Mark点改为模板匹配

AOI/mark/AoiMarkMethod.cs

@@ -19,6 +19,10 @@ namespace AOI
         /// 放大RoiPath作为SearchPath
         /// </summary>
         public float SearchPathZoom = 2.0f;
+        /// <summary>
+        /// 相似度百分比
+        /// </summary>
+        public float SamePercent = 50;
 
         /// <summary>
         /// 放大RoiPath作为SearchPath
@@ -69,24 +73,106 @@ namespace AOI
             return resultBean;
         }
 
-        public Image FixImage(Image standardImage, Image imageToCheck)
+        public Mat Fix(Image standardImage, Image imageToCheck)
         {
-            bool needCut = false;
+            bool needCut = true;
             //标准图中的Mart区域
             Image markImage = GetRoiImage(standardImage, RoiPath, needCut);
             //搜索区域
             var SearchPath = GetSearchPath();
             Image searchImage = GetRoiImage(imageToCheck, SearchPath, needCut);
+            //searchImage = imageToCheck;
             if (markImage != null && searchImage != null)
             {
-                var affine = GetAffineMat(markImage, searchImage);
-                if (affine != null)
+                Mat searchMat = ImageUtil.ToMat(new Bitmap(searchImage));
+                Mat markMat = ImageUtil.ToMat(new Bitmap(markImage));
+
+                //Cv2.CvtColor(searchMat, searchMat, ColorConversionCodes.RGB2GRAY);
+                //Cv2.CvtColor(markMat, markMat, ColorConversionCodes.RGB2GRAY);
+
+                Mat result = new Mat(searchMat.Cols - markMat.Cols + 1, searchMat.Rows - markMat.Cols + 1, MatType.CV_32FC1);
+                
+                //进行匹配(1母图,2模版子图,3返回的result，4匹配模式_这里的算法比opencv少，具体可以看opencv的相关资料说明)
+                Cv2.MatchTemplate(searchMat, markMat, result, TemplateMatchModes.CCoeffNormed);
+
+                //对结果进行归一化(这里我测试的时候没有发现有什么用,但在opencv的书里有这个操作，应该有什么神秘加成，这里也加上)
+                //Cv2.Normalize(result, result, 1, 0, NormTypes.MinMax, -1);
+                /// 通过函数 minMaxLoc 定位最匹配的位置
+                /// (这个方法在opencv里有5个参数，这里我写的时候发现在有3个重载，看了下可以直接写成拿到起始坐标就不取最大值和最小值了)
+                /// minLocation和maxLocation根据匹配调用的模式取不同的点
+                Cv2.MinMaxLoc(result, out double minVal, out double maxVal, out OpenCvSharp.Point minLocation, out OpenCvSharp.Point maxLocation);
+                //画出匹配的矩，
+                //  Cv2.Rectangle(mat1, maxLocation, new Point (maxLocation.X+mat2.Cols, maxLocation.Y+mat2.Rows), Scalar.Red, 2);
+                Cv2.Rectangle(searchMat, maxLocation, new OpenCvSharp.Point(maxLocation.X + markMat.Cols, maxLocation.Y + markMat.Rows), Scalar.Red, 2);
+
+                Cv2.ImShow("mat1", searchMat);
+
+                //Console.WriteLine(minValue);
+                //Console.WriteLine(maxValue);
+                Console.WriteLine(minLocation + "=" + minVal);
+                Console.WriteLine(maxLocation + "=" + maxVal);
+
+                if (maxVal * 100 > 20)
                 {
-                    var matToCheck = ImageUtil.ToMat(imageToCheck);
-                    var fixedMat = FixImage(affine, matToCheck);
-                    return ImageUtil.ToImage(fixedMat);
+                    //大于相似度，开始平移图像
+                    var searchBounds = SearchPath.GetBounds();
+                    var srcPoints = new Point2f[] {
+                        new Point2f(searchBounds.X + maxLocation.X, searchBounds.Y + maxLocation.Y),
+                        new Point2f(searchBounds.X + maxLocation.X+markMat.Cols, searchBounds.Y + maxLocation.Y),
+                        new Point2f(searchBounds.X + maxLocation.X, searchBounds.Y + maxLocation.Y + markMat.Rows),
+                        new Point2f(searchBounds.X + maxLocation.X+markMat.Cols, searchBounds.Y + maxLocation.Y + markMat.Rows),
+                    };
+                    //变换后的四点
+                    var markBounds = RoiPath.GetBounds();
+                    var dstPoints = new Point2f[] {
+
+                        new Point2f(markBounds.X , markBounds.Y),
+                        new Point2f(markBounds.X + markMat.Cols , markBounds.Y),
+                        new Point2f(markBounds.X , markBounds.Y + markMat.Rows),
+                        new Point2f(markBounds.X + markMat.Cols , markBounds.Y + markMat.Rows),
+                    };
+                    //根据变换前后四个点坐标,获取变换矩阵
+                    Mat mm = Cv2.GetAffineTransform(srcPoints, dstPoints);
+                    return mm;
+
                 }
             }
+
+            return null;
+            
+        }
+
+        public Image FixImage(Image standardImage, Image imageToCheck)
+        {
+            //Fix(standardImage, imageToCheck);
+            var affine = Fix(standardImage, imageToCheck);
+            if (affine != null)
+            {
+                var matToCheck = ImageUtil.ToMat(imageToCheck);
+                Mat fixedMat = new Mat();
+                Cv2.WarpAffine(matToCheck, fixedMat, affine,new OpenCvSharp.Size(standardImage.Width, standardImage.Height));
+                //var fixedMat = FixImage(affine, matToCheck);
+                Image markImage = GetRoiImage(ImageUtil.ToImage(fixedMat), RoiPath, true);
+                //Cv2.ImShow("Fixed", ImageUtil.ToMat(markImage));
+                //return ImageUtil.ToImage(fixedMat);
+                return markImage;
+            }
+            //bool needCut = false;
+            ////标准图中的Mart区域
+            //Image markImage = GetRoiImage(standardImage, RoiPath, needCut);
+            ////搜索区域
+            //var SearchPath = GetSearchPath();
+            //Image searchImage = GetRoiImage(imageToCheck, SearchPath, needCut);
+            //if (markImage != null && searchImage != null)
+            //{
+            //    var affine = GetAffineMat(markImage, searchImage);
+            //    if (affine != null)
+            //    {
+            //        var matToCheck = ImageUtil.ToMat(imageToCheck);
+            //        var fixedMat = FixImage(affine, matToCheck);
+            //        return ImageUtil.ToImage(fixedMat);
+            //    }
+            //}
             return null;
         }