mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-13 12:23:55 +08:00
2c5fd91a7f
* first draft * update api name * fix bug * fix bug and * fix bug in c api * fix bug in c_api --------- Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com>
75 lines
2.8 KiB
C++
75 lines
2.8 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/vision/common/processors/transform.h"
|
|
#include "fastdeploy/vision/common/processors/manager.h"
|
|
#include "fastdeploy/vision/common/result.h"
|
|
|
|
namespace fastdeploy {
|
|
namespace vision {
|
|
|
|
namespace ocr {
|
|
/*! @brief Preprocessor object for table model.
|
|
*/
|
|
class FASTDEPLOY_DECL StructureV2TablePreprocessor : public ProcessorManager {
|
|
public:
|
|
StructureV2TablePreprocessor();
|
|
using ProcessorManager::Run;
|
|
/** \brief Process the input image and prepare input tensors for runtime
|
|
*
|
|
* \param[in] images The input data list, all the elements are FDMat
|
|
* \param[in] outputs The output tensors which will be fed into runtime
|
|
* \return true if the preprocess successed, otherwise false
|
|
*/
|
|
bool Run(std::vector<FDMat>* images, std::vector<FDTensor>* outputs,
|
|
size_t start_index, size_t end_index,
|
|
const std::vector<int>& indices);
|
|
|
|
/** \brief Implement the virtual function of ProcessorManager, Apply() is the
|
|
* body of Run(). Apply() contains the main logic of preprocessing, Run() is
|
|
* called by users to execute preprocessing
|
|
*
|
|
* \param[in] image_batch The input image batch
|
|
* \param[in] outputs The output tensors which will feed in runtime
|
|
* \return true if the preprocess successed, otherwise false
|
|
*/
|
|
virtual bool Apply(FDMatBatch* image_batch, std::vector<FDTensor>* outputs);
|
|
|
|
/// Get the image info of the last batch, return a list of array
|
|
/// {image width, image height, resize width, resize height}
|
|
const std::vector<std::array<int, 4>>* GetBatchImgInfo() {
|
|
return &batch_det_img_info_;
|
|
}
|
|
|
|
private:
|
|
void StructureV2TableResizeImage(FDMat* mat, int batch_idx);
|
|
// for recording the switch of hwc2chw
|
|
bool disable_permute_ = false;
|
|
// for recording the switch of normalize
|
|
bool disable_normalize_ = false;
|
|
int max_len = 488;
|
|
std::vector<int> rec_image_shape_ = {3, max_len, max_len};
|
|
bool static_shape_infer_ = false;
|
|
std::shared_ptr<Resize> resize_op_;
|
|
std::shared_ptr<Pad> pad_op_;
|
|
std::shared_ptr<Normalize> normalize_op_;
|
|
std::shared_ptr<HWC2CHW> hwc2chw_op_;
|
|
std::vector<std::array<int, 4>> batch_det_img_info_;
|
|
};
|
|
|
|
} // namespace ocr
|
|
} // namespace vision
|
|
} // namespace fastdeploy
|