<double> { Value = d, Index = i })
// .OrderBy(p => p.Value)
// .Take(firstmG.Length).ToArray();
// for (int p = 0; p < firstmG.Length; ++p) {
// double d = firstmdQS[p].Value;
// int i = firstmdQS[p].Index;
// firstmG[p] = new Tuple<Tuple<int, int, double>[], double, int> {
// First = G[i].Take(k).ToArray(),
// Second = d,
// Third = i
// };
// }
//}
//#endregion
//#region 计算每个G的位置
//var L = new Vector2[m];
//{
// for (int i = 0; i < m; ++i) {
// L[i] = Vector2.Zero;
// double Mi = 0;
// var Gi = firstmG[i];
// foreach (var u_mu_d in Gi.First) {
// int u = u_mu_d.First, mu = u_mu_d.Second;
// double d = u_mu_d.Third;
// Vector2 pu = Q_Points[u], pmu = templatePoints[Gi.Third][mu];
// L[i] += (1 - d) * (pu - pmu);
// Mi += (1 - d);
// }
// L[i] /= Mi;
// g.DrawString(templateChars[Gi.Third], new Font("Arial", 12), Brushes.Green,
// new PointF((float)L[i].X, (float)L[i].Y));
// }
//}
//#endregion
mmg.Save(Path.Combine(@"D:\Play Data\测试玩意", filename + ".bmp"));
Debug("{0}\t用时{1}ms.", filename, timer.Stop());
}
#endregion
}
private static void testCAPTCHA()
{
var timer = new MyTimer();
int s = 100, K = 100, m = 180;
string[] templatefiles = Directory.GetFiles(@"D:\Play Data\my_template_data\scq-" + K + "-" + m, "*.scq")
.Take(10000).ToArray();
#region 打开量化的模板
int templatecount = templatefiles.Length;
Debug("打开{0}个量化模板----------------------------------------", templatecount);
timer.Restart();
int[][] templatehistograms = new int[templatecount][];
string[] templatechars = new string[templatecount];
for (int f = 0; f < templatecount; ++f) {
string file = templatefiles[f];
string filename = Path.GetFileNameWithoutExtension(file);
templatechars[f] = filename.Split('-')[1];
templatehistograms[f] = new int[K];
using (var fs = new FileStream(file, FileMode.Open)) {
using (var br = new BinaryReader(fs)) {
for (int i = 0; i < K; ++i) {
templatehistograms[f][i] = br.ReadInt32();
}
}
}
}
Debug("打开完成，用时{0}ms.", timer.Stop());
#endregion
#region 打开Shapeme
Debug("打开{0}个Shapeme.", K);
timer.Restart();
double[][] shapemes = new double[K][];
using (var fs = new FileStream(Path.Combine(@"D:\Play Data\my_template_data\sm-" + K, m + ".sm"), FileMode.Open)) {
using (var br = new BinaryReader(fs)) {
for (int i = 0; i < K; ++i) {
shapemes[i] = new double[60];
for (int k = 0; k < 60; ++k) {
shapemes[i][k] = br.ReadDouble();
}
}
}
}
Debug("Shapeme读取完成，用时{0}ms.", timer.Stop());
#endregion
#region 识别
foreach (var challengeFile in Directory.GetFiles(@"D:\Play Data\字符\", "*.jpg")) {
timer.Restart();
string filename = Path.GetFileNameWithoutExtension(challengeFile);
Image<Gray, Byte> img = new Image<Gray, byte>(challengeFile);
var mmp = img.Convert<Bgr, Byte>();
Graphics g = Graphics.FromImage(mmp.Bitmap);
double width_height_ratio = (double)img.Width / img.Height;
int sq = (int)(s * width_height_ratio * 1.2);
int randcount = (int)(width_height_ratio * 2);
//int windowcount = (int)(width_height_ratio * 2),
// windowstep = (int)(img.Width / windowcount),
// windowwidth = (int)(img.Width * 1.5 / windowcount);
//int maxrandcount = randcount * 3;
//Console.WriteLine("宽高比{0:F2},采样{1},随机数{2},随机上限{3}.",
// width_height_ratio, sq, randcount, maxrandcount);
int slice = 16,//(int)(width_height_ratio * width_height_ratio),
overlap = 4,
windowcount = 7;//slice - (overlap - 1);
double slice_width = (double)img.Width / slice;
Console.WriteLine("宽高比{0:F2},切片数{1},切片宽度{2:F2},窗口数{3}.",
width_height_ratio, slice, slice_width, windowcount);
var edge = getEdge(img).Sample(sq);
foreach (var p in edge) {
mmp[p] = new Bgr(0, 0, 127);
}
bool[] edge_vi = Utils.InitArray(sq, false);
#region 计算采样点之间的距离
ValueIndexPair<double>[][] edgedists = new ValueIndexPair<double>[sq][];
for (int i = 0; i < sq; ++i) {
edgedists[i] = new ValueIndexPair<double>[sq];
for (int j = 0; j < sq; ++j) {
double xi = edge[i].X, yi = edge[i].Y,
xj = edge[j].X, yj = edge[j].Y;
double d = Math.Sqrt((xi - xj) * (xi - xj) + (yi - yj) * (yi - yj));
edgedists[i][j] = new ValueIndexPair<double> { Value = d, Index = j };
}
Array.Sort(edgedists[i], (a, b) => a.Value.CompareTo(b.Value));
}
#endregion
var charlist = new List<Tuple<string, int, PointF>>(); // <ch, count, center>
//for (int rc = 0, rt = 0; rc < randcount && rt < maxrandcount; ++rt) {
// #region 随机取一个中心点，并且取离他近的点计算形状上下文
//int center = rand.Next(sq);
//if (edge_vi[center]) continue;
//else rc++;
//rc++;
//var nearby = new List<Point>();
//foreach (var pair in edgedists[center].Take((int)(s * 1.5))) {
// nearby.Add(edge[pair.Index]);
// edge_vi[pair.Index] = true;
//}
//nearby = nearby.Sample(s);
for (int wd = 0; wd < windowcount; ++wd) {
#region 滑动窗口位置
//int window_center = wd * windowstep + (windowwidth / 2);
double window_center = (wd * 2 + overlap / 2.0) * slice_width;
g.DrawLine(Pens.Green, (float)window_center, 0, (float)window_center, img.Height);
var nearby = edge.Where(p => Math.Abs(p.X - window_center) < img.Height)
.OrderBy(p => Math.Abs(p.X - window_center))
.Take((int)(s * 1.2))
.ToList().Sample(s);
if (nearby.Average(p => Math.Abs(p.X - window_center)) > img.Height) continue;
var sc = Jim.OCR.ShapeContext2D.ShapeContext.ComputeSC2(nearby);
#endregion
#region 对待测图的形状上下文进行量化
int[] histogram = new int[K];
for (int i = 0; i < s; ++i) {
double[] ds = new double[K];
for (int j = 0; j < K; ++j)
ds[j] = Jim.OCR.ShapeContext2D.ShapeContext.HistCost(sc[i], shapemes[j]);
int id = ds.Select((v, idx) => new ValueIndexPair<double> { Value = v, Index = idx })
.OrderBy(p => p.Value)
.First().Index;
++histogram[id];
}
#endregion
#region 计算量化后的比较距离
double[] dists = new double[templatecount];
for (int i = 0; i < templatecount; ++i) {
//dists[i] = Jim.OCR.ShapeContext2D.ShapeContext.ChiSquareDistance(histogram, templatehistograms[i]);
dists[i] = Jim.OCR.ShapeContext2D.ShapeContext.HistCost(
histogram.Select(d => (double)d).ToArray(),
templatehistograms[i].Select(d => (double)d).ToArray());
}
#endregion
#region 对结果进行排序和统计
var arr = dists.Select((d, i) => new ValueIndexPair<double> { Value = d, Index = i })
.OrderBy(p => p.Value)
.Select(p => new { Distance = p.Value, Char = templatechars[p.Index] })
.Where(p => "0123456789".IndexOf(p.Char) != -1)
.ToArray();
Dictionary<string, int> matchcount = new Dictionary<string, int>();
int knn = 10;
foreach (var pair in arr.Take(knn)) {
string ch = pair.Char;
matchcount[ch] = matchcount.ContainsKey(ch) ? matchcount[ch] + 1 : 1;
}
var match = matchcount.Select(pair => new { Count = pair.Value, Ch = pair.Key })
.Where(v => v.Count > 0)
.OrderByDescending(v => v.Count).ToArray();
var firstmatch = match[0];
PointF newcenter = new PointF(nearby.Average(p => (float)p.X), nearby.Average(p => (float)p.Y));
charlist.Add(new Tuple<string, int, PointF> {
First = firstmatch.Ch,
Second = firstmatch.Count,
Third = newcenter
});
#endregion
}
foreach (var tp in charlist) {
string ch = tp.First;
int acc = tp.Second;
PointF center = tp.Third;
//g.DrawString(num.ToString(), new Font("Arial", 24), new SolidBrush(Color.FromArgb(40 + 20 * acc, 0, 0)),
// new PointF(center.X - 12, center.Y - 12));
g.DrawString(ch, new Font("Arial", 24), (acc >= 5 ? Brushes.Red : Brushes.DarkGreen),
new PointF(center.X - 12, center.Y - 12));
}
mmp.Save(Path.Combine(@"D:\Play Data\测试玩意\", filename + ".jpg"));
Debug("{0}-{1}ms", filename, timer.Stop());
}
#endregion
}
public Tuple <string, int> Recognize(Image <Gray, byte> src)
{
var list = src.getEdge().Sample(100);
#region 计算形状上下文
int r = 15;
var scall = Jim.OCR.ShapeContext2D.ShapeContext.ComputeSC(list);
var scq = new double[r, 60];
for (int i = 0; i < r; ++i)
{
int pos = rand.Next(list.Count);
for (int k = 0; k < 60; ++k)
{
scq[i, k] = scall[pos, k];
}
}
#endregion
#region 计算距离
var dists = new ValueIndexPair <double> [SC.template_sc.Length];
for (int i = 0; i < SC.template_sc.Length; ++i)
{
double[,] sci = SC.template_sc[i];
double[,] costmat = Jim.OCR.ShapeContext2D.ShapeContext.HistCost(scq, sci);
double cost = 0;
for (int j = 0; j < r; ++j)
{
double min = double.MaxValue;
for (int u = 0; u < 100; ++u)
{
double val = costmat[j, u];
if (val < min)
{
min = val;
}
}
cost += min;
}
dists[i] = new ValueIndexPair <double> {
Value = cost, Index = i
};
}
#endregion
#region 对结果排序
var arr = dists
.OrderBy(p => p.Value)
.Select(p => new { Distance = p.Value, Char = SC.template_chars[p.Index] })
//.Where(p => "ABCDEFGHIJKLMNPQRSTUVWXYZ123456789".IndexOf(p.Char) != -1)
.Where(p => Filter.IndexOf(p.Char) != -1)
.ToArray();
Dictionary <string, int> matchcount = new Dictionary <string, int>();
foreach (var pair in arr.Take(Knn))
{
string ch = pair.Char;
matchcount[ch] = matchcount.ContainsKey(ch) ? matchcount[ch] + 1 : 1;
}
var match = matchcount.Select(pair => new { Count = pair.Value, Ch = pair.Key })
.Where(v => v.Count > 0)
.OrderByDescending(v => v.Count).ToArray();
//string result = "";
//foreach (var m in match.Take(3)) {
// result += String.Format("Char:'{0}',Accuracy:{1}/{2}\t", m.Ch, m.Count, knn);
//}
#endregion
return(new Tuple <string, int> {
First = match[0].Ch, Second = match[0].Count
});
}
public void Run()
{
double totaltime = 0;
int s = 100, r = 5;
string[] templatefiles = Directory.GetFiles(@"D:\Play Data\train_data\sc\", "*.sc")
.Take(100).ToArray();
#region 打开模板
string templatepath = @"D:\Play Data\template\";
int templatecount = templatefiles.Length;
Debug("打开{0}个模板--------------------------------------------", templatecount);
double[][,] templates = new double[templatecount][, ];
int[] templatenums = new int[templatecount];
timer.Restart();
for (int i = 0; i < templatefiles.Length; ++i)
{
string file = templatefiles[i];
string filename = Path.GetFileNameWithoutExtension(file);
templatenums[i] = int.Parse(filename.Split('-')[1]);
templates[i] = new double[s, 60];
using (var fs = new FileStream(file, FileMode.Open)) {
using (var br = new BinaryReader(fs)) {
for (int j = 0; j < s; ++j)
{
for (int k = 0; k < 60; ++k)
{
templates[i][j, k] = br.ReadDouble();
}
}
}
}
if (i % 100 == 0)
{
Debug("已完成{0}个", i);
}
}
Debug("模板读取完成，用时{0}ms.", timer.Stop());
#endregion
string[] testfiles = Directory.GetFiles(@"D:\Play Data\test\", "*.bmp")
.Take(1000).ToArray();
#region 测试
int testcase = testfiles.Length, acc = 0;
Debug("为{0}个对象寻找候选模板------------------------------------------", testcase);
foreach (var file in testfiles)
{
timer.Restart();
string filenameext = Path.GetFileName(file);
string filename = Path.GetFileNameWithoutExtension(file);
int thisnum = int.Parse(filename.Split('-')[1]);
Image <Gray, Byte> img = new Image <Gray, byte>(file);
var list = getEdge(img.Resize(2.5, Emgu.CV.CvEnum.INTER.CV_INTER_LINEAR)).Sample(s);
var sc100 = Jim.OCR.ShapeContext2D.ShapeContext.ComputeSC(list);
double[,] scq = new double[r, 60];
for (int i = 0; i < 5; ++i)
{
int pos = rand.Next(s);
for (int k = 0; k < 60; ++k)
{
scq[i, k] = sc100[pos, k];
}
}
var arr = new ValueIndexPair <double> [templatecount];
for (int i = 0; i < templatecount; ++i)
{
double[,] sci = templates[i];
double[,] costmat = Jim.OCR.ShapeContext2D.ShapeContext.HistCost(scq, sci);
double cost = 0;
for (int j = 0; j < 5; ++j)
{
double min = double.MaxValue;
for (int u = 0; u < s; ++u)
{
double val = costmat[j, u];
if (val < min)
{
min = val;
}
}
cost += min;
}
arr[i] = new ValueIndexPair <double> {
Value = cost, Index = i
};
}
Array.Sort(arr, (a, b) => a.Value.CompareTo(b.Value));
int knn = 10;
#region 进行精细匹配
var kmresults = new List <ValueIndexPair <double> >();
foreach (var pair in arr.Take(knn))
{
int idx = pair.Index;
var costmat = Jim.OCR.ShapeContext2D.ShapeContext.HistCost(templates[idx], sc100);
var costmat_int = new int[s, s];
for (int ii = 0; ii < s; ++ii)
{
for (int jj = 0; jj < s; ++jj)
{
costmat_int[ii, jj] = (int)(costmat[ii, jj] * 10000);
}
}
var km = new KM(s, costmat_int);
km.Match(false);
kmresults.Add(new ValueIndexPair <double> {
Index = idx, Value = km.MatchResult / 10000.0
});
}
kmresults.Sort((a, b) => a.Value.CompareTo(b.Value));
#endregion
//int firstmatch = match[0].Num;
int firstmatch = templatenums[kmresults[0].Index];
var fc = Console.ForegroundColor;
Console.ForegroundColor = firstmatch == thisnum ? ConsoleColor.Green : ConsoleColor.Red;
var timeused = timer.Stop();
totaltime += timeused;
string info = String.Format("{0} {1}ms\t", filename, timeused);
//foreach (var m in bestmatches.Take(4)) {
foreach (var m in kmresults.Take(4))
{
info += String.Format("{0}/{1:F2}\t", templatenums[m.Index], m.Value);
}
//Debug(info);
if (firstmatch != thisnum)
{
Console.Write(".");
}
Console.ForegroundColor = fc;
if (firstmatch == thisnum)
{
++acc;
}
}
Debug("\nRSC and KM 测试用例：{0}。正确率{1}。", testcase, acc);
Console.WriteLine("总用时：{0}ms，平均用时：{1}ms。", totaltime, totaltime / testcase);
#endregion
}
public void Run()
{
double totaltime = 0;
int s = 100, r = 5;
string[] templatefiles = Directory.GetFiles(@"D:\Play Data\train_data\sc\", "*.sc")
.Take(100).ToArray();
#region 打开模板
string templatepath = @"D:\Play Data\template\";
int templatecount = templatefiles.Length;
Debug("打开{0}个模板--------------------------------------------", templatecount);
double[][,] templates = new double[templatecount][, ];
int[] templatenums = new int[templatecount];
timer.Restart();
for (int i = 0; i < templatefiles.Length; ++i)
{
string file = templatefiles[i];
string filename = Path.GetFileNameWithoutExtension(file);
templatenums[i] = int.Parse(filename.Split('-')[1]);
templates[i] = new double[s, 60];
using (var fs = new FileStream(file, FileMode.Open)) {
using (var br = new BinaryReader(fs)) {
for (int j = 0; j < s; ++j)
{
for (int k = 0; k < 60; ++k)
{
templates[i][j, k] = br.ReadDouble();
}
}
}
}
if (i % 100 == 0)
{
Debug("已完成{0}个", i);
}
}
Debug("模板读取完成，用时{0}ms.", timer.Stop());
#endregion
string[] testfiles = Directory.GetFiles(@"D:\Play Data\test\", "*.bmp")
.Take(1000).ToArray();
#region 测试
int testcase = testfiles.Length, acc = 0;
Debug("为{0}个对象寻找候选模板------------------------------------------", testcase);
foreach (var file in testfiles)
{
timer.Restart();
string filenameext = Path.GetFileName(file);
string filename = Path.GetFileNameWithoutExtension(file);
int thisnum = int.Parse(filename.Split('-')[1]);
Image <Gray, Byte> img = new Image <Gray, byte>(file);
var list = getEdge(img.Resize(2.5, Emgu.CV.CvEnum.INTER.CV_INTER_LINEAR)).Sample(s);
var sc100 = Jim.OCR.ShapeContext2D.ShapeContext.ComputeSC(list);
double[,] scq = new double[r, 60];
for (int i = 0; i < 5; ++i)
{
int pos = rand.Next(s);
for (int k = 0; k < 60; ++k)
{
scq[i, k] = sc100[pos, k];
}
}
var arr = new ValueIndexPair <double> [templatecount];
for (int i = 0; i < templatecount; ++i)
{
double[,] sci = templates[i];
double[,] costmat = Jim.OCR.ShapeContext2D.ShapeContext.HistCost(scq, sci);
double cost = 0;
for (int j = 0; j < 5; ++j)
{
double min = double.MaxValue;
for (int u = 0; u < s; ++u)
{
double val = costmat[j, u];
if (val < min)
{
min = val;
}
}
cost += min;
}
arr[i] = new ValueIndexPair <double> {
Value = cost, Index = i
};
}
Array.Sort(arr, (a, b) => a.Value.CompareTo(b.Value));
int[] matchcount = new int[10];
double[] matchcost = new double[10];
int knn = 10;
foreach (var pair in arr.Take(knn))
{
int num = templatenums[pair.Index];
matchcount[num]++;
matchcost[num] += pair.Value;
}
var match = matchcount.Select((val, i) => new { Count = val, Num = i })
.Where(v => v.Count > 0)
.OrderByDescending(v => v.Count).ToArray();
//var match = matchcost.Select((val, i) => new { Cost = val / matchcount[i], Num = i })
// .Where(v => !double.IsNaN(v.Cost))
// .OrderBy(v => v.Cost).ToArray();
#region 进行精细匹配，效果一般
//double[] matchrate = new double[10];
//foreach (var m in match) {
// if (m.Count == 0) break;
// string template = Path.Combine(templatepath, m.Num + ".bmp");
// Jim.OCR.ShapeContext2D.ShapeContext sc = new Jim.OCR.ShapeContext2D.ShapeContext(file, template);
// sc.debug_flag = false;
// sc.timer_flag = false;
// sc.display_flag = false;
// sc.n_iter = 3;
// sc.matchScale = 2.5;
// sc.maxsamplecount = 100;
// matchrate[m.Num] = sc.MatchFile();
//}
//var bestmatches = matchrate.Select((val, i) => new { Cost = val, Num = i })
// .Where(m => m.Cost > 0)
// .OrderBy(m => m.Cost).ToArray();
//int firstmatch = bestmatches[0].Num;
#endregion
int firstmatch = match[0].Num;
var fc = Console.ForegroundColor;
Console.ForegroundColor = firstmatch == thisnum ? ConsoleColor.Green : ConsoleColor.Red;
var timeused = timer.Stop();
totaltime += timeused;
string info = String.Format("{0} {1}ms - {2}\t", filename, timeused, (firstmatch == thisnum ? "Right" : "Wrong"));
//foreach (var m in bestmatches.Take(4)) {
foreach (var m in match)
{
info += String.Format("{0}/{1}\t", m.Num, m.Count);
//info += String.Format("{0}/{1:F3}\t", m.Num, m.Cost);
//info += String.Format("{0}/{1:F3}\t", m.Num, m.Cost);
}
//Debug(info);
if (firstmatch != thisnum)
{
Console.Write(".");
}
Console.ForegroundColor = fc;
if (firstmatch == thisnum)
{
++acc;
}
}
Debug("\nRSC 测试用例：{0}。正确率{1}。", testcase, acc);
Console.WriteLine("总用时：{0}ms，平均用时：{1}ms。", totaltime, totaltime / testcase);
#endregion
}
public void Run()
{
double totaltime = 0;
int s = 100, r = 5;
string[] templatefiles = Directory.GetFiles(@"D:\Play Data\train_data\sc\", "*.sc")
.Take(100).ToArray();
#region 打开模板
string templatepath = @"D:\Play Data\template\";
int templatecount = templatefiles.Length;
Debug("打开{0}个模板--------------------------------------------", templatecount);
double[][,] templates = new double[templatecount][,];
int[] templatenums = new int[templatecount];
timer.Restart();
for (int i = 0; i < templatefiles.Length; ++i) {
string file = templatefiles[i];
string filename = Path.GetFileNameWithoutExtension(file);
templatenums[i] = int.Parse(filename.Split('-')[1]);
templates[i] = new double[s, 60];
using (var fs = new FileStream(file, FileMode.Open)) {
using (var br = new BinaryReader(fs)) {
for (int j = 0; j < s; ++j) {
for (int k = 0; k < 60; ++k) {
templates[i][j, k] = br.ReadDouble();
}
}
}
}
if (i % 100 == 0)
Debug("已完成{0}个", i);
}
Debug("模板读取完成，用时{0}ms.", timer.Stop());
#endregion
string[] testfiles = Directory.GetFiles(@"D:\Play Data\test\", "*.bmp")
.Take(1000).ToArray();
#region 测试
int testcase = testfiles.Length, acc = 0;
Debug("为{0}个对象寻找候选模板------------------------------------------", testcase);
foreach (var file in testfiles) {
timer.Restart();
string filenameext = Path.GetFileName(file);
string filename = Path.GetFileNameWithoutExtension(file);
int thisnum = int.Parse(filename.Split('-')[1]);
Image<Gray, Byte> img = new Image<Gray, byte>(file);
var list = getEdge(img.Resize(2.5, Emgu.CV.CvEnum.INTER.CV_INTER_LINEAR)).Sample(s);
var sc100 = Jim.OCR.ShapeContext2D.ShapeContext.ComputeSC(list);
double[,] scq = new double[r, 60];
for (int i = 0; i < 5; ++i) {
int pos = rand.Next(s);
for (int k = 0; k < 60; ++k) {
scq[i, k] = sc100[pos, k];
}
}
var arr = new ValueIndexPair<double>[templatecount];
for (int i = 0; i < templatecount; ++i) {
double[,] sci = templates[i];
double[,] costmat = Jim.OCR.ShapeContext2D.ShapeContext.HistCost(scq, sci);
double cost = 0;
for (int j = 0; j < 5; ++j) {
double min = double.MaxValue;
for (int u = 0; u < s; ++u) {
double val = costmat[j, u];
if (val < min) min = val;
}
cost += min;
}
arr[i] = new ValueIndexPair<double> { Value = cost, Index = i };
}
Array.Sort(arr, (a, b) => a.Value.CompareTo(b.Value));
int knn = 10;
#region 进行精细匹配
var kmresults = new List<ValueIndexPair<double>>();
foreach (var pair in arr.Take(knn)) {
int idx = pair.Index;
var costmat = Jim.OCR.ShapeContext2D.ShapeContext.HistCost(templates[idx], sc100);
var costmat_int = new int[s, s];
for (int ii = 0; ii < s; ++ii) {
for (int jj = 0; jj < s; ++jj) {
costmat_int[ii, jj] = (int)(costmat[ii, jj] * 10000);
}
}
var km = new KM(s, costmat_int);
km.Match(false);
kmresults.Add(new ValueIndexPair<double> { Index = idx, Value = km.MatchResult / 10000.0 });
}
kmresults.Sort((a, b) => a.Value.CompareTo(b.Value));
#endregion
//int firstmatch = match[0].Num;
int firstmatch = templatenums[kmresults[0].Index];
var fc = Console.ForegroundColor;
Console.ForegroundColor = firstmatch == thisnum ? ConsoleColor.Green : ConsoleColor.Red;
var timeused = timer.Stop();
totaltime += timeused;
string info = String.Format("{0} {1}ms\t", filename, timeused);
//foreach (var m in bestmatches.Take(4)) {
foreach (var m in kmresults.Take(4)) {
info += String.Format("{0}/{1:F2}\t", templatenums[m.Index], m.Value);
}
//Debug(info);
if (firstmatch != thisnum) Console.Write(".");
Console.ForegroundColor = fc;
if (firstmatch == thisnum) {
++acc;
}
}
Debug("\nRSC and KM 测试用例：{0}。正确率{1}。", testcase, acc);
Console.WriteLine("总用时：{0}ms，平均用时：{1}ms。", totaltime, totaltime / testcase);
#endregion
}
private void recognize_rsc()
{
if (template_histograms == null) {
MessageBox.Show("尚未读取模板。");
return;
}
new Thread(new ThreadStart(() => {
clearLog();
showStatus("搜索中");
foreach (var challenge in splitted_chars) {
timer.Restart();
var list = challenge.getEdge().Sample(100);
#region 计算形状上下文
int r = 15;
var scall = Jim.OCR.ShapeContext2D.ShapeContext.ComputeSC(list);
var scq = new double[r, 60];
for (int i = 0; i < r; ++i) {
int pos = rand.Next(list.Count);
for (int k = 0; k < 60; ++k) {
scq[i, k] = scall[pos, k];
}
}
#endregion
#region 计算距离
var dists = new ValueIndexPair<double>[template_sc.Length];
for (int i = 0; i < template_sc.Length; ++i) {
double[,] sci = template_sc[i];
double[,] costmat = Jim.OCR.ShapeContext2D.ShapeContext.HistCost(scq, sci);
double cost = 0;
for (int j = 0; j < r; ++j) {
double min = double.MaxValue;
for (int u = 0; u < 100; ++u) {
double val = costmat[j, u];
if (val < min) min = val;
}
cost += min;
}
dists[i] = new ValueIndexPair<double> { Value = cost, Index = i };
showProgress((i + 1.0) / template_histograms.Length);
}
#endregion
#region 对结果排序
var arr = dists
.OrderBy(p => p.Value)
.Select(p => new { Distance = p.Value, Char = template_chars[p.Index] })
//.Where(p => "ABCDEFGHIJKLMNPQRSTUVWXYZ123456789".IndexOf(p.Char) != -1)
.ToArray();
Dictionary<string, int> matchcount = new Dictionary<string, int>();
int knn = 10;
foreach (var pair in arr.Take(knn)) {
string ch = pair.Char;
matchcount[ch] = matchcount.ContainsKey(ch) ? matchcount[ch] + 1 : 1;
}
var match = matchcount.Select(pair => new { Count = pair.Value, Ch = pair.Key })
.Where(v => v.Count > 0)
.OrderByDescending(v => v.Count).ToArray();
string result = "";
foreach (var m in match.Take(3)) {
result += String.Format("Char:'{0}',Accuracy:{1}/{2}\t", m.Ch, m.Count, knn);
}
appendLine(result);
#endregion
}
appendLine("-----------------------------------------------------");
showStatus("搜索完成，共用时{0}ms。", timer.Stop());
})).Start();
}
private void recognize_rsc()
{
if (template_histograms == null)
{
MessageBox.Show("尚未读取模板。");
return;
}
new Thread(new ThreadStart(() => {
clearLog();
showStatus("搜索中");
foreach (var challenge in splitted_chars)
{
timer.Restart();
var list = challenge.getEdge().Sample(100);
#region 计算形状上下文
int r = 15;
var scall = Jim.OCR.ShapeContext2D.ShapeContext.ComputeSC(list);
var scq = new double[r, 60];
for (int i = 0; i < r; ++i)
{
int pos = rand.Next(list.Count);
for (int k = 0; k < 60; ++k)
{
scq[i, k] = scall[pos, k];
}
}
#endregion
#region 计算距离
var dists = new ValueIndexPair <double> [template_sc.Length];
for (int i = 0; i < template_sc.Length; ++i)
{
double[,] sci = template_sc[i];
double[,] costmat = Jim.OCR.ShapeContext2D.ShapeContext.HistCost(scq, sci);
double cost = 0;
for (int j = 0; j < r; ++j)
{
double min = double.MaxValue;
for (int u = 0; u < 100; ++u)
{
double val = costmat[j, u];
if (val < min)
{
min = val;
}
}
cost += min;
}
dists[i] = new ValueIndexPair <double> {
Value = cost, Index = i
};
showProgress((i + 1.0) / template_histograms.Length);
}
#endregion
#region 对结果排序
var arr = dists
.OrderBy(p => p.Value)
.Select(p => new { Distance = p.Value, Char = template_chars[p.Index] })
//.Where(p => "ABCDEFGHIJKLMNPQRSTUVWXYZ123456789".IndexOf(p.Char) != -1)
.ToArray();
Dictionary <string, int> matchcount = new Dictionary <string, int>();
int knn = 10;
foreach (var pair in arr.Take(knn))
{
string ch = pair.Char;
matchcount[ch] = matchcount.ContainsKey(ch) ? matchcount[ch] + 1 : 1;
}
var match = matchcount.Select(pair => new { Count = pair.Value, Ch = pair.Key })
.Where(v => v.Count > 0)
.OrderByDescending(v => v.Count).ToArray();
string result = "";
foreach (var m in match.Take(3))
{
result += String.Format("Char:'{0}',Accuracy:{1}/{2}\t", m.Ch, m.Count, knn);
}
appendLine(result);
#endregion
}
appendLine("-----------------------------------------------------");
showStatus("搜索完成，共用时{0}ms。", timer.Stop());
})).Start();
}
public void Run()
{
double totaltime = 0;
int s = 100, r = 5;
string[] templatefiles = Directory.GetFiles(@"D:\Play Data\train_data\sc\", "*.sc")
.Take(100).ToArray();
#region 打开模板
string templatepath = @"D:\Play Data\template\";
int templatecount = templatefiles.Length;
Debug("打开{0}个模板--------------------------------------------", templatecount);
double[][,] templates = new double[templatecount][,];
int[] templatenums = new int[templatecount];
timer.Restart();
for (int i = 0; i < templatefiles.Length; ++i) {
string file = templatefiles[i];
string filename = Path.GetFileNameWithoutExtension(file);
templatenums[i] = int.Parse(filename.Split('-')[1]);
templates[i] = new double[s, 60];
using (var fs = new FileStream(file, FileMode.Open)) {
using (var br = new BinaryReader(fs)) {
for (int j = 0; j < s; ++j) {
for (int k = 0; k < 60; ++k) {
templates[i][j, k] = br.ReadDouble();
}
}
}
}
if (i % 100 == 0)
Debug("已完成{0}个", i);
}
Debug("模板读取完成，用时{0}ms.", timer.Stop());
#endregion
string[] testfiles = Directory.GetFiles(@"D:\Play Data\test\", "*.bmp")
.Take(100).ToArray();
#region 测试
int testcase = testfiles.Length, acc = 0;
Debug("为{0}个对象寻找候选模板------------------------------------------", testcase);
foreach (var file in testfiles) {
timer.Restart();
string filenameext = Path.GetFileName(file);
string filename = Path.GetFileNameWithoutExtension(file);
int thisnum = int.Parse(filename.Split('-')[1]);
Image<Gray, Byte> img = new Image<Gray, byte>(file);
var list = getEdge(img.Resize(2.5, Emgu.CV.CvEnum.INTER.CV_INTER_LINEAR)).Sample(s);
var scq = Jim.OCR.ShapeContext2D.ShapeContext.ComputeSC(list);
var arr = new ValueIndexPair<double>[templatecount];
for (int i = 0; i < templatecount; ++i) {
double[,] sci = templates[i];
double[,] costmat = Jim.OCR.ShapeContext2D.ShapeContext.HistCost(scq, sci);
var costmat_int = new int[s, s];
for (int ii = 0; ii < s; ++ii) {
for (int jj = 0; jj < s; ++jj) {
costmat_int[ii, jj] = (int)(costmat[ii, jj] * 10000);
}
}
var km = new KM(s, costmat_int);
km.Match(false);
arr[i] = new ValueIndexPair<double> { Index = i, Value = km.MatchResult / 10000.0 };
}
Array.Sort(arr, (a, b) => a.Value.CompareTo(b.Value));
int[] matchcount = new int[10];
double[] matchcost = new double[10];
int knn = 10;
foreach (var pair in arr.Take(knn)) {
int num = templatenums[pair.Index];
matchcount[num]++;
matchcost[num] += pair.Value;
}
var match = matchcount.Select((val, i) => new { Count = val, Num = i })
.Where(v => v.Count > 0)
.OrderByDescending(v => v.Count).ToArray();
//var match = matchcost.Select((val, i) => new { Cost = val / matchcount[i], Num = i })
// .Where(v => !double.IsNaN(v.Cost))
// .OrderBy(v => v.Cost).ToArray();
#region 进行精细匹配，效果一般
//double[] matchrate = new double[10];
//foreach (var m in match) {
// if (m.Count == 0) break;
// string template = Path.Combine(templatepath, m.Num + ".bmp");
// Jim.OCR.ShapeContext2D.ShapeContext sc = new Jim.OCR.ShapeContext2D.ShapeContext(file, template);
// sc.debug_flag = false;
// sc.timer_flag = false;
// sc.display_flag = false;
// sc.n_iter = 3;
// sc.matchScale = 2.5;
// sc.maxsamplecount = 100;
// matchrate[m.Num] = sc.MatchFile();
//}
//var bestmatches = matchrate.Select((val, i) => new { Cost = val, Num = i })
// .Where(m => m.Cost > 0)
// .OrderBy(m => m.Cost).ToArray();
//int firstmatch = bestmatches[0].Num;
#endregion
int firstmatch = match[0].Num;
var fc = Console.ForegroundColor;
Console.ForegroundColor = firstmatch == thisnum ? ConsoleColor.Green : ConsoleColor.Red;
var timeused = timer.Stop();
totaltime += timeused;
string info = String.Format("{0} {1}ms - {2}\t", filename, timeused, (firstmatch == thisnum ? "Right" : "Wrong"));
//foreach (var m in bestmatches.Take(4)) {
foreach (var m in match) {
info += String.Format("{0}/{1}\t", m.Num, m.Count);
//info += String.Format("{0}/{1:F3}\t", m.Num, m.Cost);
//info += String.Format("{0}/{1:F3}\t", m.Num, m.Cost);
}
Debug(info);
Console.ForegroundColor = fc;
if (firstmatch == thisnum) {
++acc;
}
}
Debug("测试用例：{0}。正确率{1}。", testcase, acc);
Console.WriteLine("总用时：{0}ms，平均用时：{1}ms。", totaltime, totaltime / testcase);
#endregion
}
