// 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_PaddleSegModelWrapper FD_C_PaddleSegModelWrapper; #ifdef __cplusplus extern "C" { #endif /** \brief Create a new FD_C_PaddleSegModelWrapper object * * \param[in] model_file Path of model file, e.g net/model.pdmodel * \param[in] params_file Path of parameter file, e.g unet/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 unet/deploy.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_PaddleSegModelWrapper object */ FASTDEPLOY_CAPI_EXPORT extern __fd_give FD_C_PaddleSegModelWrapper* FD_C_CreatePaddleSegModelWrapper( 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_PaddleSegModelWrapper object * * \param[in] fd_c_paddleseg_model_wrapper pointer to FD_C_PaddleSegModelWrapper object */ FASTDEPLOY_CAPI_EXPORT extern void FD_C_DestroyPaddleSegModelWrapper( __fd_take FD_C_PaddleSegModelWrapper* fd_c_paddleseg_model_wrapper); /** \brief Predict the segmentation result for an input image * * \param[in] fd_c_paddleseg_model_wrapper pointer to FD_C_PaddleSegModelWrapper object * \param[in] img pointer to cv::Mat image * \param[in] fd_c_segmentation_result pointer to FD_C_SegmentationResult object, which stores the result. */ FASTDEPLOY_CAPI_EXPORT extern FD_C_Bool FD_C_PaddleSegModelWrapperPredict( __fd_keep FD_C_PaddleSegModelWrapper* fd_c_paddleseg_model_wrapper, FD_C_Mat img, FD_C_SegmentationResult* fd_c_segmentation_result); /** \brief Check if the model is initialized successfully * * \param[in] fd_c_paddleseg_model_wrapper pointer to FD_C_PaddleSegModelWrapper object * * \return Return a bool of value true if initialized successfully */ FASTDEPLOY_CAPI_EXPORT extern FD_C_Bool FD_C_PaddleSegModelWrapperInitialized( __fd_keep FD_C_PaddleSegModelWrapper* fd_c_paddleseg_model_wrapper); /** \brief Predict the segmentation results for a batch of input images * * \param[in] fd_c_paddleseg_model_wrapper pointer to FD_C_PaddleSegModelWrapper object * \param[in] imgs The input image list, each element comes from cv::imread() * \param[in] results The output segmentation result list * \return true if the prediction successed, otherwise false */ FASTDEPLOY_CAPI_EXPORT extern FD_C_Bool FD_C_PaddleSegModelWrapperBatchPredict( __fd_keep FD_C_PaddleSegModelWrapper* fd_c_paddleseg_model_wrapper, FD_C_OneDimMat imgs, FD_C_OneDimSegmentationResult* results); #ifdef __cplusplus } // extern "C" #endif