mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-31 11:56:44 +08:00
76 lines
2.3 KiB
C++
76 lines
2.3 KiB
C++
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
|
|
//
|
|
// Licensed under the Apache License, Version 2.0 (the "License");
|
|
// you may not use this file except in compliance with the License.
|
|
// You may obtain a copy of the License at
|
|
//
|
|
// http://www.apache.org/licenses/LICENSE-2.0
|
|
//
|
|
// Unless required by applicable law or agreed to in writing, software
|
|
// distributed under the License is distributed on an "AS IS" BASIS,
|
|
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
// See the License for the specific language governing permissions and
|
|
// limitations under the License.
|
|
|
|
#include "fastdeploy/vision/common/processors/hwc2chw.h"
|
|
|
|
namespace fastdeploy {
|
|
namespace vision {
|
|
bool HWC2CHW::CpuRun(Mat* mat) {
|
|
if (mat->layout != Layout::HWC) {
|
|
FDERROR << "HWC2CHW: The input data is not Layout::HWC format!"
|
|
<< std::endl;
|
|
return false;
|
|
}
|
|
cv::Mat* im = mat->GetCpuMat();
|
|
cv::Mat im_clone = im->clone();
|
|
int rh = im->rows;
|
|
int rw = im->cols;
|
|
int rc = im->channels();
|
|
|
|
// float* data = reinterpret_cast<float*>(im->data);
|
|
for (int i = 0; i < rc; ++i) {
|
|
// cv::extractChannel(im_clone, cv::Mat(rh, rw, im->type() % 8, data + i
|
|
// * rh * rw),
|
|
// i);
|
|
cv::extractChannel(
|
|
im_clone,
|
|
cv::Mat(rh, rw, im->type() % 8,
|
|
im->ptr() + i * rh * rw * FDDataTypeSize(mat->Type())),
|
|
i);
|
|
}
|
|
mat->layout = Layout::CHW;
|
|
return true;
|
|
}
|
|
|
|
#ifdef ENABLE_OPENCV_CUDA
|
|
bool HWC2CHW::GpuRun(Mat* mat) {
|
|
if (mat->layout != Layout::HWC) {
|
|
FDERROR << "HWC2CHW: The input data is not Layout::HWC format!"
|
|
<< std::endl;
|
|
return false;
|
|
}
|
|
cv::cuda::GpuMat* im = mat->GetGpuMat();
|
|
cv::cuda::GpuMat im_clone = im->clone();
|
|
int rh = im->rows;
|
|
int rw = im->cols;
|
|
int rc = im->channels();
|
|
int num_pixels = rh * rw;
|
|
std::vector<cv::cuda::GpuMat> channels{
|
|
cv::cuda::GpuMat(rh, rw, im->type() % 8, &(im->ptr()[0])),
|
|
cv::cuda::GpuMat(rh, rw, im->type() % 8, &(im->ptr()[num_pixels])),
|
|
cv::cuda::GpuMat(rh, rw, im->type() % 8, &(im->ptr()[num_pixels * 2]))};
|
|
cv::cuda::split(im_clone, channels);
|
|
mat->layout = Layout::CHW;
|
|
return true;
|
|
}
|
|
#endif
|
|
|
|
bool HWC2CHW::Run(Mat* mat, ProcLib lib) {
|
|
auto h = HWC2CHW();
|
|
return h(mat, lib);
|
|
}
|
|
|
|
} // namespace vision
|
|
} // namespace fastdeploy
|