mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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62e051e21d
* cvcuda resize * cvcuda center crop * cvcuda resize * add a fdtensor in fdmat * get cv mat and get tensor support gpu * paddleclas cvcuda preprocessor * fix compile err * fix windows compile error * rename reused to cached * address comment * remove debug code * add comment * add manager run * use cuda and cuda used * use cv cuda doc * address comment --------- Co-authored-by: Jason <jiangjiajun@baidu.com>
93 lines
3.1 KiB
C++
93 lines
3.1 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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#pragma once
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#include "fastdeploy/utils/utils.h"
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#include "fastdeploy/vision/common/processors/mat.h"
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#include "opencv2/highgui/highgui.hpp"
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#include "opencv2/imgproc/imgproc.hpp"
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#include <unordered_map>
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namespace fastdeploy {
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namespace vision {
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/*! @brief Enable using FlyCV to process image while deploy vision models.
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* Currently, FlyCV in only available on ARM(Linux aarch64/Android), so will
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* fallback to using OpenCV in other platform
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*/
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FASTDEPLOY_DECL void EnableFlyCV();
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/// Disable using FlyCV to process image while deploy vision models.
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FASTDEPLOY_DECL void DisableFlyCV();
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/*! @brief Set the cpu num threads of ProcLib.
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*/
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FASTDEPLOY_DECL void SetProcLibCpuNumThreads(int threads);
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class FASTDEPLOY_DECL Processor {
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public:
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// default_lib has the highest priority
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// all the function in `processor` will force to use
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// default_lib if this flag is set.
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// DEFAULT means this flag is not set
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// static ProcLib default_lib;
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virtual std::string Name() = 0;
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virtual bool ImplByOpenCV(Mat* mat) {
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FDERROR << Name() << " Not Implement Yet." << std::endl;
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return false;
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}
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virtual bool ImplByFlyCV(Mat* mat) {
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return ImplByOpenCV(mat);
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}
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virtual bool ImplByCuda(Mat* mat) {
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return ImplByOpenCV(mat);
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}
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virtual bool ImplByCvCuda(Mat* mat) {
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return ImplByOpenCV(mat);
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}
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virtual bool operator()(Mat* mat, ProcLib lib = ProcLib::DEFAULT);
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protected:
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// Update and get the cached tensor from the cached_tensors_ map.
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// The tensor is indexed by a string.
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// If the tensor doesn't exists in the map, then create a new tensor.
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// If the tensor exists and shape is getting larger, then realloc the buffer.
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// If the tensor exists and shape is not getting larger, then return the
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// cached tensor directly.
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FDTensor* UpdateAndGetCachedTensor(
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const std::vector<int64_t>& new_shape, const FDDataType& data_type,
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const std::string& tensor_name, const Device& new_device = Device::CPU,
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const bool& use_pinned_memory = false);
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// Create an input tensor on GPU and save into cached_tensors_.
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// If the Mat is on GPU, return the mat->Tensor() directly.
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// If the Mat is on CPU, then create a cached GPU tensor and copy the mat's
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// CPU tensor to this new GPU tensor.
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FDTensor* CreateCachedGpuInputTensor(Mat* mat,
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const std::string& tensor_name);
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private:
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std::unordered_map<std::string, FDTensor> cached_tensors_;
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};
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} // namespace vision
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} // namespace fastdeploy
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