mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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91 lines
3.6 KiB
C
91 lines
3.6 KiB
C
// Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#pragma once
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#include "fastdeploy_capi/fd_common.h"
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#include "fastdeploy_capi/fd_type.h"
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#include "fastdeploy_capi/runtime_option.h"
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#include "fastdeploy_capi/vision/result.h"
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typedef struct FD_C_PaddleSegModelWrapper FD_C_PaddleSegModelWrapper;
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#ifdef __cplusplus
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extern "C" {
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#endif
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/** \brief Create a new FD_C_PaddleSegModelWrapper object
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*
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* \param[in] model_file Path of model file, e.g net/model.pdmodel
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* \param[in] params_file Path of parameter file, e.g unet/model.pdiparams, if the model format is ONNX, this parameter will be ignored
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* \param[in] config_file Path of configuration file for deployment, e.g unet/deploy.yml
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* \param[in] fd_c_runtime_option_wrapper RuntimeOption for inference, the default will use cpu, and choose the backend defined in `valid_cpu_backends`
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* \param[in] model_format Model format of the loaded model, default is Paddle format
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*
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* \return Return a pointer to FD_C_PaddleSegModelWrapper object
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*/
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FASTDEPLOY_CAPI_EXPORT extern __fd_give FD_C_PaddleSegModelWrapper*
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FD_C_CreatePaddleSegModelWrapper(
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const char* model_file, const char* params_file, const char* config_file,
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FD_C_RuntimeOptionWrapper* fd_c_runtime_option_wrapper,
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const FD_C_ModelFormat model_format);
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/** \brief Destroy a FD_C_PaddleSegModelWrapper object
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*
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* \param[in] fd_c_paddleseg_model_wrapper pointer to FD_C_PaddleSegModelWrapper object
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*/
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FASTDEPLOY_CAPI_EXPORT extern void FD_C_DestroyPaddleSegModelWrapper(
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__fd_take FD_C_PaddleSegModelWrapper* fd_c_paddleseg_model_wrapper);
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/** \brief Predict the segmentation result for an input image
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*
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* \param[in] fd_c_paddleseg_model_wrapper pointer to FD_C_PaddleSegModelWrapper object
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* \param[in] img pointer to cv::Mat image
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* \param[in] fd_c_segmentation_result pointer to FD_C_SegmentationResult object, which stores the result.
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*/
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FASTDEPLOY_CAPI_EXPORT extern FD_C_Bool FD_C_PaddleSegModelWrapperPredict(
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__fd_keep FD_C_PaddleSegModelWrapper* fd_c_paddleseg_model_wrapper,
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FD_C_Mat img, FD_C_SegmentationResult* fd_c_segmentation_result);
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/** \brief Check if the model is initialized successfully
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*
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* \param[in] fd_c_paddleseg_model_wrapper pointer to FD_C_PaddleSegModelWrapper object
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*
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* \return Return a bool of value true if initialized successfully
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*/
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FASTDEPLOY_CAPI_EXPORT extern FD_C_Bool FD_C_PaddleSegModelWrapperInitialized(
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__fd_keep FD_C_PaddleSegModelWrapper* fd_c_paddleseg_model_wrapper);
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/** \brief Predict the segmentation results for a batch of input images
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*
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* \param[in] fd_c_paddleseg_model_wrapper pointer to FD_C_PaddleSegModelWrapper object
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* \param[in] imgs The input image list, each element comes from cv::imread()
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* \param[in] results The output segmentation result list
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* \return true if the prediction successed, otherwise false
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*/
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FASTDEPLOY_CAPI_EXPORT extern FD_C_Bool FD_C_PaddleSegModelWrapperBatchPredict(
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__fd_keep FD_C_PaddleSegModelWrapper* fd_c_paddleseg_model_wrapper,
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FD_C_OneDimMat imgs,
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FD_C_OneDimSegmentationResult* results);
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#ifdef __cplusplus
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} // extern "C"
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#endif
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