Files
FastDeploy/fastdeploy/vision/common/processors/mat.cc
Wang Xinyu cb7c8a07d4 [CVCUDA] PaddleDetection preprocessor support CV-CUDA (#1493)
* ppdet preproc use manager

* pad_to_size chw opencv

* pad_to_size chw flycv

* fix pad_to_size flycv

* add warning message

* cvcuda convert cubic to linear, padToSize cvcuda

* stridedpad cvcuda

* fix flycv include

* fix flycv include

* fix flycv build

* cast cvcuda

* fix pybind

* fix normalize permute cuda

* base processor move funcs to cc

* Update pad_to_size.cc
2023-03-10 12:43:57 +08:00

338 lines
10 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/mat.h"
#include "fastdeploy/utils/utils.h"
#include "fastdeploy/vision/common/processors/utils.h"
namespace fastdeploy {
namespace vision {
cv::Mat* Mat::GetOpenCVMat() {
if (mat_type == ProcLib::OPENCV) {
return &cpu_mat;
} else if (mat_type == ProcLib::FLYCV) {
#ifdef ENABLE_FLYCV
// Just a reference to fcv_mat, zero copy. After you
// call this method, cpu_mat and fcv_mat will point
// to the same memory buffer.
cpu_mat = ConvertFlyCVMatToOpenCV(fcv_mat);
mat_type = ProcLib::OPENCV;
return &cpu_mat;
#else
FDASSERT(false, "FastDeploy didn't compiled with FlyCV!");
#endif
} else if (mat_type == ProcLib::CUDA || mat_type == ProcLib::CVCUDA) {
#ifdef WITH_GPU
FDASSERT(cudaStreamSynchronize(stream) == cudaSuccess,
"[ERROR] Error occurs while sync cuda stream.");
cpu_mat = CreateZeroCopyOpenCVMatFromTensor(*fd_tensor, layout);
mat_type = ProcLib::OPENCV;
device = Device::CPU;
return &cpu_mat;
#else
FDASSERT(false, "FastDeploy didn't compiled with -DWITH_GPU=ON");
#endif
} else {
FDASSERT(false, "The mat_type of custom Mat can not be ProcLib::DEFAULT");
}
}
#ifdef ENABLE_FLYCV
fcv::Mat* Mat::GetFlyCVMat() {
if (mat_type == ProcLib::FLYCV) {
return &fcv_mat;
} else if (mat_type == ProcLib::OPENCV) {
// Just a reference to cpu_mat, zero copy. After you
// call this method, fcv_mat and cpu_mat will point
// to the same memory buffer.
fcv_mat = ConvertOpenCVMatToFlyCV(cpu_mat);
mat_type = ProcLib::FLYCV;
return &fcv_mat;
} else {
FDASSERT(false, "The mat_type of custom Mat can not be ProcLib::DEFAULT");
}
}
#endif
void* Mat::Data() {
if (mat_type == ProcLib::FLYCV) {
#ifdef ENABLE_FLYCV
return fcv_mat.data();
#else
FDASSERT(false,
"FastDeploy didn't compile with FlyCV, but met data type with "
"fcv::Mat.");
#endif
} else if (device == Device::GPU) {
return fd_tensor->Data();
}
return cpu_mat.ptr();
}
FDTensor* Mat::Tensor() {
if (mat_type == ProcLib::OPENCV) {
ShareWithTensor(fd_tensor.get());
} else if (mat_type == ProcLib::FLYCV) {
#ifdef ENABLE_FLYCV
cpu_mat = ConvertFlyCVMatToOpenCV(fcv_mat);
mat_type = ProcLib::OPENCV;
ShareWithTensor(fd_tensor.get());
#else
FDASSERT(false, "FastDeploy didn't compiled with FlyCV!");
#endif
}
return fd_tensor.get();
}
void Mat::SetTensor(FDTensor* tensor) {
fd_tensor->SetExternalData(tensor->Shape(), tensor->Dtype(), tensor->Data(),
tensor->device, tensor->device_id);
device = tensor->device;
if (layout == Layout::HWC) {
height = tensor->Shape()[0];
width = tensor->Shape()[1];
channels = tensor->Shape()[2];
} else if (layout == Layout::CHW) {
channels = tensor->Shape()[0];
height = tensor->Shape()[1];
width = tensor->Shape()[2];
}
}
void Mat::SetTensor(std::shared_ptr<FDTensor>& tensor) {
fd_tensor = tensor;
device = tensor->device;
if (layout == Layout::HWC) {
height = tensor->Shape()[0];
width = tensor->Shape()[1];
channels = tensor->Shape()[2];
} else if (layout == Layout::CHW) {
channels = tensor->Shape()[0];
height = tensor->Shape()[1];
width = tensor->Shape()[2];
}
}
void Mat::ShareWithTensor(FDTensor* tensor) {
tensor->SetExternalData({Channels(), Height(), Width()}, Type(), Data());
tensor->device = device;
if (layout == Layout::HWC) {
tensor->shape = {Height(), Width(), Channels()};
}
}
bool Mat::CopyToTensor(FDTensor* tensor) {
int total_bytes = Height() * Width() * Channels() * FDDataTypeSize(Type());
if (total_bytes != tensor->Nbytes()) {
FDERROR << "While copy Mat to Tensor, requires the memory size be same, "
"but now size of Tensor = "
<< tensor->Nbytes() << ", size of Mat = " << total_bytes << "."
<< std::endl;
return false;
}
memcpy(tensor->MutableData(), Data(), total_bytes);
return true;
}
void Mat::PrintInfo(const std::string& flag) {
std::cout << flag << ": "
<< "DataType=" << Type() << ", "
<< "Channel=" << Channels() << ", "
<< "Height=" << Height() << ", "
<< "Width=" << Width() << ", "
<< "Mean=";
if (mat_type == ProcLib::FLYCV) {
#ifdef ENABLE_FLYCV
fcv::Scalar mean = fcv::mean(fcv_mat);
for (int i = 0; i < Channels(); ++i) {
std::cout << mean[i] << " ";
}
std::cout << std::endl;
#else
FDASSERT(false,
"FastDeploy didn't compile with FlyCV, but met data type with "
"fcv::Mat.");
#endif
} else if (mat_type == ProcLib::OPENCV) {
cv::Scalar mean = cv::mean(cpu_mat);
for (int i = 0; i < Channels(); ++i) {
std::cout << mean[i] << " ";
}
std::cout << std::endl;
} else if (mat_type == ProcLib::CUDA || mat_type == ProcLib::CVCUDA) {
#ifdef WITH_GPU
FDASSERT(cudaStreamSynchronize(stream) == cudaSuccess,
"[ERROR] Error occurs while sync cuda stream.");
cv::Mat tmp_mat = CreateZeroCopyOpenCVMatFromTensor(*fd_tensor, layout);
cv::Scalar mean = cv::mean(tmp_mat);
for (int i = 0; i < Channels(); ++i) {
std::cout << mean[i] << " ";
}
std::cout << std::endl;
#else
FDASSERT(false, "FastDeploy didn't compiled with -DWITH_GPU=ON");
#endif
}
}
FDDataType Mat::Type() {
int type = -1;
if (mat_type == ProcLib::FLYCV) {
#ifdef ENABLE_FLYCV
return FlyCVDataTypeToFD(fcv_mat.type());
#else
FDASSERT(false,
"FastDeploy didn't compile with FlyCV, but met data type with "
"fcv::Mat.");
#endif
} else if (mat_type == ProcLib::CUDA || mat_type == ProcLib::CVCUDA) {
return fd_tensor->Dtype();
}
return OpenCVDataTypeToFD(cpu_mat.type());
}
Mat Mat::Create(const FDTensor& tensor) {
if (DefaultProcLib::default_lib == ProcLib::FLYCV) {
#ifdef ENABLE_FLYCV
fcv::Mat tmp_fcv_mat = CreateZeroCopyFlyCVMatFromTensor(tensor);
Mat mat = Mat(tmp_fcv_mat);
return mat;
#else
FDASSERT(false, "FastDeploy didn't compiled with FlyCV!");
#endif
}
cv::Mat tmp_ocv_mat = CreateZeroCopyOpenCVMatFromTensor(tensor);
Mat mat = Mat(tmp_ocv_mat);
return mat;
}
Mat Mat::Create(const FDTensor& tensor, ProcLib lib) {
if (lib == ProcLib::DEFAULT) {
return Create(tensor);
}
if (lib == ProcLib::FLYCV) {
#ifdef ENABLE_FLYCV
fcv::Mat tmp_fcv_mat = CreateZeroCopyFlyCVMatFromTensor(tensor);
Mat mat = Mat(tmp_fcv_mat);
return mat;
#else
FDASSERT(false, "FastDeploy didn't compiled with FlyCV!");
#endif
}
cv::Mat tmp_ocv_mat = CreateZeroCopyOpenCVMatFromTensor(tensor);
Mat mat = Mat(tmp_ocv_mat);
return mat;
}
Mat Mat::Create(int height, int width, int channels, FDDataType type,
void* data) {
if (DefaultProcLib::default_lib == ProcLib::FLYCV) {
#ifdef ENABLE_FLYCV
fcv::Mat tmp_fcv_mat =
CreateZeroCopyFlyCVMatFromBuffer(height, width, channels, type, data);
Mat mat = Mat(tmp_fcv_mat);
return mat;
#else
FDASSERT(false, "FastDeploy didn't compiled with FlyCV!");
#endif
}
cv::Mat tmp_ocv_mat =
CreateZeroCopyOpenCVMatFromBuffer(height, width, channels, type, data);
Mat mat = Mat(tmp_ocv_mat);
return mat;
}
Mat Mat::Create(int height, int width, int channels, FDDataType type,
void* data, ProcLib lib) {
if (lib == ProcLib::DEFAULT) {
return Create(height, width, channels, type, data);
}
if (lib == ProcLib::FLYCV) {
#ifdef ENABLE_FLYCV
fcv::Mat tmp_fcv_mat =
CreateZeroCopyFlyCVMatFromBuffer(height, width, channels, type, data);
Mat mat = Mat(tmp_fcv_mat);
return mat;
#else
FDASSERT(false, "FastDeploy didn't compiled with FlyCV!");
#endif
}
cv::Mat tmp_ocv_mat =
CreateZeroCopyOpenCVMatFromBuffer(height, width, channels, type, data);
Mat mat = Mat(tmp_ocv_mat);
return mat;
}
FDMat WrapMat(const cv::Mat& image) {
FDMat mat(image);
return mat;
}
std::vector<FDMat> WrapMat(const std::vector<cv::Mat>& images) {
std::vector<FDMat> mats;
for (size_t i = 0; i < images.size(); ++i) {
mats.emplace_back(FDMat(images[i]));
}
return mats;
}
bool CheckShapeConsistency(std::vector<Mat>* mats) {
if (mats == nullptr) {
return true;
}
for (size_t i = 1; i < mats->size(); ++i) {
if ((*mats)[i].Channels() != (*mats)[0].Channels() ||
(*mats)[i].Width() != (*mats)[0].Width() ||
(*mats)[i].Height() != (*mats)[0].Height()) {
return false;
}
}
return true;
}
FDTensor* CreateCachedGpuInputTensor(Mat* mat) {
#ifdef WITH_GPU
FDTensor* src = mat->Tensor();
// Need to make sure the tensor is pointed to the input_cache.
if (src->Data() == mat->output_cache->Data()) {
std::swap(mat->input_cache, mat->output_cache);
std::swap(mat->input_cache->name, mat->output_cache->name);
}
if (src->device == Device::GPU) {
return src;
} else if (src->device == Device::CPU) {
// Tensor on CPU, we need copy it from CPU to GPU
FDASSERT(src->Shape().size() == 3, "The CPU tensor must has 3 dims.")
mat->output_cache->Resize(src->Shape(), src->Dtype(), "output_cache",
Device::GPU);
FDASSERT(
cudaMemcpyAsync(mat->output_cache->Data(), src->Data(), src->Nbytes(),
cudaMemcpyHostToDevice, mat->Stream()) == 0,
"[ERROR] Error occurs while copy memory from CPU to GPU.");
std::swap(mat->input_cache, mat->output_cache);
std::swap(mat->input_cache->name, mat->output_cache->name);
return mat->input_cache;
} else {
FDASSERT(false, "FDMat is on unsupported device: %d", src->device);
}
#else
FDASSERT(false, "FastDeploy didn't compile with WITH_GPU.");
#endif
return nullptr;
}
} // namespace vision
} // namespace fastdeploy