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#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_
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