//画像ファイルロード
private bool LoadImageFile(String file_name)
{
//カスケード分類器の特徴量を取得する
CvHaarClassifierCascade cascade = CvHaarClassifierCascade.FromFile(@"C:\opencv2.4.10\sources\data\haarcascades\haarcascade_frontalface_alt.xml");
CvMemStorage strage = new CvMemStorage(0); // メモリを確保
this.ImageFileName = file_name;
using (IplImage img = new IplImage(this.ImageFileName))
{
//グレースケールに変換
using( IplImage gray_image = Cv.CreateImage(new CvSize(img.Width,img.Height),BitDepth.U8,1) )
{
Cv.CvtColor(img, gray_image, ColorConversion.BgrToGray);
//発見した矩形
var result = Cv.HaarDetectObjects(gray_image, cascade, strage);
for (int i = 0; i < result.Total; i++)
{
//矩形の大きさに書き出す
CvRect rect = result[i].Value.Rect;
Cv.Rectangle(img, rect, new CvColor(255, 0, 0));
//iplimageをコピー
img.ROI = rect;
CvRect roi_rect = img.ROI;
IplImage ipl_image = Cv.CreateImage(new CvSize(img.Width, img.Height), BitDepth.U8, 1);
ipl_image = img.Clone(img.ROI);
/*
//確認
new CvWindow(ipl_image);
Cv.WaitKey();
*/
//見つけた顔候補をすべてチェックするために記録する
this.FaceIplList.Add(ipl_image);
}
}
//メモリ解放
cascade.Dispose();
strage.Dispose();
return true;
}
}
public Bitmap Detect2()
{
IplImage image = videoCapture.QueryFrame();
IplImage ret = getHandPicturesGMG(image);
CvMemStorage storage = new CvMemStorage();
CvSeq<CvAvgComp> hands = Cv.HaarDetectObjects(ret, cascade, storage, 1.139);
foreach (CvAvgComp obj in hands)
{
ret.Rectangle(obj.Rect, CvColor.Red);
}
Bitmap bt = ret.ToBitmap();
ret.Dispose();
image.Dispose();
storage.Dispose();
hands.Dispose();
return bt;
}
/// <summary>
/// ファイル名から特徴量を出す処理
/// </summary>
/// <param name="file_name"></param>
public void MakeFeatureFromIpl(IplImage ipl_image, int face_id)
{
string eye_cascade_xml = @"C:\opencv2.4.10\sources\data\haarcascades\haarcascade_eye.xml";
string nose_cascade_xml = @"C:\opencv2.4.10\sources\data\haarcascades\haarcascade_mcs_nose.xml";
string mouth_cascade_xml = @"C:\opencv2.4.10\sources\data\haarcascades\haarcascade_mcs_mouth.xml";
CvMemStorage strage = new CvMemStorage(0); // メモリを確保
CvHaarClassifierCascade eye_cascade = CvHaarClassifierCascade.FromFile(eye_cascade_xml);
CvHaarClassifierCascade nose_cascade = CvHaarClassifierCascade.FromFile(nose_cascade_xml);
CvHaarClassifierCascade mouth_cascade = CvHaarClassifierCascade.FromFile(mouth_cascade_xml);
//リストにあるファイルを一枚づつデータにする
{
IplImage tmp_image;
//サイズが小さければ拡大して使う
if (ipl_image.Size.Width < SMALL_IMAGE_LIMIT)
{
tmp_image = Cv.CreateImage(new CvSize(ipl_image.Width * IMAGE_RESIZE_RATE, ipl_image.Height * IMAGE_RESIZE_RATE), BitDepth.U8, 3);
Cv.Resize(ipl_image, tmp_image);
}
else
{
tmp_image = Cv.CreateImage(new CvSize(ipl_image.Width, ipl_image.Height), BitDepth.U8, 3);
Cv.Resize(ipl_image, tmp_image);
}
//グレースケールに変換
IplImage gray_image = Cv.CreateImage(new CvSize(tmp_image.Width, tmp_image.Height), BitDepth.U8, 1);
Cv.CvtColor(tmp_image, gray_image, ColorConversion.BgrToGray);
//発見した矩形
this.EyeResult = Cv.HaarDetectObjects(gray_image, eye_cascade, strage);
//鼻は画像の真ん中の方だけ
{
IplImage gray_nose_image = Cv.CreateImage(new CvSize(tmp_image.Width, tmp_image.Height), BitDepth.U8, 1);
Cv.CvtColor(tmp_image, gray_nose_image, ColorConversion.BgrToGray);
CvRect rect = new CvRect(0, (int)(tmp_image.Height*0.25), tmp_image.Width, tmp_image.Height / 2);
gray_nose_image.ROI = rect;
// new CvWindow(gray_nose_image);
// Cv.WaitKey();
this.NoseResult = Cv.HaarDetectObjects(gray_nose_image, nose_cascade, strage);
}
//口は画像の下半分だけを調べる
{
IplImage gray_mouth_image = Cv.CreateImage(new CvSize(tmp_image.Width, tmp_image.Height), BitDepth.U8, 1);
Cv.CvtColor(tmp_image, gray_mouth_image, ColorConversion.BgrToGray);
CvRect rect = new CvRect(0, (int)(tmp_image.Height *0.66), tmp_image.Width, tmp_image.Height / 3);
gray_mouth_image.ROI = rect;
// new CvWindow(gray_mouth_image);
// Cv.WaitKey();
this.MouthResult = Cv.HaarDetectObjects(gray_mouth_image, mouth_cascade, strage);
}
//初期化
DataInit();
//デバッグ用の表示
// DebugPrint(tmp_image, this.ReadCount);
//左眼、右目、鼻、口の矩形を確定させる。
DecidePartsRect(gray_image);
//パーツ確定後
// DebugPrint2(gray_image, this.ReadCount);
PartsRectInfo parts_info;
parts_info.RightEye = this.RightEyeRect;
parts_info.LeftEye = this.LeftEyeRect;
parts_info.Nose = this.NoseRect;
parts_info.Mouth = this.MouthRect;
//特徴量を作る
FeatureValue feature_value = new FeatureValue();
bool ret = MakeFeatureValue(gray_image, ref parts_info, out feature_value);
//正しいデータを登録
if (ret)
{
feature_value.ID = face_id;
this.FeatuerValueList.Add(feature_value);
}
}
//メモリ解放
eye_cascade.Dispose();
nose_cascade.Dispose();
mouth_cascade.Dispose();
strage.Dispose();
return;
}
private void timer1_Tick(object sender, EventArgs e)
{
// キャプチャの開始. Capture starts.
IplImage ipl1 = capture.QueryFrame();
int l = 0;
int r = 0;
int m = 0;
// 取得したカメラ画像の高さと幅を取得し、labelに表示. Height and width of camera are shown in label.
//labelWidth.Text = capture.FrameWidth.ToString();
//labelHeight.Text = capture.FrameHeight.ToString();
if (ipl1 != null)
{
fig = true;
// pictureBoxに取得した画像を表示. Show the captured image.
pictureBox1.Image = ipl1.ToBitmap();
// メモリリークが発生するらしいので
// プログラムが動的に確保したメモリ領域のうち、
// 不要になった領域を定期的に自動解放する
if (GC.GetTotalMemory(false) > 600000)
{
GC.Collect();
}
// Image processing should be written from here.
// Extract edge of circle
CvMemStorage storage = new CvMemStorage();
IplImage gray = new IplImage(ipl1.Size, BitDepth.U8, 1);
IplImage binary = new IplImage(ipl1.Size, BitDepth.U8, 1);
//transform grayscale image from caputure image
Cv.CvtColor(ipl1, gray, ColorConversion.BgrToGray);
//グレイスケールの平滑化 誤検出を減らすため. Decrease the error recognition by Smoothing of the gray scale.
//Cv.Smooth(gray, gray, SmoothType.Gaussian, 9, 9, 1, 1);
//二値化した画像から円検出を行う(ハフ関数を使う). Using Hough function from grayscale.
CvSeq<CvCircleSegment> circl = Cv.HoughCircles(gray, storage, HoughCirclesMethod.Gradient, 2,200, 100, 100, 20, 200);
//HougCircles(input picture, memory space,Binarization method,inverse of graphic mode,shortest distance from other circle,)
foreach (CvCircleSegment crcl in circl)
{
ipl1.Circle(crcl.Center, (int)crcl.Radius, CvColor.Blue, 3);
labelCenter.Text = crcl.Center.ToString();
//labelCenter.Text = crcl.Center.ToString();
//double Area;
Area = crcl.Radius;// * crcl.Radius*3.14;
labelRadius.Text = Area.ToString();
x_pos = crcl.Center.X;
//labelArea.Text = Area.ToString();
}
//circl.Dispose();
storage.Dispose();
pictureBox1.Invalidate();
// Show the binaryimage to picturebox3.
Cv.Canny(gray,binary , 100, 100);
pictureBox3.Image = binary.ToBitmap();
//Show the capture image to picturebox2
pictureBox2.Image = ipl1.ToBitmap();
//
if (Area < 45)
{
textBox1.Text = br.Forward();
}
else if (Area > 80)
{
textBox1.Text = br.Back();
}
else
{
if (x_pos < 100 && Area > 0)
{
textBox1.Text = br.TurnLeft();
}
else if (x_pos > 220 && Area > 0)
{
textBox1.Text = br.TurnRight();
}
else
{
textBox1.Text = br.Stop();
}
}
}
else
{
timer1.Stop();
}
}