public void SetAspectRatio()
{
const double left = 0;
const double top = 0;
const double right = 100;
const double bottom = 100;
var rect = new DRectangle(left, top, right, bottom);
rect = DRectangle.SetAspectRatio(rect, 2);
Assert.AreEqual(rect.Left, -20.917784899841294);
Assert.AreEqual(rect.Top, 14.791107550079353);
Assert.AreEqual(rect.Right, 120.91778489984129);
Assert.AreEqual(rect.Bottom, 85.208892449920654);
try
{
rect = DRectangle.SetAspectRatio(rect, 0);
Assert.Fail($"{nameof(DRectangle.SetAspectRatio)} should throw {nameof(ArgumentOutOfRangeException)} if ration is 0");
}
catch (ArgumentOutOfRangeException e)
{
}
}
public void OperatorAdd()
{
var lleft = (double)this.NextRandom(0, 100);
var ltop = (double)this.NextRandom(0, 100);
var lright = lleft * 2;
var lbottom = ltop * 2;
var rleft = (double)this.NextRandom(0, 100);
var rtop = (double)this.NextRandom(0, 100);
var rright = rleft * 2;
var rbottom = rtop * 2;
var r = new DRectangle(lleft, ltop, lright, lbottom);
var l = new DRectangle(rleft, rtop, rright, rbottom);
var rl = r + l;
Assert.AreEqual(rl.Left, Math.Min(l.Left, r.Left));
Assert.AreEqual(rl.Top, Math.Min(l.Top, r.Top));
Assert.AreEqual(rl.Right, Math.Max(l.Right, r.Right));
Assert.AreEqual(rl.Bottom, Math.Max(l.Bottom, r.Bottom));
this.DisposeAndCheckDisposedState(rl);
this.DisposeAndCheckDisposedState(l);
this.DisposeAndCheckDisposedState(r);
}
public void OperatorEqual()
{
for (var left = 1; left <= 100; left++)
{
for (var top = 1; top <= 100; top++)
{
var right = left * 2;
var bottom = top * 2;
var r = new DRectangle(left, top, right, bottom);
var l = new DRectangle(left, top, right, bottom);
var l1 = new DRectangle(left, top, right * 2, bottom);
var l2 = new DRectangle(left, top, right, bottom * 2);
var l3 = new DRectangle(left * 2, top, right, bottom);
var l4 = new DRectangle(left, top * 2, right, bottom);
Assert.AreEqual(r, l, $"left: {left}, top: {top}, right: {right}, bottom: {bottom}");
Assert.AreNotEqual(r, l1, $"left: {left}, top: {top}, right: {right}, bottom: {bottom}");
Assert.AreNotEqual(r, l2, $"left: {left}, top: {top}, right: {right}, bottom: {bottom}");
Assert.AreNotEqual(r, l3, $"left: {left}, top: {top}, right: {right}, bottom: {bottom}");
Assert.AreNotEqual(r, l4, $"left: {left}, top: {top}, right: {right}, bottom: {bottom}");
}
}
}
public void TryTrack()
{
const string testName = "TryTrack";
var tests = new[]
{
new { Type = ImageTypes.Int32, ExpectResult = true }
};
var type = this.GetType().Name;
foreach (var input in tests)
{
var tracker = new CorrelationTracker();
try
{
var index = 0;
foreach (var file in this.GetDataFiles("video_frames").Where(info => info.Name.EndsWith("jpg")))
{
var expectResult = input.ExpectResult;
var inputType = input.Type;
var imageObj = DlibTest.LoadImage(input.Type, file);
if (index == 0)
{
using (var rect = DRectangle.CenteredRect(93, 110, 38, 86))
tracker.StartTrack(imageObj, rect);
}
var outputImageAction = new Func <bool, Array2DBase>(expect =>
{
if (index != 0)
{
tracker.Update(imageObj);
}
return(imageObj);
});
var successAction = new Action <Array2DBase>(image =>
{
if (index != 0)
{
tracker.Update(image);
}
using (var r = tracker.GetPosition())
{
using (var img = Dlib.LoadImage <RgbPixel>(file.FullName))
{
Dlib.DrawRectangle(img, (Rectangle)r, new RgbPixel {
Red = 255
}, 3);
Dlib.SaveJpeg(img, Path.Combine(this.GetOutDir(type), $"{Path.GetFileNameWithoutExtension(file.FullName)}.jpg"));
}
}
});
var failAction = new Action(() =>
{
Assert.Fail($"{testName} should throw excption for InputType: {inputType}.");
});
var finallyAction = new Action(() =>
{
index++;
if (imageObj != null)
{
this.DisposeAndCheckDisposedState(imageObj);
}
});
var exceptionAction = new Action(() =>
{
Console.WriteLine($"Failed to execute {testName} to InputType: {inputType}.");
});
DoTest(outputImageAction, expectResult, successAction, finallyAction, failAction, exceptionAction);
}
}
finally
{
this.DisposeAndCheckDisposedState(tracker);
}
}
}
public void Create1()
{
var rect = new DRectangle();
}
private static void Main(string[] args)
{
if (args.Length != 1)
{
Console.WriteLine("Call this program like this: ");
Console.WriteLine("VideoTracking.exe <path of video_frames directory>");
return;
}
var path = args[0];
var files = new DirectoryInfo(path).GetFiles("*.jpg").Select(info => info.FullName).ToList();
files.Sort();
if (files.Count == 0)
{
Console.WriteLine($"No images found in {path}");
return;
}
// 定义图像捕捉方式 从摄像头 ， 注意 Windows下需要选择 VideoCaptureAPIs.DSHOW
var cap = new VideoCapture(0, VideoCaptureAPIs.DSHOW);
// 定义图像捕捉方式 从摄像头 视频文件
//var cap = new VideoCapture("video.webm");
//判断捕捉设备是否打开
if (!cap.IsOpened())
{
Console.WriteLine("Unable to connect to camera");
return;
}
Mat temp = null;
var tracker = new CorrelationTracker();
int init = 0;
//定义显示窗口
using (var win = new ImageWindow())
{
Console.WriteLine("对象追踪程序启动");
Console.WriteLine("选择命令行为当前窗口，通过按键选择需要追踪的区域Width: [A,Z] Height:[S,X] X:[right,left] Y:[up,down] ,点击Enter开始追踪");
Console.WriteLine("注意：切换命令行窗口输入法为英文输入状态");
//选择追踪对象
while (!win.IsClosed())
{
//获得1帧图片
temp = cap.RetrieveMat();// new Mat();
if (temp == null)
{
Console.WriteLine("图像获取错误!");
return;
}
var array = new byte[temp.Width * temp.Height * temp.ElemSize()];
Marshal.Copy(temp.Data, array, 0, array.Length);
using (var cimg = Dlib.LoadImageData <BgrPixel>(array, (uint)temp.Height, (uint)temp.Width, (uint)(temp.Width * temp.ElemSize())))
{
init++;
if (init > 1)
{
var KK = Console.ReadKey();
if (KK.Key == ConsoleKey.Enter)
{
Console.WriteLine("开始追踪目标!");
//确定 追踪 位置
var rect2 = DRectangle.CenteredRect(a_X, a_Y, a_W, a_H);
//开始追踪
tracker.StartTrack(cimg, rect2);
win.SetImage(cimg);
win.ClearOverlay();
win.AddOverlay(rect2);
break;
}
//选择 追踪区域
if (KK.Key == ConsoleKey.RightArrow || KK.Key == ConsoleKey.LeftArrow || KK.Key == ConsoleKey.UpArrow || KK.Key == ConsoleKey.DownArrow || KK.Key == ConsoleKey.A || KK.Key == ConsoleKey.Z || KK.Key == ConsoleKey.S || KK.Key == ConsoleKey.X)
{
if (KK.Key == ConsoleKey.RightArrow)
{
a_X++;
if (a_X > cimg.Rect.Width - a_W)
{
a_X = cimg.Rect.Width - a_W;
}
}
if (KK.Key == ConsoleKey.LeftArrow)
{
a_X--;
if (a_X < 0)
{
a_X = 0;
}
}
if (KK.Key == ConsoleKey.UpArrow)
{
a_Y--;
if (a_Y < 0)
{
a_Y = 0;
}
}
if (KK.Key == ConsoleKey.DownArrow)
{
a_Y++;
if (a_Y > cimg.Rect.Height - a_H)
{
a_Y = cimg.Rect.Height - a_H;
}
}
if (KK.Key == ConsoleKey.A)
{
a_W++;
if (a_W >= cimg.Rect.Width - a_X)
{
a_W = cimg.Rect.Width - a_X;
}
}
if (KK.Key == ConsoleKey.Z)
{
a_W--;
if (a_W < 10)
{
a_W = 10;
}
}
if (KK.Key == ConsoleKey.S)
{
a_H++;
if (a_H > cimg.Rect.Height - a_Y)
{
a_H = cimg.Rect.Height - a_Y;
}
}
if (KK.Key == ConsoleKey.X)
{
a_H--;
if (a_H < 10)
{
a_H = 10;
}
}
}
}
var rect = DRectangle.CenteredRect(a_X, a_Y, a_W, a_H);
Console.WriteLine("Set RECT:" + a_X + " " + a_Y + " " + a_W + " " + a_H);
//显示图片
win.SetImage(cimg);
win.ClearOverlay();
//显示框
win.AddOverlay(rect);
}
}
//选择追踪对象
while (!win.IsClosed())
{
//获得1帧图片
temp = cap.RetrieveMat();// new Mat();
if (temp == null)
{
Console.WriteLine("图像获取错误!");
return;
}
var array = new byte[temp.Width * temp.Height * temp.ElemSize()];
Marshal.Copy(temp.Data, array, 0, array.Length);
using (var cimg = Dlib.LoadImageData <BgrPixel>(array, (uint)temp.Height, (uint)temp.Width, (uint)(temp.Width * temp.ElemSize())))
{
//更新追踪图像
tracker.Update(cimg);
win.SetImage(cimg);
win.ClearOverlay();
//获得追踪到的目标位置
DRectangle rect = tracker.GetPosition();
win.AddOverlay(rect);
Console.WriteLine("OBJ RECT:" + (int)rect.Left + " " + (int)rect.Top + " " + (int)rect.Width + " " + (int)rect.Height);
System.Threading.Thread.Sleep(100);
}
}
}
Console.WriteLine("任意键退出");
Console.ReadKey();
}
private static int ClusterDataset(CommandLineApplication commandLine)
{
// make sure the user entered an argument to this program
if (commandLine.RemainingArguments.Count != 1)
{
Console.WriteLine("The --cluster option requires you to give one XML file on the command line.");
return(ExitFailure);
}
var clusterOption = commandLine.Option("-cluster|--cluster", "", CommandOptionType.SingleValue);
var sizeOption = commandLine.Option("-size|--size", "", CommandOptionType.SingleValue);
var clusterValue = clusterOption.HasValue() ? clusterOption.Value() : "2";
var sizeValue = sizeOption.HasValue() ? sizeOption.Value() : "8000";
if (!uint.TryParse(clusterValue, out var numClusters))
{
return(ExitFailure);
}
if (!uint.TryParse(sizeValue, out var chipSize))
{
return(ExitFailure);
}
var argument = commandLine.RemainingArguments[0];
using (var data = Dlib.ImageDatasetMetadata.LoadImageDatasetMetadata(argument))
{
Environment.CurrentDirectory = Path.GetDirectoryName(argument);
double aspectRatio = MeanAspectRatio(data);
var images = new Array <Array2D <RgbPixel> >();
var feats = new List <Matrix <double> >();
var dataImages = data.Images;
//console_progress_indicator pbar(dataImages.Length);
// extract all the object chips and HOG features.
Console.WriteLine("Loading image data...");
for (var i = 0; i < dataImages.Length; ++i)
{
//pbar.print_status(i);
if (!HasNonIgnoredBoxes(dataImages[i]))
{
continue;
}
using (var img = Dlib.LoadImage <RgbPixel>(dataImages[i].FileName))
{
var boxes = dataImages[i].Boxes;
for (var j = 0; j < boxes.Length; ++j)
{
if (boxes[j].Ignore || boxes[j].Rect.Area < 10)
{
continue;
}
var rect = new DRectangle(boxes[j].Rect);
rect = DRectangle.SetAspectRatio(rect, aspectRatio);
using (var chipDetail = new ChipDetails(rect, chipSize))
{
var chip = Dlib.ExtractImageChip <RgbPixel>(img, chipDetail);
Dlib.ExtractFHogFeatures <RgbPixel>(chip, out var feature);
feats.Add(feature);
images.PushBack(chip);
}
}
}
}
if (!feats.Any())
{
Console.WriteLine("No non-ignored object boxes found in the XML dataset. You can't cluster an empty dataset.");
return(ExitFailure);
}
Console.WriteLine("\nClustering objects...");
var assignments = AngularCluster(feats, numClusters).ToList();
// Now output each cluster to disk as an XML file.
for (uint c = 0; c < numClusters; ++c)
{
// We are going to accumulate all the image metadata for cluster c. We put it
// into idata so we can sort the images such that images with central chips
// come before less central chips. The idea being to get the good chips to
// show up first in the listing, making it easy to manually remove bad ones if
// that is desired.
var idata = new List <Pair <double, Image> >(dataImages.Length);
var idx = 0;
for (var i = 0; i < dataImages.Length; ++i)
{
idata.Add(new Pair <double, Image> {
Second = new Image()
});
idata[i].First = double.PositiveInfinity;
idata[i].Second.FileName = dataImages[i].FileName;
if (!HasNonIgnoredBoxes(dataImages[i]))
{
continue;
}
var idataBoxes = new List <Box>();
var boxes = dataImages[i].Boxes;
for (var j = 0; j < boxes.Length; ++j)
{
idataBoxes.Add(boxes[j]);
if (boxes[j].Ignore || boxes[j].Rect.Area < 10)
{
continue;
}
// If this box goes into cluster c then update the score for the whole
// image based on this boxes' score. Otherwise, mark the box as
// ignored.
if (assignments[idx].C == c)
{
idata[i].First = Math.Min(idata[i].First, assignments[idx].Distance);
}
else
{
idataBoxes.Last().Ignore = true;
}
++idx;
}
idata[i].Second.Boxes = idataBoxes.ToArray();
}
// now save idata to an xml file.
idata.Sort((a, b) =>
{
var diff = a.First - b.First;
return(diff > 0 ? 1 : diff < 0 ? -1 : 0);
});
using (var cdata = new Dataset())
{
cdata.Comment = $"{data.Comment}\n\n This file contains objects which were clustered into group {c + 1} of {numClusters} groups with a chip size of {chipSize} by imglab.";
cdata.Name = data.Name;
var cdataImages = new List <Image>();
for (var i = 0; i < idata.Count; ++i)
{
// if this image has non-ignored boxes in it then include it in the output.
if (!double.IsPositiveInfinity(idata[i].First))
{
cdataImages.Add(idata[i].Second);
}
}
cdata.Images = cdataImages.ToArray();
var outfile = $"cluster_{c + 1:D3}.xml";
Console.WriteLine($"Saving {outfile}");
Dlib.ImageDatasetMetadata.SaveImageDatasetMetadata(cdata, outfile);
}
}
// Now output each cluster to disk as a big tiled jpeg file. Sort everything so, just
// like in the xml file above, the best objects come first in the tiling.
assignments.Sort();
for (uint c = 0; c < numClusters; ++c)
{
var temp = new Array <Array2D <RgbPixel> >();
for (var i = 0; i < assignments.Count(); ++i)
{
if (assignments[i].C == c)
{
temp.PushBack(images[(int)assignments[i].Index]);
}
}
var outfile = $"cluster_{c + 1:D3}.jpg";
Console.WriteLine($"Saving {outfile}");
using (var tile = Dlib.TileImages(temp))
Dlib.SaveJpeg(tile, outfile);
}
}
return(ExitSuccess);
}
public void Create1()
{
var rect = new DRectangle();
this.DisposeAndCheckDisposedState(rect);
}
public void UpdateNoscale()
{
const string testName = "UpdateNoscale";
var path = this.GetDataFile($"{LoadTarget}.bmp");
var tests = new[]
{
new { Type = ImageTypes.BgrPixel, ExpectResult = true },
new { Type = ImageTypes.RgbPixel, ExpectResult = true },
new { Type = ImageTypes.RgbAlphaPixel, ExpectResult = false },
new { Type = ImageTypes.UInt8, ExpectResult = true },
new { Type = ImageTypes.UInt16, ExpectResult = true },
new { Type = ImageTypes.UInt32, ExpectResult = true },
new { Type = ImageTypes.Int8, ExpectResult = true },
new { Type = ImageTypes.Int16, ExpectResult = true },
new { Type = ImageTypes.Int32, ExpectResult = true },
new { Type = ImageTypes.HsiPixel, ExpectResult = true },
new { Type = ImageTypes.Float, ExpectResult = true },
new { Type = ImageTypes.Double, ExpectResult = true }
};
foreach (var input in tests)
{
var expectResult = input.ExpectResult;
var inputType = input.Type;
var imageObj = DlibTest.LoadImage(input.Type, path);
var tracker = new CorrelationTracker();
var rect = new DRectangle(46, 15, 216, 205);
var outputImageAction = new Func <bool, Array2DBase>(expect =>
{
tracker.StartTrack(imageObj, rect);
return(imageObj);
});
var successAction = new Action <Array2DBase>(image =>
{
tracker.UpdateNoscale(image, rect);
});
var failAction = new Action(() =>
{
Assert.Fail($"{testName} should throw exception for InputType: {inputType}.");
});
var finallyAction = new Action(() =>
{
this.DisposeAndCheckDisposedState(tracker);
if (imageObj != null)
{
this.DisposeAndCheckDisposedState(imageObj);
}
});
var exceptionAction = new Action(() =>
{
Console.WriteLine($"Failed to execute {testName} to InputType: {inputType}.");
});
DoTest(outputImageAction, expectResult, successAction, finallyAction, failAction, exceptionAction);
}
}
public void TryTrack()
{
const string testName = "TryTrack";
var tests = new[]
{
new { Type = ImageTypes.UInt8, ExpectResult = true }
};
var type = this.GetType().Name;
foreach (var input in tests)
{
var tracker = new CorrelationTracker();
try
{
var index = 0;
foreach (var file in this.GetDataFiles("video_frames").Where(info => info.Name.EndsWith("jpg")))
{
var expectResult = input.ExpectResult;
var inputType = input.Type;
var imageObj = DlibTest.LoadImage(input.Type, file);
if (index == 0)
{
using (var rect = DRectangle.CenteredRect(93, 110, 38, 86))
tracker.StartTrack(imageObj, rect);
}
var outputImageAction = new Func <bool, Array2DBase>(expect =>
{
if (index != 0)
{
tracker.Update(imageObj);
}
return(imageObj);
});
var successAction = new Action <Array2DBase>(image =>
{
if (index != 0)
{
tracker.Update(image);
}
using (var r = tracker.GetPosition())
{
#if DEBUG
using (var tmp = Image.FromFile(file.FullName))
using (var bmp = new Bitmap(tmp))
using (var g = Graphics.FromImage(bmp))
using (var p = new Pen(Color.Red, 3f))
{
g.DrawRectangle(p, (float)r.Left, (float)r.Top, (float)r.Width, (float)r.Height);
bmp.Save(Path.Combine(this.GetOutDir(type), $"{Path.GetFileNameWithoutExtension(file.FullName)}.jpg"));
}
#endif
}
});
var failAction = new Action(() =>
{
Assert.Fail($"{testName} should throw excption for InputType: {inputType}.");
});
var finallyAction = new Action(() =>
{
index++;
if (imageObj != null)
{
this.DisposeAndCheckDisposedState(imageObj);
}
});
var exceptionAction = new Action(() =>
{
Console.WriteLine($"Failed to execute {testName} to InputType: {inputType}.");
});
DoTest(outputImageAction, expectResult, successAction, finallyAction, failAction, exceptionAction);
}
}
finally
{
this.DisposeAndCheckDisposedState(tracker);
}
}
}
