c# 联合 halcon集成了所有分类器

【实例简介】

        本例子集成了“MLP”,"SVM","KNN","GMM",分类器算法，可以作为进行物体分类，缺陷检测的参考案例。

【实例截图】

【核心代码】

    // Initialize local and output iconic variables 
            HOperatorSet.GenEmptyObj(out ho_Image);
            HOperatorSet.GenEmptyObj(out ho_SelectedRegions);
            HOperatorSet.GenEmptyObj(out ho_ObjectSelected);
            HOperatorSet.GenEmptyObj(out ho_Cross);
            try
            {
                //This example program shows how to apply a general GMM
                //classification to distinguish citrus fruits using the
                //features 'area' and 'circularity'. Additionally, the
                //2D feature space for the extracted fruits is visualized.

                hv_FeaturesArea = new HTuple();
                hv_FeaturesCircularity = new HTuple();
                hv_ClassName = new HTuple();
                hv_ClassName[0] = "橘子";
                hv_ClassName[1] = "柠檬";
                //
                //Create a GMM classifier
                HOperatorSet.CreateClassGmm(2, 2, 1, "spherical", "normalization", 10, 42, out hv_GMMHandle);
                //
                //Add training samples
                for (hv_i = 1; (int)hv_i <= inspectImgCount; hv_i = (int)hv_i 1)
                {
                    ho_Image.Dispose();
                    HOperatorSet.ReadImage(out ho_Image, files[hv_i - 1]);
                    HOperatorSet.GetImagePointer1(ho_Image, out hv_Pointer, out hv_Type, out hv_Width, out hv_Height);
                    HOperatorSet.SetDraw(hWindowControl1.HalconWindow, "margin");
                    HOperatorSet.SetLineWidth(hWindowControl1.HalconWindow, 2);
                    HOperatorSet.SetPart(hWindowControl1.HalconWindow, 0, 0, hv_Height - 1, hv_Width - 1);
                    HOperatorSet.DispObj(ho_Image, hWindowControl1.HalconWindow);

                    //'Add Samples'
                    ho_SelectedRegions.Dispose();
                    Get_regions(ho_Image, out ho_SelectedRegions);

                    HOperatorSet.DispObj(ho_SelectedRegions, hWindowControl1.HalconWindow);
                    HOperatorSet.CountObj(ho_SelectedRegions, out hv_NumberObjects);
                    HTuple end_val32 = hv_NumberObjects;
                    HTuple step_val32 = 1;
                    for (hv_j = 1; hv_j.Continue(end_val32, step_val32); hv_j = hv_j.TupleAdd(step_val32))
                    {
                        ho_ObjectSelected.Dispose();
                        HOperatorSet.SelectObj(ho_SelectedRegions, out ho_ObjectSelected, hv_j);
                        get_features(ho_ObjectSelected, out hv_Circularity, out hv_Area,
                            out hv_RowRegionCenter, out hv_ColumnRegionCenter);
                        hv_FeaturesArea = hv_FeaturesArea.TupleConcat(hv_Area);
                        hv_FeaturesCircularity = hv_FeaturesCircularity.TupleConcat(hv_Circularity);
                        hv_FeatureVector = ((hv_Circularity.TupleConcat(hv_Area))).TupleReal();
                        if ((int)(new HTuple(hv_i.TupleLessEqual(2))) != 0)
                        {
                            HOperatorSet.AddSampleClassGmm(hv_GMMHandle, hv_FeatureVector, 0, 0);
                            disp_message(hWindowControl1.HalconWindow, "Add to Class:" (hv_ClassName.TupleSelect(
                                0)), "window", hv_RowRegionCenter, hv_ColumnRegionCenter - 100, "black",
                                "true");
                        }
                        else
                        {
                            HOperatorSet.AddSampleClassGmm(hv_GMMHandle, hv_FeatureVector, 1, 0);
                            disp_message(hWindowControl1.HalconWindow, "Add to Class:" (hv_ClassName.TupleSelect(
                                1)), "window", hv_RowRegionCenter, hv_ColumnRegionCenter - 100, "black",
                                "true");
                        }
                    }

                    // stop(); only in hdevelop
                }