mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-08 01:50:27 +08:00
d3d914856d
* norm and permute batch processing * move cache to mat, batch processors * get batched tensor logic, resize on cpu logic * fix cpu compile error * remove vector mat api * nits * add comments * nits * fix batch size * move initial resize on cpu option to use_cuda api * fix pybind * processor manager pybind * rename mat and matbatch * move initial resize on cpu to ppcls preprocessor --------- Co-authored-by: Jason <jiangjiajun@baidu.com>
92 lines
2.6 KiB
C++
92 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/manager.h"
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namespace fastdeploy {
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namespace vision {
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ProcessorManager::~ProcessorManager() {
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#ifdef WITH_GPU
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if (stream_) cudaStreamDestroy(stream_);
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#endif
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}
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void ProcessorManager::UseCuda(bool enable_cv_cuda, int gpu_id) {
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#ifdef WITH_GPU
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if (gpu_id >= 0) {
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device_id_ = gpu_id;
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FDASSERT(cudaSetDevice(device_id_) == cudaSuccess,
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"[ERROR] Error occurs while setting cuda device.");
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}
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FDASSERT(cudaStreamCreate(&stream_) == cudaSuccess,
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"[ERROR] Error occurs while creating cuda stream.");
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DefaultProcLib::default_lib = ProcLib::CUDA;
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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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if (enable_cv_cuda) {
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#ifdef ENABLE_CVCUDA
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DefaultProcLib::default_lib = ProcLib::CVCUDA;
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#else
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FDASSERT(false, "FastDeploy didn't compile with CV-CUDA.");
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#endif
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}
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}
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bool ProcessorManager::CudaUsed() {
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return (DefaultProcLib::default_lib == ProcLib::CUDA ||
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DefaultProcLib::default_lib == ProcLib::CVCUDA);
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}
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bool ProcessorManager::Run(std::vector<FDMat>* images,
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std::vector<FDTensor>* outputs) {
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if (!initialized_) {
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FDERROR << "The preprocessor is not initialized." << std::endl;
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return false;
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}
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if (images->size() == 0) {
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FDERROR << "The size of input images should be greater than 0."
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<< std::endl;
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return false;
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}
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if (images->size() > input_caches_.size()) {
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input_caches_.resize(images->size());
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output_caches_.resize(images->size());
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}
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FDMatBatch image_batch(images);
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image_batch.input_cache = &batch_input_cache_;
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image_batch.output_cache = &batch_output_cache_;
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for (size_t i = 0; i < images->size(); ++i) {
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if (CudaUsed()) {
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SetStream(&image_batch);
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}
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(*images)[i].input_cache = &input_caches_[i];
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(*images)[i].output_cache = &output_caches_[i];
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}
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bool ret = Apply(&image_batch, outputs);
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if (CudaUsed()) {
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SyncStream();
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}
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return ret;
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}
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} // namespace vision
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} // namespace fastdeploy
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