mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-07 09:31:35 +08:00
6d0261e9e4
* [Model] init pp-structurev2-layout code * [Model] init pp-structurev2-layout code * [Model] init pp-structurev2-layout code * [Model] add structurev2_layout_preprocessor * [PP-StructureV2] add postprocessor and layout detector class * [PP-StructureV2] add postprocessor and layout detector class * [PP-StructureV2] add postprocessor and layout detector class * [PP-StructureV2] add postprocessor and layout detector class * [PP-StructureV2] add postprocessor and layout detector class * [pybind] add pp-structurev2-layout model pybind * [pybind] add pp-structurev2-layout model pybind * [Bug Fix] fixed code style * [examples] add pp-structurev2-layout c++ examples * [PP-StructureV2] add python example and docs * [benchmark] add pp-structurev2-layout benchmark support
95 lines
4.1 KiB
C++
95 lines
4.1 KiB
C++
// Copyright (c) 2022 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/fastdeploy_model.h"
|
|
#include "fastdeploy/vision/common/processors/transform.h"
|
|
#include "fastdeploy/vision/common/result.h"
|
|
#include "fastdeploy/vision/ocr/ppocr/utils/ocr_postprocess_op.h"
|
|
#include "fastdeploy/vision/ocr/ppocr/structurev2_layout_preprocessor.h"
|
|
#include "fastdeploy/vision/ocr/ppocr/structurev2_layout_postprocessor.h"
|
|
#include "fastdeploy/utils/unique_ptr.h"
|
|
|
|
namespace fastdeploy {
|
|
namespace vision {
|
|
namespace ocr {
|
|
/*! @brief StructureV2Layout object is used to load the PP-StructureV2-Layout detection model.
|
|
*/
|
|
class FASTDEPLOY_DECL StructureV2Layout : public FastDeployModel {
|
|
public:
|
|
StructureV2Layout();
|
|
/** \brief Set path of model file, and the configuration of runtime
|
|
*
|
|
* \param[in] model_file Path of model file, e.g ./picodet_lcnet_x1_0_fgd_layout_cdla_infer/model.pdmodel.
|
|
* \param[in] params_file Path of parameter file, e.g ./picodet_lcnet_x1_0_fgd_layout_cdla_infer/model.pdiparams, if the model format is ONNX, this parameter will be ignored.
|
|
* \param[in] custom_option 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.
|
|
*/
|
|
StructureV2Layout(const std::string& model_file,
|
|
const std::string& params_file = "",
|
|
const RuntimeOption& custom_option = RuntimeOption(),
|
|
const ModelFormat& model_format = ModelFormat::PADDLE);
|
|
|
|
/** \brief Clone a new StructureV2Layout with less memory usage when multiple instances of the same model are created
|
|
*
|
|
* \return newStructureV2Layout* type unique pointer
|
|
*/
|
|
virtual std::unique_ptr<StructureV2Layout> Clone() const;
|
|
|
|
/// Get model's name
|
|
std::string ModelName() const { return "pp-structurev2-layout"; }
|
|
|
|
/** \brief DEPRECATED 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
|
|
* \param[in] result The output detection result
|
|
* \return true if the prediction successed, otherwise false
|
|
*/
|
|
virtual bool Predict(cv::Mat* im, DetectionResult* result);
|
|
|
|
/** \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
|
|
* \param[in] result The output detection result
|
|
* \return true if the prediction successed, otherwise false
|
|
*/
|
|
virtual bool Predict(const cv::Mat& im, DetectionResult* 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
|
|
* \param[in] results The output detection result list
|
|
* \return true if the prediction successed, otherwise false
|
|
*/
|
|
virtual bool BatchPredict(const std::vector<cv::Mat>& imgs,
|
|
std::vector<DetectionResult>* results);
|
|
|
|
/// Get preprocessor reference ofStructureV2LayoutPreprocessor
|
|
virtual StructureV2LayoutPreprocessor& GetPreprocessor() {
|
|
return preprocessor_;
|
|
}
|
|
|
|
/// Get postprocessor reference ofStructureV2LayoutPostprocessor
|
|
virtual StructureV2LayoutPostprocessor& GetPostprocessor() {
|
|
return postprocessor_;
|
|
}
|
|
|
|
private:
|
|
bool Initialize();
|
|
StructureV2LayoutPreprocessor preprocessor_;
|
|
StructureV2LayoutPostprocessor postprocessor_;
|
|
};
|
|
|
|
} // namespace ocr
|
|
} // namespace vision
|
|
} // namespace fastdeploy
|