cnn.h

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/*
    Beatmup image and signal processing library
    Copyright (C) 2020, lnstadrum
 
    This program is free software: you can redistribute it and/or modify
    it under the terms of the GNU General Public License as published by
    the Free Software Foundation, either version 3 of the License, or
    (at your option) any later version.
 
    This program is distributed in the hope that it will be useful,
    but WITHOUT ANY WARRANTY; without even the implied warranty of
    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
    GNU General Public License for more details.
 
    You should have received a copy of the GNU General Public License
    along with this program.  If not, see <http://www.gnu.org/licenses/>.
*/
 
#pragma once
#include "../cnn_interface.h"
 
namespace Beatmup {
 
    /**
        x2 image upsampler using a convolutional neural network.
        Implements a neural net inference using OpenGL ES 2.0-conformant shaders.
        Used by Bitmap::Resampler. Only usable inside an AbstractTask, not intended to be directly used by the application.
    */
    class GLES20X2UpsamplingNetwork : public X2UpsamplingNetwork {
    private:
        class Layer {
        public:
            typedef InternalBitmap* Storage;
        private:
            ImageShader shader;
            Storage& output;
        public:
            Layer(GL::RecycleBin& recycleBin, GraphicPipeline& gpu, Storage& outputStorage, const char* sourceCode);
 
            void process(Context& ctx, GraphicPipeline& gpu, GL::TextureHandler& input);
            void process(Context& ctx, GraphicPipeline& gpu, Layer** inputs, int inputsCount);
 
            InternalBitmap& getOutput() {
                return *output;
            }
        };
 
        static const int
            L1_SIZE = 12,
            L2_SIZE = 8,
            L3_SIZE = 6,
            L4_SIZE = 4,
            STORAGE_SIZE = 14;    // min number of recyclable textures to cover the entire dataflow during the inference
 
        InternalBitmap* storage[STORAGE_SIZE];
 
        Layer
            *layer1[L1_SIZE],
            *layer2[L2_SIZE],
            *layer3[L3_SIZE],
            *layer4[L4_SIZE],
            *layer5;
 
        ImageShader demux;
 
        Layer::Storage& nextStorage(int& i) { return storage[i++ % STORAGE_SIZE]; }
 
    public:
        GLES20X2UpsamplingNetwork(GL::RecycleBin& recycleBin, GraphicPipeline& gpu);
        ~GLES20X2UpsamplingNetwork();
 
        void process(GraphicPipeline& gpu, GL::TextureHandler& input, AbstractBitmap& output);
        bool usesEs31Backend() const { return false; }
    };
 
}