forked from freudenreichan/info2Praktikum-NeuronalesNetz
updating
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#include <stdio.h>
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#include <stdlib.h>
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#include "imageInput.h"
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#include "mnistVisualization.h"
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#include "neuralNetwork.h"
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int main(int argc, char *argv[])
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{
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const unsigned int windowWidth = 800;
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const unsigned int windowHeight = 600;
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int exitCode = EXIT_FAILURE;
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if(argc == 3)
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{
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const char *pathToMnist = argv[1];
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const char *pathToModel = argv[2];
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GrayScaleImageSeries *series = readImages(pathToMnist);
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if(series != NULL)
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{
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NeuralNetwork model = {NULL, 0};
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printf("Loaded %u images ... \n", series->count);
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model = loadModel(pathToModel);
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if(model.numberOfLayers > 0)
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{
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unsigned char *predictions = NULL;
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printf("Processing %u images ...\n", series->count);
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predictions = predict(model, series->images, series->count);
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if(predictions != NULL)
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{
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showMnist(windowWidth, windowHeight, series, predictions);
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free(predictions);
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exitCode = EXIT_SUCCESS;
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}
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else
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{
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fprintf(stderr, "Error while processing images ...\n");
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exitCode = EXIT_FAILURE;
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}
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clearModel(&model);
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}
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else
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{
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fprintf(stderr, "Error while loading model from %s ...\n", pathToModel);
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exitCode = EXIT_FAILURE;
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}
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}
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else
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{
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fprintf(stderr, "Error while reading images from %s ...\n", pathToMnist);
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exitCode = EXIT_FAILURE;
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}
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clearSeries(series);
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}
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else
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{
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fprintf(stderr, "Usage: %s <mnist file> <model file>\n", argv[0]);
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exitCode = EXIT_FAILURE;
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}
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return exitCode;
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}
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