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https://github.com/PaddlePaddle/FastDeploy.git
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143506b654
* change ocr pre and post * add pybind * change ocr * fix bug * fix bug * fix bug * fix bug * fix bug * fix bug * fix copy bug * fix code style * fix bug * add new function * fix windows ci bug
100 lines
3.0 KiB
C++
100 lines
3.0 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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#include "fastdeploy/vision/ocr/ppocr/rec_preprocessor.h"
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#include "fastdeploy/utils/perf.h"
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#include "fastdeploy/vision/ocr/ppocr/utils/ocr_utils.h"
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#include "fastdeploy/function/concat.h"
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namespace fastdeploy {
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namespace vision {
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namespace ocr {
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RecognizerPreprocessor::RecognizerPreprocessor() {
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initialized_ = true;
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}
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void OcrRecognizerResizeImage(FDMat* mat, float max_wh_ratio,
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const std::vector<int>& rec_image_shape) {
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int imgC, imgH, imgW;
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imgC = rec_image_shape[0];
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imgH = rec_image_shape[1];
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imgW = rec_image_shape[2];
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imgW = int(imgH * max_wh_ratio);
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float ratio = float(mat->Width()) / float(mat->Height());
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int resize_w;
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if (ceilf(imgH * ratio) > imgW) {
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resize_w = imgW;
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}else{
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resize_w = int(ceilf(imgH * ratio));
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}
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Resize::Run(mat, resize_w, imgH);
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std::vector<float> value = {0, 0, 0};
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Pad::Run(mat, 0, 0, 0, int(imgW - mat->Width()), value);
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}
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bool RecognizerPreprocessor::Run(std::vector<FDMat>* images, std::vector<FDTensor>* outputs) {
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if (!initialized_) {
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FDERROR << "The preprocessor is not initialized." << std::endl;
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return false;
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}
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if (images->size() == 0) {
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FDERROR << "The size of input images should be greater than 0." << std::endl;
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return false;
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}
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int imgH = rec_image_shape_[1];
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int imgW = rec_image_shape_[2];
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float max_wh_ratio = imgW * 1.0 / imgH;
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float ori_wh_ratio;
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for (size_t i = 0; i < images->size(); ++i) {
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FDMat* mat = &(images->at(i));
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ori_wh_ratio = mat->Width() * 1.0 / mat->Height();
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max_wh_ratio = std::max(max_wh_ratio, ori_wh_ratio);
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}
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for (size_t i = 0; i < images->size(); ++i) {
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FDMat* mat = &(images->at(i));
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OcrRecognizerResizeImage(mat, max_wh_ratio, rec_image_shape_);
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NormalizeAndPermute::Run(mat, mean_, scale_, is_scale_);
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/*
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Normalize::Run(mat, mean_, scale_, is_scale_);
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HWC2CHW::Run(mat);
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Cast::Run(mat, "float");
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*/
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}
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// Only have 1 output Tensor.
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outputs->resize(1);
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// Concat all the preprocessed data to a batch tensor
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std::vector<FDTensor> tensors(images->size());
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for (size_t i = 0; i < images->size(); ++i) {
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(*images)[i].ShareWithTensor(&(tensors[i]));
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tensors[i].ExpandDim(0);
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}
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if (tensors.size() == 1) {
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(*outputs)[0] = std::move(tensors[0]);
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} else {
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function::Concat(tensors, &((*outputs)[0]), 0);
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}
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return true;
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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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