mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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101 lines
3.3 KiB
C++
101 lines
3.3 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/pad.h"
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namespace fastdeploy {
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namespace vision {
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bool Pad::CpuRun(Mat* mat) {
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if (mat->layout != Layout::HWC) {
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FDERROR << "Pad: The input data must be Layout::HWC format!" << std::endl;
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return false;
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}
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if (mat->Channels() > 4) {
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FDERROR << "Pad: Only support channels <= 4." << std::endl;
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return false;
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}
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if (mat->Channels() != value_.size()) {
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FDERROR << "Pad: Require input channels equals to size of padding value, "
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"but now channels = "
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<< mat->Channels()
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<< ", the size of padding values = " << value_.size() << "."
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<< std::endl;
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return false;
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}
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cv::Mat* im = mat->GetCpuMat();
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cv::Scalar value;
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if (value_.size() == 1) {
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value = cv::Scalar(value_[0]);
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} else if (value_.size() == 2) {
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value = cv::Scalar(value_[0], value_[1]);
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} else if (value_.size() == 3) {
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value = cv::Scalar(value_[0], value_[1], value_[2]);
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} else {
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value = cv::Scalar(value_[0], value_[1], value_[2], value_[3]);
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}
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cv::copyMakeBorder(*im, *im, top_, bottom_, left_, right_,
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cv::BORDER_CONSTANT, value);
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mat->SetHeight(im->rows);
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mat->SetWidth(im->cols);
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return true;
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}
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#ifdef ENABLE_OPENCV_CUDA
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bool Pad::GpuRun(Mat* mat) {
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if (mat->layout != Layout::HWC) {
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FDERROR << "Pad: The input data must be Layout::HWC format!" << std::endl;
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return false;
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}
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if (mat->Channels() > 4) {
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FDERROR << "Pad: Only support channels <= 4." << std::endl;
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return false;
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}
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if (mat->Channels() != value_.size()) {
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FDERROR << "Pad: Require input channels equals to size of padding value, "
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"but now channels = "
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<< mat->Channels()
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<< ", the size of padding values = " << value_.size() << "."
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<< std::endl;
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return false;
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}
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cv::cuda::GpuMat* im = mat->GetGpuMat();
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cv::Scalar value;
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if (value_.size() == 1) {
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value = cv::Scalar(value_[0]);
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} else if (value_.size() == 2) {
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value = cv::Scalar(value_[0], value_[1]);
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} else if (value_.size() == 3) {
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value = cv::Scalar(value_[0], value_[1], value_[2]);
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} else {
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value = cv::Scalar(value_[0], value_[1], value_[2], value_[3]);
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}
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cv::cuda::copyMakeBorder(*im, *im, top_, bottom_, left_, right_,
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cv::BORDER_CONSTANT, value);
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mat->SetHeight(im->rows);
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mat->SetWidth(im->cols);
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return true;
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}
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#endif
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bool Pad::Run(Mat* mat, const int& top, const int& bottom, const int& left,
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const int& right, const std::vector<float>& value,
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ProcLib lib) {
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auto p = Pad(top, bottom, left, right, value);
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return p(mat, lib);
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}
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} // namespace vision
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} // namespace fastdeploy
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