Files
FastDeploy/fastdeploy/vision/common/processors/normalize.h
DefTruth 89181042f5 Add yolox c++/pybind and model_zoo demo (#21)
* update .gitignore

* Added checking for cmake include dir

* fixed missing trt_backend option bug when init from trt

* remove un-need data layout and add pre-check for dtype

* changed RGB2BRG to BGR2RGB in ppcls model

* add model_zoo yolov6 c++/python demo

* fixed CMakeLists.txt typos

* update yolov6 cpp/README.md

* add yolox c++/pybind and model_zoo demo

* move some helpers to private

* fixed CMakeLists.txt typos

* add normalize with alpha and beta

* add version notes for yolov5/yolov6/yolox

* add copyright to yolov5.cc

* revert normalize

* fixed some bugs in yolox
2022-07-19 09:55:07 +08:00

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// 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/vision/common/processors/base.h"
namespace fastdeploy {
namespace vision {
class Normalize : public Processor {
public:
Normalize(const std::vector<float>& mean, const std::vector<float>& std,
bool is_scale = true,
const std::vector<float>& min = std::vector<float>(),
const std::vector<float>& max = std::vector<float>());
bool CpuRun(Mat* mat);
#ifdef ENABLE_OPENCV_CUDA
bool GpuRun(Mat* mat);
#endif
std::string Name() { return "Normalize"; }
// While use normalize, it is more recommend not use this function
// this function will need to compute result = ((mat / 255) - mean) / std
// if we use the following method
// ```
// auto norm = Normalize(...)
// norm(mat)
// ```
// There will be some precomputation in contruct function
// and the `norm(mat)` only need to compute result = mat * alpha + beta
// which will reduce lots of time
static bool Run(Mat* mat, const std::vector<float>& mean,
const std::vector<float>& std, bool is_scale = true,
const std::vector<float>& min = std::vector<float>(),
const std::vector<float>& max = std::vector<float>(),
ProcLib lib = ProcLib::OPENCV_CPU);
private:
std::vector<float> alpha_;
std::vector<float> beta_;
};
} // namespace vision
} // namespace fastdeploy