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authorVincent Le Garrec <legarrec.vincent@gmail.com>2018-02-18 10:59:58 +0100
committerVincent Le Garrec <legarrec.vincent@gmail.com>2018-02-18 10:59:58 +0100
commitf26664b907986b86d5f6896f7dfe6bcb3cfa6ebd (patch)
tree0ee68a6c6e5fa76854aa3d914e69908330eeb364
parent56bfe8ecdc5f3e41ea8ce84ef4e9b54c86f1e2ec (diff)
Add missing includeprivate/bansan/chardraw
and small changes to be compatible with changes of the master.
-rw-r--r--cui/source/dialogs/cuicharmap.cxx11
-rw-r--r--cui/source/factory/neuralnetworkinternal.hxx94
-rw-r--r--cui/source/inc/neuralnetwork.hxx4
3 files changed, 102 insertions, 7 deletions
diff --git a/cui/source/dialogs/cuicharmap.cxx b/cui/source/dialogs/cuicharmap.cxx
index a1fd1a8ee3c9..ae20b895160e 100644
--- a/cui/source/dialogs/cuicharmap.cxx
+++ b/cui/source/dialogs/cuicharmap.cxx
@@ -77,7 +77,7 @@ void Ocr::ReadBitmap()
}
else
{
- Color c = r->GetPixel (j, i);
+ BitmapColor c = r->GetPixel (j, i);
if (c.GetRed () == 0 && c.GetGreen () == 0 && c.GetBlue () == 0)
{
data[j*w_+i] = 1;
@@ -235,7 +235,7 @@ void Ocr::ToFann(fann_type *out_data)
}
else
{
- Color c = r->GetPixel(j, i);
+ BitmapColor c = r->GetPixel(j, i);
if (c.GetRed () == 255 && c.GetGreen () == 255 && c.GetBlue () == 255)
{
out_data[idata] = 0.;
@@ -1232,7 +1232,7 @@ IMPL_LINK_NOARG(SvxCharacterMap, DrawToggleHdl, Button*, void)
{
for (long k = 0; k < w; k++)
{
- Color c = r->GetPixel(j, k);
+ BitmapColor c = r->GetPixel(j, k);
if (c.GetRed () == 0 && c.GetGreen () == 0 && c.GetBlue () == 0)
{
std::cout << "1";
@@ -1306,15 +1306,16 @@ IMPL_LINK_NOARG(SvxCharacterMap, DrawToggleHdl, Button*, void)
delete ann;
}
- fann_type *calc_out;
fann_type input[Ocr::SIZE*Ocr::SIZE];
std::cout << "Starting loading fann" << std::endl;
AbstractNeuralNetwork * ann = AbstractNeuralNetwork::CreateFactory("/tmp/fann.net");
+ fann_type calc_out[ann->GetNumOutput()];
+
o.ToFann(&input[0]);
std::cout << "Starting finding best result" << std::endl;
- calc_out = ann->Run(input);
+ ann->Run(input, &calc_out[0]);
std::cout << "End of fann" << std::endl;
std::multimap<float, sal_UCS4> sorted_results;
diff --git a/cui/source/factory/neuralnetworkinternal.hxx b/cui/source/factory/neuralnetworkinternal.hxx
new file mode 100644
index 000000000000..3a2956adc89d
--- /dev/null
+++ b/cui/source/factory/neuralnetworkinternal.hxx
@@ -0,0 +1,94 @@
+/* -*- Mode: C++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- */
+/*
+ * This file is part of the LibreOffice project.
+ *
+ * This Source Code Form is subject to the terms of the Mozilla Public
+ * License, v. 2.0. If a copy of the MPL was not distributed with this
+ * file, You can obtain one at http://mozilla.org/MPL/2.0/.
+ *
+ * This file incorporates work covered by the following license notice:
+ *
+ * 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 .
+ */
+#ifndef INCLUDED_CUI_SOURCE_FACTORY_NEURALNETWORKINTERNAL_HXX
+#define INCLUDED_CUI_SOURCE_FACTORY_NEURALNETWORKINTERNAL_HXX
+
+#include "neuralnetwork.hxx"
+
+#include <fann.h>
+#include <vector>
+
+class NeuralNetworkInternal : public AbstractNeuralNetwork
+{
+public:
+ NeuralNetworkInternal(sal_uInt32 nLayers, const sal_uInt32* nLayer);
+ NeuralNetworkInternal(const OUString& file);
+
+ void SetActivationFunction(ActivationFunction function) override;
+ void SetTrainingAlgorithm(TrainingAlgorithm algorithm) override;
+ void SetLearningRate(float rate) override;
+
+ void InitTraining(sal_uInt32 nExamples) override;
+ sal_uInt32 GetNumInput() override;
+ float* GetInput(sal_uInt32 nIeme) override;
+ sal_uInt32 GetNumOutput() override;
+ float* GetOutput(sal_uInt32 nIeme) override;
+
+ void Train(sal_uInt32 nEpochs, float error) override;
+ void Run(float *data_input, float* result) override;
+ void Save(const OUString& file) override;
+
+ virtual ~NeuralNetworkInternal(){}
+
+ virtual void * GetTrain(){return nullptr;}
+
+private:
+ enum class FunctionTrans
+ {
+ Sigmoid,
+ SigmoidSymmetric
+ };
+ struct Neuron
+ {
+ // value of neuron.
+ // fann: value
+ // 0: input.
+ // last: output.
+ float a;
+ // weight
+ // fann: weights[first_con to last_con-2]
+ // Useless for n[0]
+ std::vector<float> w; // Number of neuron of the next layer without biais.
+ std::vector<float> dw; // Number of neuron of the next layer without biais.
+ // biais.
+ // fann: weights[last_con-1]
+ // function
+ // Useless for n[0]
+ FunctionTrans f;
+ // Steepness.
+ float stp;
+
+ // temporary field.
+ // gradient
+ float s;
+ float sum;
+
+ // b : between [-.1;.1]
+ Neuron() : a(0.), w(), f(FunctionTrans::Sigmoid), stp(1.f), sum(0) {}
+ };
+ std::vector<std::vector<Neuron>> n; // One neuron is biais.
+ float learning_rate;
+ float learning_rate_alpha;
+ std::vector<std::vector<float>> learning_input;
+ std::vector<std::vector<float>> learning_output;
+};
+
+#endif
+
+/* vim:set shiftwidth=4 softtabstop=4 expandtab: */
diff --git a/cui/source/inc/neuralnetwork.hxx b/cui/source/inc/neuralnetwork.hxx
index 045909214de9..5f0bb472074b 100644
--- a/cui/source/inc/neuralnetwork.hxx
+++ b/cui/source/inc/neuralnetwork.hxx
@@ -26,7 +26,7 @@ class AbstractNeuralNetwork
{
public:
enum class ActivationFunction {
- SIGMOID
+ SIGMOID, SIGMOID_SYMMETRIC
};
enum class TrainingAlgorithm {
INCREMENTAL
@@ -44,7 +44,7 @@ public:
virtual float* GetOutput(sal_uInt32 nIeme) = 0;
virtual void Train(sal_uInt32 nEpochs, float error) = 0;
- virtual float* Run(float *data_input) = 0;
+ virtual void Run(float *data_input, float* result) = 0;
virtual void Save(const OUString& file) = 0;
virtual ~AbstractNeuralNetwork(){}