mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-31 20:02:53 +08:00
a36f5d3396
* cuda normalize and permute, cuda concat * add use cuda option for preprocessor * ppyoloe use cuda normalize * ppseg use cuda normalize * add proclib cuda in processor base * ppcls add use cuda preprocess api * ppcls preprocessor set gpu id * fix pybind * refine ppcls preprocessing use gpu logic * fdtensor device id is -1 by default * refine assert message Co-authored-by: heliqi <1101791222@qq.com>
86 lines
2.6 KiB
C++
86 lines
2.6 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/base.h"
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#include "fastdeploy/vision/common/processors/proc_lib.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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bool Processor::operator()(Mat* mat, ProcLib lib) {
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ProcLib target = lib;
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if (lib == ProcLib::DEFAULT) {
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target = DefaultProcLib::default_lib;
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}
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if (target == ProcLib::FLYCV) {
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#ifdef ENABLE_FLYCV
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return ImplByFlyCV(mat);
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#else
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FDASSERT(false, "FastDeploy didn't compile with FlyCV.");
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#endif
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} else if (target == ProcLib::CUDA) {
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#ifdef WITH_GPU
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return ImplByCuda(mat);
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#else
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FDASSERT(false, "FastDeploy didn't compile with WITH_GPU.");
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#endif
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}
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// DEFAULT & OPENCV
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return ImplByOpenCV(mat);
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}
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FDTensor* Processor::UpdateAndGetReusedBuffer(
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const std::vector<int64_t>& new_shape, const int& opencv_dtype,
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const std::string& buffer_name, const Device& new_device,
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const bool& use_pinned_memory) {
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if (reused_buffers_.count(buffer_name) == 0) {
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reused_buffers_[buffer_name] = FDTensor();
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}
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reused_buffers_[buffer_name].is_pinned_memory = use_pinned_memory;
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reused_buffers_[buffer_name].Resize(new_shape,
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OpenCVDataTypeToFD(opencv_dtype),
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buffer_name, new_device);
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return &reused_buffers_[buffer_name];
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}
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void EnableFlyCV() {
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#ifdef ENABLE_FLYCV
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DefaultProcLib::default_lib = ProcLib::FLYCV;
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FDINFO << "Will change to use image processing library "
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<< DefaultProcLib::default_lib << std::endl;
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#else
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FDWARNING << "FastDeploy didn't compile with FlyCV, "
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"will fallback to use OpenCV instead."
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<< std::endl;
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#endif
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}
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void DisableFlyCV() {
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DefaultProcLib::default_lib = ProcLib::OPENCV;
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FDINFO << "Will change to use image processing library "
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<< DefaultProcLib::default_lib << std::endl;
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}
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void SetProcLibCpuNumThreads(int threads) {
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cv::setNumThreads(threads);
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#ifdef ENABLE_FLYCV
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fcv::set_thread_num(threads);
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#endif
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}
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} // namespace vision
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} // namespace fastdeploy
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