[C#] Add c sharp apis for yolo serial models (#1424)

* add c sharp apis for yolo serial models

* fix

* fix

---------

Co-authored-by: heliqi <1101791222@qq.com>

examples/vision/detection/yolov5/csharp/infer.cs

@@ -0,0 +1,58 @@
+// Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+using System;
+using System.IO;
+using System.Runtime.InteropServices;
+using OpenCvSharp;
+using fastdeploy;
+
+namespace Test
+{
+    public class TestYOLOv5
+    {
+        public static void Main(string[] args)
+        {
+            if (args.Length < 3) {
+                Console.WriteLine(
+                    "Usage: infer_demo path/to/model path/to/image run_option, " +
+                    "e.g ./infer_model ./yolov5.onnx ./test.jpeg 0"
+                );
+                Console.WriteLine( "The data type of run_option is int, 0: run with cpu; 1: run with gpu");
+                return;
+            }
+            string model_path = args[0];
+            string image_path = args[1];
+            
+            RuntimeOption runtimeoption = new RuntimeOption();
+            int device_option = Int32.Parse(args[2]);
+            if(device_option==0){
+                runtimeoption.UseCpu();
+            }else{
+                runtimeoption.UseGpu();
+            }
+            fastdeploy.vision.detection.YOLOv5 model = new fastdeploy.vision.detection.YOLOv5(model_path, "", runtimeoption, ModelFormat.ONNX);
+            if(!model.Initialized()){
+                Console.WriteLine("Failed to initialize.\n");
+            }
+            Mat image = Cv2.ImRead(image_path);
+            fastdeploy.vision.DetectionResult res = model.Predict(image);
+            Console.WriteLine(res.ToString());
+            Mat res_img = fastdeploy.vision.Visualize.VisDetection(image, res, 0, 1, 0.5f);
+            Cv2.ImShow("result.png", res_img);
+            Cv2.WaitKey(0);
+        }
+
+    }
+}