#include #include #include #include #include #include std::vector readAndNormalizeImage(const std::string& imagePath, int width, int height) { // Read the image using OpenCV cv::Mat image = cv::imread(imagePath, cv::IMREAD_GRAYSCALE); // Resize and normalize the image cv::resize(image, image, cv::Size(width, height)); image.convertTo(image, CV_32F); cv::normalize(image, image, 0.0, 1.0, cv::NORM_MINMAX); // Convert the 2D image matrix to a 1D array of floats std::vector imageData; for (int i = 0; i < image.rows; ++i) { for (int j = 0; j < image.cols; ++j) { imageData.push_back(image.at(i, j)); } } return imageData; } CUDANet::Model* createModel(const int inputSize, const int inputChannels, const int outputSize) { CUDANet::Model *model = new CUDANet::Model(inputSize, inputChannels, outputSize); // AlexNet CUDANet::Layers::Conv2d *conv1 = new CUDANet::Layers::Conv2d( inputSize, inputChannels, 11, 4, 96, CUDANet::Layers::Padding::SAME, CUDANet::Layers::ActivationType::RELU ); model->addLayer("conv1", conv1); CUDANet::Layers::MaxPooling *pool1 = new CUDANet::Layers::MaxPooling( 3, 2 ) return model; } int main(int argc, const char* const argv[]) { if (argc != 3) { std::cerr << "Usage: " << argv[0] << " " << std::endl; return 1; // Return error code indicating incorrect usage } // Path to the image file std::string modelWeightsPath = argv[1]; std::string imagePath = argv[2]; const int inputSize = 227; const int inputChannels = 3; const int outputSize = 1000; CUDANet::Model *model = createModel(inputSize, inputChannels, outputSize); // Read and normalize the image std::vector imageData = readAndNormalizeImage(imagePath, inputSize, inputSize); // Print the size of the image data std::cout << "Size of image data: " << imageData.size() << std::endl; return 0; }