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[Doc] add doxygen docs for c sharp api (#1495)

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add doxygen docs for c sharp api

Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com>
This commit is contained in:
chenjian
2023-04-09 12:32:22 +08:00
committed by GitHub
parent ed19c759df
commit fc15124800
11 changed files with 3201 additions and 36 deletions
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66
csharp/fastdeploy/vision/detection/contrib/model.cs
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@@ -24,6 +24,9 @@ namespace vision {
namespace detection {
// YOLOv5
/*! @brief YOLOv5 model
*/
public class YOLOv5 {
public YOLOv5( string model_file, string params_file,
@@ -39,6 +42,12 @@ public class YOLOv5 {
~YOLOv5() { FD_C_DestroyYOLOv5Wrapper(fd_yolov5_wrapper); }
/** \brief Predict the detection result for an input image
* \param[in] im The input image data, comes from cv::imread(), is a 3-D array with layout HWC, BGR format
*
* \return DetectionResult
*/
public DetectionResult Predict(Mat img) {
FD_DetectionResult fd_detection_result = new FD_DetectionResult();
if(! FD_C_YOLOv5WrapperPredict(fd_yolov5_wrapper, img.CvPtr,
@@ -53,6 +62,12 @@ public class YOLOv5 {
return detection_result;
}
/** \brief Predict the detection result for an input image list
* \param[in] im The input image list, all the elements come from cv::imread(), is a 3-D array with layout HWC, BGR format
*
* \return List<DetectionResult>
*/
public List<DetectionResult> BatchPredict(List<Mat> imgs){
FD_OneDimMat imgs_in = new FD_OneDimMat();
imgs_in.size = (nuint)imgs.Count;
@@ -80,6 +95,8 @@ public class YOLOv5 {
return results_out;
}
/// Check whether model is initialized successfully
public bool Initialized() {
return FD_C_YOLOv5WrapperInitialized(fd_yolov5_wrapper);
}
@@ -123,6 +140,9 @@ public class YOLOv5 {
// YOLOv7
/*! @brief YOLOv7 model
*/
public class YOLOv7 {
public YOLOv7( string model_file, string params_file,
@@ -138,6 +158,12 @@ public class YOLOv7 {
~YOLOv7() { FD_C_DestroyYOLOv7Wrapper(fd_yolov7_wrapper); }
/** \brief Predict the detection result for an input image
* \param[in] im The input image data, comes from cv::imread(), is a 3-D array with layout HWC, BGR format
*
* \return DetectionResult
*/
public DetectionResult Predict(Mat img) {
FD_DetectionResult fd_detection_result = new FD_DetectionResult();
if(! FD_C_YOLOv7WrapperPredict(fd_yolov7_wrapper, img.CvPtr,
@@ -152,6 +178,12 @@ public class YOLOv7 {
return detection_result;
}
/** \brief Predict the detection result for an input image list
* \param[in] im The input image list, all the elements come from cv::imread(), is a 3-D array with layout HWC, BGR format
*
* \return List<DetectionResult>
*/
public List<DetectionResult> BatchPredict(List<Mat> imgs){
FD_OneDimMat imgs_in = new FD_OneDimMat();
imgs_in.size = (nuint)imgs.Count;
@@ -179,6 +211,8 @@ public class YOLOv7 {
return results_out;
}
/// Check whether model is initialized successfully
public bool Initialized() {
return FD_C_YOLOv7WrapperInitialized(fd_yolov7_wrapper);
}
@@ -221,6 +255,9 @@ public class YOLOv7 {
// YOLOv8
/*! @brief YOLOv8 model
*/
public class YOLOv8 {
public YOLOv8( string model_file, string params_file,
@@ -236,6 +273,12 @@ public class YOLOv8 {
~YOLOv8() { FD_C_DestroyYOLOv8Wrapper(fd_yolov8_wrapper); }
/** \brief Predict the detection result for an input image
* \param[in] im The input image data, comes from cv::imread(), is a 3-D array with layout HWC, BGR format
*
* \return DetectionResult
*/
public DetectionResult Predict(Mat img) {
FD_DetectionResult fd_detection_result = new FD_DetectionResult();
if(! FD_C_YOLOv8WrapperPredict(fd_yolov8_wrapper, img.CvPtr,
@@ -250,6 +293,12 @@ public class YOLOv8 {
return detection_result;
}
/** \brief Predict the detection result for an input image list
* \param[in] im The input image list, all the elements come from cv::imread(), is a 3-D array with layout HWC, BGR format
*
* \return List<DetectionResult>
*/
public List<DetectionResult> BatchPredict(List<Mat> imgs){
FD_OneDimMat imgs_in = new FD_OneDimMat();
imgs_in.size = (nuint)imgs.Count;
@@ -277,6 +326,8 @@ public class YOLOv8 {
return results_out;
}
/// Check whether model is initialized successfully
public bool Initialized() {
return FD_C_YOLOv8WrapperInitialized(fd_yolov8_wrapper);
}
@@ -321,6 +372,9 @@ public class YOLOv8 {
// YOLOv6
/*! @brief YOLOv6 model
*/
public class YOLOv6 {
public YOLOv6( string model_file, string params_file,
@@ -352,6 +406,8 @@ public class YOLOv6 {
return detection_result;
}
/// Check whether model is initialized successfully
public bool Initialized() {
return FD_C_YOLOv6WrapperInitialized(fd_yolov6_wrapper);
}
@@ -390,6 +446,9 @@ public class YOLOv6 {
// YOLOR
/*! @brief YOLOR model
*/
public class YOLOR {
public YOLOR( string model_file, string params_file,
@@ -421,6 +480,8 @@ public class YOLOR {
return detection_result;
}
/// Check whether model is initialized successfully
public bool Initialized() {
return FD_C_YOLORWrapperInitialized(fd_yolor_wrapper);
}
@@ -460,6 +521,9 @@ public class YOLOR {
// YOLOX
/*! @brief YOLOX model
*/
public class YOLOX {
public YOLOX( string model_file, string params_file,
@@ -491,6 +555,8 @@ public class YOLOX {
return detection_result;
}
/// Check whether model is initialized successfully
public bool Initialized() {
return FD_C_YOLOXWrapperInitialized(fd_yolox_wrapper);
}