noise_data_transformer is added

nnforge/nnforge.h

@@ -40,6 +40,7 @@
 #include "distort_2d_data_transformer.h"
 #include "extract_2d_data_transformer.h"
 #include "rotate_band_2d_data_transformer.h"
+#include "noise_data_transformer.h"
 
 namespace nnforge
 {

nnforge/noise_data_transformer.cpp

@@ -0,0 +1,65 @@
+/*
+ *  Copyright 2011-2013 Maxim Milakov
+ *
+ *  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.
+ */
+
+#include "noise_data_transformer.h"
+
+#include "neural_network_exception.h"
+
+#include <opencv2/core/core.hpp>
+#include <boost/format.hpp>
+
+namespace nnforge
+{
+	noise_data_transformer::noise_data_transformer(
+		bool is_same_sequence_from_reset,
+		unsigned int max_noise)
+		: is_same_sequence_from_reset(is_same_sequence_from_reset)
+	{
+		if (!is_same_sequence_from_reset)
+			generator = rnd::get_random_generator();
+
+		max_noise_distribution = std::tr1::uniform_int<int>(-static_cast<int>(max_noise), static_cast<int>(max_noise));
+	}
+
+	noise_data_transformer::~noise_data_transformer()
+	{
+	}
+
+	void noise_data_transformer::reset()
+	{
+		if (is_same_sequence_from_reset)
+			generator = rnd::get_random_generator(48576435);
+	}
+
+	void noise_data_transformer::transform(
+		const void * input_data,
+		void * output_data,
+		neuron_data_type::input_type type,
+		const layer_configuration_specific& original_config)
+	{
+		if (type != neuron_data_type::type_byte)
+			throw neural_network_exception("noise_data_transformer is implemented for data stored as bytes only");
+
+		unsigned char * data = static_cast<unsigned char *>(output_data);
+		unsigned int elem_count = original_config.get_neuron_count();
+
+		for(unsigned char * data_it = data; data_it != (data + elem_count); data_it++)
+		{
+			int shift = max_noise_distribution(generator);
+			*data_it = static_cast<unsigned char>(std::min<int>(std::max<int>((shift + static_cast<int>(*data_it)), 0), 255));
+		}
+	}
+}

nnforge/noise_data_transformer.h

@@ -0,0 +1,50 @@
+/*
+ *  Copyright 2011-2013 Maxim Milakov
+ *
+ *  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.
+ */
+
+#pragma once
+
+#include "data_transformer.h"
+
+#include "rnd.h"
+
+#include <memory>
+
+namespace nnforge
+{
+	class noise_data_transformer : public data_transformer
+	{
+	public:
+		noise_data_transformer(
+			bool is_same_sequence_from_reset,
+			unsigned int max_noise);
+
+		virtual ~noise_data_transformer();
+
+		virtual void transform(
+			const void * input_data,
+			void * output_data,
+			neuron_data_type::input_type type,
+			const layer_configuration_specific& original_config);
+
+		virtual void reset();
+
+	protected:
+		bool is_same_sequence_from_reset;
+		random_generator generator;
+
+		std::tr1::uniform_int<int> max_noise_distribution;
+	};
+}

nnforge/rotate_band_2d_data_transformer.cpp

@@ -54,13 +54,13 @@ namespace nnforge
 		const layer_configuration_specific& original_config)
 	{
 		if (type != neuron_data_type::type_byte)
-			throw neural_network_exception("distort_2d_data_transformer is implemented for data stored as bytes only");
+			throw neural_network_exception("rotate_band_2d_data_transformer is implemented for data stored as bytes only");
 
 		if (original_config.dimension_sizes.size() != 2)
-			throw neural_network_exception((boost::format("distort_2d_data_transformer is processing 2d data only, data is passed with number of dimensions %1%") % original_config.dimension_sizes.size()).str());
+			throw neural_network_exception((boost::format("rotate_band_2d_data_transformer is processing 2d data only, data is passed with number of dimensions %1%") % original_config.dimension_sizes.size()).str());
 
 		if (original_config.feature_map_count != 1)
-			throw neural_network_exception("distort_2d_data_transformer is implemented for 1 feature map data only");
+			throw neural_network_exception("rotate_band_2d_data_transformer is implemented for 1 feature map data only");
 
 		cv::Mat1b image(static_cast<int>(original_config.dimension_sizes[1]), static_cast<int>(original_config.dimension_sizes[0]), static_cast<unsigned char *>(output_data));