mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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d3845eb4e1
* avoid mem copy for cpp benchmark * set CMAKE_BUILD_TYPE to Release * Add SegmentationDiff * change pointer to reference * fixed bug * cast uint8 to int32 * Add diff compare for OCR * Add diff compare for OCR * rm ppocr pipeline * Add yolov5 diff compare * Add yolov5 diff compare * deal with comments * deal with comments * fixed bug * fixed bug
77 lines
2.4 KiB
C++
77 lines
2.4 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/faceid/contrib/adaface/preprocessor.h"
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namespace fastdeploy {
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namespace vision {
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namespace faceid {
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AdaFacePreprocessor::AdaFacePreprocessor() {
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// parameters for preprocess
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size_ = {112, 112};
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alpha_ = {1.f / 127.5f, 1.f / 127.5f, 1.f / 127.5f};
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beta_ = {-1.f, -1.f, -1.f}; // RGB
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permute_ = true;
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}
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bool AdaFacePreprocessor::Preprocess(FDMat* mat, FDTensor* output) {
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// face recognition model's preprocess steps in insightface
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// reference: insightface/recognition/arcface_torch/inference.py
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// 1. Resize
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// 2. BGR2RGB
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// 3. Convert(opencv style) or Normalize
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// 4. HWC2CHW
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int resize_w = size_[0];
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int resize_h = size_[1];
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if (resize_h != mat->Height() || resize_w != mat->Width()) {
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Resize::Run(mat, resize_w, resize_h);
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}
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if (permute_) {
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BGR2RGB::Run(mat);
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}
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Convert::Run(mat, alpha_, beta_);
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HWC2CHW::Run(mat);
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Cast::Run(mat, "float");
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mat->ShareWithTensor(output);
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output->ExpandDim(0); // reshape to n, c, h, w
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return true;
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}
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bool AdaFacePreprocessor::Run(std::vector<FDMat>* images,
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std::vector<FDTensor>* outputs) {
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if (images->empty()) {
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FDERROR << "The size of input images should be greater than 0."
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<< std::endl;
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return false;
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}
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FDASSERT(images->size() == 1, "Only support batch = 1 now.");
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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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if (!Preprocess(&(*images)[i], &tensors[i])) {
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FDERROR << "Failed to preprocess input image." << std::endl;
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return false;
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}
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}
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(*outputs)[0] = std::move(tensors[0]);
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return true;
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}
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} // namespace faceid
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} // namespace vision
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} // namespace fastdeploy
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