Files
FastDeploy/fastdeploy/vision/detection/ppdet/preprocessor.h
Jason beaa0fd190 [Model] Refactor PaddleDetection module (#575)
* Add namespace for functions

* Refactor PaddleDetection module

* finish all the single image test

* Update preprocessor.cc

* fix some litte detail

* add python api

* Update postprocessor.cc
2022-11-15 10:43:23 +08:00

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1.8 KiB
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// 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/vision/common/processors/transform.h"
#include "fastdeploy/vision/common/result.h"
namespace fastdeploy {
namespace vision {
namespace detection {
/*! @brief Preprocessor object for PaddleDet serials model.
*/
class FASTDEPLOY_DECL PaddleDetPreprocessor {
public:
PaddleDetPreprocessor() = default;
/** \brief Create a preprocessor instance for PaddleDet serials model
*
* \param[in] config_file Path of configuration file for deployment, e.g ppyoloe/infer_cfg.yml
*/
explicit PaddleDetPreprocessor(const std::string& config_file);
/** \brief Process the input image and prepare input tensors for runtime
*
* \param[in] images The input image data list, all the elements are returned by cv::imread()
* \param[in] outputs The output tensors which will feed in runtime, include image, scale_factor, im_shape
* \return true if the preprocess successed, otherwise false
*/
bool Run(std::vector<FDMat>* images, std::vector<FDTensor>* outputs);
private:
bool BuildPreprocessPipelineFromConfig(const std::string& config_file);
std::vector<std::shared_ptr<Processor>> processors_;
bool initialized_ = false;
};
} // namespace detection
} // namespace vision
} // namespace fastdeploy