| /** |
| * Licensed to the Apache Software Foundation (ASF) under one |
| * or more contributor license agreements. See the NOTICE file |
| * distributed with this work for additional information |
| * regarding copyright ownership. The ASF licenses this file |
| * to you 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. |
| */ |
| |
| #ifndef SINGA_IO_TRANSFORMER_H_ |
| #define SINGA_IO_TRANSFORMER_H_ |
| |
| #include <vector> |
| #include <string> |
| #include "singa/core/tensor.h" |
| #include "singa/proto/io.pb.h" |
| #include "singa/proto/model.pb.h" |
| |
| namespace singa { |
| |
| /// Base apply class that does data transformations in pre-processing stage. |
| class Transformer { |
| public: |
| Transformer() {} |
| virtual ~Transformer() {} |
| |
| virtual void Setup(const TransformerConf& conf) {} |
| |
| virtual Tensor Apply(int flag, Tensor& input) = 0; |
| }; |
| |
| class ImageTransformer: public Transformer { |
| public: |
| void Setup(const TransformerConf& conf) override { |
| featurewise_center_ = conf.featurewise_center(); |
| featurewise_std_norm_ = conf.featurewise_std_norm(); |
| resize_height_ = conf.resize_height(); |
| resize_width_ = conf.resize_width(); |
| rescale_ = conf.rescale(); |
| horizontal_mirror_ = conf.horizontal_mirror(); |
| image_dim_order_ = conf.image_dim_order(); |
| |
| /// if crop_shape not contain 2 elements, ignore crop option. |
| if (conf.crop_shape_size() == 2) |
| crop_shape_ = {conf.crop_shape(0), conf.crop_shape(1)}; |
| } |
| |
| Tensor Apply(int flag, Tensor& input) override; |
| |
| const bool featurewise_center() const { return featurewise_center_; } |
| const bool featurewise_std_norm() const { return featurewise_std_norm_; } |
| const bool horizontal_mirror() const { return horizontal_mirror_; } |
| const int resize_height() const { return resize_height_; } |
| const int resize_width() const { return resize_width_; } |
| const float rescale() const { return rescale_; } |
| const Shape crop_shape() const { return crop_shape_; } |
| const string image_dim_order() const { return image_dim_order_; } |
| |
| private: |
| bool featurewise_center_ = false; |
| bool featurewise_std_norm_ = false; |
| bool horizontal_mirror_ = false; |
| int resize_height_ = 0; |
| int resize_width_ = 0; |
| float rescale_ = 0.f; |
| Shape crop_shape_ = {}; |
| std::string image_dim_order_ = "CHW"; |
| }; |
| |
| #ifdef USE_OPENCV |
| Tensor resize(Tensor& input, const size_t resize_height, |
| const size_t resize_width, const string& image_dim_order); |
| #endif |
| Tensor crop(Tensor& input, const size_t crop_height, |
| const size_t crop_width, const size_t crop_h_offset, |
| const size_t crop_w_offset, const string& image_dim_order); |
| Tensor mirror(Tensor& input, const bool horizontal_mirror, |
| const bool vertical_mirror, const string& image_dim_order); |
| } // namespace singa |
| #endif // SINGA_IO_TRANSFORMER_H_ |