mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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a36d49a973
* [Backend] fix lite backend save model error * [Backend] fixed typos * [FlyCV] optimize the integration of FlyCV * [cmake] close some tests options * [cmake] close some test option * [FlyCV] remove un-need warnings * [FlyCV] remove un-need GetMat method * [FlyCV] optimize FlyCV codes * [cmake] remove un-need cmake function in examples/CMakelists * [cmake] support gflags for Android
68 lines
2.2 KiB
C++
68 lines
2.2 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/common/processors/convert.h"
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namespace fastdeploy {
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namespace vision {
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Convert::Convert(const std::vector<float>& alpha,
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const std::vector<float>& beta) {
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FDASSERT(alpha.size() == beta.size(),
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"Convert: requires the size of alpha equal to the size of beta.");
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FDASSERT(alpha.size() != 0,
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"Convert: requires the size of alpha and beta > 0.");
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alpha_.assign(alpha.begin(), alpha.end());
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beta_.assign(beta.begin(), beta.end());
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}
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bool Convert::ImplByOpenCV(Mat* mat) {
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cv::Mat* im = mat->GetOpenCVMat();
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std::vector<cv::Mat> split_im;
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cv::split(*im, split_im);
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for (int c = 0; c < im->channels(); c++) {
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split_im[c].convertTo(split_im[c], CV_32FC1, alpha_[c], beta_[c]);
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}
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cv::merge(split_im, *im);
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return true;
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}
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#ifdef ENABLE_FLYCV
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bool Convert::ImplByFlyCV(Mat* mat) {
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fcv::Mat* im = mat->GetFlyCVMat();
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FDASSERT(im->channels() == 3, "Only support 3-channels image in FlyCV.");
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std::vector<float> mean(3, 0);
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std::vector<float> std(3, 0);
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for (size_t i = 0; i < 3; ++i) {
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std[i] = 1.0 / alpha_[i];
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mean[i] = -1 * beta_[i] * std[i];
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}
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fcv::Mat new_im;
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fcv::normalize_to_submean_to_reorder(*im, mean, std, std::vector<uint32_t>(),
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new_im, true);
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mat->SetMat(new_im);
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return true;
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}
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#endif
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bool Convert::Run(Mat* mat, const std::vector<float>& alpha,
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const std::vector<float>& beta, ProcLib lib) {
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auto c = Convert(alpha, beta);
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return c(mat, lib);
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}
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} // namespace vision
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} // namespace fastdeploy
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