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8c3ccc2cc2
* update ppocrv3 for rknpu2 * add config * add config * detele unuseful * update useful results * Repair note * Repair note * fixed bugs * update
89 lines
3.6 KiB
C++
89 lines
3.6 KiB
C++
// Copyright (c) 2022 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/vision/common/processors/transform.h"
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#include "fastdeploy/vision/common/result.h"
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namespace fastdeploy {
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namespace vision {
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namespace ocr {
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/*! @brief Preprocessor object for PaddleClas serials model.
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*/
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class FASTDEPLOY_DECL RecognizerPreprocessor {
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public:
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/** \brief Process the input image and prepare input tensors for runtime
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*
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* \param[in] images The input data list, all the elements are FDMat
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* \param[in] outputs The output tensors which will be fed into runtime
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* \return true if the preprocess successed, otherwise false
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*/
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bool Run(std::vector<FDMat>* images, std::vector<FDTensor>* outputs);
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bool Run(std::vector<FDMat>* images, std::vector<FDTensor>* outputs,
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size_t start_index, size_t end_index,
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const std::vector<int>& indices);
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/// Set static_shape_infer is true or not. When deploy PP-OCR
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/// on hardware which can not support dynamic input shape very well,
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/// like Huawei Ascned, static_shape_infer needs to to be true.
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void SetStaticShapeInfer(bool static_shape_infer) {
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static_shape_infer_ = static_shape_infer;
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}
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/// Get static_shape_infer of the recognition preprocess
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bool GetStaticShapeInfer() const { return static_shape_infer_; }
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/// Set mean value for the image normalization in recognition preprocess
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void SetMean(const std::vector<float>& mean) { mean_ = mean; }
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/// Get mean value of the image normalization in recognition preprocess
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std::vector<float> GetMean() const { return mean_; }
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/// Set scale value for the image normalization in recognition preprocess
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void SetScale(const std::vector<float>& scale) { scale_ = scale; }
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/// Get scale value of the image normalization in recognition preprocess
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std::vector<float> GetScale() const { return scale_; }
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/// Set is_scale for the image normalization in recognition preprocess
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void SetIsScale(bool is_scale) { is_scale_ = is_scale; }
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/// Get is_scale of the image normalization in recognition preprocess
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bool GetIsScale() const { return is_scale_; }
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/// Set rec_image_shape for the recognition preprocess
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void SetRecImageShape(const std::vector<int>& rec_image_shape) {
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rec_image_shape_ = rec_image_shape;
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}
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/// Get rec_image_shape for the recognition preprocess
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std::vector<int> GetRecImageShape() { return rec_image_shape_; }
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/// This function will disable normalize in preprocessing step.
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void DisableNormalize() { disable_permute_ = true; }
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/// This function will disable hwc2chw in preprocessing step.
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void DisablePermute() { disable_normalize_ = true; }
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private:
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// for recording the switch of hwc2chw
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bool disable_permute_ = false;
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// for recording the switch of normalize
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bool disable_normalize_ = false;
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std::vector<int> rec_image_shape_ = {3, 48, 320};
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std::vector<float> mean_ = {0.5f, 0.5f, 0.5f};
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std::vector<float> scale_ = {0.5f, 0.5f, 0.5f};
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bool is_scale_ = true;
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bool static_shape_infer_ = false;
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};
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} // namespace ocr
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} // namespace vision
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} // namespace fastdeploy
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