public void Exec(String input, String output)
{
this.InputFileList = input;
this.OutPutFolda = output;
//学習するファイルを読み込む
ReadFileList();
FaceFeature face_feature = new FaceFeature();
face_feature.FaceList = this.FaceList;
face_feature.IDList = this.IDList;
face_feature.OutPutFolda = this.OutPutFolda;
//特徴点を出す
face_feature.DetectFacePoint();
//学習実行
SVMManage svm_manage = new SVMManage();
svm_manage.TrainingExec(face_feature.FeatuerValueList);
//学習ファイルをxmlに書き出す
String xml_name = @"SvmLearning.xml";
svm_manage.svm.Save(xml_name);
// svm_manage.SVMJudge();
}
public void Exec(String input, String output)
{
this.InputFileList = input;
this.OutPutFolda = output;
//学習するファイルを読み込む
ReadFileList();
FaceFeature face_feature = new FaceFeature();
face_feature.FaceList = this.FaceList;
face_feature.IDList = this.IDList;
face_feature.OutPutFolda = this.OutPutFolda;
//特徴点を出す
face_feature.DetectFacePoint();
//学習実行
SVMManage svm_manage = new SVMManage();
svm_manage.TrainingExec(face_feature.FeatuerValueList);
//学習ファイルをxmlに書き出す
String xml_name = @"SvmLearning.xml";
svm_manage.svm.Save(xml_name);
// svm_manage.SVMJudge();
}
//SVM判定
public int SVMPredict(FaceFeature.FeatureValue feature)
{
//学習ファイルを読み込んでいなかったらロード
if (this.LoadFlag == false)
{
this.libSVM_model_1 = SVM.LoadModel(@"model_Feature_L_EYE_NOSE.xml");
this.libSVM_model_2 = SVM.LoadModel(@"model_Feature_L_EYE_MOUTH.xml");
this.libSVM_model_3 = SVM.LoadModel(@"model_Feature_R_EYE_MOUTH.xml");
this.LoadFlag = true;
}
double[] feature_array = new double[2];
int[] answer = new int[3];
{
SetFeatureToArray(feature, ref feature_array, LEARNING_TYPE.L_EYE_NOSE);
//問題を作成
SVMNode[] node_array = new SVMNode[2];
node_array[0] = new SVMNode(1, feature_array[0]);
node_array[1] = new SVMNode(2, feature_array[1]);
answer[0] = (int)SVM.Predict(libSVM_model_1, node_array);
return answer[0];
}
/*
{
SetFeatureToArray(feature, ref feature_array, LEARNING_TYPE.L_EYE_MOUTH);
//問題を作成
SVMNode[] node_array = new SVMNode[2];
node_array[0] = new SVMNode(1, feature_array[0]);
node_array[1] = new SVMNode(2, feature_array[1]);
answer[1] = (int)SVM.Predict(libSVM_model_2, node_array);
}
{
SetFeatureToArray(feature, ref feature_array, LEARNING_TYPE.R_EYE_MOUTH);
//問題を作成
SVMNode[] node_array = new SVMNode[2];
node_array[0] = new SVMNode(1, feature_array[0]);
node_array[1] = new SVMNode(2, feature_array[1]);
answer[2] = (int)SVM.Predict(libSVM_model_2, node_array);
}
*/
int final = answer[0] + answer[1] + answer[2];
if(final < 5) { final = 1; }
else { final = 2; }
return final;
}
//リストから学習を行う
private void buttonTrainFile_Click(object sender, EventArgs e)
{
//ファイルを選択
OpenFileDialog ofd = new OpenFileDialog();
//はじめのファイル名を指定する
//はじめに「ファイル名」で表示される文字列を指定する
ofd.FileName = "";
//はじめに表示されるフォルダを指定する
//指定しない（空の文字列）の時は、現在のディレクトリが表示される
ofd.InitialDirectory = @"";
//[ファイルの種類]に表示される選択肢を指定する
//指定しないとすべてのファイルが表示される
ofd.Filter =
"学習用ファイルリスト|*.txt";
//[ファイルの種類]ではじめに
//「すべてのファイル」が選択されているようにする
ofd.FilterIndex = 2;
//タイトルを設定する
ofd.Title = "判定する画像ファイルを選択して下さい";
ofd.RestoreDirectory = true;
ofd.CheckFileExists = true;
ofd.CheckPathExists = true;
//ダイアログを表示する
if (ofd.ShowDialog() == DialogResult.OK)
{
}
//出力用のフォルダを設定する
InputFileList = ofd.FileName;
OutPutFolda = @"D:\myprog\github\svm_out"; // 仮設定
//学習するファイルを読み込む
ReadFileList();
FaceFeature face_feature = new FaceFeature();
face_feature.FaceList = this.FaceList;
face_feature.IDList = this.IDList;
face_feature.OutPutFolda = this.OutPutFolda;
//特徴点を出す
face_feature.DetectFacePoint();
//学習実行
SVMManage svm_manage = new SVMManage();
svm_manage.TrainingExec(face_feature.FeatuerValueList);
//エラー表示
MessageBox.Show("lisvm_model.xmlを作成しました",
"完了",
MessageBoxButtons.OK
);
}
/// <summary>
/// 単体の特徴量構造体を配列に直す 要検討
/// </summary>
/// <param name="feature"></param>
/// <param name="value_array"></param>
private void SetFeatureToArray(FaceFeature.FeatureValue feature, ref double[] value_array)
{
int idx = 0;
value_array[idx++] = (feature.LeftEyeValueL);
// value_array[idx++] = (feature.LeftEyeValueR);
// value_array[idx++] = (feature.RightEyeValueL);
// value_array[idx++] = (feature.RightEyeValueR);
value_array[idx++] = (feature.NoseLValueL);
// value_array[idx++] = (feature.NoseLValueR);
// value_array[idx++] = (feature.MouthLValueL);
// value_array[idx++] = (feature.MouthLValueR);
}
//SVM判定
public int SVMPredict(FaceFeature.FeatureValue feature)
{
double[] feature_array = new double[2];
SetFeatureToArray(feature, ref feature_array);
CvMat dataMat = new CvMat(1, 2, MatrixType.F32C1, feature_array, true);
//学習ファイルを読み込んでいなかったらロード
if (this.LoadFlag == false)
{
svm.Load(@"SvmLearning.xml");
this.LoadFlag = true;
}
return (int)this.svm.Predict(dataMat);
}
/// <summary>
/// 単体の特徴量構造体を配列に直す 要検討
/// </summary>
/// <param name="feature"></param>
/// <param name="value_array"></param>
private void SetFeatureToArray(FaceFeature.FeatureValue feature, ref double[] value_array, LEARNING_TYPE type)
{
int idx = 0;
if (type == LEARNING_TYPE.L_EYE_NOSE)
{
value_array[idx++] = (feature.LeftEyeValueL);
// value_array[idx++] = (feature.LeftEyeValueR);
// value_array[idx++] = (feature.RightEyeValueL);
// value_array[idx++] = (feature.RightEyeValueR);
value_array[idx++] = (feature.NoseLValueL);
// value_array[idx++] = (feature.NoseLValueR);
// value_array[idx++] = (feature.MouthLValueL);
// value_array[idx++] = (feature.MouthLValueR);
}
else if (type == LEARNING_TYPE.L_EYE_MOUTH)
{
value_array[idx++] = (feature.LeftEyeValueL);
// value_array[idx++] = (feature.LeftEyeValueR);
// value_array[idx++] = (feature.RightEyeValueL);
// value_array[idx++] = (feature.RightEyeValueR);
//value_array[idx++] = (feature.NoseLValueL);
// value_array[idx++] = (feature.NoseLValueR);
value_array[idx++] = (feature.MouthLValueL);
// value_array[idx++] = (feature.MouthLValueR);
}
else if (type == LEARNING_TYPE.R_EYE_MOUTH)
{
//value_array[idx++] = (feature.LeftEyeValueL);
// value_array[idx++] = (feature.LeftEyeValueR);
value_array[idx++] = (feature.RightEyeValueL);
// value_array[idx++] = (feature.RightEyeValueR);
//value_array[idx++] = (feature.NoseLValueL);
// value_array[idx++] = (feature.NoseLValueR);
value_array[idx++] = (feature.MouthLValueL);
// value_array[idx++] = (feature.MouthLValueR);
}
}
