// Copyright (c) 2020 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 #include #include #include #include #include #include #include #include namespace PaddleX { /* * @brief * This class represents object for storing all preprocessed data * */ class ImageBlob { public: // Original image height and width std::vector ori_im_size_ = std::vector(2); // Newest image height and width after process std::vector new_im_size_ = std::vector(2); // Image height and width before resize std::vector> im_size_before_resize_; // Reshape order std::vector reshape_order_; // Resize scale float scale = 1.0; // Buffer for image data after preprocessing std::vector im_data_; void clear() { im_size_before_resize_.clear(); reshape_order_.clear(); im_data_.clear(); } }; /* * @brief * Abstraction of preprocessing operation class * */ class Transform { public: virtual void Init(const YAML::Node& item) = 0; /* * @brief * This method executes preprocessing operation on image matrix, * result will be returned at second parameter. * @param im: single image matrix to be preprocessed * @param data: the raw data of single image matrix after preprocessed * @return true if transform successfully * */ virtual bool Run(cv::Mat* im, ImageBlob* data) = 0; }; /* * @brief * This class execute normalization operation on image matrix * */ class Normalize : public Transform { public: virtual void Init(const YAML::Node& item) { mean_ = item["mean"].as>(); std_ = item["std"].as>(); } virtual bool Run(cv::Mat* im, ImageBlob* data); private: std::vector mean_; std::vector std_; }; /* * @brief * This class execute resize by short operation on image matrix. At first, it resizes * the short side of image matrix to specified length. Accordingly, the long side * will be resized in the same proportion. If new length of long side exceeds max * size, the long size will be resized to max size, and the short size will be * resized in the same proportion * */ class ResizeByShort : public Transform { public: virtual void Init(const YAML::Node& item) { short_size_ = item["short_size"].as(); if (item["max_size"].IsDefined()) { max_size_ = item["max_size"].as(); } else { max_size_ = -1; } } virtual bool Run(cv::Mat* im, ImageBlob* data); private: float GenerateScale(const cv::Mat& im); int short_size_; int max_size_; }; /* * @brief * This class execute resize by long operation on image matrix. At first, it resizes * the long side of image matrix to specified length. Accordingly, the short side * will be resized in the same proportion. * */ class ResizeByLong : public Transform { public: virtual void Init(const YAML::Node& item) { long_size_ = item["long_size"].as(); } virtual bool Run(cv::Mat* im, ImageBlob* data); private: int long_size_; }; /* * @brief * This class execute resize operation on image matrix. It resizes width and height * to specified length. * */ class Resize : public Transform { public: virtual void Init(const YAML::Node& item) { if (item["interp"].IsDefined()) { interp_ = item["interp"].as(); } if (item["target_size"].IsScalar()) { height_ = item["target_size"].as(); width_ = item["target_size"].as(); } else if (item["target_size"].IsSequence()) { std::vector target_size = item["target_size"].as>(); width_ = target_size[0]; height_ = target_size[1]; } if (height_ <= 0 || width_ <= 0) { std::cerr << "[Resize] target_size should greater than 0" << std::endl; exit(-1); } } virtual bool Run(cv::Mat* im, ImageBlob* data); private: int height_; int width_; std::string interp_; }; /* * @brief * This class execute center crop operation on image matrix. It crops the center * of image matrix accroding to specified size. * */ class CenterCrop : public Transform { public: virtual void Init(const YAML::Node& item) { if (item["crop_size"].IsScalar()) { height_ = item["crop_size"].as(); width_ = item["crop_size"].as(); } else if (item["crop_size"].IsSequence()) { std::vector crop_size = item["crop_size"].as>(); width_ = crop_size[0]; height_ = crop_size[1]; } } virtual bool Run(cv::Mat* im, ImageBlob* data); private: int height_; int width_; }; /* * @brief * This class execute padding operation on image matrix. It makes border on edge * of image matrix. * */ class Padding : public Transform { public: virtual void Init(const YAML::Node& item) { if (item["coarsest_stride"].IsDefined()) { coarsest_stride_ = item["coarsest_stride"].as(); if (coarsest_stride_ < 1) { std::cerr << "[Padding] coarest_stride should greater than 0" << std::endl; exit(-1); } } if (item["target_size"].IsDefined()) { if (item["target_size"].IsScalar()) { width_ = item["target_size"].as(); height_ = item["target_size"].as(); } else if (item["target_size"].IsSequence()) { width_ = item["target_size"].as>()[0]; height_ = item["target_size"].as>()[1]; } } if (item["im_padding_value"].IsDefined()) { im_value_ = item["im_padding_value"].as>(); } else { im_value_ = {0, 0, 0}; } } virtual bool Run(cv::Mat* im, ImageBlob* data); private: int coarsest_stride_ = -1; int width_ = 0; int height_ = 0; std::vector im_value_; }; /* * @brief * This class is transform operations manager. It stores all neccessary * transform operations and run them in correct order. * */ class Transforms { public: void Init(const YAML::Node& node, bool to_rgb = true); std::shared_ptr CreateTransform(const std::string& name); bool Run(cv::Mat* im, ImageBlob* data); private: std::vector> transforms_; bool to_rgb_ = true; }; } // namespace PaddleX