int main(int argc, char** argv)
{
_CrtSetDbgFlag(_CRTDBG_ALLOC_MEM_DF | _CRTDBG_LEAK_CHECK_DF);
setRandSeed(12345679);
if (argc != 2)
exitWithUsageError();
if (strcmp(argv[1], "-t") == 0)
{
std::cerr << "Testing basic graph activity.\n";
testBasic();
std::cerr << "Testing Tarjan`s algorithm.\n";
testTarjan();
std::cerr << "Testing 2-SAT solution.\n";
test2SAT();
return 0;
}
std::unique_ptr<IDigraph> graph = prepareInput(argv[1]);
int variables = graph->getNumberOfVertices() / 2;
std::vector<int> result = solve2SAT(graph, variables);
if (result[0] == -1) std::cout << "No solution." << std::endl;
else
{
std::cout << "Solution is:" << std::endl;
for (int i = 0; i < variables; i++)
std::cout << i + 1 << " -- " << (result[i] == 0 ? "false" : "true") << std::endl;
}
return 0;
}
void jpcnn_classify_image(void* networkHandle, void* inputHandle, unsigned int flags, int layerOffset, float** outPredictionsValues, int* outPredictionsLength, char*** outPredictionsNames, int* outPredictionsNamesLength) {
const bool doMultiSample = (flags & JPCNN_MULTISAMPLE);
const bool doRandomSample = (flags & JPCNN_RANDOM_SAMPLE);
const bool skipRescale = (flags & JPCNN_SKIP_RESCALE);
Graph* graph = (Graph*)(networkHandle);
Buffer* input = (Buffer*)(inputHandle);
bool doFlip;
int imageSize;
bool isMeanChanneled;
if (graph->_isHomebrewed) {
imageSize = 224;
doFlip = false;
isMeanChanneled = true;
} else {
imageSize = 227;
doFlip = true;
isMeanChanneled = false;
}
Buffer* rescaledInput;
if (skipRescale) {
// substract mean
rescaledInput = new Buffer(Dimensions(input->_dims[0], graph->_inputSize, graph->_inputSize, 1));
rescaledInput->copyDataFrom(input);
matrix_add_inplace(rescaledInput, graph->_dataMean, -1.0f);
} else {
const int rescaledSize = graph->_inputSize;
PrepareInput prepareInput(graph->_dataMean, !doMultiSample, doFlip, doRandomSample, imageSize, rescaledSize, isMeanChanneled);
rescaledInput = prepareInput.run(input);
}
Buffer* predictions = graph->run(rescaledInput, layerOffset);
*outPredictionsValues = predictions->_data;
*outPredictionsLength = predictions->_dims.elementCount();
if (layerOffset == 0) {
*outPredictionsNames = graph->_labelNames;
*outPredictionsNamesLength = graph->_labelNamesLength;
} else {
*outPredictionsNames = NULL;
*outPredictionsNamesLength = predictions->_dims.removeDimensions(1).elementCount();
}
}