try to install deps with cmake in the release dir

.gitignore

@@ -27,8 +27,27 @@
 *.a
 *.lib
 
+# Build results
+[Dd]ebug/
+[Dd]ebugPublic/
+[Rr]elease/
+[Rr]eleases/
+x64/
+x86/
+[Ww][Ii][Nn]32/
+[Aa][Rr][Mm]/
+[Aa][Rr][Mm]64/
+bld/
+[Bb]in/
+[Oo]bj/
+[Ll]og/
+[Ll]ogs/
+out/
+build/
+
 # Executables
 *.exe
 *.out
 *.app
 
+.vscode/*

CMakeLists.txt

@@ -0,0 +1,72 @@
+cmake_minimum_required(VERSION 3.18)
+project(TV_Denoising_CUDA)
+
+set(CMAKE_BUILD_TYPE "Release")
+
+
+list(APPEND CMAKE_MODULE_PATH ${CMAKE_BINARY_DIR})
+
+# Find the Qt5 package
+find_package(Qt5 COMPONENTS Widgets REQUIRED)
+
+# Find OpenCV
+if(NOT DEFINED OpenCV_DIR)
+    set(OpenCV_DIR "C:/Users/Culis/.conan2/p/b/openc720995090ff52/b/")
+    # message(FATAL_ERROR "OpenCV_DIR is set to ${OpenCV_DIR}. Please set it to the appropriate directory.")
+endif()
+
+find_package(OpenCV REQUIRED)
+
+if(NOT OpenCV_FOUND)
+    message(FATAL_ERROR "OpenCV package not found. Please make sure OpenCV is installed and OpenCV_DIR is set correctly.")
+endif()
+
+find_package(OpenCV REQUIRED)
+  
+# Find CUDA
+enable_language(CUDA)
+
+# Set CUDA flags and properties
+set(CUDA_SEPARABLE_COMPILATION ON)
+set(CUDA_PROPAGATE_HOST_FLAGS OFF)
+
+# Add the CUDA source files
+file(GLOB CUDA_SOURCE_FILES "src/*.cu")
+set_source_files_properties(${CUDA_SOURCE_FILES} PROPERTIES CUDA_SOURCE_PROPERTY_FORMAT OBJ)
+
+# Add the C++ source files
+file(GLOB CPP_SOURCE_FILES "src/*.cpp")
+
+# Set the include directories
+include_directories(${OpenCV_DIR} ${CUDA_INCLUDE_DIRS} ${OpenCV_INCLUDE_DIRS} ${Qt5Widgets_INCLUDE_DIRS} "include")
+
+# Create the executable
+add_executable(TV_Denoising_CUDA ${CPP_SOURCE_FILES} ${CUDA_SOURCE_FILES})
+
+# Link CUDA libraries
+target_link_libraries(TV_Denoising_CUDA ${CUDA_LIBRARIES} ${OpenCV_LIBS} Qt5::Widgets)
+
+set_property(TARGET TV_Denoising_CUDA PROPERTY ENVIRONMENT "PATH=${CMAKE_CURRENT_BINARY_DIR}/Debug;${CMAKE_CURRENT_BINARY_DIR}/Release")
+
+if(WIN32)
+    set_target_properties(TV_Denoising_CUDA PROPERTIES RUNTIME_OUTPUT_DIRECTORY "${CMAKE_CURRENT_BINARY_DIR}" WIN32_EXECUTABLE TRUE)
+endif()   
+
+# Copy necessary DLLs and runtime files to the release directory
+install(
+    DIRECTORY "${CMAKE_CURRENT_BINARY_DIR}/"
+    DESTINATION "${CMAKE_CURRENT_BINARY_DIR}/Release/"
+    FILES_MATCHING PATTERN "*.dll"
+)
+install(
+    TARGETS TV_Denoising_CUDA
+    RUNTIME DESTINATION "${CMAKE_CURRENT_BINARY_DIR}/"
+    LIBRARY DESTINATION "${CMAKE_CURRENT_BINARY_DIR}/"
+    ARCHIVE DESTINATION "${CMAKE_CURRENT_BINARY_DIR}/"
+)
+
+install(
+    DIRECTORY "${OpenCV_INSTALL_PATH}/"
+    DESTINATION "${CMAKE_CURRENT_BINARY_DIR}/"
+    FILES_MATCHING PATTERN "*.dll"
+)

CMakeUserPresets.json

@@ -0,0 +1,9 @@
+{
+    "version": 4,
+    "vendor": {
+        "conan": {}
+    },
+    "include": [
+        "E:\\programming\\C++\\tv-image-denoising\\build\\CMakePresets.json"
+    ]
+}

README.md

@@ -1,3 +1,31 @@
 # tv-image-denoising
 
-Using the TV algorithm to denoise images with c++ and cuda.
+Using the TV algorithm to denoise images with c++ and cuda.
+
+## Requirements
+    g++
+    vcpkg
+    cmake
+    gtk
+    opencv2
+    cuda
+## Build
+```bash
+# Generate build files
+cmake -B build .
+# Build
+cmake --build build
+```
+## Run
+```bash
+./TV_Denoising_CUDA <input_image> <output_image> <lambda> <iterations>
+```
+
+## Original Exercise:
+7. Image denoising (up to 50+10+20=80%+)
+- [x] Use and implement a total variation image denoising method for the GPU. The input should be a noisy image, processed on the GPU by solving the energy minimization problem, then the output image should be displayed or saved to the disk. (50%) 
+
+- [ ] You can gain extra points for providing a simple GUI that allows the user to tune the parameters of the denoising algorithm, and immediately display the results! (+10%)
+
+- [ ] Additional extra points can be achieved by also submitting a comparative evaluation of yours and other denoising techniques, applied to various inputs. I.e., use metrics such as SSIM, NCC, MAD, etc. to compare results to ground truth images. (+20%)
+(Plus points: The more techniques you compare or the better quality that your figures,charts & diagrams are, you may be rewarded by further extra points.)

conanfile.txt

@@ -0,0 +1,11 @@
+[requires]
+opencv/4.5.5
+qt/5.15.8
+
+[options]
+qt/5.15.8:qttools=True
+qt/5.15.8:shared=True
+
+[generators]
+CMakeDeps
+CMakeToolchain

include/tv_denoising.hpp

@@ -0,0 +1,12 @@
+/*
+Author: Vargha Csongor Csaba
+Created: 2023-06-25 10:23:33
+*/
+#ifndef TV_DENOISING_H
+#define TV_DENOISING_H
+
+#include <opencv2/opencv.hpp>
+
+extern "C" void TVDenoising(cv::Mat& image, float lambda, int maxIterations);
+
+#endif // TV_DENOISING_H

src/main.cpp

@@ -0,0 +1,217 @@
+/*
+Author: Vargha Csongor Csaba
+Created: 2023-06-25 10:10:13
+
+Description:
+    This file contains the main function for the TV image denoising cli tool.
+    It reads an image file, denoises it using the TV denoising algorithm,
+    and saves the denoised image to a file.
+    You can run it with the following command:
+        ./TV_Denoising_CUDA <input_image> <output_image> <lambda> <iterations>
+    where:
+        - <input_image> is the path to the input image file you want to denoise.
+        - <output_image> is the path to the output denoised image file.
+        - <lambda> is the regularization parameter for TV denoising (optional, default: 0.02).
+        - <iterations> is the number of iterations for TV denoising (optional, default: 10).
+*/
+#include <iostream>
+#include <QApplication>
+#include <QVBoxLayout>
+#include <QHBoxLayout>
+#include <QLabel>
+#include <QDebug>
+#include <QLineEdit>
+#include <QPushButton>
+#include <QSlider>
+#include <QFileDialog>
+#include <QMessageBox>
+#include <QImageReader>
+#include <QImage>
+#include <opencv2/opencv.hpp>
+#include "tv_denoising.hpp"
+
+// Global variables for GUI elements
+QLabel *originalImageLabel;
+QLabel *resultImageLabel;
+QLineEdit *inputImagePathEdit;
+QLineEdit *outputImagePathEdit;
+QSlider *lambdaSlider;
+QSlider *iterationsSlider;
+
+void updateDenoisedImage()
+{
+    std::string inputImagePath = inputImagePathEdit->text().toStdString();
+    std::string outputImagePath = outputImagePathEdit->text().toStdString();
+    float lambda = lambdaSlider->value() / 100.0;
+    int iterations = iterationsSlider->value();
+
+    // Read the input image
+    cv::Mat image = cv::imread(inputImagePath, cv::IMREAD_GRAYSCALE);
+
+    // Check if the image was successfully loaded
+    if (image.empty())
+    {
+        QMessageBox::critical(nullptr, "Error", "Failed to read the input image.");
+        return;
+    }
+
+    // Perform TV denoising
+    TVDenoising(image, lambda, iterations);
+
+    // Display the denoised image
+    QImage resultImage(image.data, image.cols, image.rows, QImage::Format_Grayscale8);
+    resultImageLabel->setPixmap(QPixmap::fromImage(resultImage));
+
+    // Save the denoised image
+    cv::imwrite(outputImagePath, image);
+}
+
+void openInputImage()
+{
+    QString filePath = QFileDialog::getOpenFileName(nullptr, "Select Input Image");
+    if (!filePath.isEmpty())
+        inputImagePathEdit->setText(filePath);
+}
+
+void openOutputImage()
+{
+    QString filePath = QFileDialog::getSaveFileName(nullptr, "Select Output Image");
+    if (!filePath.isEmpty())
+        outputImagePathEdit->setText(filePath);
+}
+
+int main(int argc, char **argv)
+{
+    QApplication app(argc, argv);
+
+    // Create the main window
+    QWidget window;
+    window.setWindowTitle("TV Image Denoising");
+    window.resize(800, 600);
+
+    // Create the layout
+    QGridLayout *layout = new QGridLayout(&window);
+
+    // Create the original image label
+    QLabel *originalImageLabel = new QLabel("Original Image");
+    layout->addWidget(originalImageLabel, 0, 0, 1, 2); // Row 0, spanning 1 row, 2 columns
+
+    // Create the original image display widget
+    QLabel *originalImageDisplay = new QLabel();
+    originalImageDisplay->setAlignment(Qt::AlignCenter);
+    layout->addWidget(originalImageDisplay, 1, 0, 1, 2); // Row 1, spanning 1 row, 2 columns
+
+    // Create the result image label
+    QLabel *resultImageLabel = new QLabel("Result Image");
+    layout->addWidget(resultImageLabel, 0, 2, 1, 2); // Row 0, spanning 1 row, 2 columns
+
+    // Create the result image display widget
+    QLabel *resultImageDisplay = new QLabel();
+    resultImageDisplay->setAlignment(Qt::AlignCenter);
+    layout->addWidget(resultImageDisplay, 1, 2, 1, 2); // Row 1, spanning 1 row, 2 columns
+
+    // Create the input image path input field
+    QHBoxLayout *inputLayout = new QHBoxLayout;
+    QLabel *inputLabel = new QLabel("Input Image:");
+    QLineEdit *inputImagePathEdit = new QLineEdit;
+    QPushButton *inputBrowseButton = new QPushButton("Browse");
+    QObject::connect(inputBrowseButton, &QPushButton::clicked, openInputImage);
+    inputLayout->addWidget(inputLabel);
+    inputLayout->addWidget(inputImagePathEdit);
+    inputLayout->addWidget(inputBrowseButton);
+    layout->addLayout(inputLayout, 2, 0, 1, 4); // Row 2, spanning 1 row, 4 columns
+
+    // Create the output image path input field
+    QHBoxLayout *outputLayout = new QHBoxLayout;
+    QLabel *outputLabel = new QLabel("Output Image:");
+    QLineEdit *outputImagePathEdit = new QLineEdit;
+    QPushButton *outputBrowseButton = new QPushButton("Browse");
+    QObject::connect(outputBrowseButton, &QPushButton::clicked, openOutputImage);
+    outputLayout->addWidget(outputLabel);
+    outputLayout->addWidget(outputImagePathEdit);
+    outputLayout->addWidget(outputBrowseButton);
+    layout->addLayout(outputLayout, 3, 0, 1, 4); // Row 3, spanning 1 row, 4 columns
+
+    // Create the lambda slider
+    QLabel *lambdaLabel = new QLabel("Lambda:");
+    QSlider *lambdaSlider = new QSlider(Qt::Horizontal);
+    lambdaSlider->setObjectName("LambdaSlider"); // Set object name for styling
+    lambdaSlider->setMinimum(0);
+    lambdaSlider->setMaximum(100);
+
+    // Create the iterations slider
+    QLabel *iterationsLabel = new QLabel("Iterations:");
+    QSlider *iterationsSlider = new QSlider(Qt::Horizontal);
+    iterationsSlider->setObjectName("IterationsSlider"); // Set object name for styling
+    iterationsSlider->setMinimum(1);
+    iterationsSlider->setMaximum(100);
+
+    // Create labels to display slider values
+    QLabel *lambdaValueLabel = new QLabel();
+    QLabel *iterationsValueLabel = new QLabel();
+
+    // Set stylesheet for dark design
+    QString styleSheet = "QLabel { color: white; }"                                                                // Set label text color to white
+                         "QSlider::groove:horizontal { background-color: #555555; height: 6px; }"                  // Set groove color and height
+                         "QSlider::handle:horizontal { background-color: #ffffff; width: 10px; margin: -6px 0; }"; // Set handle color and size
+
+    lambdaSlider->setStyleSheet(styleSheet);
+    iterationsSlider->setStyleSheet(styleSheet);
+
+    // Set size policies for sliders
+    lambdaSlider->setSizePolicy(QSizePolicy::Expanding, QSizePolicy::Preferred);
+    iterationsSlider->setSizePolicy(QSizePolicy::Expanding, QSizePolicy::Preferred);
+
+    // Create the denoise button
+    QPushButton *denoiseButton = new QPushButton("Denoise");
+    QObject::connect(denoiseButton, &QPushButton::clicked, updateDenoisedImage);
+
+    // Add the lambda slider and its label
+    layout->addWidget(lambdaLabel, 4, 0);      // Row 4, column 0
+    layout->addWidget(lambdaSlider, 4, 1);     // Row 4, column 1
+    layout->addWidget(lambdaValueLabel, 5, 0); // Row 5, column 0
+
+    // Add the iterations slider and its label
+    layout->addWidget(iterationsLabel, 4, 2);      // Row 4, column 2
+    layout->addWidget(iterationsSlider, 4, 3);     // Row 4, column 3
+    layout->addWidget(iterationsValueLabel, 5, 2); // Row 5, column 2
+
+    // Add the denoise button
+    layout->addWidget(denoiseButton, 6, 0, 1, 4); // Row 6, spanning 1 row, 4 columns
+
+    QList<QByteArray> supportedFormats = QImageReader::supportedImageFormats();
+    qDebug() << "Supported image formats:" << supportedFormats;
+
+    // Load and display the input image
+    QString inputImagePath = inputImagePathEdit->text();
+    QImage inputImage(inputImagePath);
+    if (inputImage.isNull())
+    {
+        qDebug() << "Failed to load input image";
+    }
+    else
+    {
+        qDebug() << "Input image loaded successfully";
+    }
+    QPixmap inputPixmap = QPixmap::fromImage(inputImage);
+    originalImageDisplay->setPixmap(inputPixmap.scaled(originalImageDisplay->size(), Qt::KeepAspectRatio));
+
+    // Load and display the output image
+    QString outputImagePath = outputImagePathEdit->text();
+    QImage outputImage(outputImagePath);
+    if (outputImage.isNull())
+    {
+        qDebug() << "Failed to load input image";
+    }
+    else
+    {
+        qDebug() << "Input image loaded successfully";
+    }
+    QPixmap outputPixmap = QPixmap::fromImage(outputImage);
+    resultImageDisplay->setPixmap(outputPixmap.scaled(resultImageDisplay->size(), Qt::KeepAspectRatio));
+
+    // Show the main window
+    window.show();
+
+    return app.exec();
+}

src/tv_denoising.cu

@@ -0,0 +1,77 @@
+#include <cuda.h>
+#include <cuda_runtime.h>
+#include <device_launch_parameters.h>
+#include <opencv2/opencv.hpp>
+
+#define BLOCK_SIZE_X 16
+#define BLOCK_SIZE_Y 16
+
+__global__ void tvDenoisingKernel(float* image, int width, int height, float lambda, int maxIterations)
+{
+    // Calculate the global thread index
+    int col = blockIdx.x * blockDim.x + threadIdx.x;
+    int row = blockIdx.y * blockDim.y + threadIdx.y;
+    int index = row * width + col;
+
+     // Declare shared memory arrays
+     __shared__ float gradientX[BLOCK_SIZE_X][BLOCK_SIZE_Y];
+     __shared__ float gradientY[BLOCK_SIZE_X][BLOCK_SIZE_Y];
+     __shared__ float updatedImage[BLOCK_SIZE_X][BLOCK_SIZE_Y];
+ 
+     // Perform TV denoising iteratively
+     for (int iteration = 0; iteration < maxIterations; ++iteration)
+     {
+         // Calculate the gradients using central differences
+        gradientX[threadIdx.x][threadIdx.y] = image[index + 1] - image[index - 1];
+        gradientY[threadIdx.x][threadIdx.y] = image[index + width] - image[index - width];
+
+        // Synchronize threads to ensure all gradient calculations are complete
+        __syncthreads();
+
+        // Apply TV denoising update rule
+        updatedImage[threadIdx.x][threadIdx.y] = image[index] + lambda * (
+            gradientX[threadIdx.x][threadIdx.y] - gradientX[threadIdx.x - 1][threadIdx.y] +
+            gradientY[threadIdx.x][threadIdx.y] - gradientY[threadIdx.x][threadIdx.y - 1]
+        );
+
+        // Update the global image array with the updated pixel values
+        image[index] = updatedImage[threadIdx.x][threadIdx.y];
+
+        // Synchronize threads to ensure all image updates are complete
+        __syncthreads();
+     }
+}
+
+extern "C" void TVDenoising(cv::Mat& image, float lambda, int maxIterations)
+{
+    // Convert the image to float precision
+    cv::Mat floatImage;
+    image.convertTo(floatImage, CV_32F);
+
+    // Get image dimensions
+    int width = image.cols;
+    int height = image.rows;
+
+    // Calculate the number of blocks and threads per block
+    dim3 blockSize(16, 16);
+    dim3 gridSize((width + blockSize.x - 1) / blockSize.x, (height + blockSize.y - 1) / blockSize.y);
+
+    // Allocate GPU memory for the image
+    float* d_image;
+    cudaMalloc(&d_image, width * height * sizeof(float));
+
+    // Copy the image data from host to device
+    cudaMemcpy(d_image, floatImage.ptr<float>(0), width * height * sizeof(float), cudaMemcpyHostToDevice);
+
+    // Invoke the TV denoising kernel
+    tvDenoisingKernel<<<gridSize, blockSize>>>(d_image, width, height, lambda, maxIterations);
+
+    // Copy the denoised image data back from device to host
+    cudaMemcpy(floatImage.ptr<float>(0), d_image, width * height * sizeof(float), cudaMemcpyDeviceToHost);
+
+    // Convert the denoised image back to the original data type
+    floatImage.convertTo(image, image.type());
+
+    // Free the GPU memory
+    cudaFree(d_image);
+}