Start implementing AlexNet

examples/alexnet/CMakeLists.txt

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+cmake_minimum_required(VERSION 3.17)
+
+project(AlexNet
+        LANGUAGES CXX CUDA
+)
+
+add_executable(alexnet main.cpp)
+
+find_library(CUDANet_LIBRARY NAMES CUDANet HINTS ${CMAKE_CURRENT_SOURCE_DIR}/../../build)
+find_package(OpenCV REQUIRED COMPONENTS core imgcodecs imgproc)
+find_package(CUDAToolkit REQUIRED)
+
+set (CUDANet_INCLUDE_DIRS
+    ${CMAKE_CURRENT_SOURCE_DIR}/../../include
+    ${CMAKE_CURRENT_SOURCE_DIR}/../../include/utils
+    ${CMAKE_CURRENT_SOURCE_DIR}/../../include/kernels
+    ${CMAKE_CURRENT_SOURCE_DIR}/../../include/layers
+    ${CMAKE_CURRENT_SOURCE_DIR}/../../include/model
+)
+
+target_include_directories(
+    alexnet PRIVATE ${OpenCV_INCLUDE_DIRS} ${CUDANet_INCLUDE_DIRS} ${CUDAToolkit_INCLUDE_DIRS})
+
+target_link_libraries(alexnet PRIVATE ${CUDANet_LIBRARY} ${OpenCV_LIBS} CUDA::cudart)
+
+set_property(TARGET alexnet PROPERTY CXX_STANDARD 20)

examples/alexnet/main.cpp

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+#include <iostream>
+#include <string>
+#include <vector>
+#include <opencv2/opencv.hpp>
+
+#include <model.hpp>
+
+std::vector<float> 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<float> imageData;
+    for (int i = 0; i < image.rows; ++i) {
+        for (int j = 0; j < image.cols; ++j) {
+            imageData.push_back(image.at<float>(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);
+    return model;
+}
+
+int main(int argc, const char* const argv[]) {
+
+    if (argc != 3) {
+        std::cerr << "Usage: " << argv[0] << "<model_weights_path> <image_path>" << 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<float> imageData = readAndNormalizeImage(imagePath, inputSize, inputSize);
+
+    // Print the size of the image data
+    std::cout << "Size of image data: " << imageData.size() << std::endl;
+
+    return 0;
+}