mirror of
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103 lines
3.3 KiB
C++
103 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/center_crop.h"
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namespace fastdeploy {
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namespace vision {
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bool CenterCrop::ImplByOpenCV(FDMat* mat) {
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cv::Mat* im = mat->GetOpenCVMat();
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int height = static_cast<int>(im->rows);
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int width = static_cast<int>(im->cols);
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if (height < height_ || width < width_) {
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FDERROR << "[CenterCrop] Image size less than crop size" << std::endl;
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return false;
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}
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int offset_x = static_cast<int>((width - width_) / 2);
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int offset_y = static_cast<int>((height - height_) / 2);
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cv::Rect crop_roi(offset_x, offset_y, width_, height_);
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cv::Mat new_im = (*im)(crop_roi).clone();
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mat->SetMat(new_im);
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mat->SetWidth(width_);
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mat->SetHeight(height_);
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return true;
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}
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#ifdef ENABLE_FLYCV
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bool CenterCrop::ImplByFlyCV(FDMat* mat) {
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fcv::Mat* im = mat->GetFlyCVMat();
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int height = static_cast<int>(im->height());
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int width = static_cast<int>(im->width());
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if (height < height_ || width < width_) {
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FDERROR << "[CenterCrop] Image size less than crop size" << std::endl;
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return false;
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}
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int offset_x = static_cast<int>((width - width_) / 2);
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int offset_y = static_cast<int>((height - height_) / 2);
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fcv::Rect crop_roi(offset_x, offset_y, width_, height_);
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fcv::Mat new_im;
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fcv::crop(*im, new_im, crop_roi);
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mat->SetMat(new_im);
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mat->SetWidth(width_);
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mat->SetHeight(height_);
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return true;
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}
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#endif
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#ifdef ENABLE_CVCUDA
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bool CenterCrop::ImplByCvCuda(FDMat* mat) {
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// Prepare input tensor
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FDTensor* src = CreateCachedGpuInputTensor(mat);
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auto src_tensor = CreateCvCudaTensorWrapData(*src);
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// Prepare output tensor
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mat->output_cache->Resize({height_, width_, mat->Channels()}, src->Dtype(),
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"output_cache", Device::GPU);
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auto dst_tensor = CreateCvCudaTensorWrapData(*(mat->output_cache));
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int offset_x = static_cast<int>((mat->Width() - width_) / 2);
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int offset_y = static_cast<int>((mat->Height() - height_) / 2);
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NVCVRectI crop_roi = {offset_x, offset_y, width_, height_};
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cvcuda_crop_op_(mat->Stream(), *src_tensor, *dst_tensor, crop_roi);
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mat->SetTensor(mat->output_cache);
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mat->SetWidth(width_);
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mat->SetHeight(height_);
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mat->device = Device::GPU;
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mat->mat_type = ProcLib::CVCUDA;
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return true;
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}
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bool CenterCrop::ImplByCvCuda(FDMatBatch* mat_batch) {
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for (size_t i = 0; i < mat_batch->mats->size(); ++i) {
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if (ImplByCvCuda(&((*(mat_batch->mats))[i])) != true) {
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return false;
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}
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}
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mat_batch->device = Device::GPU;
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mat_batch->mat_type = ProcLib::CVCUDA;
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return true;
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}
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#endif
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bool CenterCrop::Run(FDMat* mat, const int& width, const int& height,
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ProcLib lib) {
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auto c = CenterCrop(width, height);
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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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