set OUTPUT_DIRECTORY="$(TargetDir)model"
if not exist %OUTPUT_DIRECTORY% mkdir %OUTPUT_DIRECTORY%
copy "$(SolutionDir)bin" "$(TargetDir)"
copy "$(SolutionDir)model" "$(TargetDir)model"
copy "$(SolutionDir)config" "$(TargetDir)"

private void Form1_Load(object sender, EventArgs e)
{
   //経過時間計測用のカウンタ周期情報取得
   QueryPerformanceFrequency(ref timefrequencyCounter);

   //Log用ListBox準備
   var log_header = new ColumnHeader();
   log_header.Width = 700;
   log_header.Text = "Log";
   //LogBox.Columns.Add(log_header);

   //Result用ListBox準備
   var result_header = new ColumnHeader();
   result_header.Width = 700;
   result_header.Text = "Result";

   flag_closing = false;

   try
   {
       //AISVision初期化
       string dirpath = AppDomain.CurrentDomain.BaseDirectory + "model";
       string[] extensions = { ".ditox", ".ditir" };

       filepaths = Directory.EnumerateFiles(dirpath, "*.*", SearchOption.AllDirectories)
                   .Where(file => extensions.Contains(Path.GetExtension(file)))
                   .ToList();
       var filenames = filepaths.Select(Path.GetFileName).ToList();
       if (filenames.Count == 0)
       {
           MessageBox.Show("No AImodel On PC", "Error", MessageBoxButtons.OK, MessageBoxIcon.Error);
           this.Close();
           return;
       }

       foreach (var name in filenames)
       {
           comboBox_modelpath.Items.Add(name);
       }

       if (comboBox_modelpath.Items.Count != 0)
       {
           comboBox_modelpath.SelectedIndex = 0;
           comboBox_modelpath.Enabled = true;
           button_modelload.Enabled = true;
       }

       //AIモデル読み込み
       readAIModel();

       //IC Imaging Control3.5でカメラオープン
       if (!icImagingControl1.DeviceValid)
       {
           icImagingControl1.LoadShowSaveDeviceState("lastDevice.xml");
       }
       else
       {
           MessageBox.Show("デバイスが見つかりませんでした。", "Error", MessageBoxButtons.OK, MessageBoxIcon.Error);
           this.Close();
           return;
       }

       icImagingControl1.LiveDisplayDefault = false;
       icImagingControl1.LiveCaptureLastImage = false;
       icImagingControl1.LiveDisplay = false; //ライブ画像を表示しない
       icImagingControl1.Sink = new FrameQueueSink(mDataStream_NewBufferEvent, TIS.Imaging.MediaSubtypes.RGB32, 5);

       if(icImagingControl1.DeviceValid) icImagingControl1.LiveStart();
       icImagingControl1.LiveDisplayZoomFactor = (float)0.98f;



       this.WindowState = FormWindowState.Maximized;


       // PictureBox のサイズを更新
       pictureBox_result.Size = new System.Drawing.Size(
           (int)(icImagingControl1.Width * (float)1.5f),
           (int)(icImagingControl1.Height * (float)1.5f)
       );

   }
   catch (ICException ex)
   {
       addlog("ErrorType:" + ex.GetType().ToString());
       addlog("ErrorException:" + ex.GetBaseException().ToString());
       addlog("Error:Form1_Load");
   }
}

private void readAIModel() 
{

    //読み込み済みなら一度閉じる
    if (predict.CheckSession())
    {
        predict.Dispose();
        predict = new Predictor();
    }

    var path = filepaths.ElementAt(comboBox_modelpath.SelectedIndex);
    if (Path.GetFileName(path).Contains("ditox") == true)
    {
        //AIモデルファイル読み込み
        predict.LoadModel(path, true, 0);
        //読み込み成否チェック
        if (predict.CheckSession())
        {
            //モデル情報取得
            predict.GetModelInfo(out modelInfo);
            label_modelinfo.Text = modelInfo.ModelType.ToString();
            addlog("");
            addlog("AISVision Predicter Opened");
            addlog("Model Type: " + modelInfo.ModelType.ToString());
            addlog("Model Status: " + modelInfo.ModelStatus.ToString());
            addlog("Project Name: " + modelInfo.ProjectName.ToString());
            addlog("Task Name: " + modelInfo.TaskName.ToString());

            comboBox_classthreshold.Items.Clear();
            classlist.Clear();
            if (modelInfo.ModelType == Predictor.ModelType.Classification || modelInfo.ModelType == Predictor.ModelType.ObjectDetection || modelInfo.ModelType == Predictor.ModelType.OrientedObjectDetection)
            {
                numericUpDown_classthresholdvalue.Enabled = true;
                comboBox_classthreshold.Enabled = true;
                //カテゴリ情報取得
                Predictor.AisvCategoryInfo cat_temp = new Predictor.AisvCategoryInfo();
                predict.GetCategoryInfo(out cat_temp);
                for (int i = 0; i < cat_temp.Size; ++i)
                {
                    classlist.Add(cat_temp.CategoryList[i].Name, cat_temp.CategoryList[i].Threshold);
                    categorylist.Add(i, cat_temp.CategoryList[i].Name);
                    categoryfontlist.Add(i, cat_temp.CategoryList[i].Color);
                    comboBox_classthreshold.Items.Add(cat_temp.CategoryList[i].Name);
                }
                comboBox_classthreshold.SelectedIndex = 0;
                numericUpDown_classthresholdvalue.Value = (decimal)classlist[cat_temp.CategoryList[0].Name];
                target = comboBox_classthreshold.Text;
            }
            else
            {
                numericUpDown_classthresholdvalue.Enabled = false;
                comboBox_classthreshold.Enabled = false;
            }
        }
        else
        {
            predict.Dispose();
            addlog("Error: Faild AISVision Predicter Loading");
        }
    }
    else
    {
        addlog("Please select *.ditox file");
    }

}

private FrameQueuedResult mDataStream_NewBufferEvent(IFrameQueueBuffer buffer)
{

    // フレームが閉じている場合は再キューイングを行う
    if (flag_closing) return FrameQueuedResult.ReQueue;

    if (buffer == null)
    {
        // データが格納されていない場合のエラーログ
        addlog("Error: Buffer Timeout ");
    }
    else
    {
        // 非同期タスクで画像処理を実行
        Task.Run(() =>
        {
            IFrameQueueBuffer controlbuffer = buffer;
            icImagingControl1.DisplayImageBuffer(buffer);
            resultsimage = Enumerable.Repeat<Bitmap>(new Bitmap(cam_width, cam_height, PixelFormat.Format8bppIndexed), num_resultview).ToArray();

            // バッファからBitmapを作成し、Matに変換
            Mat matImage = OpenCvSharp.Extensions.BitmapConverter.ToMat(buffer.CreateBitmapWrap());
            if (matImage != null)
            {
                // 青チャンネル（Bチャンネル）のみを抽出
                Mat blueChannel = new Mat();
                Cv2.ExtractChannel(matImage, blueChannel, 0); // Bチャンネルはインデックス0

                // 全体の明るさを補正する（ガンマ補正で暗い青を明るくする）
                Mat adjustedBlueChannel = new Mat();
                blueChannel.ConvertTo(adjustedBlueChannel, MatType.CV_8U, alpha: 1.5, beta: 20);
                // alpha: コントラスト調整係数、beta: 明るさ補正値

                // 画像の中心座標を計算
                int centerX = adjustedBlueChannel.Cols / 2; // 画像幅の中心
                int centerY = adjustedBlueChannel.Rows / 2; // 画像高さの中心

                // 真ん中の5x5領域を抽出
                int rectSize = 5; // 矩形サイズ
                int startX = Math.Max(0, centerX - rectSize / 2); // X方向の開始座標
                int startY = Math.Max(0, centerY - rectSize / 2); // Y方向の開始座標
                int width = Math.Min(rectSize, adjustedBlueChannel.Cols - startX); // 幅
                int height = Math.Min(rectSize, adjustedBlueChannel.Rows - startY); // 高さ

                // 抽出領域（Region of Interest）を設定
                Rect roi = new Rect(startX, startY, width, height);
                Mat roiMat = new Mat(adjustedBlueChannel, roi); // 抽出領域を切り出す

                // 5x5領域の輝度平均を計算
                Scalar meanBrightness = Cv2.Mean(roiMat);

                // 輝度平均をログに出力
                addlog("5x5領域の輝度平均: " + meanBrightness.Val0.ToString());
                double meanValue = meanBrightness.Val0;

                // 輝度平均が75を超える場合、バッファをコピー
                if (meanValue > 75)
                {
      //AI画像処理処理へ
                    copybuf(controlbuffer);
                }
            }
        });
    }
    return FrameQueuedResult.ReQueue;

}

private void copybuf(IFrameQueueBuffer buffer)
{

   if (flag_closing) return;
   if (imagelock) return;
   if (rwLock.TryEnterWriteLock(1))
   {
       try
       {

           currentimage = buffer.CreateBitmapWrap();
           imagelock = true;

            //AISVision推論用バッファ作成
            aisimage_source = predict.ConvertBitmapToImage(buffer.CreateBitmapWrap());

           //AISVision推論
           predictbuf();
       }
       finally
       {
           if (rwLock.IsWriteLockHeld)
           {
               rwLock.ExitWriteLock();
           }
       }

       //メインスレッドでUI更新
       this.BeginInvoke(new Action(() =>
       {
               pictureBox_result.Invalidate();
               flag_paintmain = false;
       }));

   }

}

private void predictbuf()
{
    // フォームが閉じられている場合は処理を終了
    if (flag_closing) return;

    // 書き込みロックを取得
    if (predictLock.TryEnterWriteLock(1))
    {
        ulong checkstart = 0;
        ulong checkend = 0;

        try
        {
            // 処理時間計測：開始ポイント
            QueryPerformanceCounter(ref checkstart);

            // 推論実行
            predictInfo = predict.Predict(aisimage_source);

            // 処理時間計測：終了ポイント
            QueryPerformanceCounter(ref checkend);

            // 結果画像生成
            aisimage_result = predict.VisualizeResult(aisimage_source, predictInfo, true);
            predictimage = predict.ConvertImageToBitmap(aisimage_result);
        }
        catch (OperationCanceledException)
        {
            // タスクがキャンセルされた場合の処理
            return;
        }
        finally
        {
            // 書き込みロックを解放
            if (predictLock.IsWriteLockHeld)
            {
                predictLock.ExitWriteLock();
            }
        }

        // 処理時間計算
        var processingtime = ((checkend - checkstart) * 1000 / timefrequencyCounter);

        // メインスレッドでUI更新
        this.BeginInvoke(new Action(() =>
        {
            label_predicttime.Text = "Predict processing time: " + (processingtime).ToString() + " ms";
        }));

        // 推論結果表示
        if (resultLock.TryEnterWriteLock(1))
        {
            try
            {
                // モデルタイプに応じた結果処理
                //モデルタイプ：アノマリー
                if (modelInfo.ModelType == Predictor.ModelType.AnomalyDetection)
                {
                    addresult("[Anomaly] Result:" + predictInfo.anomalydetectionInfo.Name + " [" + Math.Round(predictInfo.anomalydetectionInfo.Score, 2, MidpointRounding.AwayFromZero).ToString() + "%]");
                    if (predictInfo.anomalydetectionInfo.Name == target)
                    {
                        if (!flag_detect)
                        {
                            for (int i = 0; i < resultsimage.Length; ++i)
                            {
                                if (i != num_resultview - 1)
                                {
                                    resultsimage[i] = resultsimage[i + 1];
                                }
                                else
                                {
                                    resultsimage[i] = predictimage;
                                }
                            }
                            flag_detect = true;
                        }
                    }
                    else
                    {
                        flag_detect = false;
                    }
                }
                //モデルタイプ：クラス分類
                else if (modelInfo.ModelType == Predictor.ModelType.Classification)
                {
                    addresult("[Classification] Result:" + predictInfo.classificationInfo.Name + " [" + Math.Round(predictInfo.classificationInfo.Prob, 2, MidpointRounding.AwayFromZero).ToString() + "%]");

                    this.BeginInvoke(new Action(() =>
                    {
                        if (predictimage != null)
                        {
                            pictureBox_result.Image = (System.Drawing.Image)predictimage.Clone();
                        }
                    }));

                    string_Judgement = predictInfo.classificationInfo.Name + " [" + Math.Round(predictInfo.classificationInfo.Prob, 2, MidpointRounding.AwayFromZero).ToString() + "%]";

                    if (check_saveimage.Checked && imagelock) SaveImageBasedOnJudgement((Bitmap)currentimage.Clone(), predictInfo.classificationInfo.Name, Math.Round(predictInfo.classificationInfo.Prob, 2, MidpointRounding.AwayFromZero).ToString());
                    imagelock = false;

                    if (predictInfo.classificationInfo.Name == target)
                    {
                        if (!flag_detect)
                        {
                            flag_detect = true;
                        }
                    }
                    else
                    {
                        flag_detect = false;
                    }
                }
                //モデルタイプ：物体検出
                else if (modelInfo.ModelType == Predictor.ModelType.ObjectDetection)
                {
                    addresult("[ObjectDetection] Detected items:" + predictInfo.objectdetectionInfo.Size.ToString());
                    foreach (var items in predictInfo.objectdetectionInfo.ResultList)
                    {
                        addresult("[" + items.Name + "] [Prob=" + Math.Round(items.Prob, 2, MidpointRounding.AwayFromZero).ToString() + "] [X=" + Math.Round(items.TopLeftX) + ",Y=" + Math.Round(items.TopLeftY) + "] [Width=" + Math.Round(items.Width) + ",Height=" + Math.Round(items.Height) + "]");
                    }
                    if (predictInfo.objectdetectionInfo.ResultList.Any(res => res.Name == target))
                    {
                        if (!flag_detect)
                        {
                            for (int i = 0; i < resultsimage.Length; ++i)
                            {
                                if (i != num_resultview - 1)
                                {
                                    resultsimage[i] = resultsimage[i + 1];
                                }
                                else
                                {
                                    resultsimage[i] = predictimage;
                                }
                            }
                            flag_detect = true;
                        }
                    }
                    else
                    {
                        flag_detect = false;
                    }
                }
                //物体検出（回転あり）
                else if (modelInfo.ModelType == Predictor.ModelType.OrientedObjectDetection)
                {
                    addresult("[OrientedObjectDetection] Detected items:" + predictInfo.orientedobjectdetectionInfo.Size.ToString());
                    foreach (var items in predictInfo.orientedobjectdetectionInfo.ResultList)
                    {
                        addresult("[" + items.Name + "] [Prob=" + Math.Round(items.Prob, 2, MidpointRounding.AwayFromZero).ToString() + "] [CenterX=" + Math.Round(items.CenterX) + ",CenterY=" + Math.Round(items.CenterY) + "] [Width=" + Math.Round(items.Width) + ",Height=" + Math.Round(items.Height) + "] [Angle=" + items.Angle + "]");
                    }
                    if (predictInfo.orientedobjectdetectionInfo.ResultList.Any(res => res.Name == target))
                    {
                        if (!flag_detect)
                        {
                            for (int i = 0; i < resultsimage.Length; ++i)
                            {
                                if (i != num_resultview - 1)
                                {
                                    resultsimage[i] = resultsimage[i + 1];
                                }
                                else
                                {
                                    resultsimage[i] = predictimage;
                                }
                            }
                            flag_detect = true;
                        }
                    }
                    else
                    {
                        flag_detect = false;
                    }
                }
                //モデルタイプ：セグメンテーション
                else if (modelInfo.ModelType == Predictor.ModelType.Segmentation)
                {
                    addresult("[Segmentation] Detected items:" + predictInfo.segmentationInfo.CategorySize.ToString());
                    foreach (var items in predictInfo.segmentationInfo.CategoryList)
                    {
                        addresult("[" + items.Name + "] [Threshold=" + items.Threshold + "]");
                    }
                    if (predictInfo.segmentationInfo.CategoryList.Any(res => res.Name == target))
                    {
                        if (!flag_detect)
                        {
                            for (int i = 0; i < resultsimage.Length; ++i)
                            {
                                if (i != num_resultview - 1)
                                {
                                    resultsimage[i] = resultsimage[i + 1];
                                }
                                else
                                {
                                    resultsimage[i] = predictimage;
                                }
                            }
                            flag_detect = true;
                        }
                    }
                    else
                    {
                        flag_detect = false;
                    }
                }
            }
            finally
            {
                // 書き込みロックを解放
                if (resultLock.IsWriteLockHeld)
                {
                    resultLock.ExitWriteLock();
                }
            }
        }
    }
}

private void SaveImageBasedOnJudgement(Bitmap saveImage, string judgement, string probability)
{
    // 保存先のベースディレクトリを指定
    string baseDirectory = @"D:\ImageResults"; // 必要に応じて変更
    string subDirectory;

    // Judgementに応じてフォルダを決定
    switch (judgement.ToLower())
    {
        case "ok":
            subDirectory = "OK";
            break;
        case "ng":
            subDirectory = "NG";
            break;

        default:
            subDirectory = "unknown";
            break;
    }

    // フォルダパスを組み立てる
    string targetDirectory = Path.Combine(baseDirectory, subDirectory);

    // フォルダが存在しない場合は作成
    if (!Directory.Exists(targetDirectory))
    {
        Directory.CreateDirectory(targetDirectory);
    }
    counter_save++;
    // ファイル名をユニークにするためにタイムスタンプを使用
    string fileName = $"Image_{subDirectory}_{probability}_{counter_save}_{DateTime.Now:yyyyMMdd_HHmmssfff}.bmp";
    string filePath = Path.Combine(targetDirectory, fileName);

    // Bitmap を指定したパスに保存
    saveImage.Save(filePath, System.Drawing.Imaging.ImageFormat.Bmp);

    addlog($"Image saved to: {filePath}");
}