CUDA小白 - NPP(4) 图像处理 Data Exchange and Initialization（1）-编程知识

cuda小白
原始API链接 NPP

GPU架构近些年也有不少的变化，具体的可以参考别的博主的介绍，都比较详细。还有一些cuda中的专有名词的含义，可以参考《详解CUDA的Context、Stream、Warp、SM、SP、Kernel、Block、Grid》

常见的NppStatus，可以看这里。

如有问题，请指出，谢谢

Image Set Operations

当前模块主要功能是set图像中的像素值，主要分为三个大类：将ROI区域内的所有像素设置为一个特殊的值（Set），mask赋值（Masked Set），以及单通道赋值（Channel Set）。
三个大类分别以一个三通道的uint8_t为例子简单介绍一下。

// ROI区域内的三通道设置为aValue
NppStatus nppiSet_8u_C3R(const Npp8u aValue[3],Npp8u *pDst,int nDstStep,NppiSize oSizeROI);
// 通过mask控制ROI区域内的那些像素会被set
NppStatus nppiSet_8u_C3MR(const Npp8u aValue[3],Npp8u *pDst,int nDstStep,NppiSize oSizeROI,const Npp8u *pMask,int nMaskStep);	
// 通过pointer的起始位置区别，选择某通道设置为固定值
NppStatus nppiSet_8u_C3CR(Npp8u nValue,Npp8u *pDst,int nDstStep,NppiSize oSizeROI);

code

#include <iostream>
#include <cuda_runtime.h>
#include <npp.h>
#include <opencv2/opencv.hpp>#define CUDA_FREE(ptr) { if (ptr != nullptr) { cudaFree(ptr); ptr = nullptr; } }int main() {std::string directory = "../";// =============== load image ===============cv::Mat image_dog = cv::imread(directory + "dog.png");int image_width = image_dog.cols;int image_height = image_dog.rows;int image_size = image_width * image_height;// =============== device memory ===============uint8_t *out_ptr1, *out_ptr2, *out_ptr3;cudaMalloc((void**)&out_ptr1, image_size * 3 * sizeof(uint8_t));cudaMalloc((void**)&out_ptr2, image_size * 3 * sizeof(uint8_t));cudaMalloc((void**)&out_ptr3, image_size * 3 * sizeof(uint8_t));cudaMemcpy(out_ptr1, image_dog.data, image_size * 3 * sizeof(uint8_t), cudaMemcpyHostToDevice);cudaMemcpy(out_ptr2, image_dog.data, image_size * 3 * sizeof(uint8_t), cudaMemcpyHostToDevice);cudaMemcpy(out_ptr3, image_dog.data, image_size * 3 * sizeof(uint8_t), cudaMemcpyHostToDevice);cv::Mat mask = cv::Mat::zeros(image_height, image_width, CV_8UC1);cv::Mat mask1 = cv::Mat::ones(image_height * 3 / 4, image_width * 3 / 4, CV_8UC1);cv::Rect rc1 = cv::Rect(image_width / 4, image_height / 4, image_width * 3 / 4, image_height * 3 / 4);mask1.copyTo(mask(rc1));uint8_t *gpu_mask;cudaMalloc((void**)&gpu_mask, image_size * sizeof(uint8_t));cudaMemcpy(gpu_mask, mask.data, image_size * sizeof(uint8_t), cudaMemcpyHostToDevice);NppiSize roi1, roi2;roi1.width = image_width;roi1.height = image_height;roi2.width = image_width / 2;roi2.height = image_height / 2;cv::Mat out_image = cv::Mat::zeros(image_height, image_width, CV_8UC3);NppStatus status;// =============== nppiSet_8u_C3R ===============uint8_t value[3] = { 255, 0, 0 };status = nppiSet_8u_C3R(value, out_ptr1, image_width * 3, roi1);if (status != NPP_SUCCESS) {std::cout << "[GPU] ERROR nppiSet_8u_C3R failed, status = " << status << std::endl;return false;}cudaMemcpy(out_image.data, out_ptr1, image_size * 3, cudaMemcpyDeviceToHost);cv::imwrite(directory + "set.jpg", out_image);// =============== nppiSet_8u_C3R ===============uint8_t value2[3] = { 0, 0, 255 };status = nppiSet_8u_C3MR(value2, out_ptr2, image_width * 3, roi1, gpu_mask, image_width);if (status != NPP_SUCCESS) {std::cout << "[GPU] ERROR nppiSet_8u_C3MR failed, status = " << status << std::endl;return false;}cudaMemcpy(out_image.data, out_ptr2, image_size * 3, cudaMemcpyD![请添加图片描述](https://img-blog.csdnimg.cn/9da721ce7d4649839ef40228bb3937e1.png)
eviceToHost);cv::imwrite(directory + "set_mask.jpg", out_image);// greenstatus = nppiSet_8u_C3CR(255, out_ptr3 + image_width * 3 * 200 + 1, image_width * 3, roi1);if (status != NPP_SUCCESS) {std::cout << "[GPU] ERROR nppiSet_8u_C3CR failed, status = " << status << std::endl;return false;}cudaMemcpy(out_image.data, out_ptr3, image_size * 3, cudaMemcpyDeviceToHost);cv::imwrite(directory + "set_channel.jpg", out_image);// freeCUDA_FREE(out_ptr1)CUDA_FREE(out_ptr2)CUDA_FREE(out_ptr3)
}

make

cmake_minimum_required(VERSION 3.20)
project(test)find_package(OpenCV REQUIRED)
include_directories(${OpenCV_INCLUDE_DIRS})find_package(CUDA REQUIRED)
include_directories(${CUDA_INCLUDE_DIRS})
file(GLOB CUDA_LIBS "/usr/local/cuda/lib64/*.so")add_executable(test test.cpp)
target_link_libraries(test${OpenCV_LIBS}${CUDA_LIBS}
)

result

请添加图片描述
注意：

mask使用的是单通道的，仅表示那些像素需要进行set，那些不需要
通道的set，通过指针来表示是针对那个通道进行转换。输入指针表示开始set的起始位置，对于三通道的图像而言，则是隔两个set一次。

Image Copy Operations

除了比较常见的copy操作（copy，masked copy，channel copy）之外，还有一些planar和packed之间的来回拷贝，拷贝的同时伴随着border，以及Copy Sub-pixel（没接触过）

// 单纯的拷贝
NppStatus nppiCopy_8u_C3R(const Npp8u *pSrc,int nSrcStep,Npp8u *pDst,int nDstStep,NppiSize oSizeROI);	
// 依据mask有选择性的进行拷贝
NppStatus nppiCopy_8u_C3MR(const Npp8u *pSrc,int nSrcStep,Npp8u *pDst,int nDstStep,NppiSize oSizeROI,const Npp8u *pMask,int nMaskStep);	
// Channel Copy, 将一个多通道的某个通道拷贝到另外一个多通道图像的某一个channel
NppStatus nppiCopy_8u_C3CR(const Npp8u *pSrc,int nSrcStep,Npp8u *pDst,int nDstStep,NppiSize oSizeROI);	
// Extract Channel Copy, 将一个多通道的某个通道拷贝到另外一个单通道的图像
NppStatus nppiCopy_8u_C3C1R(const Npp8u * pSrc,int nSrcStep,Npp8u *pDst,int nDstStep,NppiSize oSizeROI);	
// Insert Channel Copy, 一个单通道的图像拷贝到多通道中的某一个通道
NppStatus nppiCopy_8u_C1C3R(const Npp8u * pSrc,int nSrcStep,Npp8u * pDst,int nDstStep,NppiSize oSizeROI);
// 剩下的接口平时接触较少，所以暂时不做详细介绍

code

#include <iostream>
#include <cuda_runtime.h>
#include <npp.h>
#include <opencv2/opencv.hpp>#define CUDA_FREE(ptr) { if (ptr != nullptr) { cudaFree(ptr); ptr = nullptr; } }int main() {std::string directory = "../";// =============== load image ===============cv::Mat image_dog = cv::imread(directory + "dog.png");cv::Mat image_dog_gray;cv::cvtColor(image_dog, image_dog_gray, CV_RGB2GRAY);int image_width = image_dog.cols;int image_height = image_dog.rows;int image_size = image_width * image_height;// =============== device memory ===============uint8_t *in_image, *in_img_gray;cudaMalloc((void**)&in_image, image_size * 3 * sizeof(uint8_t));cudaMalloc((void**)&in_img_gray, image_size * sizeof(uint8_t));cudaMemcpy(in_image, image_dog.data, image_size * 3 * sizeof(uint8_t), cudaMemcpyHostToDevice);cudaMemcpy(in_img_gray, image_dog_gray.data, image_size * sizeof(uint8_t), cudaMemcpyHostToDevice);uint8_t *out_ptr1, *out_ptr2, *out_ptr3, *out_ptr4, *out_ptr5;cudaMalloc((void**)&out_ptr1, image_size * 3 * sizeof(uint8_t));  // 三通道cudaMalloc((void**)&out_ptr2, image_size * 3 * sizeof(uint8_t));  // 三通道cudaMalloc((void**)&out_ptr3, image_size * 3 * sizeof(uint8_t));  // 三通道cudaMalloc((void**)&out_ptr4, image_size * sizeof(uint8_t));  // 单通道cudaMalloc((void**)&out_ptr5, image_size * 3 * sizeof(uint8_t));  // 三通道// maskcv::Mat mask = cv::Mat::zeros(image_height, image_width, CV_8UC1);cv::Mat mask1 = cv::Mat::ones(image_height * 3 / 4, image_width * 3 / 4, CV_8UC1);cv::Rect rc1 = cv::Rect(image_width / 4, image_height / 4, image_width * 3 / 4, image_height * 3 / 4);mask1.copyTo(mask(rc1));uint8_t *gpu_mask;cudaMalloc((void**)&gpu_mask, image_size * sizeof(uint8_t));cudaMemcpy(gpu_mask, mask.data, image_size * sizeof(uint8_t), cudaMemcpyHostToDevice);NppiSize roi1, roi2;roi1.width = image_width;roi1.height = image_height;roi2.width = image_width / 2;roi2.height = image_height / 2;cv::Mat out_image = cv::Mat::zeros(image_height, image_width, CV_8UC3);cv::Mat out_single = cv::Mat::zeros(image_height, image_width, CV_8UC1);NppStatus status;// =============== nppiCopy_8u_C3R ===============status = nppiCopy_8u_C3R(in_image, image_width * 3, out_ptr1, image_width * 3, roi1);if (status != NPP_SUCCESS) {std::cout << "[GPU] ERROR nppiCopy_8u_C3R failed, status = " << status << std::endl;return false;}cudaMemcpy(out_image.data, out_ptr1, image_size * 3, cudaMemcpyDeviceToHost);cv::imwrite(directory + "copy.jpg", out_image);// =============== nppiCopy_8u_C3MR ===============status = nppiCopy_8u_C3MR(in_image, image_width * 3, out_ptr2, image_width * 3, roi1, gpu_mask, image_width);if (status != NPP_SUCCESS) {std::cout << "[GPU] ERROR nppiCopy_8u_C3MR failed, status = " << status << std::endl;return false;}cudaMemcpy(out_image.data, out_ptr2, image_size * 3, cudaMemcpyDeviceToHost);cv::imwrite(directory + "copy_mask.jpg", out_image);// =============== nppiCopy_8u_C3CR ===============status = nppiCopy_8u_C3CR(in_image, image_width * 3, out_ptr3, image_width * 3, roi1);if (status != NPP_SUCCESS) {std::cout << "[GPU] ERROR nppiCopy_8u_C3CR failed, status = " << status << std::endl;return false;}cudaMemcpy(out_image.data, out_ptr3, image_size * 3, cudaMemcpyDeviceToHost);cv::imwrite(directory + "copy_channel.jpg", out_image);// =============== nppiCopy_8u_C3C1R ===============status = nppiCopy_8u_C3C1R(in_image, image_width * 3, out_ptr4, image_width, roi1);if (status != NPP_SUCCESS) {std::cout << "[GPU] ERROR nppiCopy_8u_C3C1R failed, status = " << status << std::endl;return false;}cudaMemcpy(out_single.data, out_ptr4, image_size, cudaMemcpyDeviceToHost);cv::imwrite(directory + "copy_channel_extract.jpg", out_single);// =============== nppiCopy_8u_C1C3R ===============status = nppiCopy_8u_C1C3R(in_img_gray, image_width, out_ptr5, image_width * 3, roi1);if (status != NPP_SUCCESS) {std::cout << "[GPU] ERROR nppiCopy_8u_C1C3R failed, status = " << status << std::endl;return false;}cudaMemcpy(out_image.data, out_ptr5, image_size * 3, cudaMemcpyDeviceToHost);cv::imwrite(directory + "copy_channel_insert.jpg", out_image);// freeCUDA_FREE(in_image)CUDA_FREE(in_img_gray)CUDA_FREE(out_ptr1)CUDA_FREE(out_ptr2)CUDA_FREE(out_ptr3)CUDA_FREE(out_ptr4)CUDA_FREE(out_ptr5)
}

make

cmake_minimum_required(VERSION 3.20)
project(test)find_package(OpenCV REQUIRED)
include_directories(${OpenCV_INCLUDE_DIRS})find_package(CUDA REQUIRED)
include_directories(${CUDA_INCLUDE_DIRS})
file(GLOB CUDA_LIBS "/usr/local/cuda/lib64/*.so")add_executable(test test.cpp)
target_link_libraries(test${OpenCV_LIBS}${CUDA_LIBS}
)