#ifndef CAFFE_WINDOW_DATA_LAYER_HPP_

#define CAFFE_WINDOW_DATA_LAYER_HPP_

#include <string>

#include <utility>

#include <vector>

#include "caffe/blob.hpp"

#include "caffe/data_transformer.hpp"

#include "caffe/internal_thread.hpp"

#include "caffe/layer.hpp"

#include "caffe/layers/base_data_layer.hpp"

#include "caffe/proto/caffe.pb.h"

namespace caffe {

/**

* @brief Provides data to the Net from windows of images files, specified

* by a window data file. This layer is *DEPRECATED* and only kept for

* archival purposes for use by the original R-CNN.

*

* TODO(dox): thorough documentation for Forward and proto params.

*/

template <typename Dtype>

class WindowDataLayer : public BasePrefetchingDataLayer<Dtype> {

public:

explicit WindowDataLayer(const LayerParameter& param)

: BasePrefetchingDataLayer<Dtype>(param) {}

virtual ~WindowDataLayer();

virtual void DataLayerSetUp(const vector<Blob<Dtype>*>& bottom,

const vector<Blob<Dtype>*>& top);

virtual inline const char* type() const { return "WindowData"; }

virtual inline int ExactNumBottomBlobs() const { return 0; }

virtual inline int ExactNumTopBlobs() const { return 2; }

protected:

virtual unsigned int PrefetchRand();

virtual void load_batch(Batch<Dtype>* batch);

shared_ptr<Caffe::RNG> prefetch_rng_;

vector<std::pair<std::string, vector<int> > > image_database_;

enum WindowField { IMAGE_INDEX, LABEL, OVERLAP, X1, Y1, X2, Y2, NUM };

vector<vector<float> > fg_windows_;

vector<vector<float> > bg_windows_;

Blob<Dtype> data_mean_;

vector<Dtype> mean_values_;

bool has_mean_file_;

bool has_mean_values_;

bool cache_images_;

vector<std::pair<std::string, Datum > > image_database_cache_;

};

} // namespace caffe

#endif // CAFFE_WINDOW_DATA_LAYER_HPP_