diff --git a/csharp/fastdeploy/vision/detection/ppdet/model.cs b/csharp/fastdeploy/vision/detection/ppdet/model.cs
index a6f5c0953..84ae9a239 100644
--- a/csharp/fastdeploy/vision/detection/ppdet/model.cs
+++ b/csharp/fastdeploy/vision/detection/ppdet/model.cs
@@ -33,7 +33,7 @@ public class PPYOLOE {
       custom_option = new RuntimeOption();
     }
     fd_ppyoloe_wrapper =
-        FD_C_CreatesPPYOLOEWrapper(model_file, params_file, config_file,
+        FD_C_CreatePPYOLOEWrapper(model_file, params_file, config_file,
                                    custom_option.GetWrapperPtr(), model_format);
   }
 
@@ -84,8 +84,8 @@ public class PPYOLOE {
 
   // below are underlying C api
   private IntPtr fd_ppyoloe_wrapper;
-  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreatesPPYOLOEWrapper")]
-  private static extern IntPtr FD_C_CreatesPPYOLOEWrapper(
+  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreatePPYOLOEWrapper")]
+  private static extern IntPtr FD_C_CreatePPYOLOEWrapper(
       string model_file, string params_file, string config_file,
       IntPtr fd_runtime_option_wrapper, ModelFormat model_format);
   [DllImport("fastdeploy.dll", EntryPoint = "FD_C_DestroyPPYOLOEWrapper")]
@@ -136,7 +136,7 @@ public class PicoDet {
       custom_option = new RuntimeOption();
     }
     fd_picodet_wrapper =
-        FD_C_CreatesPicoDetWrapper(model_file, params_file, config_file,
+        FD_C_CreatePicoDetWrapper(model_file, params_file, config_file,
                                    custom_option.GetWrapperPtr(), model_format);
   }
 
@@ -187,8 +187,8 @@ public class PicoDet {
 
   // below are underlying C api
   private IntPtr fd_picodet_wrapper;
-  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreatesPicoDetWrapper")]
-  private static extern IntPtr FD_C_CreatesPicoDetWrapper(
+  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreatePicoDetWrapper")]
+  private static extern IntPtr FD_C_CreatePicoDetWrapper(
       string model_file, string params_file, string config_file,
       IntPtr fd_runtime_option_wrapper, ModelFormat model_format);
   [DllImport("fastdeploy.dll", EntryPoint = "FD_C_DestroyPicoDetWrapper")]
@@ -241,7 +241,7 @@ public class PPYOLO {
       custom_option = new RuntimeOption();
     }
     fd_ppyolo_wrapper =
-        FD_C_CreatesPPYOLOWrapper(model_file, params_file, config_file,
+        FD_C_CreatePPYOLOWrapper(model_file, params_file, config_file,
                                    custom_option.GetWrapperPtr(), model_format);
   }
 
@@ -292,8 +292,8 @@ public class PPYOLO {
 
   // below are underlying C api
   private IntPtr fd_ppyolo_wrapper;
-  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreatesPPYOLOWrapper")]
-  private static extern IntPtr FD_C_CreatesPPYOLOWrapper(
+  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreatePPYOLOWrapper")]
+  private static extern IntPtr FD_C_CreatePPYOLOWrapper(
       string model_file, string params_file, string config_file,
       IntPtr fd_runtime_option_wrapper, ModelFormat model_format);
   [DllImport("fastdeploy.dll", EntryPoint = "FD_C_DestroyPPYOLOWrapper")]
@@ -345,7 +345,7 @@ public class YOLOv3 {
       custom_option = new RuntimeOption();
     }
     fd_yolov3_wrapper =
-        FD_C_CreatesYOLOv3Wrapper(model_file, params_file, config_file,
+        FD_C_CreateYOLOv3Wrapper(model_file, params_file, config_file,
                                    custom_option.GetWrapperPtr(), model_format);
   }
 
@@ -396,8 +396,8 @@ public class YOLOv3 {
 
   // below are underlying C api
   private IntPtr fd_yolov3_wrapper;
-  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreatesYOLOv3Wrapper")]
-  private static extern IntPtr FD_C_CreatesYOLOv3Wrapper(
+  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreateYOLOv3Wrapper")]
+  private static extern IntPtr FD_C_CreateYOLOv3Wrapper(
       string model_file, string params_file, string config_file,
       IntPtr fd_runtime_option_wrapper, ModelFormat model_format);
   [DllImport("fastdeploy.dll", EntryPoint = "FD_C_DestroyYOLOv3Wrapper")]
@@ -449,7 +449,7 @@ public class PaddleYOLOX {
       custom_option = new RuntimeOption();
     }
     fd_paddleyolox_wrapper =
-        FD_C_CreatesPaddleYOLOXWrapper(model_file, params_file, config_file,
+        FD_C_CreatePaddleYOLOXWrapper(model_file, params_file, config_file,
                                    custom_option.GetWrapperPtr(), model_format);
   }
 
@@ -500,8 +500,8 @@ public class PaddleYOLOX {
 
   // below are underlying C api
   private IntPtr fd_paddleyolox_wrapper;
-  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreatesPaddleYOLOXWrapper")]
-  private static extern IntPtr FD_C_CreatesPaddleYOLOXWrapper(
+  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreatePaddleYOLOXWrapper")]
+  private static extern IntPtr FD_C_CreatePaddleYOLOXWrapper(
       string model_file, string params_file, string config_file,
       IntPtr fd_runtime_option_wrapper, ModelFormat model_format);
   [DllImport("fastdeploy.dll", EntryPoint = "FD_C_DestroyPaddleYOLOXWrapper")]
@@ -553,7 +553,7 @@ public class FasterRCNN {
       custom_option = new RuntimeOption();
     }
     fd_fasterrcnn_wrapper =
-        FD_C_CreatesFasterRCNNWrapper(model_file, params_file, config_file,
+        FD_C_CreateFasterRCNNWrapper(model_file, params_file, config_file,
                                    custom_option.GetWrapperPtr(), model_format);
   }
 
@@ -604,8 +604,8 @@ public class FasterRCNN {
 
   // below are underlying C api
   private IntPtr fd_fasterrcnn_wrapper;
-  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreatesFasterRCNNWrapper")]
-  private static extern IntPtr FD_C_CreatesFasterRCNNWrapper(
+  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreateFasterRCNNWrapper")]
+  private static extern IntPtr FD_C_CreateFasterRCNNWrapper(
       string model_file, string params_file, string config_file,
       IntPtr fd_runtime_option_wrapper, ModelFormat model_format);
   [DllImport("fastdeploy.dll", EntryPoint = "FD_C_DestroyFasterRCNNWrapper")]
@@ -657,7 +657,7 @@ public class MaskRCNN {
       custom_option = new RuntimeOption();
     }
     fd_maskrcnn_wrapper =
-        FD_C_CreatesMaskRCNNWrapper(model_file, params_file, config_file,
+        FD_C_CreateMaskRCNNWrapper(model_file, params_file, config_file,
                                    custom_option.GetWrapperPtr(), model_format);
   }
 
@@ -708,8 +708,8 @@ public class MaskRCNN {
 
   // below are underlying C api
   private IntPtr fd_maskrcnn_wrapper;
-  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreatesMaskRCNNWrapper")]
-  private static extern IntPtr FD_C_CreatesMaskRCNNWrapper(
+  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreateMaskRCNNWrapper")]
+  private static extern IntPtr FD_C_CreateMaskRCNNWrapper(
       string model_file, string params_file, string config_file,
       IntPtr fd_runtime_option_wrapper, ModelFormat model_format);
   [DllImport("fastdeploy.dll", EntryPoint = "FD_C_DestroyMaskRCNNWrapper")]
@@ -761,7 +761,7 @@ public class SSD {
       custom_option = new RuntimeOption();
     }
     fd_ssd_wrapper =
-        FD_C_CreatesSSDWrapper(model_file, params_file, config_file,
+        FD_C_CreateSSDWrapper(model_file, params_file, config_file,
                                    custom_option.GetWrapperPtr(), model_format);
   }
 
@@ -812,8 +812,8 @@ public class SSD {
 
   // below are underlying C api
   private IntPtr fd_ssd_wrapper;
-  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreatesSSDWrapper")]
-  private static extern IntPtr FD_C_CreatesSSDWrapper(
+  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreateSSDWrapper")]
+  private static extern IntPtr FD_C_CreateSSDWrapper(
       string model_file, string params_file, string config_file,
       IntPtr fd_runtime_option_wrapper, ModelFormat model_format);
   [DllImport("fastdeploy.dll", EntryPoint = "FD_C_DestroySSDWrapper")]
@@ -865,7 +865,7 @@ public class PaddleYOLOv5 {
       custom_option = new RuntimeOption();
     }
     fd_paddleyolov5_wrapper =
-        FD_C_CreatesPaddleYOLOv5Wrapper(model_file, params_file, config_file,
+        FD_C_CreatePaddleYOLOv5Wrapper(model_file, params_file, config_file,
                                    custom_option.GetWrapperPtr(), model_format);
   }
 
@@ -916,8 +916,8 @@ public class PaddleYOLOv5 {
 
   // below are underlying C api
   private IntPtr fd_paddleyolov5_wrapper;
-  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreatesPaddleYOLOv5Wrapper")]
-  private static extern IntPtr FD_C_CreatesPaddleYOLOv5Wrapper(
+  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreatePaddleYOLOv5Wrapper")]
+  private static extern IntPtr FD_C_CreatePaddleYOLOv5Wrapper(
       string model_file, string params_file, string config_file,
       IntPtr fd_runtime_option_wrapper, ModelFormat model_format);
   [DllImport("fastdeploy.dll", EntryPoint = "FD_C_DestroyPaddleYOLOv5Wrapper")]
@@ -969,7 +969,7 @@ public class PaddleYOLOv6 {
       custom_option = new RuntimeOption();
     }
     fd_paddleyolov6_wrapper =
-        FD_C_CreatesPaddleYOLOv6Wrapper(model_file, params_file, config_file,
+        FD_C_CreatePaddleYOLOv6Wrapper(model_file, params_file, config_file,
                                    custom_option.GetWrapperPtr(), model_format);
   }
 
@@ -1020,8 +1020,8 @@ public class PaddleYOLOv6 {
 
   // below are underlying C api
   private IntPtr fd_paddleyolov6_wrapper;
-  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreatesPaddleYOLOv6Wrapper")]
-  private static extern IntPtr FD_C_CreatesPaddleYOLOv6Wrapper(
+  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreatePaddleYOLOv6Wrapper")]
+  private static extern IntPtr FD_C_CreatePaddleYOLOv6Wrapper(
       string model_file, string params_file, string config_file,
       IntPtr fd_runtime_option_wrapper, ModelFormat model_format);
   [DllImport("fastdeploy.dll", EntryPoint = "FD_C_DestroyPaddleYOLOv6Wrapper")]
@@ -1073,7 +1073,7 @@ public class PaddleYOLOv7 {
       custom_option = new RuntimeOption();
     }
     fd_paddleyolov7_wrapper =
-        FD_C_CreatesPaddleYOLOv7Wrapper(model_file, params_file, config_file,
+        FD_C_CreatePaddleYOLOv7Wrapper(model_file, params_file, config_file,
                                    custom_option.GetWrapperPtr(), model_format);
   }
 
@@ -1124,8 +1124,8 @@ public class PaddleYOLOv7 {
 
   // below are underlying C api
   private IntPtr fd_paddleyolov7_wrapper;
-  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreatesPaddleYOLOv7Wrapper")]
-  private static extern IntPtr FD_C_CreatesPaddleYOLOv7Wrapper(
+  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreatePaddleYOLOv7Wrapper")]
+  private static extern IntPtr FD_C_CreatePaddleYOLOv7Wrapper(
       string model_file, string params_file, string config_file,
       IntPtr fd_runtime_option_wrapper, ModelFormat model_format);
   [DllImport("fastdeploy.dll", EntryPoint = "FD_C_DestroyPaddleYOLOv7Wrapper")]
@@ -1177,7 +1177,7 @@ public class PaddleYOLOv8 {
       custom_option = new RuntimeOption();
     }
     fd_paddleyolov8_wrapper =
-        FD_C_CreatesPaddleYOLOv8Wrapper(model_file, params_file, config_file,
+        FD_C_CreatePaddleYOLOv8Wrapper(model_file, params_file, config_file,
                                    custom_option.GetWrapperPtr(), model_format);
   }
 
@@ -1228,8 +1228,8 @@ public class PaddleYOLOv8 {
 
   // below are underlying C api
   private IntPtr fd_paddleyolov8_wrapper;
-  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreatesPaddleYOLOv8Wrapper")]
-  private static extern IntPtr FD_C_CreatesPaddleYOLOv8Wrapper(
+  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreatePaddleYOLOv8Wrapper")]
+  private static extern IntPtr FD_C_CreatePaddleYOLOv8Wrapper(
       string model_file, string params_file, string config_file,
       IntPtr fd_runtime_option_wrapper, ModelFormat model_format);
   [DllImport("fastdeploy.dll", EntryPoint = "FD_C_DestroyPaddleYOLOv8Wrapper")]
@@ -1281,7 +1281,7 @@ public class RTMDet {
       custom_option = new RuntimeOption();
     }
     fd_rtmdet_wrapper =
-        FD_C_CreatesRTMDetWrapper(model_file, params_file, config_file,
+        FD_C_CreateRTMDetWrapper(model_file, params_file, config_file,
                                    custom_option.GetWrapperPtr(), model_format);
   }
 
@@ -1332,8 +1332,8 @@ public class RTMDet {
 
   // below are underlying C api
   private IntPtr fd_rtmdet_wrapper;
-  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreatesRTMDetWrapper")]
-  private static extern IntPtr FD_C_CreatesRTMDetWrapper(
+  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreateRTMDetWrapper")]
+  private static extern IntPtr FD_C_CreateRTMDetWrapper(
       string model_file, string params_file, string config_file,
       IntPtr fd_runtime_option_wrapper, ModelFormat model_format);
   [DllImport("fastdeploy.dll", EntryPoint = "FD_C_DestroyRTMDetWrapper")]
@@ -1385,7 +1385,7 @@ public class CascadeRCNN {
       custom_option = new RuntimeOption();
     }
     fd_cascadercnn_wrapper =
-        FD_C_CreatesCascadeRCNNWrapper(model_file, params_file, config_file,
+        FD_C_CreateCascadeRCNNWrapper(model_file, params_file, config_file,
                                    custom_option.GetWrapperPtr(), model_format);
   }
 
@@ -1436,8 +1436,8 @@ public class CascadeRCNN {
 
   // below are underlying C api
   private IntPtr fd_cascadercnn_wrapper;
-  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreatesCascadeRCNNWrapper")]
-  private static extern IntPtr FD_C_CreatesCascadeRCNNWrapper(
+  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreateCascadeRCNNWrapper")]
+  private static extern IntPtr FD_C_CreateCascadeRCNNWrapper(
       string model_file, string params_file, string config_file,
       IntPtr fd_runtime_option_wrapper, ModelFormat model_format);
   [DllImport("fastdeploy.dll", EntryPoint = "FD_C_DestroyCascadeRCNNWrapper")]
@@ -1489,7 +1489,7 @@ public class PSSDet {
       custom_option = new RuntimeOption();
     }
     fd_pssdet_wrapper =
-        FD_C_CreatesPSSDetWrapper(model_file, params_file, config_file,
+        FD_C_CreatePSSDetWrapper(model_file, params_file, config_file,
                                    custom_option.GetWrapperPtr(), model_format);
   }
 
@@ -1540,8 +1540,8 @@ public class PSSDet {
 
   // below are underlying C api
   private IntPtr fd_pssdet_wrapper;
-  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreatesPSSDetWrapper")]
-  private static extern IntPtr FD_C_CreatesPSSDetWrapper(
+  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreatePSSDetWrapper")]
+  private static extern IntPtr FD_C_CreatePSSDetWrapper(
       string model_file, string params_file, string config_file,
       IntPtr fd_runtime_option_wrapper, ModelFormat model_format);
   [DllImport("fastdeploy.dll", EntryPoint = "FD_C_DestroyPSSDetWrapper")]
@@ -1593,7 +1593,7 @@ public class RetinaNet {
       custom_option = new RuntimeOption();
     }
     fd_retinanet_wrapper =
-        FD_C_CreatesRetinaNetWrapper(model_file, params_file, config_file,
+        FD_C_CreateRetinaNetWrapper(model_file, params_file, config_file,
                                    custom_option.GetWrapperPtr(), model_format);
   }
 
@@ -1644,8 +1644,8 @@ public class RetinaNet {
 
   // below are underlying C api
   private IntPtr fd_retinanet_wrapper;
-  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreatesRetinaNetWrapper")]
-  private static extern IntPtr FD_C_CreatesRetinaNetWrapper(
+  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreateRetinaNetWrapper")]
+  private static extern IntPtr FD_C_CreateRetinaNetWrapper(
       string model_file, string params_file, string config_file,
       IntPtr fd_runtime_option_wrapper, ModelFormat model_format);
   [DllImport("fastdeploy.dll", EntryPoint = "FD_C_DestroyRetinaNetWrapper")]
@@ -1697,7 +1697,7 @@ public class FCOS {
       custom_option = new RuntimeOption();
     }
     fd_fcos_wrapper =
-        FD_C_CreatesFCOSWrapper(model_file, params_file, config_file,
+        FD_C_CreateFCOSWrapper(model_file, params_file, config_file,
                                    custom_option.GetWrapperPtr(), model_format);
   }
 
@@ -1748,8 +1748,8 @@ public class FCOS {
 
   // below are underlying C api
   private IntPtr fd_fcos_wrapper;
-  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreatesFCOSWrapper")]
-  private static extern IntPtr FD_C_CreatesFCOSWrapper(
+  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreateFCOSWrapper")]
+  private static extern IntPtr FD_C_CreateFCOSWrapper(
       string model_file, string params_file, string config_file,
       IntPtr fd_runtime_option_wrapper, ModelFormat model_format);
   [DllImport("fastdeploy.dll", EntryPoint = "FD_C_DestroyFCOSWrapper")]
@@ -1801,7 +1801,7 @@ public class TTFNet {
       custom_option = new RuntimeOption();
     }
     fd_ttfnet_wrapper =
-        FD_C_CreatesTTFNetWrapper(model_file, params_file, config_file,
+        FD_C_CreateTTFNetWrapper(model_file, params_file, config_file,
                                    custom_option.GetWrapperPtr(), model_format);
   }
 
@@ -1852,8 +1852,8 @@ public class TTFNet {
 
   // below are underlying C api
   private IntPtr fd_ttfnet_wrapper;
-  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreatesTTFNetWrapper")]
-  private static extern IntPtr FD_C_CreatesTTFNetWrapper(
+  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreateTTFNetWrapper")]
+  private static extern IntPtr FD_C_CreateTTFNetWrapper(
       string model_file, string params_file, string config_file,
       IntPtr fd_runtime_option_wrapper, ModelFormat model_format);
   [DllImport("fastdeploy.dll", EntryPoint = "FD_C_DestroyTTFNetWrapper")]
@@ -1905,7 +1905,7 @@ public class TOOD {
       custom_option = new RuntimeOption();
     }
     fd_tood_wrapper =
-        FD_C_CreatesTOODWrapper(model_file, params_file, config_file,
+        FD_C_CreateTOODWrapper(model_file, params_file, config_file,
                                    custom_option.GetWrapperPtr(), model_format);
   }
 
@@ -1956,8 +1956,8 @@ public class TOOD {
 
   // below are underlying C api
   private IntPtr fd_tood_wrapper;
-  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreatesTOODWrapper")]
-  private static extern IntPtr FD_C_CreatesTOODWrapper(
+  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreateTOODWrapper")]
+  private static extern IntPtr FD_C_CreateTOODWrapper(
       string model_file, string params_file, string config_file,
       IntPtr fd_runtime_option_wrapper, ModelFormat model_format);
   [DllImport("fastdeploy.dll", EntryPoint = "FD_C_DestroyTOODWrapper")]
@@ -2009,7 +2009,7 @@ public class GFL {
       custom_option = new RuntimeOption();
     }
     fd_gfl_wrapper =
-        FD_C_CreatesGFLWrapper(model_file, params_file, config_file,
+        FD_C_CreateGFLWrapper(model_file, params_file, config_file,
                                    custom_option.GetWrapperPtr(), model_format);
   }
 
@@ -2060,8 +2060,8 @@ public class GFL {
 
   // below are underlying C api
   private IntPtr fd_gfl_wrapper;
-  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreatesGFLWrapper")]
-  private static extern IntPtr FD_C_CreatesGFLWrapper(
+  [DllImport("fastdeploy.dll", EntryPoint = "FD_C_CreateGFLWrapper")]
+  private static extern IntPtr FD_C_CreateGFLWrapper(
       string model_file, string params_file, string config_file,
       IntPtr fd_runtime_option_wrapper, ModelFormat model_format);
   [DllImport("fastdeploy.dll", EntryPoint = "FD_C_DestroyGFLWrapper")]
diff --git a/examples/vision/classification/paddleclas/c/CMakeLists.txt b/examples/vision/classification/paddleclas/c/CMakeLists.txt
new file mode 100644
index 000000000..b228346da
--- /dev/null
+++ b/examples/vision/classification/paddleclas/c/CMakeLists.txt
@@ -0,0 +1,13 @@
+PROJECT(infer_demo C)
+CMAKE_MINIMUM_REQUIRED (VERSION 3.10)
+
+# 指定下载解压后的fastdeploy库路径
+option(FASTDEPLOY_INSTALL_DIR "Path of downloaded fastdeploy sdk.")
+
+include(${FASTDEPLOY_INSTALL_DIR}/FastDeploy.cmake)
+
+# 添加FastDeploy依赖头文件
+include_directories(${FASTDEPLOY_INCS})
+
+add_executable(infer_demo ${PROJECT_SOURCE_DIR}/infer.c)
+target_link_libraries(infer_demo ${FASTDEPLOY_LIBS})
diff --git a/examples/vision/classification/paddleclas/c/README.md b/examples/vision/classification/paddleclas/c/README.md
new file mode 100755
index 000000000..4b125e4ab
--- /dev/null
+++ b/examples/vision/classification/paddleclas/c/README.md
@@ -0,0 +1,183 @@
+English | [简体中文](README_CN.md)
+# PaddleClas C Deployment Example
+
+This directory provides examples that `infer.c` fast finishes the deployment of PaddleClas models on CPU/GPU.
+
+Before deployment, two steps require confirmation.
+
+- 1. Software and hardware should meet the requirements. Please refer to [FastDeploy Environment Requirements](../../../../../docs/en/build_and_install/download_prebuilt_libraries.md).  
+- 2. Download the precompiled deployment library and samples code according to your development environment. Refer to [FastDeploy Precompiled Library](../../../../../docs/en/build_and_install/download_prebuilt_libraries.md).
+
+Taking ResNet50_vd inference on Linux as an example, the compilation test can be completed by executing the following command in this directory. FastDeploy version 1.0.4 or above (x.x.x>=1.0.4)  is required to support this model.
+
+```bash
+mkdir build
+cd build
+# Download FastDeploy precompiled library. Users can choose your appropriate version in the`FastDeploy Precompiled Library` mentioned above
+wget https://bj.bcebos.com/fastdeploy/release/cpp/fastdeploy-linux-x64-x.x.x.tgz
+tar xvf fastdeploy-linux-x64-x.x.x.tgz
+cmake .. -DFASTDEPLOY_INSTALL_DIR=${PWD}/fastdeploy-linux-x64-x.x.x
+make -j
+
+# Download ResNet50_vd model file and test images
+wget https://bj.bcebos.com/paddlehub/fastdeploy/ResNet50_vd_infer.tgz
+tar -xvf ResNet50_vd_infer.tgz
+wget https://gitee.com/paddlepaddle/PaddleClas/raw/release/2.4/deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg
+
+
+# CPU inference
+./infer_demo ResNet50_vd_infer ILSVRC2012_val_00000010.jpeg 0
+# GPU inference
+./infer_demo ResNet50_vd_infer ILSVRC2012_val_00000010.jpeg 1
+```
+
+The above command works for Linux or MacOS. Refer to
+- [How to use FastDeploy C++ SDK in Windows](../../../../../docs/cn/faq/use_sdk_on_windows.md) for SDK use-pattern in Windows
+
+## PaddleClas C Interface
+
+### RuntimeOption
+
+```c
+FD_C_RuntimeOptionWrapper* FD_C_CreateRuntimeOptionWrapper()
+```
+
+> Create a RuntimeOption object, and return a pointer to manipulate it.
+>
+> **Return**
+>
+> * **fd_c_runtime_option_wrapper**(FD_C_RuntimeOptionWrapper*): Pointer to manipulate RuntimeOption object.
+
+
+```c
+void FD_C_RuntimeOptionWrapperUseCpu(
+     FD_C_RuntimeOptionWrapper* fd_c_runtime_option_wrapper)
+```
+
+> Enable Cpu inference.
+>
+> **Params**
+>
+> * **fd_c_runtime_option_wrapper**(FD_C_RuntimeOptionWrapper*): Pointer to manipulate RuntimeOption object.
+
+```c
+void FD_C_RuntimeOptionWrapperUseGpu(
+    FD_C_RuntimeOptionWrapper* fd_c_runtime_option_wrapper,
+    int gpu_id)
+```
+> 开启GPU推理
+>
+> **参数**
+>
+> * **fd_c_runtime_option_wrapper**(FD_C_RuntimeOptionWrapper*): Pointer to manipulate RuntimeOption object.
+> * **gpu_id**(int): gpu id
+
+
+### Model
+
+```c
+
+FD_C_PaddleClasModelWrapper* FD_C_CreatePaddleClasModelWrapper(
+    const char* model_file, const char* params_file, const char* config_file,
+    FD_C_RuntimeOptionWrapper* runtime_option,
+    const FD_C_ModelFormat model_format)
+
+```
+
+> Create a PaddleClas model object, and return a pointer to manipulate it.
+>
+> **Params**
+>
+> * **model_file**(const char*): Model file path
+> * **params_file**(const char*): Parameter file path
+> * **config_file**(const char*): Configuration file path, which is the deployment yaml file exported by PaddleClas.
+> * **runtime_option**(FD_C_RuntimeOptionWrapper*): Backend inference configuration. None by default, which is the default configuration
+> * **model_format**(FD_C_ModelFormat): Model format. Paddle format by default
+>
+> **Return**
+> * **fd_c_ppclas_wrapper**(FD_C_PaddleClasModelWrapper*): Pointer to manipulate PaddleClas object.
+
+
+#### Read and write image
+
+```c
+FD_C_Mat FD_C_Imread(const char* imgpath)
+```
+
+> Read an image, and return a pointer to cv::Mat.
+>
+> **Params**
+>
+> * **imgpath**(const char*): image path
+>
+> **Return**
+>
+> * **imgmat**(FD_C_Mat): pointer to cv::Mat object which holds the image.
+
+
+```c
+FD_C_Bool FD_C_Imwrite(const char* savepath,  FD_C_Mat img);
+```
+
+> Write image to a file.
+>
+> **Params**
+>
+> * **savepath**(const char*): save path
+> * **img**(FD_C_Mat): pointer to cv::Mat object
+>
+> **Return**
+>
+> * **result**(FD_C_Bool): bool to indicate success or failure
+
+
+#### Prediction
+
+```c
+FD_C_Bool FD_C_PaddleClasModelWrapperPredict(
+    __fd_take FD_C_PaddleClasModelWrapper* fd_c_ppclas_wrapper, FD_C_Mat img,
+    FD_C_ClassifyResult* fd_c_ppclas_result)
+```
+>
+> Predict an image, and generate classification result.
+>
+> **Params**
+> * **fd_c_ppclas_wrapper**(FD_C_PaddleClasModelWrapper*): pointer to manipulate PaddleClas object
+> * **img**（FD_C_Mat）: pointer to cv::Mat object, which can be obained by FD_C_Imread interface
+> * **fd_c_ppclas_result** (FD_C_ClassifyResult*): The classification result, including label_id, and the corresponding confidence. Refer to [Visual Model Prediction Results](../../../../../docs/api/vision_results/) for the description of ClassifyResult
+
+
+#### Result
+
+```c
+FD_C_ClassifyResultWrapper* FD_C_CreateClassifyResultWrapperFromData(
+    FD_C_ClassifyResult* fd_c_classify_result)
+```
+>
+> Create a pointer to FD_C_ClassifyResultWrapper structure, which contains `fastdeploy::vision::ClassifyResult` object in C++. You can call methods in C++ ClassifyResult object by C API with this pointer.
+>
+> **Params**
+> * **fd_c_classify_result**(FD_C_ClassifyResult*): pointer to FD_C_ClassifyResult structure
+>
+> **Return**
+> * **fd_c_classify_result_wrapper**(FD_C_ClassifyResultWrapper*): pointer to FD_C_ClassifyResultWrapper structure
+
+
+```c
+char* FD_C_ClassifyResultWrapperStr(
+    FD_C_ClassifyResultWrapper* fd_c_classify_result_wrapper);
+```
+>
+> Call Str() methods in `fastdeploy::vision::ClassifyResult` object contained in FD_C_ClassifyResultWrapper structure，and return a string to describe information in result.
+>
+> **Params**
+> * **fd_c_classify_result_wrapper**(FD_C_ClassifyResultWrapper*): pointer to FD_C_ClassifyResultWrapper structure
+>
+> **Return**
+> * **str**(char*): a string to describe information in result
+
+
+- [Model Description](../../)
+- [Python Deployment](../python)
+- [Visual Model prediction results](../../../../../docs/api/vision_results/)
+- [How to switch the model inference backend engine](../../../../../docs/en/faq/how_to_change_backend.md)
diff --git a/examples/vision/classification/paddleclas/c/README_CN.md b/examples/vision/classification/paddleclas/c/README_CN.md
new file mode 100644
index 000000000..1cf59d21d
--- /dev/null
+++ b/examples/vision/classification/paddleclas/c/README_CN.md
@@ -0,0 +1,189 @@
+[English](README.md) | 简体中文
+# PaddleClas C 部署示例
+
+本目录下提供`infer_xxx.c`来调用C API快速完成PaddleClas系列模型在CPU/GPU上部署的示例。
+
+在部署前，需确认以下两个步骤
+
+- 1. 软硬件环境满足要求，参考[FastDeploy环境要求](../../../../../docs/cn/build_and_install/download_prebuilt_libraries.md)  
+- 2. 根据开发环境，下载预编译部署库和samples代码，参考[FastDeploy预编译库](../../../../../docs/cn/build_and_install/download_prebuilt_libraries.md)
+
+以Linux上ResNet50_vd推理为例，在本目录执行如下命令即可完成编译测试，支持此模型需保证FastDeploy版本1.0.4以上(x.x.x>=1.0.4)
+
+```bash
+mkdir build
+cd build
+# 下载FastDeploy预编译库，用户可在上文提到的`FastDeploy预编译库`中自行选择合适的版本使用
+wget https://bj.bcebos.com/fastdeploy/release/cpp/fastdeploy-linux-x64-x.x.x.tgz
+tar xvf fastdeploy-linux-x64-x.x.x.tgz
+cmake .. -DFASTDEPLOY_INSTALL_DIR=${PWD}/fastdeploy-linux-x64-x.x.x
+make -j
+
+# 下载ResNet50_vd模型文件和测试图片
+wget https://bj.bcebos.com/paddlehub/fastdeploy/ResNet50_vd_infer.tgz
+tar -xvf ResNet50_vd_infer.tgz
+wget https://gitee.com/paddlepaddle/PaddleClas/raw/release/2.4/deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg
+
+
+# CPU推理
+./infer_demo ResNet50_vd_infer ILSVRC2012_val_00000010.jpeg 0
+# GPU推理
+./infer_demo ResNet50_vd_infer ILSVRC2012_val_00000010.jpeg 1
+```
+
+以上命令只适用于Linux或MacOS, Windows下SDK的使用方式请参考:  
+- [如何在Windows中使用FastDeploy C++ SDK](../../../../../docs/cn/faq/use_sdk_on_windows.md)
+
+如果用户使用华为昇腾NPU部署, 请参考以下方式在部署前初始化部署环境:
+- [如何使用华为昇腾NPU部署](../../../../../docs/cn/faq/use_sdk_on_ascend.md)
+
+## PaddleClas C API接口
+
+### 配置
+
+```c
+FD_C_RuntimeOptionWrapper* FD_C_CreateRuntimeOptionWrapper()
+```
+
+> 创建一个RuntimeOption的配置对象，并且返回操作它的指针。
+>
+> **返回**
+>
+> * **fd_c_runtime_option_wrapper**(FD_C_RuntimeOptionWrapper*): 指向RuntimeOption对象的指针
+
+
+```c
+void FD_C_RuntimeOptionWrapperUseCpu(
+     FD_C_RuntimeOptionWrapper* fd_c_runtime_option_wrapper)
+```
+
+> 开启CPU推理
+>
+> **参数**
+>
+> * **fd_c_runtime_option_wrapper**(FD_C_RuntimeOptionWrapper*): 指向RuntimeOption对象的指针
+
+```c
+void FD_C_RuntimeOptionWrapperUseGpu(
+    FD_C_RuntimeOptionWrapper* fd_c_runtime_option_wrapper,
+    int gpu_id)
+```
+> 开启GPU推理
+>
+> **参数**
+>
+> * **fd_c_runtime_option_wrapper**(FD_C_RuntimeOptionWrapper*): 指向RuntimeOption对象的指针
+> * **gpu_id**(int): 显卡号
+
+
+### 模型
+
+```c
+
+FD_C_PaddleClasModelWrapper* FD_C_CreatePaddleClasModelWrapper(
+    const char* model_file, const char* params_file, const char* config_file,
+    FD_C_RuntimeOptionWrapper* runtime_option,
+    const FD_C_ModelFormat model_format)
+
+```
+
+> 创建一个PaddleClas的模型，并且返回操作它的指针。
+>
+> **参数**
+>
+> * **model_file**(const char*): 模型文件路径
+> * **params_file**(const char*): 参数文件路径
+> * **config_file**(const char*): 配置文件路径，即PaddleClas导出的部署yaml文件
+> * **runtime_option**(FD_C_RuntimeOptionWrapper*): 指向RuntimeOption的指针，表示后端推理配置
+> * **model_format**(FD_C_ModelFormat): 模型格式
+>
+> **返回**
+> * **fd_c_ppclas_wrapper**(FD_C_PaddleClasModelWrapper*): 指向PaddleClas模型对象的指针
+
+
+#### 读写图像
+
+```c
+FD_C_Mat FD_C_Imread(const char* imgpath)
+```
+
+> 读取一个图像，并且返回cv::Mat的指针。
+>
+> **参数**
+>
+> * **imgpath**(const char*): 图像文件路径
+>
+> **返回**
+>
+> * **imgmat**(FD_C_Mat): 指向图像数据cv::Mat的指针。
+
+
+```c
+FD_C_Bool FD_C_Imwrite(const char* savepath,  FD_C_Mat img);
+```
+
+> 将图像写入文件中。
+>
+> **参数**
+>
+> * **savepath**(const char*): 保存图像的路径
+> * **img**(FD_C_Mat): 指向图像数据的指针
+>
+> **返回**
+>
+> * **result**(FD_C_Bool): 表示操作是否成功
+
+
+#### Predict函数
+
+```c
+FD_C_Bool FD_C_PaddleClasModelWrapperPredict(
+    __fd_take FD_C_PaddleClasModelWrapper* fd_c_ppclas_wrapper, FD_C_Mat img,
+    FD_C_ClassifyResult* fd_c_ppclas_result)
+```
+>
+> 模型预测接口，输入图像直接并生成分类结果。
+>
+> **参数**
+> * **fd_c_ppclas_wrapper**(FD_C_PaddleClasModelWrapper*): 指向PaddleClas模型的指针
+> * **img**（FD_C_Mat）: 输入图像的指针，指向cv::Mat对象，可以调用FD_C_Imread读取图像获取
+> * **fd_c_ppclas_result**（FD_C_ClassifyResult*): 分类结果，包括label_id，以及相应的置信度, ClassifyResult说明参考[视觉模型预测结果](../../../../../docs/api/vision_results/)
+
+
+#### Predict结果
+
+```c
+FD_C_ClassifyResultWrapper* FD_C_CreateClassifyResultWrapperFromData(
+    FD_C_ClassifyResult* fd_c_classify_result)
+```
+>
+> 创建一个FD_C_ClassifyResultWrapper对象的指针，FD_C_ClassifyResultWrapper中包含了C++的`fastdeploy::vision::ClassifyResult`对象，通过该指针，使用C API可以访问调用对应C++中的函数。
+>
+>
+> **参数**
+> * **fd_c_classify_result**(FD_C_ClassifyResult*): 指向FD_C_ClassifyResult对象的指针
+>
+> **返回**
+> * **fd_c_classify_result_wrapper**(FD_C_ClassifyResultWrapper*): 指向FD_C_ClassifyResultWrapper的指针
+
+
+```c
+char* FD_C_ClassifyResultWrapperStr(
+    FD_C_ClassifyResultWrapper* fd_c_classify_result_wrapper);
+```
+>
+> 调用FD_C_ClassifyResultWrapper所包含的`fastdeploy::vision::ClassifyResult`对象的Str()方法，返回相关结果内数据信息的字符串。
+>
+> **参数**
+> * **fd_c_classify_result_wrapper**(FD_C_ClassifyResultWrapper*): 指向FD_C_ClassifyResultWrapper对象的指针
+>
+> **返回**
+> * **str**(char*): 表示结果数据信息的字符串
+
+
+
+
+- [模型介绍](../../)
+- [Python部署](../python)
+- [视觉模型预测结果](../../../../../docs/api/vision_results/)
+- [如何切换模型推理后端引擎](../../../../../docs/cn/faq/how_to_change_backend.md)
diff --git a/examples/vision/classification/paddleclas/c/infer.c b/examples/vision/classification/paddleclas/c/infer.c
new file mode 100644
index 000000000..97a8659d3
--- /dev/null
+++ b/examples/vision/classification/paddleclas/c/infer.c
@@ -0,0 +1,156 @@
+// 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.
+
+#include <stdio.h>
+#include <stdlib.h>
+
+#include "fastdeploy_capi/vision.h"
+
+#ifdef WIN32
+const char sep = '\\';
+#else
+const char sep = '/';
+#endif
+
+void CpuInfer(const char* model_dir, const char* image_file) {
+  char model_file[100];
+  char params_file[100];
+  char config_file[100];
+  int max_size = 99;
+  snprintf(model_file, max_size, "%s%c%s", model_dir, sep, "inference.pdmodel");
+  snprintf(params_file, max_size, "%s%c%s", model_dir, sep,
+           "inference.pdiparams");
+  snprintf(config_file, max_size, "%s%c%s", model_dir, sep,
+           "inference_cls.yaml");
+
+  FD_C_RuntimeOptionWrapper* option = FD_C_CreateRuntimeOptionWrapper();
+  FD_C_RuntimeOptionWrapperUseCpu(option);
+
+  FD_C_PaddleClasModelWrapper* model = FD_C_CreatePaddleClasModelWrapper(
+      model_file, params_file, config_file, option, PADDLE);
+
+  if (!FD_C_PaddleClasModelWrapperInitialized(model)) {
+    printf("Failed to initialize.\n");
+    FD_C_DestroyRuntimeOptionWrapper(option);
+    FD_C_DestroyPaddleClasModelWrapper(model);
+    return;
+  }
+
+  FD_C_Mat im = FD_C_Imread(image_file);
+
+  FD_C_ClassifyResult* result =
+      (FD_C_ClassifyResult*)malloc(sizeof(FD_C_ClassifyResult));
+
+  if (!FD_C_PaddleClasModelWrapperPredict(model, im, result)) {
+    printf("Failed to predict.\n");
+    FD_C_DestroyRuntimeOptionWrapper(option);
+    FD_C_DestroyPaddleClasModelWrapper(model);
+    FD_C_DestroyMat(im);
+    free(result);
+    return;
+  }
+
+  // print res
+  // You can directly access fields in FD_C_ClassifyResult and print it refer to
+  // ClassifyResult API Doc Or you can wrap it using
+  // FD_C_ClassifyResult_Wrapper, which containes C++ structure
+  // fastdeploy::vision::ClassifyResult, and using C API
+  // FD_C_ClassifyResultWrapperStr to call
+  // fastdeploy::vision::ClassifyResult::Str() in it. For convenience, we choose
+  // this method to print it.
+  FD_C_ClassifyResultWrapper* result_wrapper =
+      FD_C_CreateClassifyResultWrapperFromData(result);
+  printf("%s", FD_C_ClassifyResultWrapperStr(result_wrapper));
+  FD_C_DestroyRuntimeOptionWrapper(option);
+  FD_C_DestroyPaddleClasModelWrapper(model);
+  FD_C_DestroyClassifyResultWrapper(result_wrapper);
+  FD_C_DestroyClassifyResult(result);
+  FD_C_DestroyMat(im);
+}
+
+void GpuInfer(const char* model_dir, const char* image_file) {
+  char model_file[100];
+  char params_file[100];
+  char config_file[100];
+  int max_size = 99;
+  snprintf(model_file, max_size, "%s%c%s", model_dir, sep, "inference.pdmodel");
+  snprintf(params_file, max_size, "%s%c%s", model_dir, sep,
+           "inference.pdiparams");
+  snprintf(config_file, max_size, "%s%c%s", model_dir, sep,
+           "inference_cls.yaml");
+
+  FD_C_RuntimeOptionWrapper* option = FD_C_CreateRuntimeOptionWrapper();
+  FD_C_RuntimeOptionWrapperUseGpu(option, 0);
+
+  FD_C_PaddleClasModelWrapper* model = FD_C_CreatePaddleClasModelWrapper(
+      model_file, params_file, config_file, option, PADDLE);
+
+  if (!FD_C_PaddleClasModelWrapperInitialized(model)) {
+    printf("Failed to initialize.\n");
+    FD_C_DestroyRuntimeOptionWrapper(option);
+    FD_C_DestroyPaddleClasModelWrapper(model);
+    return;
+  }
+
+  FD_C_Mat im = FD_C_Imread(image_file);
+
+  FD_C_ClassifyResult* result =
+      (FD_C_ClassifyResult*)malloc(sizeof(FD_C_ClassifyResult));
+
+  if (!FD_C_PaddleClasModelWrapperPredict(model, im, result)) {
+    printf("Failed to predict.\n");
+    FD_C_DestroyRuntimeOptionWrapper(option);
+    FD_C_DestroyPaddleClasModelWrapper(model);
+    FD_C_DestroyMat(im);
+    free(result);
+    return;
+  }
+
+  // print res
+  // You can directly access fields in FD_C_ClassifyResult and print it refer to
+  // ClassifyResult API Doc Or you can wrap it using
+  // FD_C_ClassifyResult_Wrapper, which containes C++ structure
+  // fastdeploy::vision::ClassifyResult, and using C API
+  // FD_C_ClassifyResultWrapperStr to call
+  // fastdeploy::vision::ClassifyResult::Str() in it. For convenience, we choose
+  // this method to print it.
+  FD_C_ClassifyResultWrapper* result_wrapper =
+      FD_C_CreateClassifyResultWrapperFromData(result);
+  printf("%s", FD_C_ClassifyResultWrapperStr(result_wrapper));
+  FD_C_DestroyRuntimeOptionWrapper(option);
+  FD_C_DestroyPaddleClasModelWrapper(model);
+  FD_C_DestroyClassifyResultWrapper(result_wrapper);
+  FD_C_DestroyClassifyResult(result);
+  FD_C_DestroyMat(im);
+}
+
+int main(int argc, char* argv[]) {
+  if (argc < 4) {
+    printf(
+        "Usage: infer_demo path/to/model_dir path/to/image run_option, "
+        "e.g ./infer_model ./ppyoloe_model_dir ./test.jpeg 0"
+        "\n");
+    printf(
+        "The data type of run_option is int, 0: run with cpu; 1: run with gpu"
+        "\n");
+    return -1;
+  }
+
+  if (atoi(argv[3]) == 0) {
+    CpuInfer(argv[1], argv[2]);
+  } else if (atoi(argv[3]) == 1) {
+    GpuInfer(argv[1], argv[2]);
+  }
+  return 0;
+}
diff --git a/examples/vision/classification/paddleclas/csharp/CMakeLists.txt b/examples/vision/classification/paddleclas/csharp/CMakeLists.txt
new file mode 100644
index 000000000..7ae8e2aba
--- /dev/null
+++ b/examples/vision/classification/paddleclas/csharp/CMakeLists.txt
@@ -0,0 +1,22 @@
+PROJECT(infer_demo CSharp)
+CMAKE_MINIMUM_REQUIRED (VERSION 3.10)
+
+# Set the C# language version (defaults to 3.0 if not set).
+set(CMAKE_CSharp_FLAGS "/langversion:10")
+set(CMAKE_DOTNET_TARGET_FRAMEWORK "net6.0")
+set(CMAKE_DOTNET_SDK "Microsoft.NET.Sdk")
+
+# 指定下载解压后的fastdeploy库路径
+option(FASTDEPLOY_INSTALL_DIR "Path of downloaded fastdeploy sdk.")
+
+include(${FASTDEPLOY_INSTALL_DIR}/FastDeployCSharp.cmake)
+
+
+add_executable(infer_demo ${PROJECT_SOURCE_DIR}/infer.cs)
+
+set_property(TARGET infer_demo PROPERTY VS_DOTNET_REFERENCES
+    ${FASTDEPLOY_DOTNET_REFERENCES}
+)
+
+set_property(TARGET infer_demo
+    PROPERTY VS_PACKAGE_REFERENCES  ${FASTDEPLOY_PACKAGE_REFERENCES})
diff --git a/examples/vision/classification/paddleclas/csharp/README.md b/examples/vision/classification/paddleclas/csharp/README.md
new file mode 100755
index 000000000..0afbd5d7a
--- /dev/null
+++ b/examples/vision/classification/paddleclas/csharp/README.md
@@ -0,0 +1,99 @@
+English | [简体中文](README_CN.md)
+# PaddleClas C# Deployment Example
+
+This directory provides example `infer.cs` to fastly finish the deployment of PaddleClas models on CPU/GPU.
+
+Before deployment, two steps require confirmation
+
+- 1. Software and hardware should meet the requirements. Please refer to [FastDeploy Environment Requirements](../../../../../docs/en/build_and_install/download_prebuilt_libraries.md)  
+- 2.  Download the precompiled deployment library and samples code according to your development environment. Refer to [FastDeploy Precompiled Library](../../../../../docs/en/build_and_install/download_prebuilt_libraries.md)
+
+Please follow below instructions to compile and test in Windows. FastDeploy version 1.0.4 or above (x.x.x>=1.0.4) is required to support this model.
+
+## 1. Download C# package management tool nuget client
+> https://dist.nuget.org/win-x86-commandline/v6.4.0/nuget.exe
+
+Add nuget program into system variable **PATH**
+
+## 2. Download model and image for test
+> https://bj.bcebos.com/paddlehub/fastdeploy/ResNet50_vd_infer.tgz # (下载后解压缩)
+> https://gitee.com/paddlepaddle/PaddleClas/raw/release/2.4/deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg
+
+## 3. Compile example code
+
+Open `x64 Native Tools Command Prompt for VS 2019` command tool on Windows, cd to the demo path of ppyoloe and execute commands
+
+```shell
+cd D:\Download\fastdeploy-win-x64-gpu-x.x.x\examples\vision\classification\paddleclas\csharp
+
+mkdir build && cd build
+cmake .. -G "Visual Studio 16 2019" -A x64 -DFASTDEPLOY_INSTALL_DIR=D:\Download\fastdeploy-win-x64-gpu-x.x.x -DCUDA_DIRECTORY="C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v11.2"
+
+nuget restore
+msbuild infer_demo.sln /m:4 /p:Configuration=Release /p:Platform=x64
+```
+
+For more information about how to use FastDeploy SDK to compile a project with Visual Studio 2019. Please refer to
+- [Using the FastDeploy C++ SDK on Windows Platform](../../../../../docs/en/faq/use_sdk_on_windows.md)
+
+## 4. Execute compiled program
+fastdeploy.dll and related dynamic libraries are required by the program. FastDeploy provide a script to copy all required dll to your program path.
+
+```shell
+cd D:\Download\fastdeploy-win-x64-gpu-x.x.x
+
+fastdeploy_init.bat install %cd% D:\Download\fastdeploy-win-x64-gpu-x.x.x\examples\vision\classification\paddleclas\csharp\build\Release
+```
+Then you can run your program and test the model with image
+
+```shell
+cd Release
+# CPU inference
+./infer_demo ResNet50_vd_infer ILSVRC2012_val_00000010.jpeg 0
+# GPU inference
+./infer_demo ResNet50_vd_infer ILSVRC2012_val_00000010.jpeg 1
+```
+
+## PaddleClas C# Interface
+
+### Model Class
+
+```c#
+fastdeploy.vision.classification.PaddleClasModel(
+        string model_file,
+        string params_file,
+        string config_file
+        fastdeploy.RuntimeOption runtime_option = null,
+        fastdeploy.ModelFormat model_format = ModelFormat.PADDLE)
+```
+
+> PaddleClasModel initilization.
+
+> **Params**
+
+>> * **model_file**(str): Model file path
+>> * **params_file**(str): Parameter file path
+>> * **config_file**(str): Configuration file path, which is the deployment yaml file exported by PaddleClas
+>> * **runtime_option**(RuntimeOption): Backend inference configuration. null by default, which is the default configuration
+>> * **model_format**(ModelFormat): Model format. Paddle format by default
+
+#### Predict Function
+
+```c#
+fastdeploy.ClassifyResult Predict(OpenCvSharp.Mat im)
+```
+
+> Model prediction interface. Input images and output results directly.
+>
+> **Params**
+>
+>> * **im**(Mat): Input images in HWC or BGR format
+>
+> **Return**
+>
+>> * **result**(ClassifyResult): The classification result, including label_id, and the corresponding confidence. Refer to [Visual Model Prediction Results](../../../../../docs/api/vision_results/) for the description of ClassifyResult
+
+- [Model Description](../../)
+- [Python Deployment](../python)
+- [Vision Model prediction results](../../../../../docs/api/vision_results/)
+- [How to switch the model inference backend engine](../../../../../docs/en/faq/how_to_change_backend.md)
diff --git a/examples/vision/classification/paddleclas/csharp/README_CN.md b/examples/vision/classification/paddleclas/csharp/README_CN.md
new file mode 100644
index 000000000..a9373c440
--- /dev/null
+++ b/examples/vision/classification/paddleclas/csharp/README_CN.md
@@ -0,0 +1,101 @@
+[English](README.md) | 简体中文
+# PaddleClas C#部署示例
+
+本目录下提供`infer.cs`来调用C# API快速完成PaddleClas系列模型在CPU/GPU上部署的示例。
+
+在部署前，需确认以下两个步骤
+
+- 1. 软硬件环境满足要求，参考[FastDeploy环境要求](../../../../../docs/cn/build_and_install/download_prebuilt_libraries.md)  
+- 2. 根据开发环境，下载预编译部署库和samples代码，参考[FastDeploy预编译库](../../../../../docs/cn/build_and_install/download_prebuilt_libraries.md)
+
+以Linux上ResNet50_vd推理为例，在本目录执行如下命令即可完成编译测试，支持此模型需保证FastDeploy版本1.0.4以上(x.x.x>=1.0.4)
+
+## 1. 下载C#包管理程序nuget客户端
+> https://dist.nuget.org/win-x86-commandline/v6.4.0/nuget.exe
+
+下载完成后将该程序添加到环境变量**PATH**中
+
+## 2. 下载模型文件和测试图片
+> https://bj.bcebos.com/paddlehub/fastdeploy/ResNet50_vd_infer.tgz # (下载后解压缩)
+> https://gitee.com/paddlepaddle/PaddleClas/raw/release/2.4/deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg
+
+## 3. 编译示例代码
+
+本文档编译的示例代码可在解压的库中找到，编译工具依赖VS 2019的安装，**Windows打开x64 Native Tools Command Prompt for VS 2019命令工具**，通过如下命令开始编译
+
+```shell
+cd D:\Download\fastdeploy-win-x64-gpu-x.x.x\examples\vision\classification\paddleclas\csharp
+
+mkdir build && cd build
+cmake .. -G "Visual Studio 16 2019" -A x64 -DFASTDEPLOY_INSTALL_DIR=D:\Download\fastdeploy-win-x64-gpu-x.x.x -DCUDA_DIRECTORY="C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v11.2"
+
+nuget restore
+msbuild infer_demo.sln /m:4 /p:Configuration=Release /p:Platform=x64
+```
+
+关于使用Visual Studio 2019创建sln工程，或者CMake工程等方式编译的更详细信息，可参考如下文档
+- [在 Windows 使用 FastDeploy C++ SDK](../../../../../docs/cn/faq/use_sdk_on_windows.md)
+- [FastDeploy C++库在Windows上的多种使用方式](../../../../../docs/cn/faq/use_sdk_on_windows_build.md)
+
+## 4. 运行可执行程序
+
+注意Windows上运行时，需要将FastDeploy依赖的库拷贝至可执行程序所在目录, 或者配置环境变量。FastDeploy提供了工具帮助我们快速将所有依赖库拷贝至可执行程序所在目录,通过如下命令将所有依赖的dll文件拷贝至可执行程序所在的目录(可能生成的可执行文件在Release下还有一层目录，这里假设生成的可执行文件在Release处)
+```shell
+cd D:\Download\fastdeploy-win-x64-gpu-x.x.x
+
+fastdeploy_init.bat install %cd% D:\Download\fastdeploy-win-x64-gpu-x.x.x\examples\vision\classification\paddleclas\csharp\build\Release
+```
+
+将dll拷贝到当前路径后，准备好模型和图片，使用如下命令运行可执行程序即可
+```shell
+cd Release
+# CPU推理
+./infer_demo ResNet50_vd_infer ILSVRC2012_val_00000010.jpeg 0
+# GPU推理
+./infer_demo ResNet50_vd_infer ILSVRC2012_val_00000010.jpeg 1
+```
+
+## PaddleClas C#接口
+
+### 模型
+
+```c#
+fastdeploy.vision.classification.PaddleClasModel(
+        string model_file,
+        string params_file,
+        string config_file,
+        fastdeploy.RuntimeOption runtime_option = null,
+        fastdeploy.ModelFormat model_format = ModelFormat.PADDLE)
+```
+
+> PaddleClasModel模型加载和初始化。
+
+> **参数**
+
+>> * **model_file**(str): 模型文件路径
+>> * **params_file**(str): 参数文件路径
+>> * **config_file**(str): 配置文件路径，即PaddleClas导出的部署yaml文件
+>> * **runtime_option**(RuntimeOption): 后端推理配置，默认为null，即采用默认配置
+>> * **model_format**(ModelFormat): 模型格式，默认为PADDLE格式
+
+#### Predict函数
+
+```c#
+fastdeploy.ClassifyResult Predict(OpenCvSharp.Mat im)
+```
+
+> 模型预测接口，输入图像直接输出检测结果。
+>
+> **参数**
+>
+>> * **im**(Mat): 输入图像，注意需为HWC，BGR格式
+>>
+> **返回值**
+>
+>> * **result**: 分类结果，包括label_id，以及相应的置信度, ClassifyResult说明参考[视觉模型预测结果](../../../../../docs/api/vision_results/)
+
+
+- [模型介绍](../../)
+- [Python部署](../python)
+- [视觉模型预测结果](../../../../../docs/api/vision_results/)
+- [如何切换模型推理后端引擎](../../../../../docs/cn/faq/how_to_change_backend.md)
diff --git a/examples/vision/classification/paddleclas/csharp/infer.cs b/examples/vision/classification/paddleclas/csharp/infer.cs
new file mode 100644
index 000000000..b7dd5afeb
--- /dev/null
+++ b/examples/vision/classification/paddleclas/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 TestPaddleClas
+    {
+        public static void Main(string[] args)
+        {
+            if (args.Length < 3) {
+                Console.WriteLine(
+                    "Usage: infer_demo path/to/model_dir path/to/image run_option, " +
+                    "e.g ./infer_model ./ppyolo_dirname ./test.jpeg 0"
+                );
+                Console.WriteLine( "The data type of run_option is int, 0: run with cpu; 1: run with gpu");
+                return;
+            }
+            string model_dir = args[0];
+            string image_path = args[1];
+            string model_file = model_dir + "\\" + "inference.pdmodel";
+            string params_file = model_dir + "\\" + "inference.pdiparams";
+            string config_file = model_dir + "\\" + "inference_cls.yaml";
+            RuntimeOption runtimeoption = new RuntimeOption();
+            int device_option = Int32.Parse(args[2]);
+            if(device_option==0){
+                runtimeoption.UseCpu();
+            }else{
+                runtimeoption.UseGpu();
+            }
+            fastdeploy.vision.classification.PaddleClasModel model = new fastdeploy.vision.classification.PaddleClasModel(model_file, params_file, config_file, runtimeoption, ModelFormat.PADDLE);
+            if(!model.Initialized()){
+                Console.WriteLine("Failed to initialize.\n");
+            }
+            Mat image = Cv2.ImRead(image_path);
+            fastdeploy.vision.ClassifyResult res = model.Predict(image);
+            Console.WriteLine(res.ToString());
+
+        }
+
+    }
+}
\ No newline at end of file
diff --git a/examples/vision/detection/paddledetection/c/README.md b/examples/vision/detection/paddledetection/c/README.md
index 79a33e51a..9ab7110b3 100644
--- a/examples/vision/detection/paddledetection/c/README.md
+++ b/examples/vision/detection/paddledetection/c/README.md
@@ -78,7 +78,7 @@ void FD_C_RuntimeOptionWrapperUseGpu(
 
 ```c
 
-FD_C_PPYOLOEWrapper* FD_C_CreatesPPYOLOEWrapper(
+FD_C_PPYOLOEWrapper* FD_C_CreatePPYOLOEWrapper(
     const char* model_file, const char* params_file, const char* config_file,
     FD_C_RuntimeOptionWrapper* runtime_option,
     const FD_C_ModelFormat model_format)
@@ -137,7 +137,7 @@ FD_C_Bool FD_C_Imwrite(const char* savepath,  FD_C_Mat img);
 ```c
 FD_C_Bool FD_C_PPYOLOEWrapperPredict(
     __fd_take FD_C_PPYOLOEWrapper* fd_c_ppyoloe_wrapper, FD_C_Mat img,
-    FD_C_DetectionResultWrapper* fd_c_detection_result_wrapper)
+    FD_C_DetectionResult* fd_c_detection_result)
 ```
 >
 > Predict an image, and generate detection result.
@@ -145,37 +145,11 @@ FD_C_Bool FD_C_PPYOLOEWrapperPredict(
 > **Params**
 > * **fd_c_ppyoloe_wrapper**(FD_C_PPYOLOEWrapper*): pointer to manipulate PPYOLOE object
 > * **img**（FD_C_Mat）: pointer to cv::Mat object, which can be obained by FD_C_Imread interface
-> * **result**（FD_C_DetectionResultWrapper*): Detection result, including detection box and confidence of each box. Refer to [Vision Model Prediction Result](../../../../../docs/api/vision_results/) for DetectionResult
+> * **fd_c_detection_result**FD_C_DetectionResult*): Detection result, including detection box and confidence of each box. Refer to [Vision Model Prediction Result](../../../../../docs/api/vision_results/) for DetectionResult
 
 
 #### Result
 
-```c
-FD_C_DetectionResultWrapper* FD_C_CreateDetectionResultWrapper();
-```
->
-> Create a DetectionResult object to keep the detection result，return a pointer to manipulate it.
->
-> **Return**
-> * **fd_c_detection_result_wrapper**(FD_C_DetectionResultWrapper*): pointer to manipulate DetectionResult object
-
-
-
-```c
-FD_C_DetectionResult* FD_C_DetectionResultWrapperGetData(
-     FD_C_DetectionResultWrapper* fd_c_detection_result_wrapper)
-```
->
-> Get the C DetectionResult structure from FD_C_DetectionResultWrapper, which can access the fileds directly.
->
-> **Params**
-> * **fd_c_detection_result_wrapper**(FD_C_DetectionResultWrapper*): pointer to manipulate DetectionResult object
->
-> **Return**
-> * **fd_c_detection_result**(FD_C_DetectionResult*): pointer to C DetectionResult structure
-
-
-
 ```c
 FD_C_Mat FD_C_VisDetection(FD_C_Mat im, FD_C_DetectionResult* fd_detection_result,
                   float score_threshold, int line_size, float font_size);
diff --git a/examples/vision/detection/paddledetection/c/README_CN.md b/examples/vision/detection/paddledetection/c/README_CN.md
index 22cbd311c..fecad1d6a 100644
--- a/examples/vision/detection/paddledetection/c/README_CN.md
+++ b/examples/vision/detection/paddledetection/c/README_CN.md
@@ -82,7 +82,7 @@ void FD_C_RuntimeOptionWrapperUseGpu(
 
 ```c
 
-FD_C_PPYOLOEWrapper* FD_C_CreatesPPYOLOEWrapper(
+FD_C_PPYOLOEWrapper* FD_C_CreatePPYOLOEWrapper(
     const char* model_file, const char* params_file, const char* config_file,
     FD_C_RuntimeOptionWrapper* runtime_option,
     const FD_C_ModelFormat model_format)
@@ -141,7 +141,7 @@ FD_C_Bool FD_C_Imwrite(const char* savepath,  FD_C_Mat img);
 ```c
 FD_C_Bool FD_C_PPYOLOEWrapperPredict(
     __fd_take FD_C_PPYOLOEWrapper* fd_c_ppyoloe_wrapper, FD_C_Mat img,
-    FD_C_DetectionResultWrapper* fd_c_detection_result_wrapper)
+    FD_C_DetectionResult* fd_c_detection_result)
 ```
 >
 > 模型预测接口，输入图像直接并生成检测结果。
@@ -149,37 +149,11 @@ FD_C_Bool FD_C_PPYOLOEWrapperPredict(
 > **参数**
 > * **fd_c_ppyoloe_wrapper**(FD_C_PPYOLOEWrapper*): 指向PPYOLOE模型的指针
 > * **img**（FD_C_Mat）: 输入图像的指针，指向cv::Mat对象，可以调用FD_C_Imread读取图像获取
-> * **result**（FD_C_DetectionResultWrapper*): 指向检测结果的指针，检测结果包括检测框，各个框的置信度, DetectionResult说明参考[视觉模型预测结果](../../../../../docs/api/vision_results/)
+> * **fd_c_detection_result**FD_C_DetectionResult*): 指向检测结果的指针，检测结果包括检测框，各个框的置信度, DetectionResult说明参考[视觉模型预测结果](../../../../../docs/api/vision_results/)
 
 
 #### Predict结果
 
-```c
-FD_C_DetectionResultWrapper* FD_C_CreateDetectionResultWrapper();
-```
->
-> 创建一个DetectionResult对象，用来保存推理的结果，并返回所创建的DetectionResult对象的指针。
->
-> **返回**
-> * **fd_c_detection_result_wrapper**(FD_C_DetectionResultWrapper*): 指向DetectionResult对象的指针
-
-
-
-```c
-FD_C_DetectionResult* FD_C_DetectionResultWrapperGetData(
-     FD_C_DetectionResultWrapper* fd_c_detection_result_wrapper)
-```
->
-> 从DetectionResult对象中提取纯C结构的DetectionResult结果，并返回结构指针，通过该指针可直接返回结构中的字段。
->
-> **参数**
-> * **fd_c_detection_result_wrapper**(FD_C_DetectionResultWrapper*): 指向DetectionResult对象的指针
->
-> **返回**
-> * **fd_c_detection_result**(FD_C_DetectionResult*): 指向纯C结构的DetectionResult的指针
-
-
-
 ```c
 FD_C_Mat FD_C_VisDetection(FD_C_Mat im, FD_C_DetectionResult* fd_detection_result,
                   float score_threshold, int line_size, float font_size);
@@ -189,7 +163,7 @@ FD_C_Mat FD_C_VisDetection(FD_C_Mat im, FD_C_DetectionResult* fd_detection_resul
 >
 > **参数**
 > * **im**(FD_C_Mat): 指向输入图像的指针
-> * **fd_detection_result**(FD_C_DetectionResult*): 指向纯C结构DetectionResult的指针
+> * **fd_detection_result**(FD_C_DetectionResult*): 指向FD_C_DetectionResult结构的指针
 > * **score_threshold**(float): 检测阈值
 > * **line_size**(int): 检测框线大小
 > * **font_size**(float): 检测框字体大小
diff --git a/examples/vision/detection/paddledetection/c/infer_ppyoloe.c b/examples/vision/detection/paddledetection/c/infer_ppyoloe.c
index 6b9cc4369..4db5f7549 100644
--- a/examples/vision/detection/paddledetection/c/infer_ppyoloe.c
+++ b/examples/vision/detection/paddledetection/c/infer_ppyoloe.c
@@ -35,21 +35,30 @@ void CpuInfer(const char* model_dir, const char* image_file) {
   FD_C_RuntimeOptionWrapper* option = FD_C_CreateRuntimeOptionWrapper();
   FD_C_RuntimeOptionWrapperUseCpu(option);
 
-  FD_C_PPYOLOEWrapper* model = FD_C_CreatesPPYOLOEWrapper(
+  FD_C_PPYOLOEWrapper* model = FD_C_CreatePPYOLOEWrapper(
       model_file, params_file, config_file, option, PADDLE);
 
-  FD_C_Mat im = FD_C_Imread(image_file);
-
-  FD_C_DetectionResultWrapper* result_wrapper =
-      FD_C_CreateDetectionResultWrapper();
-
-  if (!FD_C_PPYOLOEWrapperPredict(model, im, result_wrapper)) {
-    printf("Failed to predict.\n");
+  if (!FD_C_PPYOLOEWrapperInitialized(model)) {
+    printf("Failed to initialize.\n");
+    FD_C_DestroyRuntimeOptionWrapper(option);
+    FD_C_DestroyPaddleClasModelWrapper(model);
     return;
   }
 
+  FD_C_Mat im = FD_C_Imread(image_file);
+
   FD_C_DetectionResult* result =
-      FD_C_DetectionResultWrapperGetData(result_wrapper);
+      (FD_C_DetectionResult*)malloc(sizeof(FD_C_DetectionResult));
+
+  if (!FD_C_PPYOLOEWrapperPredict(model, im, result)) {
+    printf("Failed to predict.\n");
+    FD_C_DestroyRuntimeOptionWrapper(option);
+    FD_C_DestroyPaddleClasModelWrapper(model);
+    FD_C_DestroyMat(im);
+    free(result);
+    return;
+  }
+
   FD_C_Mat vis_im = FD_C_VisDetection(im, result, 0.5, 1, 0.5);
 
   FD_C_Imwrite("vis_result.jpg", vis_im);
@@ -57,7 +66,6 @@ void CpuInfer(const char* model_dir, const char* image_file) {
 
   FD_C_DestroyRuntimeOptionWrapper(option);
   FD_C_DestroyPPYOLOEWrapper(model);
-  FD_C_DestroyDetectionResultWrapper(result_wrapper);
   FD_C_DestroyDetectionResult(result);
   FD_C_DestroyMat(im);
   FD_C_DestroyMat(vis_im);
@@ -75,21 +83,30 @@ void GpuInfer(const char* model_dir, const char* image_file) {
   FD_C_RuntimeOptionWrapper* option = FD_C_CreateRuntimeOptionWrapper();
   FD_C_RuntimeOptionWrapperUseGpu(option, 0);
 
-  FD_C_PPYOLOEWrapper* model = FD_C_CreatesPPYOLOEWrapper(
+  FD_C_PPYOLOEWrapper* model = FD_C_CreatePPYOLOEWrapper(
       model_file, params_file, config_file, option, PADDLE);
 
-  FD_C_Mat im = FD_C_Imread(image_file);
-
-  FD_C_DetectionResultWrapper* result_wrapper =
-      FD_C_CreateDetectionResultWrapper();
-
-  if (!FD_C_PPYOLOEWrapperPredict(model, im, result_wrapper)) {
-    printf("Failed to predict.\n");
+  if (!FD_C_PPYOLOEWrapperInitialized(model)) {
+    printf("Failed to initialize.\n");
+    FD_C_DestroyRuntimeOptionWrapper(option);
+    FD_C_DestroyPaddleClasModelWrapper(model);
     return;
   }
 
+  FD_C_Mat im = FD_C_Imread(image_file);
+
   FD_C_DetectionResult* result =
-      FD_C_DetectionResultWrapperGetData(result_wrapper);
+      (FD_C_DetectionResult*)malloc(sizeof(FD_C_DetectionResult));
+
+  if (!FD_C_PPYOLOEWrapperPredict(model, im, result)) {
+    printf("Failed to predict.\n");
+    FD_C_DestroyRuntimeOptionWrapper(option);
+    FD_C_DestroyPaddleClasModelWrapper(model);
+    FD_C_DestroyMat(im);
+    free(result);
+    return;
+  }
+
   FD_C_Mat vis_im = FD_C_VisDetection(im, result, 0.5, 1, 0.5);
 
   FD_C_Imwrite("vis_result.jpg", vis_im);
@@ -97,7 +114,6 @@ void GpuInfer(const char* model_dir, const char* image_file) {
 
   FD_C_DestroyRuntimeOptionWrapper(option);
   FD_C_DestroyPPYOLOEWrapper(model);
-  FD_C_DestroyDetectionResultWrapper(result_wrapper);
   FD_C_DestroyDetectionResult(result);
   FD_C_DestroyMat(im);
   FD_C_DestroyMat(vis_im);
diff --git a/examples/vision/detection/paddledetection/csharp/README_CN.md b/examples/vision/detection/paddledetection/csharp/README_CN.md
index 36b300448..632f2eba4 100644
--- a/examples/vision/detection/paddledetection/csharp/README_CN.md
+++ b/examples/vision/detection/paddledetection/csharp/README_CN.md
@@ -39,7 +39,7 @@ msbuild infer_demo.sln /m:4 /p:Configuration=Release /p:Platform=x64
 
 ## 4. 运行可执行程序
 
-注意Windows上运行时，需要将FastDeploy依赖的库拷贝至可执行程序所在目录, 或者配置环境变量。FastDeploy提供了工具帮助我们快速将所有依赖库拷贝至可执行程序所在目录,通过如下命令将所有依赖的dll文件拷贝至可执行程序所在的目录
+注意Windows上运行时，需要将FastDeploy依赖的库拷贝至可执行程序所在目录, 或者配置环境变量。FastDeploy提供了工具帮助我们快速将所有依赖库拷贝至可执行程序所在目录,通过如下命令将所有依赖的dll文件拷贝至可执行程序所在的目录(可能生成的可执行文件在Release下还有一层目录，这里假设生成的可执行文件在Release处)
 ```shell
 cd D:\Download\fastdeploy-win-x64-gpu-x.x.x
 
diff --git a/examples/vision/detection/paddledetection/csharp/infer_ppyoloe.cs b/examples/vision/detection/paddledetection/csharp/infer_ppyoloe.cs
index c64e4c6af..41ed355da 100644
--- a/examples/vision/detection/paddledetection/csharp/infer_ppyoloe.cs
+++ b/examples/vision/detection/paddledetection/csharp/infer_ppyoloe.cs
@@ -44,13 +44,16 @@ namespace Test
             }else{
                 runtimeoption.UseGpu();
             }
-            vision.detection.PPYOLOE model = new vision.detection.PPYOLOE(model_file, params_file, config_file, runtimeoption, ModelFormat.PADDLE);
+            fastdeploy.vision.detection.PPYOLOE model = new fastdeploy.vision.detection.PPYOLOE(model_file, params_file, config_file, runtimeoption, ModelFormat.PADDLE);
+            if(!model.Initialized()){
+                Console.WriteLine("Failed to initialize.\n");
+            }
             Mat image = Cv2.ImRead(image_path);
-            vision.DetectionResult res = model.Predict(image);
-            Mat res_img = vision.Visualize.VisDetection(image, res, 0, 1, 0.5f);
+            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);
-
         }
 
     }