mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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121 lines
3.4 KiB
C++
121 lines
3.4 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/common/processors/mat.h"
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#include "fastdeploy/utils/utils.h"
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namespace fastdeploy {
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namespace vision {
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#ifdef ENABLE_OPENCV_CUDA
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cv::cuda::GpuMat* Mat::GetGpuMat() {
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if (device == Device::CPU) {
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gpu_mat.upload(cpu_mat);
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}
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return &gpu_mat;
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}
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#endif
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cv::Mat* Mat::GetCpuMat() {
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#ifdef ENABLE_OPENCV_CUDA
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if (device == Device::GPU) {
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gpu_mat.download(cpu_mat);
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}
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#endif
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return &cpu_mat;
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}
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void Mat::ShareWithTensor(FDTensor* tensor) {
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if (device == Device::GPU) {
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#ifdef ENABLE_OPENCV_CUDA
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tensor->SetExternalData({Channels(), Height(), Width()}, Type(),
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GetGpuMat()->ptr());
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tensor->device = Device::GPU;
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#endif
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} else {
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tensor->SetExternalData({Channels(), Height(), Width()}, Type(),
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GetCpuMat()->ptr());
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tensor->device = Device::CPU;
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}
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if (layout == Layout::HWC) {
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tensor->shape = {Height(), Width(), Channels()};
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}
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}
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bool Mat::CopyToTensor(FDTensor* tensor) {
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cv::Mat* im = GetCpuMat();
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int total_bytes = im->total() * im->elemSize();
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if (total_bytes != tensor->Nbytes()) {
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FDERROR << "While copy Mat to Tensor, requires the memory size be same, "
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"but now size of Tensor = "
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<< tensor->Nbytes() << ", size of Mat = " << total_bytes << "."
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<< std::endl;
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return false;
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}
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memcpy(tensor->MutableData(), im->ptr(), im->total() * im->elemSize());
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return true;
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}
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void Mat::PrintInfo(const std::string& flag) {
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cv::Mat* im = GetCpuMat();
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cv::Scalar mean = cv::mean(*im);
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std::cout << flag << ": "
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<< "Channel=" << Channels() << ", height=" << Height()
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<< ", width=" << Width() << ", mean=";
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for (int i = 0; i < Channels(); ++i) {
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std::cout << mean[i] << " ";
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}
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std::cout << std::endl;
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}
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FDDataType Mat::Type() {
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int type = -1;
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if (device == Device::GPU) {
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#ifdef ENABLE_OPENCV_CUDA
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type = gpu_mat.type();
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#endif
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} else {
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type = cpu_mat.type();
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}
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if (type < 0) {
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FDASSERT(false,
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"While calling Mat::Type(), get negative value, which is not "
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"expected!.");
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}
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type = type % 8;
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if (type == 0) {
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return FDDataType::UINT8;
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} else if (type == 1) {
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return FDDataType::INT8;
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} else if (type == 2) {
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FDASSERT(false,
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"While calling Mat::Type(), get UINT16 type which is not "
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"supported now.");
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} else if (type == 3) {
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return FDDataType::INT16;
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} else if (type == 4) {
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return FDDataType::INT32;
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} else if (type == 5) {
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return FDDataType::FP32;
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} else if (type == 6) {
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return FDDataType::FP64;
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} else {
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FDASSERT(
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false,
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"While calling Mat::Type(), get type = %d, which is not expected!.",
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type);
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}
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}
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} // namespace vision
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} // namespace fastdeploy
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