Files
FastDeploy/fastdeploy/vision/detection/contrib/rknpu2/preprocessor.h
Zheng_Bicheng c7dc7d5eee Add RKYOLOv5 RKYOLOX RKYOLOV7 (#709)
* 更正代码格式

* 更正代码格式

* 修复语法错误

* fix rk error

* update

* update

* update

* update

* update

* update

* update

Co-authored-by: Jason <jiangjiajun@baidu.com>
2022-12-10 15:44:00 +08:00

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3.4 KiB
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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/transform.h"
#include "fastdeploy/vision/common/result.h"
namespace fastdeploy {
namespace vision {
namespace detection {
/*! @brief Preprocessor object for YOLOv5 serials model.
*/
class FASTDEPLOY_DECL RKYOLOPreprocessor {
public:
/** \brief Create a preprocessor instance for YOLOv5 serials model
*/
RKYOLOPreprocessor();
/** \brief Process the input image 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
* \param[in] ims_info The shape info list, record input_shape and output_shape
* \return true if the preprocess successed, otherwise false
*/
bool Run(std::vector<FDMat>* images, std::vector<FDTensor>* outputs);
/// Set target size, tuple of (width, height), default size = {640, 640}
void SetSize(const std::vector<int>& size) { size_ = size; }
/// Get target size, tuple of (width, height), default size = {640, 640}
std::vector<int> GetSize() const { return size_; }
/// Set padding value, size should be the same as channels
void SetPaddingValue(const std::vector<float>& padding_value) {
padding_value_ = padding_value;
}
/// Get padding value, size should be the same as channels
std::vector<float> GetPaddingValue() const { return padding_value_; }
/// Set is_scale_up, if is_scale_up is false, the input image only
/// can be zoom out, the maximum resize scale cannot exceed 1.0, default true
void SetScaleUp(bool is_scale_up) { is_scale_up_ = is_scale_up; }
/// Get is_scale_up, default true
bool GetScaleUp() const { return is_scale_up_; }
std::vector<std::vector<int>> GetPadHWValues() const {
return pad_hw_values_;
}
std::vector<float> GetScale() const { return scale_; }
protected:
bool Preprocess(FDMat* mat, FDTensor* output);
void LetterBox(FDMat* mat);
// target size, tuple of (width, height), default size = {640, 640}
std::vector<int> size_;
// padding value, size should be the same as channels
std::vector<float> padding_value_;
// only pad to the minimum rectange which height and width is times of stride
bool is_mini_pad_;
// while is_mini_pad = false and is_no_pad = true,
// will resize the image to the set size
bool is_no_pad_;
// if is_scale_up is false, the input image only can be zoom out,
// the maximum resize scale cannot exceed 1.0
bool is_scale_up_;
// padding stride, for is_mini_pad
int stride_;
// for offseting the boxes by classes when using NMS
float max_wh_;
std::vector<std::vector<int>> pad_hw_values_;
std::vector<float> scale_;
};
} // namespace detection
} // namespace vision
} // namespace fastdeploy