微信二维码检测的C# 实现——opencvsharp Dnn Caffe推理部署

早些时候微信二维码开源在opencv， 找码快解码强，最近我研究DataMartix解码库libdmtx的时候，发现它解码还行，找码有点慢，心想何不让深度学习助它一臂之力？于有了这个；

 internal class SSDDetector
    {
        private static float CLIP(float x, float x1, float x2) => Math.Max(x1, Math.Min(x, x2));

        public SSDDetector(string proto_path, string model_path)
        {
            net_ = CvDnn.ReadNetFromCaffe(proto_path, model_path);
        }

        private Net net_;

       unsafe public List Forward(Mat img, int target_width, int target_height)
        {
            int img_w = img.Cols;
            int img_h = img.Rows;
            using Mat input = new();
            Cv2.Resize(img, input, new Size(target_width, target_height), 0, 0, InterpolationFlags.Cubic);

            using var blob = CvDnn.BlobFromImage(input, 1.0 / 255, new Size(input.Cols, input.Rows), new Scalar(0f, 0f, 0f),
                     false, false);

            net_.SetInput(blob, "data");

            using var prob = net_.Forward("detection_output");
            List point_list = new();
            // the shape is (1,1,100,7)=>(batch,channel,count,dim)
            for (int row = 0; row < prob.Size(2); row++)
            {
                float* prob_score = (float*)prob.Ptr(0, 0, row).ToPointer();

                // prob_score[0] is not used.
                // prob_score[1]==1 stands for qrcode
                if (prob_score[1] == 1 && prob_score[2] > 1E-5)
                {
                    // add a safe score threshold due to https://github.com/opencv/opencv_contrib/issues/2877
                    // prob_score[2] is the probability of the qrcode, which is not used.
                    var point = new Mat(4, 2, MatType.CV_32FC1);
                    float x0 = CLIP(prob_score[3] * img_w, 0.0f, img_w - 1.0f);
                    float y0 = CLIP(prob_score[4] * img_h, 0.0f, img_h - 1.0f);
                    float x1 = CLIP(prob_score[5] * img_w, 0.0f, img_w - 1.0f);
                    float y1 = CLIP(prob_score[6] * img_h, 0.0f, img_h - 1.0f);

                    point.At(0, 0) = x0;
                    point.At(0, 1) = y0;
                    point.At(1, 0) = x1;
                    point.At(1, 1) = y0;
                    point.At(2, 0) = x1;
                    point.At(2, 1) = y1;
                    point.At(3, 0) = x0;
                    point.At(3, 1) = y1;
                    point_list.Add(point);
                }
            }
            net_.Dispose();
            return point_list;
        }
    }

   private static void Main(string[] args)
        {
            Mat src = Cv2.ImRead("dm.bmp");
            int img_w = src.Cols;
            int img_h = src.Rows;

            // hard code input size
            int minInputSize = 1600;
            float resizeRatio = (float)Math.Sqrt(img_w * img_h * 1.0 / (minInputSize * minInputSize));
            int detect_width = (int)(img_w / resizeRatio);
            int detect_height = (int)(img_h / resizeRatio);
            var key = Cv2.WaitKey(1);
            int fconut = 0;
            Cv2.NamedWindow("img", WindowFlags.FreeRatio);
            int windowH = 1200 * img_h / img_w;
            Cv2.ResizeWindow("img", new(1200, windowH));
            Cv2.MoveWindow("img", 200, 20);
            while (key != 113) // q 退出
            {
                fconut++; 
                
                Scalar scalar = Scalar.RandomColor();int thickness = 2;
                using Mat img = src.Clone();
                using Mat gray = src.CvtColor(ColorConversionCodes.BGR2GRAY);
                SSDDetector SSDD = new("detect.prototxt", "detect.caffemodel");
                var pointslist = SSDD.Forward(gray, detect_width, detect_height);
                foreach (var points in pointslist)
                {
                    img.Line((int)points.At(0, 0), (int)points.At(0, 1),
                              (int)points.At(1, 0), (int)points.At(1, 1),
                               scalar, thickness);
                    img.Line((int)points.At(1, 0), (int)points.At(1, 1),
                                (int)points.At(2, 0), (int)points.At(2, 1),
                                scalar, thickness);
                    img.Line((int)points.At(2, 0), (int)points.At(2, 1),
                                (int)points.At(3, 0), (int)points.At(3, 1),
                                scalar, thickness);
                    img.Line((int)points.At(3, 0), (int)points.At(3, 1),
                                (int)points.At(0, 0), (int)points.At(0, 1),
                                scalar, thickness);
                }
                img.PutText(fconut.ToString(), new(20, 20), HersheyFonts.HersheyDuplex, 1, Scalar.Red);
                img.PutText("q : quit", new(20, 60), HersheyFonts.HersheyDuplex, 1, Scalar.Red);
                Cv2.ImShow("img", img);

                key = Cv2.WaitKey();
            }
        }

 原连接：

https://github.com/opencv/opencv_contrib/blob/master/modules/wechat_qrcode/src/detector/ssd_detector.cpp

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