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// File: input.h
// Description: Input layer class for neural network implementations.
// Author: Ray Smith
// Created: Thu Mar 13 08:56:26 PDT 2014
//
// (C) Copyright 2014, Google Inc.
// 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.
///////////////////////////////////////////////////////////////////////
#ifndef TESSERACT_LSTM_INPUT_H_
#define TESSERACT_LSTM_INPUT_H_
#include "network.h"
class ScrollView;
namespace tesseract {
class Input : public Network {
public:
Input(const STRING& name, int ni, int no);
Input(const STRING& name, const StaticShape& shape);
virtual ~Input();
virtual STRING spec() const {
STRING spec;
spec.add_str_int("", shape_.batch());
spec.add_str_int(",", shape_.height());
spec.add_str_int(",", shape_.width());
spec.add_str_int(",", shape_.depth());
return spec;
}
// Returns the required shape input to the network.
virtual StaticShape InputShape() const { return shape_; }
// Returns the shape output from the network given an input shape (which may
// be partially unknown ie zero).
virtual StaticShape OutputShape(const StaticShape& input_shape) const {
return shape_;
}
// Writes to the given file. Returns false in case of error.
// Should be overridden by subclasses, but called by their Serialize.
virtual bool Serialize(TFile* fp) const;
// Reads from the given file. Returns false in case of error.
virtual bool DeSerialize(TFile* fp);
// Returns an integer reduction factor that the network applies to the
// time sequence. Assumes that any 2-d is already eliminated. Used for
// scaling bounding boxes of truth data.
// WARNING: if GlobalMinimax is used to vary the scale, this will return
// the last used scale factor. Call it before any forward, and it will return
// the minimum scale factor of the paths through the GlobalMinimax.
virtual int XScaleFactor() const;
// Provides the (minimum) x scale factor to the network (of interest only to
// input units) so they can determine how to scale bounding boxes.
virtual void CacheXScaleFactor(int factor);
// Runs forward propagation of activations on the input line.
// See Network for a detailed discussion of the arguments.
virtual void Forward(bool debug, const NetworkIO& input,
const TransposedArray* input_transpose,
NetworkScratch* scratch, NetworkIO* output);
// Runs backward propagation of errors on the deltas line.
// See Network for a detailed discussion of the arguments.
virtual bool Backward(bool debug, const NetworkIO& fwd_deltas,
NetworkScratch* scratch,
NetworkIO* back_deltas);
// Creates and returns a Pix of appropriate size for the network from the
// image_data. If non-null, *image_scale returns the image scale factor used.
// Returns nullptr on error.
/* static */
static Pix* PrepareLSTMInputs(const ImageData& image_data,
const Network* network, int min_width,
TRand* randomizer, float* image_scale);
// Converts the given pix to a NetworkIO of height and depth appropriate to
// the given StaticShape:
// If depth == 3, convert to 24 bit color, otherwise normalized grey.
// Scale to target height, if the shape's height is > 1, or its depth if the
// height == 1. If height == 0 then no scaling.
// NOTE: It isn't safe for multiple threads to call this on the same pix.
static void PreparePixInput(const StaticShape& shape, const Pix* pix,
TRand* randomizer, NetworkIO* input);
private:
// Input shape determines how images are dealt with.
StaticShape shape_;
// Cached total network x scale factor for scaling bounding boxes.
int cached_x_scale_;
};
} // namespace tesseract.
#endif // TESSERACT_LSTM_INPUT_H_
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