Files
FastDeploy/c_api/fastdeploy_capi/vision/classification/ppcls/model.h
chenjian 266ae046f2 [C API] Refactor code structure (#1449)
* refactor code

* move files

* fix doc

* fix
2023-02-27 20:19:13 +08:00

91 lines
3.7 KiB
C

// 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
#include "fastdeploy_capi/core/fd_common.h"
#include "fastdeploy_capi/core/fd_type.h"
#include "fastdeploy_capi/runtime/runtime_option.h"
#include "fastdeploy_capi/vision/result.h"
typedef struct FD_C_PaddleClasModelWrapper FD_C_PaddleClasModelWrapper;
#ifdef __cplusplus
extern "C" {
#endif
/** \brief Create a new FD_C_PaddleClasModelWrapper object
*
* \param[in] model_file Path of model file, e.g resnet/model.pdmodel
* \param[in] params_file Path of parameter file, e.g resnet/model.pdiparams, if the model format is ONNX, this parameter will be ignored
* \param[in] config_file Path of configuration file for deployment, e.g resnet/infer_cfg.yml
* \param[in] fd_c_runtime_option_wrapper RuntimeOption for inference, the default will use cpu, and choose the backend defined in `valid_cpu_backends`
* \param[in] model_format Model format of the loaded model, default is Paddle format
*
* \return Return a pointer to FD_C_PaddleClasModelWrapper object
*/
FASTDEPLOY_CAPI_EXPORT extern __fd_give FD_C_PaddleClasModelWrapper*
FD_C_CreatePaddleClasModelWrapper(
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);
/** \brief Destroy a FD_C_PaddleClasModelWrapper object
*
* \param[in] fd_c_paddleclas_model_wrapper pointer to FD_C_PaddleClasModelWrapper object
*/
FASTDEPLOY_CAPI_EXPORT extern void FD_C_DestroyPaddleClasModelWrapper(
__fd_take FD_C_PaddleClasModelWrapper* fd_c_paddleclas_model_wrapper);
/** \brief Predict the classification result for an input image
*
* \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 pointer to FD_C_ClassifyResult object, which stores the result.
*/
FASTDEPLOY_CAPI_EXPORT extern FD_C_Bool FD_C_PaddleClasModelWrapperPredict(
__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"
#endif