Files
FastDeploy/fastdeploy/vision/classification/contrib/yolov5cls/preprocessor.h
guxukai 9cd00ad4c5 [Model] Refactoring code of YOLOv5Cls with new model type (#1237)
* Refactoring code of YOLOv5Cls with new model type

* fix reviewed problem

* Normalize&HWC2CHW -> NormalizeAndPermute

* remove cast()
2023-02-08 11:19:00 +08:00

58 lines
2.1 KiB
C++

// 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 classification {
/*! @brief Preprocessor object for YOLOv5Cls serials model.
*/
class FASTDEPLOY_DECL YOLOv5ClsPreprocessor {
public:
/** \brief Create a preprocessor instance for YOLOv5Cls serials model
*/
YOLOv5ClsPreprocessor();
/** \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,
std::vector<std::map<std::string, std::array<float, 2>>>* ims_info);
/// Set target size, tuple of (width, height), default size = {224, 224}
void SetSize(const std::vector<int>& size) { size_ = size; }
/// Get target size, tuple of (width, height), default size = {224, 224}
std::vector<int> GetSize() const { return size_; }
protected:
bool Preprocess(FDMat* mat, FDTensor* output,
std::map<std::string, std::array<float, 2>>* im_info);
// target size, tuple of (width, height), default size = {224, 224}
std::vector<int> size_;
};
} // namespace classification
} // namespace vision
} // namespace fastdeploy