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https://github.com/PaddlePaddle/FastDeploy.git
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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>
106 lines
3.7 KiB
C++
106 lines
3.7 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/structurev2_table_preprocessor.h"
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#include "fastdeploy/function/concat.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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namespace fastdeploy {
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namespace vision {
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namespace ocr {
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StructureV2TablePreprocessor::StructureV2TablePreprocessor() {
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resize_op_ = std::make_shared<Resize>(-1, -1);
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std::vector<float> value = {0, 0, 0};
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pad_op_ = std::make_shared<Pad>(0, 0, 0, 0, value);
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std::vector<float> mean = {0.485f, 0.456f, 0.406f};
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std::vector<float> std = {0.229f, 0.224f, 0.225f};
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normalize_op_ = std::make_shared<Normalize>(mean, std, true);
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hwc2chw_op_ = std::make_shared<HWC2CHW>();
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}
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void StructureV2TablePreprocessor::StructureV2TableResizeImage(FDMat* mat,
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int batch_idx) {
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float img_h = float(rec_image_shape_[1]);
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float img_w = float(rec_image_shape_[2]);
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float width = float(mat->Width());
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float height = float(mat->Height());
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float ratio = max_len / (std::max(height, width) * 1.0);
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int resize_h = int(height * ratio);
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int resize_w = int(width * ratio);
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resize_op_->SetWidthAndHeight(resize_w, resize_h);
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(*resize_op_)(mat);
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(*normalize_op_)(mat);
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pad_op_->SetPaddingSize(0, int(max_len - resize_h), 0,
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int(max_len - resize_w));
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(*pad_op_)(mat);
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(*hwc2chw_op_)(mat);
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batch_det_img_info_[batch_idx] = {int(width), int(height), resize_w,
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resize_h};
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}
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bool StructureV2TablePreprocessor::Run(std::vector<FDMat>* images,
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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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if (images->size() == 0 || end_index <= start_index ||
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end_index > images->size()) {
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FDERROR << "images->size() or index error. Correct is: 0 <= start_index < "
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"end_index <= images->size()"
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<< std::endl;
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return false;
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}
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std::vector<FDMat> mats(end_index - start_index);
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for (size_t i = start_index; i < end_index; ++i) {
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size_t real_index = i;
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if (indices.size() != 0) {
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real_index = indices[i];
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}
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mats[i - start_index] = images->at(real_index);
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}
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return Run(&mats, outputs);
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}
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bool StructureV2TablePreprocessor::Apply(FDMatBatch* image_batch,
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std::vector<FDTensor>* outputs) {
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batch_det_img_info_.clear();
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batch_det_img_info_.resize(image_batch->mats->size());
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for (size_t i = 0; i < image_batch->mats->size(); ++i) {
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FDMat* mat = &(image_batch->mats->at(i));
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StructureV2TableResizeImage(mat, i);
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}
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// Only have 1 output Tensor.
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outputs->resize(1);
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// Get the NCHW tensor
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FDTensor* tensor = image_batch->Tensor();
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(*outputs)[0].SetExternalData(tensor->Shape(), tensor->Dtype(),
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tensor->Data(), tensor->device,
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tensor->device_id);
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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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