// 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. #pragma once #include "fastdeploy/utils/utils.h" #include "fastdeploy/vision/common/processors/mat.h" #include "fastdeploy/vision/common/processors/mat_batch.h" #include "fastdeploy/vision/common/processors/base.h" namespace fastdeploy { namespace vision { /*! @brief ProcessorManager for Preprocess */ class FASTDEPLOY_DECL ProcessorManager { public: ~ProcessorManager(); /** \brief Use CUDA to boost the performance of processors * * \param[in] enable_cv_cuda ture: use CV-CUDA, false: use CUDA only * \param[in] gpu_id GPU device id * \return true if the preprocess successed, otherwise false */ void UseCuda(bool enable_cv_cuda = false, int gpu_id = -1); bool CudaUsed(); #ifdef WITH_GPU cudaStream_t Stream() const { return stream_; } #endif void SetStream(FDMat* mat) { #ifdef WITH_GPU mat->SetStream(stream_); #endif } void SetStream(FDMatBatch* mat_batch) { #ifdef WITH_GPU mat_batch->SetStream(stream_); #endif } void SyncStream() { #ifdef WITH_GPU FDASSERT(cudaStreamSynchronize(stream_) == cudaSuccess, "[ERROR] Error occurs while sync cuda stream."); #endif } int DeviceId() { return device_id_; } /** \brief Process the input images and prepare input tensors for runtime * * \param[in] images The input image data list, all the elements are returned by cv::imread() * \param[in] outputs The output tensors which will feed in runtime * \return true if the preprocess successed, otherwise false */ bool Run(std::vector* images, std::vector* outputs); /** \brief Apply() is the body of Run() function, it needs to be implemented by a derived class * * \param[in] image_batch The input image batch * \param[in] outputs The output tensors which will feed in runtime * \return true if the preprocess successed, otherwise false */ virtual bool Apply(FDMatBatch* image_batch, std::vector* outputs) = 0; void PreApply(FDMatBatch* image_batch); void PostApply(); protected: ProcLib proc_lib_ = ProcLib::DEFAULT; private: #ifdef WITH_GPU cudaStream_t stream_ = nullptr; #endif int device_id_ = -1; std::vector input_caches_; std::vector output_caches_; FDTensor batch_input_cache_; FDTensor batch_output_cache_; }; } // namespace vision } // namespace fastdeploy