[C API] Supplement C api for models (#1317)

* add batch_predict and initialized api for c

* add batch_predict and result str in C api

* modify visualization function

* add micro to add models batchify

* refactor and add models for ppdet others

* add base define

* fix

* refine predict api
This commit is contained in:
chenjian
2023-02-17 11:03:12 +08:00
committed by GitHub
parent c38b7d4377
commit db9739a76e
12 changed files with 1942 additions and 98 deletions

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@@ -67,6 +67,11 @@ typedef struct FD_C_TwoDimArrayFloat {
typedef void* FD_C_Mat;
typedef struct FD_C_OneDimMat {
size_t size;
FD_C_Mat* data;
} FD_C_OneDimMat;
#ifdef __cplusplus
extern "C" {
#endif

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@@ -18,38 +18,108 @@ namespace fastdeploy {
#ifdef ENABLE_VISION
std::unique_ptr<fastdeploy::vision::classification::PaddleClasModel>&
FD_C_CheckAndConvertPaddleClasModelWrapper(
FD_C_PaddleClasModelWrapper* fd_c_paddleclas_model_wrapper) {
FDASSERT(
fd_c_paddleclas_model_wrapper != nullptr,
"The pointer of fd_c_paddleclas_model_wrapper shouldn't be nullptr.");
return fd_c_paddleclas_model_wrapper->paddleclas_model;
}
// results:
std::unique_ptr<fastdeploy::vision::detection::PPYOLOE>&
FD_C_CheckAndConvertPPYOLOEWrapper(FD_C_PPYOLOEWrapper* fd_c_ppyoloe_wrapper) {
FDASSERT(fd_c_ppyoloe_wrapper != nullptr,
"The pointer of fd_c_ppyoloe_wrapper shouldn't be nullptr.");
return fd_c_ppyoloe_wrapper->ppyoloe_model;
}
// ClassifyResult
DECL_AND_IMPLEMENT_RESULT_FUNC_FOR_GET_PTR_FROM_WRAPPER(
ClassifyResult, fd_classify_result_wrapper, classify_result)
// DetectionResult
DECL_AND_IMPLEMENT_RESULT_FUNC_FOR_GET_PTR_FROM_WRAPPER(
DetectionResult, fd_detection_result_wrapper, detection_result)
std::unique_ptr<fastdeploy::vision::ClassifyResult>&
FD_C_CheckAndConvertClassifyResultWrapper(
FD_C_ClassifyResultWrapper* fd_c_classify_result_wrapper) {
FDASSERT(fd_c_classify_result_wrapper != nullptr,
"The pointer of fd_c_classify_result_wrapper shouldn't be nullptr.");
return fd_c_classify_result_wrapper->classify_result;
}
// Models:
// Classification
// PaddleClasModel
DECL_AND_IMPLEMENT_CLASSIFICATION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(
PaddleClasModel, fd_paddleclas_model_wrapper, paddleclas_model)
// detection models:
// PPYOLOE
DECL_AND_IMPLEMENT_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(
PPYOLOE, fd_ppyoloe_wrapper, ppyoloe_model)
// PicoDet
DECL_AND_IMPLEMENT_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(
PicoDet, fd_picodet_wrapper, picodet_model)
// PPYOLO
DECL_AND_IMPLEMENT_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(
PPYOLO, fd_ppyolo_wrapper, ppyolo_model)
// YOLOv3
DECL_AND_IMPLEMENT_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(
YOLOv3, fd_yolov3_wrapper, yolov3_model)
// PaddleYOLOX
DECL_AND_IMPLEMENT_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(
PaddleYOLOX, fd_paddleyolox_wrapper, paddleyolox_model)
// FasterRCNN
DECL_AND_IMPLEMENT_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(
FasterRCNN, fd_fasterrcnn_wrapper, fasterrcnn_model)
// MaskRCNN
DECL_AND_IMPLEMENT_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(
MaskRCNN, fd_maskrcnn_wrapper, maskrcnn_model)
// SSD
DECL_AND_IMPLEMENT_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(SSD,
fd_ssd_wrapper,
ssd_model)
// PaddleYOLOv5
DECL_AND_IMPLEMENT_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(
PaddleYOLOv5, fd_paddleyolov5_wrapper, paddleyolov5_model)
// PaddleYOLOv6
DECL_AND_IMPLEMENT_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(
PaddleYOLOv6, fd_paddleyolov6_wrapper, paddleyolov6_model)
// PaddleYOLOv7
DECL_AND_IMPLEMENT_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(
PaddleYOLOv7, fd_paddleyolov7_wrapper, paddleyolov7_model)
// PaddleYOLOv8
DECL_AND_IMPLEMENT_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(
PaddleYOLOv8, fd_paddleyolov8_wrapper, paddleyolov8_model)
// RTMDet
DECL_AND_IMPLEMENT_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(
RTMDet, fd_rtmdet_wrapper, rtmdet_model)
// CascadeRCNN
DECL_AND_IMPLEMENT_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(
CascadeRCNN, fd_cascadercnn_wrapper, cascadercnn_model)
// PSSDet
DECL_AND_IMPLEMENT_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(
PSSDet, fd_pssdet_wrapper, pssdet_model)
// RetinaNet
DECL_AND_IMPLEMENT_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(
RetinaNet, fd_retinanet_wrapper, retinanet_model)
// FCOS
DECL_AND_IMPLEMENT_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(
FCOS, fd_fcos_wrapper, fcos_model)
// TTFNet
DECL_AND_IMPLEMENT_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(
TTFNet, fd_ttfnet_wrapper, ttfnet_model)
// TOOD
DECL_AND_IMPLEMENT_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(
TOOD, fd_tood_wrapper, tood_model)
// GFL
DECL_AND_IMPLEMENT_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(GFL,
fd_gfl_wrapper,
gfl_model)
std::unique_ptr<fastdeploy::vision::DetectionResult>&
FD_C_CheckAndConvertDetectionResultWrapper(
FD_C_DetectionResultWrapper* fd_c_detection_result_wrapper) {
FDASSERT(
fd_c_detection_result_wrapper != nullptr,
"The pointer of fd_c_detection_result_wrapper shouldn't be nullptr.");
return fd_c_detection_result_wrapper->detection_result;
}
#endif
std::unique_ptr<fastdeploy::RuntimeOption>&

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@@ -23,39 +23,246 @@
#include "fastdeploy/vision/common/result.h"
#include "fastdeploy/vision/detection/ppdet/model.h"
typedef struct FD_C_ClassifyResultWrapper {
std::unique_ptr<fastdeploy::vision::ClassifyResult> classify_result;
} FD_C_ClassifyResultWrapper;
#define DEFINE_RESULT_WRAPPER_STRUCT(typename, varname) typedef struct FD_C_##typename##Wrapper { \
std::unique_ptr<fastdeploy::vision::typename> varname; \
} FD_C_##typename##Wrapper
typedef struct FD_C_DetectionResultWrapper {
std::unique_ptr<fastdeploy::vision::DetectionResult> detection_result;
} FD_C_DetectionResultWrapper;
#define DEFINE_CLASSIFICATION_MODEL_WRAPPER_STRUCT(typename, varname) typedef struct FD_C_##typename##Wrapper { \
std::unique_ptr<fastdeploy::vision::classification::typename> \
varname; \
} FD_C_##typename##Wrapper
typedef struct FD_C_PaddleClasModelWrapper {
std::unique_ptr<fastdeploy::vision::classification::PaddleClasModel>
paddleclas_model;
} FD_C_PaddleClasModelWrapper;
#define DEFINE_DETECTION_MODEL_WRAPPER_STRUCT(typename, varname) typedef struct FD_C_##typename##Wrapper { \
std::unique_ptr<fastdeploy::vision::detection::typename> varname; \
} FD_C_##typename##Wrapper
typedef struct FD_C_PPYOLOEWrapper {
std::unique_ptr<fastdeploy::vision::detection::PPYOLOE> ppyoloe_model;
} FD_C_PPYOLOEWrapper;
// ------------- belows are wrapper struct define --------------------- //
// Results:
// ClassifyResult
DEFINE_RESULT_WRAPPER_STRUCT(ClassifyResult, classify_result);
// DetectionResult
DEFINE_RESULT_WRAPPER_STRUCT(DetectionResult, detection_result);
// Models:
// Classification
// PaddleClasModel
DEFINE_CLASSIFICATION_MODEL_WRAPPER_STRUCT(PaddleClasModel, paddleclas_model);
// Detection
// PPYOLOE
DEFINE_DETECTION_MODEL_WRAPPER_STRUCT(PPYOLOE, ppyoloe_model);
// PicoDet
DEFINE_DETECTION_MODEL_WRAPPER_STRUCT(PicoDet, picodet_model);
// PPYOLO
DEFINE_DETECTION_MODEL_WRAPPER_STRUCT(PPYOLO, ppyolo_model);
// YOLOv3
DEFINE_DETECTION_MODEL_WRAPPER_STRUCT(YOLOv3, yolov3_model);
// PaddleYOLOX
DEFINE_DETECTION_MODEL_WRAPPER_STRUCT(PaddleYOLOX, paddleyolox_model);
// FasterRCNN
DEFINE_DETECTION_MODEL_WRAPPER_STRUCT(FasterRCNN, fasterrcnn_model);
// MaskRCNN
DEFINE_DETECTION_MODEL_WRAPPER_STRUCT(MaskRCNN, maskrcnn_model);
// SSD
DEFINE_DETECTION_MODEL_WRAPPER_STRUCT(SSD, ssd_model);
// PaddleYOLOv5
DEFINE_DETECTION_MODEL_WRAPPER_STRUCT(PaddleYOLOv5, paddleyolov5_model);
// PaddleYOLOv6
DEFINE_DETECTION_MODEL_WRAPPER_STRUCT(PaddleYOLOv6, paddleyolov6_model);
// PaddleYOLOv7
DEFINE_DETECTION_MODEL_WRAPPER_STRUCT(PaddleYOLOv7, paddleyolov7_model);
// PaddleYOLOv8
DEFINE_DETECTION_MODEL_WRAPPER_STRUCT(PaddleYOLOv8, paddleyolov8_model);
// RTMDet
DEFINE_DETECTION_MODEL_WRAPPER_STRUCT(RTMDet, rtmdet_model);
// CascadeRCNN
DEFINE_DETECTION_MODEL_WRAPPER_STRUCT(CascadeRCNN, cascadercnn_model);
// PSSDet
DEFINE_DETECTION_MODEL_WRAPPER_STRUCT(PSSDet, pssdet_model);
// RetinaNet
DEFINE_DETECTION_MODEL_WRAPPER_STRUCT(RetinaNet, retinanet_model);
// FCOS
DEFINE_DETECTION_MODEL_WRAPPER_STRUCT(FCOS, fcos_model);
// TTFNet
DEFINE_DETECTION_MODEL_WRAPPER_STRUCT(TTFNet, ttfnet_model);
// TOOD
DEFINE_DETECTION_MODEL_WRAPPER_STRUCT(TOOD, tood_model);
// GFL
DEFINE_DETECTION_MODEL_WRAPPER_STRUCT(GFL, gfl_model);
// ------------- belows are function declaration for get ptr from wrapper --------------------- //
#define DECLARE_RESULT_FUNC_FOR_GET_PTR_FROM_WRAPPER(typename, varname) std::unique_ptr<fastdeploy::vision::typename>& \
FD_C_CheckAndConvert##typename##Wrapper( \
FD_C_##typename##Wrapper* varname)
#define DECLARE_CLASSIFICATION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(typename, varname) std::unique_ptr<fastdeploy::vision::classification::typename>& \
FD_C_CheckAndConvert##typename##Wrapper( \
FD_C_##typename##Wrapper* varname)
#define DECLARE_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(typename, varname) std::unique_ptr<fastdeploy::vision::detection::typename>& \
FD_C_CheckAndConvert##typename##Wrapper( \
FD_C_##typename##Wrapper* varname)
namespace fastdeploy {
std::unique_ptr<fastdeploy::vision::ClassifyResult>&
FD_C_CheckAndConvertClassifyResultWrapper(
FD_C_ClassifyResultWrapper* fd_classify_result_wrapper);
std::unique_ptr<fastdeploy::vision::DetectionResult>&
FD_C_CheckAndConvertDetectionResultWrapper(
FD_C_DetectionResultWrapper* fd_detection_result_wrapper);
std::unique_ptr<fastdeploy::vision::classification::PaddleClasModel>&
FD_C_CheckAndConvertPaddleClasModelWrapper(
FD_C_PaddleClasModelWrapper* fd_paddleclas_model_wrapper);
std::unique_ptr<fastdeploy::vision::detection::PPYOLOE>&
FD_C_CheckAndConvertPPYOLOEWrapper(FD_C_PPYOLOEWrapper* fd_ppyoloe_wrapper);
// results:
// ClassifyResult
DECLARE_RESULT_FUNC_FOR_GET_PTR_FROM_WRAPPER(ClassifyResult,
fd_classify_result_wrapper);
// DetectionResult
DECLARE_RESULT_FUNC_FOR_GET_PTR_FROM_WRAPPER(DetectionResult,
fd_detection_result_wrapper);
// Models:
// Classification
// PaddleClasModel
DECLARE_CLASSIFICATION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(
PaddleClasModel, fd_paddleclas_model_wrapper);
// detection models:
// PPYOLOE
DECLARE_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(PPYOLOE,
fd_ppyoloe_wrapper);
// PicoDet
DECLARE_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(PicoDet,
fd_picodet_wrapper);
// PPYOLO
DECLARE_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(PPYOLO,
fd_ppyolo_wrapper);
// YOLOv3
DECLARE_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(YOLOv3,
fd_yolov3_wrapper);
// PaddleYOLOX
DECLARE_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(PaddleYOLOX,
fd_paddleyolox_wrapper);
// FasterRCNN
DECLARE_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(FasterRCNN,
fd_fasterrcnn_wrapper);
// MaskRCNN
DECLARE_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(MaskRCNN,
fd_maskrcnn_wrapper);
// SSD
DECLARE_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(SSD,
fd_ssd_wrapper);
// PaddleYOLOv5
DECLARE_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(PaddleYOLOv5,
fd_paddleyolov5_wrapper);
// PaddleYOLOv6
DECLARE_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(PaddleYOLOv6,
fd_paddleyolov6_wrapper);
// PaddleYOLOv7
DECLARE_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(PaddleYOLOv7,
fd_paddleyolov7_wrapper);
// PaddleYOLOv8
DECLARE_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(PaddleYOLOv8,
fd_paddleyolov8_wrapper);
// RTMDet
DECLARE_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(RTMDet,
fd_rtmdet_wrapper);
// CascadeRCNN
DECLARE_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(CascadeRCNN,
fd_cascadercnn_wrapper);
// PSSDet
DECLARE_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(PSSDet,
fd_pssdet_wrapper);
// RetinaNet
DECLARE_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(RetinaNet,
fd_retinanet_wrapper);
// FCOS
DECLARE_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(FCOS,
fd_fcos_wrapper);
// TTFNet
DECLARE_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(TTFNet,
fd_ttfnet_wrapper);
// TOOD
DECLARE_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(TOOD,
fd_tood_wrapper);
// GFL
DECLARE_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(GFL,
fd_gfl_wrapper);
} // namespace fastdeploy
#endif
typedef struct FD_C_RuntimeOptionWrapper {
std::unique_ptr<fastdeploy::RuntimeOption> runtime_option;
} FD_C_RuntimeOptionWrapper;
@@ -68,3 +275,27 @@ FD_C_CheckAndConvertRuntimeOptionWrapper(
#define CHECK_AND_CONVERT_FD_TYPE(TYPENAME, variable_name) \
fastdeploy::FD_C_CheckAndConvert##TYPENAME(variable_name)
#define DECL_AND_IMPLEMENT_RESULT_FUNC_FOR_GET_PTR_FROM_WRAPPER(typename, var_wrapper_name, var_ptr_name) std::unique_ptr<fastdeploy::vision::typename>& \
FD_C_CheckAndConvert##typename##Wrapper( \
FD_C_##typename##Wrapper* var_wrapper_name) { \
FDASSERT(var_wrapper_name != nullptr, \
"The pointer of " #var_wrapper_name " shouldn't be nullptr."); \
return var_wrapper_name->var_ptr_name; \
}
#define DECL_AND_IMPLEMENT_CLASSIFICATION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(typename, var_wrapper_name, var_ptr_name) std::unique_ptr<fastdeploy::vision::classification::typename>& \
FD_C_CheckAndConvert##typename##Wrapper( \
FD_C_##typename##Wrapper* var_wrapper_name) { \
FDASSERT(var_wrapper_name != nullptr, \
"The pointer of " #var_wrapper_name " shouldn't be nullptr."); \
return var_wrapper_name->var_ptr_name; \
}
#define DECL_AND_IMPLEMENT_DETECTION_MODEL_FUNC_FOR_GET_PTR_FROM_WRAPPER(typename, var_wrapper_name, var_ptr_name) std::unique_ptr<fastdeploy::vision::detection::typename>& \
FD_C_CheckAndConvert##typename##Wrapper( \
FD_C_##typename##Wrapper* var_wrapper_name) { \
FDASSERT(var_wrapper_name != nullptr, \
"The pointer of " #var_wrapper_name " shouldn't be nullptr."); \
return var_wrapper_name->var_ptr_name; \
}

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@@ -38,21 +38,82 @@ FD_C_PaddleClasModelWrapper* FD_C_CreatePaddleClasModelWrapper(
}
void FD_C_DestroyPaddleClasModelWrapper(
__fd_take FD_C_PaddleClasModelWrapper* fd_c_paddleclas_model_wrapper) {
FD_C_PaddleClasModelWrapper* fd_c_paddleclas_model_wrapper) {
delete fd_c_paddleclas_model_wrapper;
}
FD_C_Bool FD_C_PaddleClasModelWrapperPredict(
__fd_take FD_C_PaddleClasModelWrapper* fd_c_paddleclas_model_wrapper,
FD_C_Mat img, FD_C_ClassifyResultWrapper* fd_c_classify_result_wrapper) {
FD_C_PaddleClasModelWrapper* fd_c_paddleclas_model_wrapper, FD_C_Mat img,
FD_C_ClassifyResult* fd_c_classify_result) {
cv::Mat* im = reinterpret_cast<cv::Mat*>(img);
auto& paddleclas_model = CHECK_AND_CONVERT_FD_TYPE(
PaddleClasModelWrapper, fd_c_paddleclas_model_wrapper);
FD_C_ClassifyResultWrapper* fd_c_classify_result_wrapper =
FD_C_CreateClassifyResultWrapper();
auto& classify_result = CHECK_AND_CONVERT_FD_TYPE(
ClassifyResultWrapper, fd_c_classify_result_wrapper);
return paddleclas_model->Predict(im, classify_result.get());
bool successful = paddleclas_model->Predict(im, classify_result.get());
if (successful) {
FD_C_ClassifyResult* res =
FD_C_ClassifyResultWrapperGetData(fd_c_classify_result_wrapper);
*fd_c_classify_result = *res;
}
return successful;
}
FD_C_Bool FD_C_PaddleClasModelWrapperInitialized(
FD_C_PaddleClasModelWrapper* fd_c_paddleclas_model_wrapper) {
auto& paddleclas_model = CHECK_AND_CONVERT_FD_TYPE(
PaddleClasModelWrapper, fd_c_paddleclas_model_wrapper);
return paddleclas_model->Initialized();
}
FD_C_ClassifyResult* FD_C_ClassifyResultToC(
fastdeploy::vision::ClassifyResult* classify_result) {
// Internal use, transfer fastdeploy::vision::ClassifyResult to
// FD_C_ClassifyResult
FD_C_ClassifyResult* fd_c_classify_result_data = new FD_C_ClassifyResult();
// copy label_ids
fd_c_classify_result_data->label_ids.size = classify_result->label_ids.size();
fd_c_classify_result_data->label_ids.data =
new int32_t[fd_c_classify_result_data->label_ids.size];
memcpy(fd_c_classify_result_data->label_ids.data,
classify_result->label_ids.data(),
sizeof(int32_t) * fd_c_classify_result_data->label_ids.size);
// copy scores
fd_c_classify_result_data->scores.size = classify_result->scores.size();
fd_c_classify_result_data->scores.data =
new float[fd_c_classify_result_data->scores.size];
memcpy(fd_c_classify_result_data->scores.data, classify_result->scores.data(),
sizeof(float) * fd_c_classify_result_data->scores.size);
fd_c_classify_result_data->type =
static_cast<FD_C_ResultType>(classify_result->type);
return fd_c_classify_result_data;
}
FD_C_Bool FD_C_PaddleClasModelWrapperBatchPredict(
FD_C_PaddleClasModelWrapper* fd_c_paddleclas_model_wrapper,
FD_C_OneDimMat imgs, FD_C_OneDimClassifyResult* results) {
std::vector<cv::Mat> imgs_vec;
std::vector<fastdeploy::vision::ClassifyResult> results_out;
for (int i = 0; i < imgs.size; i++) {
imgs_vec.push_back(*(reinterpret_cast<cv::Mat*>(imgs.data[i])));
}
auto& paddleclas_model = CHECK_AND_CONVERT_FD_TYPE(
PaddleClasModelWrapper, fd_c_paddleclas_model_wrapper);
bool successful = paddleclas_model->BatchPredict(imgs_vec, &results_out);
if (successful) {
// copy results back to FD_C_OneDimClassifyResult
results->size = results_out.size();
results->data = new FD_C_ClassifyResult[results->size];
for (int i = 0; i < results_out.size(); i++) {
results->data[i] = *FD_C_ClassifyResultToC(&results_out[i]);
}
}
return successful;
}
#ifdef __cplusplus
}
#endif
#endif

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@@ -54,12 +54,36 @@ FASTDEPLOY_CAPI_EXPORT extern void FD_C_DestroyPaddleClasModelWrapper(
*
* \param[in] fd_c_paddleclas_model_wrapper pointer to FD_C_PaddleClasModelWrapper object
* \param[in] img pointer to cv::Mat image
* \param[in] fd_c_classify_result_wrapper pointer to FD_C_PaddleClasModelWrapper object, which stores the result.
* \param[in] fd_c_classify_result pointer to FD_C_ClassifyResult object, which stores the result.
*/
FASTDEPLOY_CAPI_EXPORT extern FD_C_Bool FD_C_PaddleClasModelWrapperPredict(
__fd_take FD_C_PaddleClasModelWrapper* fd_c_paddleclas_model_wrapper,
FD_C_Mat img, FD_C_ClassifyResultWrapper* fd_c_classify_result_wrapper);
__fd_keep FD_C_PaddleClasModelWrapper* fd_c_paddleclas_model_wrapper,
FD_C_Mat img, FD_C_ClassifyResult* fd_c_classify_result_wrapper);
/** \brief Check if the model is initialized successfully
*
* \param[in] fd_c_paddleclas_model_wrapper pointer to FD_C_PaddleClasModelWrapper object
*
* \return Return a bool of value true if initialized successfully
*/
FASTDEPLOY_CAPI_EXPORT extern FD_C_Bool FD_C_PaddleClasModelWrapperInitialized(
__fd_keep FD_C_PaddleClasModelWrapper* fd_c_paddleclas_model_wrapper);
/** \brief Predict the classification results for a batch of input images
*
* \param[in] fd_c_paddleclas_model_wrapper pointer to FD_C_PaddleClasModelWrapper object
* \param[in] imgs The input image list, each element comes from cv::imread()
* \param[in] results The output classification result list
* \return true if the prediction successed, otherwise false
*/
FASTDEPLOY_CAPI_EXPORT extern FD_C_Bool FD_C_PaddleClasModelWrapperBatchPredict(
__fd_keep FD_C_PaddleClasModelWrapper* fd_c_paddleclas_model_wrapper,
FD_C_OneDimMat imgs,
FD_C_OneDimClassifyResult* results);
#ifdef __cplusplus
} // extern "C"

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@@ -0,0 +1,119 @@
// 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.
#pragma once
#define DECLARE_CREATE_WRAPPER_FUNCTION(model_type) FASTDEPLOY_CAPI_EXPORT extern __fd_give FD_C_##model_type##Wrapper* \
FD_C_Creates##model_type##Wrapper( \
const char* model_file, const char* params_file, const char* config_file, \
FD_C_RuntimeOptionWrapper* fd_c_runtime_option_wrapper, \
const FD_C_ModelFormat model_format)
#define DECLARE_DESTROY_WRAPPER_FUNCTION(model_type, wrapper_var_name) FASTDEPLOY_CAPI_EXPORT extern void \
FD_C_Destroy##model_type##Wrapper(__fd_take FD_C_##model_type##Wrapper* wrapper_var_name);
#define DECLARE_PREDICT_FUNCTION(model_type, wrapper_var_name) FASTDEPLOY_CAPI_EXPORT extern FD_C_Bool FD_C_##model_type##WrapperPredict( \
__fd_take FD_C_##model_type##Wrapper* wrapper_var_name, FD_C_Mat img, \
FD_C_DetectionResult* fd_c_detection_result)
#define DECLARE_INITIALIZED_FUNCTION(model_type, wrapper_var_name) FASTDEPLOY_CAPI_EXPORT extern FD_C_Bool FD_C_##model_type##WrapperInitialized( \
__fd_keep FD_C_##model_type##Wrapper* wrapper_var_name)
#define DECLARE_BATCH_PREDICT_FUNCTION(model_type, wrapper_var_name) FASTDEPLOY_CAPI_EXPORT extern FD_C_Bool FD_C_##model_type##WrapperBatchPredict( \
__fd_keep FD_C_##model_type##Wrapper* wrapper_var_name, \
FD_C_OneDimMat imgs, \
FD_C_OneDimDetectionResult* results)
#define IMPLEMENT_CREATE_WRAPPER_FUNCTION(model_type, var_name) \
auto& runtime_option = CHECK_AND_CONVERT_FD_TYPE(RuntimeOptionWrapper, \
fd_c_runtime_option_wrapper); \
FD_C_##model_type##Wrapper* fd_c_##model_type##_wrapper = new FD_C_##model_type##Wrapper(); \
fd_c_##model_type##_wrapper->var_name = \
std::unique_ptr<fastdeploy::vision::detection::model_type>( \
new fastdeploy::vision::detection::model_type( \
std::string(model_file), std::string(params_file), \
std::string(config_file), *runtime_option, \
static_cast<fastdeploy::ModelFormat>(model_format))); \
return fd_c_##model_type##_wrapper
#define IMPLEMENT_DESTROY_WRAPPER_FUNCTION(model_type, wrapper_var_name) delete wrapper_var_name
#define IMPLEMENT_PREDICT_FUNCTION(model_type, wrapper_var_name) \
cv::Mat* im = reinterpret_cast<cv::Mat*>(img); \
auto& model = \
CHECK_AND_CONVERT_FD_TYPE(model_type##Wrapper, wrapper_var_name); \
FD_C_DetectionResultWrapper* fd_c_detection_result_wrapper = \
FD_C_CreateDetectionResultWrapper(); \
auto& detection_result = CHECK_AND_CONVERT_FD_TYPE( \
DetectionResultWrapper, fd_c_detection_result_wrapper); \
bool successful = model->Predict(im, detection_result.get()); \
if (successful) { \
FD_C_DetectionResult* res = \
FD_C_DetectionResultWrapperGetData(fd_c_detection_result_wrapper); \
*fd_c_detection_result = *res; \
} \
return successful
#define IMPLEMENT_INITIALIZED_FUNCTION(model_type, wrapper_var_name) auto& model = \
CHECK_AND_CONVERT_FD_TYPE(model_type##Wrapper, wrapper_var_name); \
return model->Initialized();
#define IMPLEMENT_BATCH_PREDICT_FUNCTION(model_type, wrapper_var_name) std::vector<cv::Mat> imgs_vec; \
std::vector<fastdeploy::vision::DetectionResult> results_out; \
for (int i = 0; i < imgs.size; i++) { \
imgs_vec.push_back(*(reinterpret_cast<cv::Mat*>(imgs.data[i]))); \
} \
auto& model = \
CHECK_AND_CONVERT_FD_TYPE(model_type##Wrapper, wrapper_var_name); \
bool successful = model->BatchPredict(imgs_vec, &results_out); \
if (successful) { \
results->size = results_out.size(); \
results->data = new FD_C_DetectionResult[results->size]; \
for (int i = 0; i < results_out.size(); i++) { \
results->data[i] = *FD_C_DetectionResultToC(&results_out[i]); \
} \
} \
return successful;
#define DECLARE_AND_IMPLEMENT_CREATE_WRAPPER_FUNCTION(model_type, var_name) FD_C_##model_type##Wrapper* FD_C_Creates##model_type##Wrapper(\
const char* model_file, const char* params_file, const char* config_file, \
FD_C_RuntimeOptionWrapper* fd_c_runtime_option_wrapper, \
const FD_C_ModelFormat model_format) { \
IMPLEMENT_CREATE_WRAPPER_FUNCTION(model_type, var_name); \
}
#define DECLARE_AND_IMPLEMENT_DESTROY_WRAPPER_FUNCTION(model_type, wrapper_var_name) void FD_C_Destroy##model_type##Wrapper( \
__fd_take FD_C_##model_type##Wrapper* wrapper_var_name) { \
IMPLEMENT_DESTROY_WRAPPER_FUNCTION(model_type, wrapper_var_name); \
}
#define DECLARE_AND_IMPLEMENT_PREDICT_FUNCTION(model_type, wrapper_var_name) FD_C_Bool FD_C_##model_type##WrapperPredict( \
FD_C_##model_type##Wrapper* wrapper_var_name, FD_C_Mat img, \
FD_C_DetectionResult* fd_c_detection_result) { \
IMPLEMENT_PREDICT_FUNCTION(model_type, wrapper_var_name); \
}
#define DECLARE_AND_IMPLEMENT_INITIALIZED_FUNCTION(model_type, wrapper_var_name) FD_C_Bool FD_C_##model_type##WrapperInitialized( \
FD_C_##model_type##Wrapper* wrapper_var_name) { \
IMPLEMENT_INITIALIZED_FUNCTION(model_type, wrapper_var_name); \
}
#define DECLARE_AND_IMPLEMENT_BATCH_PREDICT_FUNCTION(model_type, wrapper_var_name) FD_C_Bool FD_C_##model_type##WrapperBatchPredict( \
FD_C_##model_type##Wrapper* wrapper_var_name, FD_C_OneDimMat imgs, \
FD_C_OneDimDetectionResult* results) { \
IMPLEMENT_BATCH_PREDICT_FUNCTION(model_type, wrapper_var_name); \
}

View File

@@ -21,38 +21,248 @@
extern "C" {
#endif
// PPYOLOE
FD_C_PPYOLOEWrapper* FD_C_CreatesPPYOLOEWrapper(
const char* model_file, const char* params_file, const char* config_file,
FD_C_RuntimeOptionWrapper* fd_c_runtime_option_wrapper,
const FD_C_ModelFormat model_format) {
auto& runtime_option = CHECK_AND_CONVERT_FD_TYPE(RuntimeOptionWrapper,
fd_c_runtime_option_wrapper);
FD_C_PPYOLOEWrapper* fd_c_ppyoloe_wrapper = new FD_C_PPYOLOEWrapper();
fd_c_ppyoloe_wrapper->ppyoloe_model =
std::unique_ptr<fastdeploy::vision::detection::PPYOLOE>(
new fastdeploy::vision::detection::PPYOLOE(
std::string(model_file), std::string(params_file),
std::string(config_file), *runtime_option,
static_cast<fastdeploy::ModelFormat>(model_format)));
return fd_c_ppyoloe_wrapper;
IMPLEMENT_CREATE_WRAPPER_FUNCTION(PPYOLOE, ppyoloe_model);
}
void FD_C_DestroyPPYOLOEWrapper(
__fd_take FD_C_PPYOLOEWrapper* fd_c_ppyoloe_wrapper) {
delete fd_c_ppyoloe_wrapper;
__fd_take FD_C_PPYOLOEWrapper* fd_ppyoloe_wrapper) {
IMPLEMENT_DESTROY_WRAPPER_FUNCTION(PPYOLOE, fd_ppyoloe_wrapper);
}
FD_C_Bool FD_C_PPYOLOEWrapperPredict(
FD_C_PPYOLOEWrapper* fd_c_ppyoloe_wrapper, FD_C_Mat img,
FD_C_DetectionResultWrapper* fd_c_detection_result_wrapper) {
cv::Mat* im = reinterpret_cast<cv::Mat*>(img);
auto& ppyoloe_model =
CHECK_AND_CONVERT_FD_TYPE(PPYOLOEWrapper, fd_c_ppyoloe_wrapper);
auto& detection_result = CHECK_AND_CONVERT_FD_TYPE(
DetectionResultWrapper, fd_c_detection_result_wrapper);
return ppyoloe_model->Predict(im, detection_result.get());
FD_C_PPYOLOEWrapper* fd_ppyoloe_wrapper, FD_C_Mat img,
FD_C_DetectionResult* fd_c_detection_result) {
IMPLEMENT_PREDICT_FUNCTION(PPYOLOE, fd_ppyoloe_wrapper);
}
FD_C_Bool FD_C_PPYOLOEWrapperInitialized(
FD_C_PPYOLOEWrapper* fd_ppyoloe_wrapper) {
IMPLEMENT_INITIALIZED_FUNCTION(PPYOLOE, fd_ppyoloe_wrapper);
}
FD_C_DetectionResult* FD_C_DetectionResultToC(
fastdeploy::vision::DetectionResult* detection_result) {
// Internal use, transfer fastdeploy::vision::DetectionResult to
// FD_C_DetectionResult
FD_C_DetectionResult* fd_c_detection_result = new FD_C_DetectionResult();
// copy boxes
const int boxes_coordinate_dim = 4;
fd_c_detection_result->boxes.size = detection_result->boxes.size();
fd_c_detection_result->boxes.data =
new FD_C_OneDimArrayFloat[fd_c_detection_result->boxes.size];
for (size_t i = 0; i < detection_result->boxes.size(); i++) {
fd_c_detection_result->boxes.data[i].size = boxes_coordinate_dim;
fd_c_detection_result->boxes.data[i].data = new float[boxes_coordinate_dim];
for (size_t j = 0; j < boxes_coordinate_dim; j++) {
fd_c_detection_result->boxes.data[i].data[j] =
detection_result->boxes[i][j];
}
}
// copy scores
fd_c_detection_result->scores.size = detection_result->scores.size();
fd_c_detection_result->scores.data =
new float[fd_c_detection_result->scores.size];
memcpy(fd_c_detection_result->scores.data, detection_result->scores.data(),
sizeof(float) * fd_c_detection_result->scores.size);
// copy label_ids
fd_c_detection_result->label_ids.size = detection_result->label_ids.size();
fd_c_detection_result->label_ids.data =
new int32_t[fd_c_detection_result->label_ids.size];
memcpy(fd_c_detection_result->label_ids.data,
detection_result->label_ids.data(),
sizeof(int32_t) * fd_c_detection_result->label_ids.size);
// copy masks
fd_c_detection_result->masks.size = detection_result->masks.size();
fd_c_detection_result->masks.data =
new FD_C_Mask[fd_c_detection_result->masks.size];
for (size_t i = 0; i < detection_result->masks.size(); i++) {
// copy data in mask
fd_c_detection_result->masks.data[i].data.size =
detection_result->masks[i].data.size();
fd_c_detection_result->masks.data[i].data.data =
new uint8_t[detection_result->masks[i].data.size()];
memcpy(fd_c_detection_result->masks.data[i].data.data,
detection_result->masks[i].data.data(),
sizeof(uint8_t) * detection_result->masks[i].data.size());
// copy shape in mask
fd_c_detection_result->masks.data[i].shape.size =
detection_result->masks[i].shape.size();
fd_c_detection_result->masks.data[i].shape.data =
new int64_t[detection_result->masks[i].shape.size()];
memcpy(fd_c_detection_result->masks.data[i].shape.data,
detection_result->masks[i].shape.data(),
sizeof(int64_t) * detection_result->masks[i].shape.size());
fd_c_detection_result->masks.data[i].type =
static_cast<FD_C_ResultType>(detection_result->masks[i].type);
}
fd_c_detection_result->contain_masks = detection_result->contain_masks;
fd_c_detection_result->type =
static_cast<FD_C_ResultType>(detection_result->type);
return fd_c_detection_result;
}
FD_C_Bool FD_C_PPYOLOEWrapperBatchPredict(
FD_C_PPYOLOEWrapper* fd_ppyoloe_wrapper, FD_C_OneDimMat imgs,
FD_C_OneDimDetectionResult* results) {
IMPLEMENT_BATCH_PREDICT_FUNCTION(PPYOLOE, fd_ppyoloe_wrapper);
}
// PicoDet
DECLARE_AND_IMPLEMENT_CREATE_WRAPPER_FUNCTION(PicoDet, picodet_model)
DECLARE_AND_IMPLEMENT_DESTROY_WRAPPER_FUNCTION(PicoDet, fd_picodet_wrapper)
DECLARE_AND_IMPLEMENT_PREDICT_FUNCTION(PicoDet, fd_picodet_wrapper)
DECLARE_AND_IMPLEMENT_INITIALIZED_FUNCTION(PicoDet, fd_picodet_wrapper)
DECLARE_AND_IMPLEMENT_BATCH_PREDICT_FUNCTION(PicoDet, fd_picodet_wrapper)
// PPYOLO
DECLARE_AND_IMPLEMENT_CREATE_WRAPPER_FUNCTION(PPYOLO, ppyolo_model)
DECLARE_AND_IMPLEMENT_DESTROY_WRAPPER_FUNCTION(PPYOLO, fd_ppyolo_wrapper)
DECLARE_AND_IMPLEMENT_PREDICT_FUNCTION(PPYOLO, fd_ppyolo_wrapper)
DECLARE_AND_IMPLEMENT_INITIALIZED_FUNCTION(PPYOLO, fd_ppyolo_wrapper)
DECLARE_AND_IMPLEMENT_BATCH_PREDICT_FUNCTION(PPYOLO, fd_ppyolo_wrapper)
// YOLOv3
DECLARE_AND_IMPLEMENT_CREATE_WRAPPER_FUNCTION(YOLOv3, yolov3_model)
DECLARE_AND_IMPLEMENT_DESTROY_WRAPPER_FUNCTION(YOLOv3, fd_yolov3_wrapper)
DECLARE_AND_IMPLEMENT_PREDICT_FUNCTION(YOLOv3, fd_yolov3_wrapper)
DECLARE_AND_IMPLEMENT_INITIALIZED_FUNCTION(YOLOv3, fd_yolov3_wrapper)
DECLARE_AND_IMPLEMENT_BATCH_PREDICT_FUNCTION(YOLOv3, fd_yolov3_wrapper)
// PaddleYOLOX
DECLARE_AND_IMPLEMENT_CREATE_WRAPPER_FUNCTION(PaddleYOLOX, paddleyolox_model)
DECLARE_AND_IMPLEMENT_DESTROY_WRAPPER_FUNCTION(PaddleYOLOX,
fd_paddleyolox_wrapper)
DECLARE_AND_IMPLEMENT_PREDICT_FUNCTION(PaddleYOLOX, fd_paddleyolox_wrapper)
DECLARE_AND_IMPLEMENT_INITIALIZED_FUNCTION(PaddleYOLOX, fd_paddleyolox_wrapper)
DECLARE_AND_IMPLEMENT_BATCH_PREDICT_FUNCTION(PaddleYOLOX,
fd_paddleyolox_wrapper)
// FasterRCNN
DECLARE_AND_IMPLEMENT_CREATE_WRAPPER_FUNCTION(FasterRCNN, fasterrcnn_model)
DECLARE_AND_IMPLEMENT_DESTROY_WRAPPER_FUNCTION(FasterRCNN,
fd_fasterrcnn_wrapper)
DECLARE_AND_IMPLEMENT_PREDICT_FUNCTION(FasterRCNN, fd_fasterrcnn_wrapper)
DECLARE_AND_IMPLEMENT_INITIALIZED_FUNCTION(FasterRCNN, fd_fasterrcnn_wrapper)
DECLARE_AND_IMPLEMENT_BATCH_PREDICT_FUNCTION(FasterRCNN, fd_fasterrcnn_wrapper)
// MaskRCNN
DECLARE_AND_IMPLEMENT_CREATE_WRAPPER_FUNCTION(MaskRCNN, maskrcnn_model)
DECLARE_AND_IMPLEMENT_DESTROY_WRAPPER_FUNCTION(MaskRCNN, fd_maskrcnn_wrapper)
DECLARE_AND_IMPLEMENT_PREDICT_FUNCTION(MaskRCNN, fd_maskrcnn_wrapper)
DECLARE_AND_IMPLEMENT_INITIALIZED_FUNCTION(MaskRCNN, fd_maskrcnn_wrapper)
DECLARE_AND_IMPLEMENT_BATCH_PREDICT_FUNCTION(MaskRCNN, fd_maskrcnn_wrapper)
// SSD
DECLARE_AND_IMPLEMENT_CREATE_WRAPPER_FUNCTION(SSD, ssd_model)
DECLARE_AND_IMPLEMENT_DESTROY_WRAPPER_FUNCTION(SSD, fd_ssd_wrapper)
DECLARE_AND_IMPLEMENT_PREDICT_FUNCTION(SSD, fd_ssd_wrapper)
DECLARE_AND_IMPLEMENT_INITIALIZED_FUNCTION(SSD, fd_ssd_wrapper)
DECLARE_AND_IMPLEMENT_BATCH_PREDICT_FUNCTION(SSD, fd_ssd_wrapper)
// PaddleYOLOv5
DECLARE_AND_IMPLEMENT_CREATE_WRAPPER_FUNCTION(PaddleYOLOv5, paddleyolov5_model)
DECLARE_AND_IMPLEMENT_DESTROY_WRAPPER_FUNCTION(PaddleYOLOv5,
fd_paddleyolov5_wrapper)
DECLARE_AND_IMPLEMENT_PREDICT_FUNCTION(PaddleYOLOv5, fd_paddleyolov5_wrapper)
DECLARE_AND_IMPLEMENT_INITIALIZED_FUNCTION(PaddleYOLOv5,
fd_paddleyolov5_wrapper)
DECLARE_AND_IMPLEMENT_BATCH_PREDICT_FUNCTION(PaddleYOLOv5,
fd_paddleyolov5_wrapper)
// PaddleYOLOv6
DECLARE_AND_IMPLEMENT_CREATE_WRAPPER_FUNCTION(PaddleYOLOv6, paddleyolov6_model)
DECLARE_AND_IMPLEMENT_DESTROY_WRAPPER_FUNCTION(PaddleYOLOv6,
fd_paddleyolov6_wrapper)
DECLARE_AND_IMPLEMENT_PREDICT_FUNCTION(PaddleYOLOv6, fd_paddleyolov6_wrapper)
DECLARE_AND_IMPLEMENT_INITIALIZED_FUNCTION(PaddleYOLOv6,
fd_paddleyolov6_wrapper)
DECLARE_AND_IMPLEMENT_BATCH_PREDICT_FUNCTION(PaddleYOLOv6,
fd_paddleyolov6_wrapper)
// PaddleYOLOv7
DECLARE_AND_IMPLEMENT_CREATE_WRAPPER_FUNCTION(PaddleYOLOv7, paddleyolov7_model)
DECLARE_AND_IMPLEMENT_DESTROY_WRAPPER_FUNCTION(PaddleYOLOv7,
fd_paddleyolov7_wrapper)
DECLARE_AND_IMPLEMENT_PREDICT_FUNCTION(PaddleYOLOv7, fd_paddleyolov7_wrapper)
DECLARE_AND_IMPLEMENT_INITIALIZED_FUNCTION(PaddleYOLOv7,
fd_paddleyolov7_wrapper)
DECLARE_AND_IMPLEMENT_BATCH_PREDICT_FUNCTION(PaddleYOLOv7,
fd_paddleyolov7_wrapper)
// PaddleYOLOv8
DECLARE_AND_IMPLEMENT_CREATE_WRAPPER_FUNCTION(PaddleYOLOv8, paddleyolov8_model)
DECLARE_AND_IMPLEMENT_DESTROY_WRAPPER_FUNCTION(PaddleYOLOv8,
fd_paddleyolov8_wrapper)
DECLARE_AND_IMPLEMENT_PREDICT_FUNCTION(PaddleYOLOv8, fd_paddleyolov8_wrapper)
DECLARE_AND_IMPLEMENT_INITIALIZED_FUNCTION(PaddleYOLOv8,
fd_paddleyolov8_wrapper)
DECLARE_AND_IMPLEMENT_BATCH_PREDICT_FUNCTION(PaddleYOLOv8,
fd_paddleyolov8_wrapper)
// RTMDet
DECLARE_AND_IMPLEMENT_CREATE_WRAPPER_FUNCTION(RTMDet, rtmdet_model)
DECLARE_AND_IMPLEMENT_DESTROY_WRAPPER_FUNCTION(RTMDet, fd_rtmdet_wrapper)
DECLARE_AND_IMPLEMENT_PREDICT_FUNCTION(RTMDet, fd_rtmdet_wrapper)
DECLARE_AND_IMPLEMENT_INITIALIZED_FUNCTION(RTMDet, fd_rtmdet_wrapper)
DECLARE_AND_IMPLEMENT_BATCH_PREDICT_FUNCTION(RTMDet, fd_rtmdet_wrapper)
// CascadeRCNN
DECLARE_AND_IMPLEMENT_CREATE_WRAPPER_FUNCTION(CascadeRCNN, cascadercnn_model)
DECLARE_AND_IMPLEMENT_DESTROY_WRAPPER_FUNCTION(CascadeRCNN,
fd_cascadercnn_wrapper)
DECLARE_AND_IMPLEMENT_PREDICT_FUNCTION(CascadeRCNN, fd_cascadercnn_wrapper)
DECLARE_AND_IMPLEMENT_INITIALIZED_FUNCTION(CascadeRCNN, fd_cascadercnn_wrapper)
DECLARE_AND_IMPLEMENT_BATCH_PREDICT_FUNCTION(CascadeRCNN,
fd_cascadercnn_wrapper)
// PSSDet
DECLARE_AND_IMPLEMENT_CREATE_WRAPPER_FUNCTION(PSSDet, pssdet_model)
DECLARE_AND_IMPLEMENT_DESTROY_WRAPPER_FUNCTION(PSSDet, fd_pssdet_wrapper)
DECLARE_AND_IMPLEMENT_PREDICT_FUNCTION(PSSDet, fd_pssdet_wrapper)
DECLARE_AND_IMPLEMENT_INITIALIZED_FUNCTION(PSSDet, fd_pssdet_wrapper)
DECLARE_AND_IMPLEMENT_BATCH_PREDICT_FUNCTION(PSSDet, fd_pssdet_wrapper)
// RetinaNet
DECLARE_AND_IMPLEMENT_CREATE_WRAPPER_FUNCTION(RetinaNet, retinanet_model)
DECLARE_AND_IMPLEMENT_DESTROY_WRAPPER_FUNCTION(RetinaNet, fd_retinanet_wrapper)
DECLARE_AND_IMPLEMENT_PREDICT_FUNCTION(RetinaNet, fd_retinanet_wrapper)
DECLARE_AND_IMPLEMENT_INITIALIZED_FUNCTION(RetinaNet, fd_retinanet_wrapper)
DECLARE_AND_IMPLEMENT_BATCH_PREDICT_FUNCTION(RetinaNet, fd_retinanet_wrapper)
// FCOS
DECLARE_AND_IMPLEMENT_CREATE_WRAPPER_FUNCTION(FCOS, fcos_model)
DECLARE_AND_IMPLEMENT_DESTROY_WRAPPER_FUNCTION(FCOS, fd_fcos_wrapper)
DECLARE_AND_IMPLEMENT_PREDICT_FUNCTION(FCOS, fd_fcos_wrapper)
DECLARE_AND_IMPLEMENT_INITIALIZED_FUNCTION(FCOS, fd_fcos_wrapper)
DECLARE_AND_IMPLEMENT_BATCH_PREDICT_FUNCTION(FCOS, fd_fcos_wrapper)
// TTFNet
DECLARE_AND_IMPLEMENT_CREATE_WRAPPER_FUNCTION(TTFNet, ttfnet_model)
DECLARE_AND_IMPLEMENT_DESTROY_WRAPPER_FUNCTION(TTFNet, fd_ttfnet_wrapper)
DECLARE_AND_IMPLEMENT_PREDICT_FUNCTION(TTFNet, fd_ttfnet_wrapper)
DECLARE_AND_IMPLEMENT_INITIALIZED_FUNCTION(TTFNet, fd_ttfnet_wrapper)
DECLARE_AND_IMPLEMENT_BATCH_PREDICT_FUNCTION(TTFNet, fd_ttfnet_wrapper)
// TOOD
DECLARE_AND_IMPLEMENT_CREATE_WRAPPER_FUNCTION(TOOD, tood_model)
DECLARE_AND_IMPLEMENT_DESTROY_WRAPPER_FUNCTION(TOOD, fd_tood_wrapper)
DECLARE_AND_IMPLEMENT_PREDICT_FUNCTION(TOOD, fd_tood_wrapper)
DECLARE_AND_IMPLEMENT_INITIALIZED_FUNCTION(TOOD, fd_tood_wrapper)
DECLARE_AND_IMPLEMENT_BATCH_PREDICT_FUNCTION(TOOD, fd_tood_wrapper)
// GFL
DECLARE_AND_IMPLEMENT_CREATE_WRAPPER_FUNCTION(GFL, gfl_model)
DECLARE_AND_IMPLEMENT_DESTROY_WRAPPER_FUNCTION(GFL, fd_gfl_wrapper)
DECLARE_AND_IMPLEMENT_PREDICT_FUNCTION(GFL, fd_gfl_wrapper)
DECLARE_AND_IMPLEMENT_INITIALIZED_FUNCTION(GFL, fd_gfl_wrapper)
DECLARE_AND_IMPLEMENT_BATCH_PREDICT_FUNCTION(GFL, fd_gfl_wrapper)
#ifdef __cplusplus
}
#endif
#endif

File diff suppressed because it is too large Load Diff

View File

@@ -90,6 +90,16 @@ FD_C_ClassifyResultWrapper* FD_C_CreateClassifyResultWrapperFromData(
return fd_c_classify_result_wrapper;
}
char* FD_C_ClassifyResultWrapperStr(
FD_C_ClassifyResultWrapper* fd_c_classify_result_wrapper) {
auto& classify_result = CHECK_AND_CONVERT_FD_TYPE(
ClassifyResultWrapper, fd_c_classify_result_wrapper);
std::string information = classify_result->Str();
char* cstr = new char[information.length() + 1];
std::strcpy(cstr, information.c_str());
return cstr;
}
// Detection Results
FD_C_DetectionResultWrapper* FD_C_CreateDetectionResultWrapper() {
@@ -237,6 +247,17 @@ FD_C_DetectionResultWrapper* FD_C_CreateDetectionResultWrapperFromData(
return fd_c_detection_result_wrapper;
}
char* FD_C_DetectionResultWrapperStr(
FD_C_DetectionResultWrapper* fd_c_detection_result_wrapper) {
auto& detection_result = CHECK_AND_CONVERT_FD_TYPE(
DetectionResultWrapper, fd_c_detection_result_wrapper);
std::string information = detection_result->Str();
char* cstr = new char[information.length() + 1];
std::strcpy(cstr, information.c_str());
return cstr;
}
#ifdef __cplusplus
}
#endif
#endif

View File

@@ -30,6 +30,11 @@ typedef struct FD_C_ClassifyResult {
FD_C_ResultType type;
} FD_C_ClassifyResult;
typedef struct FD_C_OneDimClassifyResult {
size_t size;
FD_C_ClassifyResult* data;
} FD_C_OneDimClassifyResult;
typedef struct FD_C_Mask {
FD_C_OneDimArrayUint8 data;
FD_C_OneDimArrayInt64 shape;
@@ -50,6 +55,11 @@ typedef struct FD_C_DetectionResult {
FD_C_ResultType type;
} FD_C_DetectionResult;
typedef struct FD_C_OneDimDetectionResult {
size_t size;
FD_C_DetectionResult* data;
} FD_C_OneDimDetectionResult;
// Classification Results
/** \brief Create a new FD_C_ClassifyResultWrapper object
@@ -95,6 +105,16 @@ FASTDEPLOY_CAPI_EXPORT extern __fd_give FD_C_ClassifyResultWrapper*
FD_C_CreateClassifyResultWrapperFromData(
__fd_keep FD_C_ClassifyResult* fd_c_classify_result);
/** \brief Print ClassifyResult formated information
*
* \param[in] fd_c_classify_result_wrapper pointer to FD_C_ClassifyResultWrapper object
* \return Return a string pointer
*/
FASTDEPLOY_CAPI_EXPORT extern __fd_give char*
FD_C_ClassifyResultWrapperStr(
__fd_keep FD_C_ClassifyResultWrapper* fd_c_classify_result_wrapper);
// Detection Results
/** \brief Create a new FD_C_DetectionResultWrapper object
@@ -140,6 +160,16 @@ FASTDEPLOY_CAPI_EXPORT extern __fd_give FD_C_DetectionResultWrapper*
FD_C_CreateDetectionResultWrapperFromData(
__fd_keep FD_C_DetectionResult* fd_c_detection_result);
/** \brief Print DetectionResult formated information
*
* \param[in] fd_c_detection_result_wrapper pointer to FD_C_DetectionResultWrapper object
* \return Return a string pointer
*/
FASTDEPLOY_CAPI_EXPORT extern __fd_give char*
FD_C_DetectionResultWrapperStr(
__fd_keep FD_C_DetectionResultWrapper* fd_c_detection_result_wrapper);
#ifdef __cplusplus
} // extern "C"
#endif

View File

@@ -29,11 +29,31 @@ FD_C_Mat FD_C_VisDetection(FD_C_Mat im,
FD_C_CreateDetectionResultWrapperFromData(fd_c_detection_result);
auto& detection_result = CHECK_AND_CONVERT_FD_TYPE(
DetectionResultWrapper, fd_c_detection_result_wrapper);
cv::Mat result = fastdeploy::vision::Visualize::VisDetection(
cv::Mat result = fastdeploy::vision::VisDetection(
*(reinterpret_cast<cv::Mat*>(im)), *detection_result, score_threshold,
line_size, font_size);
return new cv::Mat(result);
}
FD_C_Mat FD_C_VisDetectionWithLabel(FD_C_Mat im,
FD_C_DetectionResult* fd_c_detection_result,
FD_C_OneDimArrayCstr* labels,
float score_threshold, int line_size,
float font_size) {
std::vector<std::string> labels_in;
for (int i = 0; i < labels->size; i++) {
labels_in.emplace_back(labels->data[i].data);
}
FD_C_DetectionResultWrapper* fd_c_detection_result_wrapper =
FD_C_CreateDetectionResultWrapperFromData(fd_c_detection_result);
auto& detection_result = CHECK_AND_CONVERT_FD_TYPE(
DetectionResultWrapper, fd_c_detection_result_wrapper);
cv::Mat result = fastdeploy::vision::VisDetection(
*(reinterpret_cast<cv::Mat*>(im)), *detection_result, labels_in,
score_threshold, line_size, font_size);
return new cv::Mat(result);
}
#ifdef __cplusplus
}
#endif
#endif

View File

@@ -22,15 +22,37 @@
extern "C" {
#endif
/** \brief Visualize Detection
/** \brief Show the visualized results for detection models
*
* \return Return a pointer to cv::Mat object
* \param[in] im the input image data, comes from cv::imread(), is a 3-D array with layout HWC, BGR format
* \param[in] result the result produced by model
* \param[in] score_threshold threshold for result scores, the bounding box will not be shown if the score is less than score_threshold
* \param[in] line_size line size for bounding boxes
* \param[in] font_size font size for text
* \return cv::Mat type stores the visualized results
*/
FASTDEPLOY_CAPI_EXPORT extern __fd_give 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);
/** \brief Show the visualized results with custom labels for detection models
*
* \param[in] im the input image data, comes from cv::imread(), is a 3-D array with layout HWC, BGR format
* \param[in] result the result produced by model
* \param[in] labels the visualized result will show the bounding box contain class label
* \param[in] score_threshold threshold for result scores, the bounding box will not be shown if the score is less than score_threshold
* \param[in] line_size line size for bounding boxes
* \param[in] font_size font size for text
* \return cv::Mat type stores the visualized results
*/
FASTDEPLOY_CAPI_EXPORT extern __fd_give FD_C_Mat FD_C_VisDetectionWithLabel(
FD_C_Mat im,
FD_C_DetectionResult* fd_detection_result,
FD_C_OneDimArrayCstr* labels,
float score_threshold,
int line_size, float font_size);
#ifdef __cplusplus
} // extern "C"
#endif