CUDA小白 - NPP(11) 图像处理 Comparison Operations

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。

Thresholding Operations

分通道，逐像素进行比较，根据指定的Operation，如果不符合则更新当前值。当前模块分为两大类，一个是直接原地址进行操作，另外一类则是指定不同的输出地址。

/*
enum NppCmpOp {
  NPP_CMP_LESS,
  NPP_CMP_LESS_EQ,
  NPP_CMP_EQ,
  NPP_CMP_GREATER_EQ,
  NPP_CMP_GREATER
}; 
*/
// 通用的，如果满足比较条件，则
NppStatus nppiThreshold_8u_C3R(const Npp8u *pSrc,
							   int nSrcStep,
							   Npp8u *pDst,
							   int nDstStep,
							   NppiSize oSizeROI,
							   const Npp8u rThresholds[3],
							   NppCmpOp eComparisonOperation);
// 大于   NPP_CMP_GREATER_EQ
NppStatus nppiThreshold_GT_8u_C3R(const Npp8u *pSrc,
								  int nSrcStep,
							      Npp8u *pDst,
							      int nDstStep,
								  NppiSize oSizeROI,
							      const Npp8u rThresholds[3]);
// 小于 NPP_CMP_LESS_EQ
NppStatus nppiThreshold_LT_8u_C3R(const Npp8u *pSrc,
							      int nSrcStep,
								  Npp8u *pDst,
								  int nDstStep,
								  NppiSize oSizeROI,
								  const Npp8u rThresholds[3]);
// 指定需要设置的值
NppStatus nppiThreshold_Val_8u_C3R(const Npp8u *pSrc,
								   int nSrcStep,
								   Npp8u *pDst,
								   int nDstStep,
								   NppiSize oSizeROI,
								   const Npp8u rThresholds[3],
								   const Npp8u rValues[3],
								   NppCmpOp eComparisonOperation);
NppStatus nppiThreshold_GTVal_8u_C3R(const Npp8u * pSrc,
									 int nSrcStep,
									 Npp8u *pDst,
									 int nDstStep,
									 NppiSize oSizeROI,
									 const Npp8u rThresholds[3],
									 const Npp8u rValues[3]);
NppStatus nppiThreshold_LTVal_8u_C3R(const Npp8u *pSrc,
									 int nSrcStep,
									 Npp8u *pDst,
									 int nDstStep,
									 NppiSize oSizeROI,
									 const Npp8u rThresholds[3],
									 const Npp8u rValues[3]);
// 设置上下界
NppStatus nppiThreshold_LTValGTVal_8u_C3R(const Npp8u *pSrc,
										  int nSrcStep,
										  Npp8u *pDst,
										  int nDstStep,
										  NppiSize oSizeROI,
										  const Npp8u rThresholdsLT[3],
										  const Npp8u rValuesLT[3],
										  const Npp8u rThresholdsGT[3],
										  const Npp8u rValuesGT[3]);

两边各选用一个接口作为示例

code

#include 
#include 
#include 
#include 

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

int main() {
  std::string directory = "../";
  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 ===============
  // input
  uint8_t *in_image;
  cudaMalloc((void**)&in_image, image_size * 3 * sizeof(uint8_t));
  cudaMemcpy(in_image, image_dog.data, image_size * 3 * sizeof(uint8_t), cudaMemcpyHostToDevice);

  // output
  uint8_t *out_ptr1, *out_ptr2;
  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

  NppiSize in_size;
  in_size.width = image_width;
  in_size.height = image_height;

  uint8_t threshold[3] = {150, 150, 150};
  cv::Mat out_image = cv::Mat::zeros(image_height, image_width, CV_8UC3);
  // =============== nppiThreshold_GT_8u_C3R ===============
  NppStatus status;
  status = nppiThreshold_GT_8u_C3R(in_image, image_width * 3, out_ptr1, image_width * 3, 
                                   in_size, threshold);
  if (status != NPP_SUCCESS) {
    std::cout << "[GPU] ERROR nppiThreshold_GT_8u_C3R failed, status = " << status << std::endl;
    return false;
  }
  cudaMemcpy(out_image.data, out_ptr1, image_size * 3, cudaMemcpyDeviceToHost);
  cv::imwrite(directory + "threshold_gt.jpg", out_image);

  // =============== nppiThreshold_GTVal_8u_C3R ===============
  uint8_t value[3] = {255, 255, 255};
  status = nppiThreshold_GTVal_8u_C3R(in_image, image_width * 3, out_ptr2, image_width * 3, 
                                      in_size, threshold, value);
  if (status != NPP_SUCCESS) {
    std::cout << "[GPU] ERROR nppiThreshold_GTVal_8u_C3R failed, status = " << status << std::endl;
    return false;
  }
  cudaMemcpy(out_image.data, out_ptr2, image_size * 3, cudaMemcpyDeviceToHost);
  cv::imwrite(directory + "threshold_gt_value.jpg", out_image);

  // free
  CUDA_FREE(in_image)
  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

Comparison Operations

本文到此就只阐述比较简单的两个接口，其他的结果按需索取

NppStatus nppiCompare_8u_C3R(const Npp8u *pSrc1,
							 int nSrc1Step,
							 const Npp8u *pSrc2,
							 int nSrc2Step,
							 Npp8u *pDst,
							 int nDstStep,
							 NppiSize oSizeROI,
							 NppCmpOp eComparisonOperation);
NppStatus nppiCompareC_8u_C3R(const Npp8u *pSrc,
							  int nSrcStep,
							  const Npp8u *pConstants,
							  Npp8u * pDst,
							  int nDstStep,
							  NppiSize oSizeROI,
							  NppCmpOp eComparisonOperation);

目的就是比较两张图或者将一张图与一个constant进行比较，并且生成一个二进制的结果图像。二进制的结果图像类型是8UC1，如果是不同的话，则设置为0，反之表示uint8_t的最大值。

code

#include 
#include 
#include 
#include 

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

int main() {
  std::string directory = "../";
  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 ===============
  // input
  uint8_t *in_image1, *in_image2;
  cudaMalloc((void**)&in_image1, image_size * 3 * sizeof(uint8_t));
  cudaMalloc((void**)&in_image2, image_size * 3 * sizeof(uint8_t));
  cudaMemcpy(in_image1, image_dog.data, image_size * 3 * sizeof(uint8_t), cudaMemcpyHostToDevice);
  
  cv::Mat mask = cv::Mat::zeros(image_height, image_width, CV_8UC3);
  int step = 4;
  int step_width = image_width / step;
  cv::Mat ones = cv::Mat::ones(image_height, step_width, CV_8UC3);
  for (int i = 1; i < step; ++i) {
    cv::Rect rc1 = cv::Rect(i * step_width, 0, step_width, image_height);
    mask(rc1) = ones.clone() * 50 * i;
  }
  
  cudaMemcpy(in_image2, mask.data, image_size * 3 * sizeof(uint8_t), cudaMemcpyHostToDevice);

  // output
  uint8_t *out_ptr1, *out_ptr2;
  cudaMalloc((void**)&out_ptr1, image_size * sizeof(uint8_t));  // 三通道
  cudaMalloc((void**)&out_ptr2, image_size * sizeof(uint8_t));  // 三通道

  NppiSize in_size;
  in_size.width = image_width;
  in_size.height = image_height;

  cv::Mat out_image = cv::Mat::zeros(image_height, image_width, CV_8UC1);
  NppStatus status;
  // =============== nppiCompare_8u_C3R ===============
  status = nppiCompare_8u_C3R(in_image1, image_width * 3, in_image2, image_width * 3, 
                              out_ptr1, image_width, in_size, NPP_CMP_GREATER);
  if (status != NPP_SUCCESS) {
    std::cout << "[GPU] ERROR nppiCompare_8u_C3R failed, status = " << status << std::endl;
    return false;
  }
  cudaMemcpy(out_image.data, out_ptr1, image_size, cudaMemcpyDeviceToHost);
  cv::imwrite(directory + "compare.jpg", out_image);

  // =============== nppiCompareC_8u_C3R ===============
  uint8_t constant[3] = {100, 100, 100};
  status = nppiCompareC_8u_C3R(in_image1, image_width * 3, constant, out_ptr2, image_width, 
                               in_size, NPP_CMP_GREATER);
  if (status != NPP_SUCCESS) {
    std::cout << "[GPU] ERROR nppiCompareC_8u_C3R failed, status = " << status << std::endl;
    return false;
  }
  cudaMemcpy(out_image.data, out_ptr2, image_size, cudaMemcpyDeviceToHost);
  cv::imwrite(directory + "comparec.jpg", out_image);

  // free
  CUDA_FREE(in_image1)
  CUDA_FREE(in_image2)
  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}![请添加图片描述](https://img-blog.csdnimg.cn/81402e58c241462fa7d22d7783b5d176.png)

                      ${CUDA_LIBS}
)

result