CUDA小白 - NPP(2) - Arithmetic and Logical Operations(1)-Toy模板网

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cuda小白
原文链接 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

Arithmetic Operations

当前模块主要是加减乘除，abs，平方，矩阵相乘，开根，ln，exp等。不同相同功能，以其中一个为例进行介绍。

AddC

针对图像中每一个像素添加一个常量值。与之类似的还有MulC，SubC，DivC，AbsDiffC，MulScale
大概接口样式：

// 两个结果的区别在于，有I的结果可以就原始的图像地址进行操作，无需进行拷贝
// Sfs的含义 表示可以对图像的数值范围进行约束操作。
NppStatus nppiAddC_[数据类型]_C[通道数]RSfs_[是否使用流]
NppStatus nppiAddC_[数据类型]_C[通道数]IRSfs_[是否使用流]

以为三通道的uint8_t的图像数据为例子：

NppStatus nppiAddC_8u_C3RSfs(const Npp8u * pSrc1,
							 int nSrc1Step,
							 const Npp8u aConstants[3],
							 Npp8u *pDst,
							 int nDstStep,
							 NppiSize oSizeROI,
							 int nScaleFactor);
NppStatus nppiAddC_8u_C3RSfs(const Npp8u aConstants[3],
							 Npp8u *pDst,
							 int nDstStep,
							 NppiSize oSizeROI,
							 int nScaleFactor);

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 = cv::imread(directory + "dog.png");
  if (image.empty()) {
    std::cout << "Load image error!" << std::endl;
    return -1;
  }

  int image_width = image.cols;
  int image_height = image.rows;
  int image_size = image_width * image_height * 3 * sizeof(uint8_t);
  std::cout << "Image info : image_width = " << image_width
            << ", image_height = " << image_height << std::endl;

  // =============== malloc && cpy ===============
  uint8_t *in_ptr, *in_ptr2, *out_ptr, *roi_out_ptr;
  cudaMalloc((void**)&in_ptr, image_size);
  cudaMalloc((void**)&in_ptr2, image_size);
  cudaMalloc((void**)&out_ptr, image_size);
  cudaMalloc((void**)&roi_out_ptr, image_size);
  cudaMemcpy(in_ptr, image.data, image_size, cudaMemcpyHostToDevice);
  cudaMemcpy(in_ptr2, image.data, image_size, cudaMemcpyHostToDevice);

  uint8_t host_constant[3] = { (uint8_t)0, (uint8_t)20, (uint8_t)0 };

  NppiSize roi1, roi2;
  roi1.width = image_width;
  roi1.height = image_height;
  roi2.width = image_width / 2;
  roi2.height = image_height / 2;
  
  // nppiAddC_8u_C3RSfs
  cv::Mat out_image = cv::Mat::zeros(image_height, image_width, CV_8UC3);
  NppStatus status;
  status = nppiAddC_8u_C3RSfs(in_ptr, image_width * 3, host_constant, out_ptr, 
                              image_width * 3, roi1, 0);
  if (status != NPP_SUCCESS) {
    std::cout << "[GPU] ERROR nppiAddC_8u_C3RSfs failed, status = " << status << std::endl;
    return false;
  }
  cudaMemcpy(out_image.data, out_ptr, image_size, cudaMemcpyDeviceToHost);
  cv::imwrite(directory + "add_constant.jpg", out_image);

  status = nppiAddC_8u_C3RSfs(in_ptr, image_width * 3, host_constant, out_ptr, image_width * 3, 
                              roi1, 1);
  if (status != NPP_SUCCESS) {
    std::cout << "[GPU] ERROR nppiAddC_8u_C3RSfs failed, status = " << status << std::endl;
    return false;
  }
  cudaMemcpy(out_image.data, out_ptr, image_size, cudaMemcpyDeviceToHost);
  cv::imwrite(directory + "add_constant_scale.jpg", out_image);

  status = nppiAddC_8u_C3RSfs(in_ptr, image_width * 3, host_constant, out_ptr, image_width * 3, 
                              roi2, 0);
  if (status != NPP_SUCCESS) {
    std::cout << "[GPU] ERROR nppiAddC_8u_C3RSfs failed, status = " << status << std::endl;
    return false;
  }
  cudaMemcpy(out_image.data, out_ptr, image_size, cudaMemcpyDeviceToHost);
  cv::imwrite(directory + "add_constant_roi.jpg", out_image);

  // free
  CUDA_FREE(in_ptr)
  CUDA_FREE(in_ptr2)
  CUDA_FREE(out_ptr)
  CUDA_FREE(roi_out_ptr)
}

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

CUDA小白 - NPP(2) - Arithmetic and Logical Operations(1),c++,CUDA,NPP
注意点：

对图像的进行值的范围进行一定的约束，最初的图像RGB的值都是[0, 255]，如果对应的scale设置为1的时候，相当于将数值的范围变为2的-nScaleFactor倍数，即[0, 128]，超过128的会变成128，因此整体的图像色调会变暗；同样的，如果设置为-1，则整体的会变为2倍，因为存图的限制只能是[0, 255]，所以整体看起来会变亮。
如果指定的roi不是整张图的时候，由于roi的类型是NppiSize（width, height），因此输入的指针不是指向图像的起始位置，而是roi的起始位置。
MulScale相较于MulC来说，默认nScaleFactor为0；
AbsDiffC中主要功能就是得到整张图像与host_constant的绝对差值。
每个结果都有一个对应的包含cudastream的版本，按需使用。

Add

与AddC不同的是，Add输入的是两张图像。同样的还有Mul，MulScale，Sub，Div，Div_round，Abs，AbsDiff，Sqr，Sqrt，Ln，Exp。（由于Abs，AbsDiff，Sqr，Sqrt，Ln，Exp在图像出列方面使用的不是很多，就不细述）。
以uint8_t的三通道图像为例：

// 命名规则与nppiAddC*类似
NppStatus nppiAdd_8u_C3RSfs(const Npp8u * pSrc1,
							int nSrc1Step,
						    const Npp8u *pSrc2,
							int nSrc2Step,
							Npp8u * pDst,
							int nDstStep,
							NppiSize oSizeROI,
							int nScaleFactor);
NppStatus nppiAdd_8u_C3IRSfs(const Npp8u *pSrc,
							 int nSrcStep,
							 Npp8u *pSrcDst,
							 int nSrcDstStep,
							 NppiSize oSizeROI,
							 int nScaleFactor);

code

#include <iostream>
#include <cuda_runtime.h>
#include <npp.h>
#include <opencv2/opencv.hpp>

#define PRINT_VALUE(value) {  \
  std::cout << "[GPU] " << #value << " = " << value << std::endl; }

#define CUDA_FREE(ptr) { if (ptr != nullptr) { cudaFree(ptr); ptr = nullptr; } }

int main() {
  std::string directory = "../";
  // =============== load image ===============
  cv::Mat image = cv::imread(directory + "dog.png");
  if (image.empty()) {
    std::cout << "Load image error!" << std::endl;
    return -1;
  }

  int image_width = image.cols;
  int image_height = image.rows;
  int image_size = image_width * image_height * 3 * sizeof(uint8_t);
  std::cout << "Image info : image_width = " << image_width
            << ", image_height = " << image_height << std::endl;

  // =============== malloc && cpy ===============
  uint8_t *in_ptr, *in_ptr2, *out_ptr, *roi_out_ptr;
  cudaMalloc((void**)&in_ptr, image_size);
  cudaMalloc((void**)&in_ptr2, image_size);
  cudaMalloc((void**)&out_ptr, image_size);
  cudaMalloc((void**)&roi_out_ptr, image_size);
  cudaMemcpy(in_ptr, image.data, image_size, cudaMemcpyHostToDevice);
  cudaMemcpy(in_ptr2, image.data, image_size, cudaMemcpyHostToDevice);

  NppiSize roi1, roi2;
  roi1.width = image_width;
  roi1.height = image_height;
  roi2.width = image_width / 2;
  roi2.height = image_height / 2;
  
  // nppiAdd_8u_C3RSfs
  cv::Mat out_image = cv::Mat::zeros(image_height, image_width, CV_8UC3);
  NppStatus status;
  status = nppiAdd_8u_C3RSfs(in_ptr, image_width * 3, in_ptr2, image_width * 3, out_ptr, 
                             image_width * 3, roi1, 0);
  if (status != NPP_SUCCESS) {
    std::cout << "[GPU] ERROR nppiAdd_8u_C3RSfs failed, status = " << status << std::endl;
    return false;
  }
  cudaMemcpy(out_image.data, out_ptr, image_size, cudaMemcpyDeviceToHost);
  cv::imwrite(directory + "add.jpg", out_image);

  status = nppiAdd_8u_C3RSfs(in_ptr, image_width * 3, in_ptr2, image_width * 3, out_ptr, 
                             image_width * 3, roi1, 1);
  if (status != NPP_SUCCESS) {
    std::cout << "[GPU] ERROR nppiAdd_8u_C3RSfs failed, status = " << status << std::endl;
    return false;
  }
  cudaMemcpy(out_image.data, out_ptr, image_size, cudaMemcpyDeviceToHost);
  cv::imwrite(directory + "add_scale.jpg", out_image);

  status = nppiAdd_8u_C3RSfs(in_ptr, image_width * 3, in_ptr2, image_width * 3, out_ptr, 
                             image_width * 3, roi2, 0);
  if (status != NPP_SUCCESS) {
    std::cout << "[GPU] ERROR nppiAdd_8u_C3RSfs failed, status = " << status << std::endl;
    return false;
  }
  cudaMemcpy(out_image.data, out_ptr, image_size, cudaMemcpyDeviceToHost);
  cv::imwrite(directory + "add_roi.jpg", out_image);

  // free
  CUDA_FREE(in_ptr)
  CUDA_FREE(in_ptr2)
  CUDA_FREE(out_ptr)
  CUDA_FREE(roi_out_ptr)
}

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

CUDA小白 - NPP(2) - Arithmetic and Logical Operations(1),c++,CUDA,NPP
注意点：

nScaleFactor与AddC中的功能一致。roi的操作也与AddC中的一致。
由于使用的是两个相同的图片进行相加，因此在nScaleFactor为1的时候，所有的数值都变成原来的值，因此保存的图像与原图一致。
同样有cudastream版本，按需使用。

AddWeighted

将特定区域的图像进行填充weight

NppStatus nppiAddWeighted_8u32f_C1IR(const Npp8u *pSrc,
									 int nSrcStep,
									 Npp32f * pSrcDst,
									 int nSrcDstStep,
									 NppiSize oSizeROI,
								     Npp32f nAlpha);
NppStatus nppiAddWeighted_8u32f_C1IMR(const Npp8u *pSrc,
									  int nSrcStep,
									  const Npp8u *pMask,
									  int nMaskStep,
									  Npp32f * pSrcDst,
									  int nSrcDstStep,
									  NppiSize oSizeROI,
									  Npp32f nAlpha);

code

#include <iostream>
#include <cuda_runtime.h>
#include <npp.h>
#include <opencv2/opencv.hpp>

#define PRINT_VALUE(value) {  \
  std::cout << "[GPU] " << #value << " = " << value << std::endl; }

#define CUDA_FREE(ptr) { if (ptr != nullptr) { cudaFree(ptr); ptr = nullptr; } }

int main() {
  std::string directory = "../";
  // =============== load image ===============
  cv::Mat image = cv::imread(directory + "dog.png");
  if (image.empty()) {
    std::cout << "Load image error!" << std::endl;
    return -1;
  }

  cv::Mat gray;
  cv::cvtColor(image, gray, CV_BGR2GRAY);
  cv::imwrite(directory + "gray.jpg", gray);

  int image_width = gray.cols;
  int image_height = gray.rows;
  int image_size = image_width * image_height;
  std::cout << "Image info : image_width = " << image_width
            << ", image_height = " << image_height << std::endl;

  cv::Mat mat_mask = cv::Mat::ones(image_height, image_width, CV_8UC1);

  cv::Rect rc_center = cv::Rect(image_width / 4, image_height / 4, 
                                image_width / 2, image_height / 2);
  mat_mask(rc_center) = cv::Mat::ones(image_height / 2, image_width / 2, CV_8UC1) * 255;
  cv::imwrite(directory + "mask.jpg", mat_mask);

  // =============== malloc && cpy ===============
  uint8_t *in_ptr, *mask;
  cudaMalloc((void**)&in_ptr, image_size * sizeof(uint8_t));
  cudaMalloc((void**)&mask, image_size * sizeof(uint8_t));
  cudaMemcpy(in_ptr, gray.data, image_size, cudaMemcpyHostToDevice);
  cudaMemcpy(mask, mat_mask.data, image_size, cudaMemcpyHostToDevice);

  float *out_ptr, *out_ptr1, *out_ptr2;
  cudaMalloc((void**)&out_ptr, image_size * sizeof(float));
  cudaMalloc((void**)&out_ptr1, image_size * sizeof(float));
  cudaMalloc((void**)&out_ptr2, image_size * sizeof(float));
  
  NppiSize roi1, roi2;
  roi1.width = image_width;
  roi1.height = image_height;
  roi2.width = image_width / 2;
  roi2.height = image_height / 2;
  
  // nppiAdd_8u_C3RSfs
  cv::Mat out_image = cv::Mat::zeros(image_height, image_width, CV_32FC1);
  NppStatus status;
  status = nppiAddWeighted_8u32f_C1IMR(in_ptr, image_width * sizeof(uint8_t), 
                                       mask, image_width * sizeof(uint8_t), 
                                       out_ptr, image_width * sizeof(float), 
                                       roi1, 1.0);
  if (status != NPP_SUCCESS) {
    std::cout << "[GPU] ERROR nppiAddWeighted_8u32f_C1IMR failed, status = " << status << std::endl;
    return false;
  }
  cudaMemcpy(out_image.data, out_ptr, image_size * sizeof(float), cudaMemcpyDeviceToHost);
  cv::imwrite(directory + "addweight.jpg", out_image);

  status = nppiAddWeighted_8u32f_C1IMR(in_ptr, image_width * sizeof(uint8_t), 
                                       mask, image_width * sizeof(uint8_t), 
                                       out_ptr1, image_width * sizeof(float), 
                                       roi1, 0.5);
  if (status != NPP_SUCCESS) {
    std::cout << "[GPU] ERROR nppiAddWeighted_8u32f_C1IMR failed, status = " << status << std::endl;
    return false;
  }
  cudaMemcpy(out_image.data, out_ptr1, image_size * sizeof(float), cudaMemcpyDeviceToHost);
  cv::imwrite(directory + "addweight_scale.jpg", out_image);

  status = nppiAddWeighted_8u32f_C1IMR(in_ptr, image_width * sizeof(uint8_t), 
                                       mask, image_width * sizeof(uint8_t), 
                                       out_ptr2, image_width * sizeof(float), 
                                       roi2, 0.5);
  if (status != NPP_SUCCESS) {
    std::cout << "[GPU] ERROR nppiAddWeighted_8u32f_C1IMR failed, status = " << status << std::endl;
    return false;
  }
  cudaMemcpy(out_image.data, out_ptr2, image_size * sizeof(float), cudaMemcpyDeviceToHost);
  cv::imwrite(directory + "addweight_roi_scale.jpg", out_image);

  // free
  CUDA_FREE(in_ptr)
  CUDA_FREE(mask)
  CUDA_FREE(out_ptr)
  CUDA_FREE(out_ptr1)
  CUDA_FREE(out_ptr2)
}

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

CUDA小白 - NPP(2) - Arithmetic and Logical Operations(1),c++,CUDA,NPP
注意点：
1.nAlpha是针对原图中的每一个像素的值需要添加的权重，mask仅影响目标位置中那些部分需要输出。
2. roi表示输入的区域约束。文章来源地址https://www.toymoban.com/news/detail-688637.html