-
CUDA小白 - NPP(6) 图像处理 Geometry Transforms (2)
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。
Affine Transform
仿射变换
// 仿射变换 NppStatus nppiWarpAffine_8u_C3R(const Npp8u *pSrc, NppiSize oSrcSize, int nSrcStep, NppiRect oSrcROI, Npp8u *pDst, int nDstStep, NppiRect oDstROI, const double aCoeffs[2][3], int eInterpolation); // 同样的2x3的矩阵的逆仿射变换 NppStatus nppiWarpAffineBack_8u_C3R(const Npp8u *pSrc, NppiSize oSrcSize, int nSrcStep, NppiRect oSrcROI, Npp8u *pDst, int nDstStep, NppiRect oDstROI, const double aCoeffs[2][3], int eInterpolation); // 源图像的四边形 仿射变换到 目标的四边形，平时使用较少，后续不进行测试 NppStatus nppiWarpAffineQuad_8u_C3R(const Npp8u *pSrc, NppiSize oSrcSize, int nSrcStep, NppiRect oSrcROI, const double aSrcQuad[4][2], Npp8u *pDst, int nDstStep, NppiRect oDstROI, const double aDstQuad[4][2], int eInterpolation);- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10
- 11
- 12
- 13
- 14
- 15
- 16
- 17
- 18
- 19
- 20
- 21
- 22
- 23
- 24
- 25
- 26
- 27
- 28
- 29
- 30
- 31
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 double angle = 30.0; double scale = 0.6; cv::Point center = cv::Point(image_width / 2, image_height / 2); cv::Mat rot_mat = cv::getRotationMatrix2D(center, angle, scale); double coeffs[2][3] = { rot_mat.at<double>(0, 0), rot_mat.at<double>(0, 1), rot_mat.at<double>(0, 2), rot_mat.at<double>(1, 0), rot_mat.at<double>(1, 1), rot_mat.at<double>(1, 2)}; NppiSize in_size; in_size.width = image_width; in_size.height = image_height; NppiRect rc; rc.x = 0; rc.y = 0; rc.width = image_width; rc.height = image_height; cv::Mat out_image = cv::Mat::zeros(image_height, image_width, CV_8UC3); NppStatus status; // =============== nppiWarpAffine_8u_C3R =============== status = nppiWarpAffine_8u_C3R(in_image, in_size, image_width * 3, rc, out_ptr1, image_width * 3, rc, coeffs, NPPI_INTER_LINEAR); if (status != NPP_SUCCESS) { std::cout << "[GPU] ERROR nppiWarpAffine_8u_C3R failed, status = " << status << std::endl; return false; } cudaMemcpy(out_image.data, out_ptr1, image_size * 3, cudaMemcpyDeviceToHost); cv::imwrite(directory + "affine.jpg", out_image); // =============== nppiWarpAffineBack_8u_C3R =============== status = nppiWarpAffineBack_8u_C3R(out_ptr1, in_size, image_width * 3, rc, out_ptr2, image_width * 3, rc, coeffs, NPPI_INTER_LINEAR); if (status != NPP_SUCCESS) { std::cout << "[GPU] ERROR nppiWarpAffineBack_8u_C3R failed, status = " << status << std::endl; return false; } cudaMemcpy(out_image.data, out_ptr2, image_size * 3, cudaMemcpyDeviceToHost); cv::imwrite(directory + "affine_back.jpg", out_image); // free CUDA_FREE(in_image) CUDA_FREE(out_ptr1) CUDA_FREE(out_ptr2) } - 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10
- 11
- 12
- 13
- 14
- 15
- 16
- 17
- 18
- 19
- 20
- 21
- 22
- 23
- 24
- 25
- 26
- 27
- 28
- 29
- 30
- 31
- 32
- 33
- 34
- 35
- 36
- 37
- 38
- 39
- 40
- 41
- 42
- 43
- 44
- 45
- 46
- 47
- 48
- 49
- 50
- 51
- 52
- 53
- 54
- 55
- 56
- 57
- 58
- 59
- 60
- 61
- 62
- 63
- 64
- 65
- 66
- 67
- 68
- 69
- 70
- 71
- 72
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} )- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10
- 11
- 12
- 13
- 14
- 15
result
Perspective Transform
透视变换
NppStatus nppiWarpPerspective_8u_C3R(const Npp8u *pSrc, NppiSize oSrcSize, int nSrcStep, NppiRect oSrcROI, Npp8u *pDst, int nDstStep, NppiRect oDstROI, const double aCoeffs[3][3], int eInterpolation); NppStatus nppiWarpPerspectiveBack_8u_C3R(const Npp8u *pSrc, NppiSize oSrcSize, int nSrcStep, NppiRect oSrcROI, Npp8u *pDst, int nDstStep, NppiRect oDstROI, const double aCoeffs[3][3], int eInterpolation);- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10
- 11
- 12
- 13
- 14
- 15
- 16
- 17
- 18
- 19
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 cv::Point2f src_pts[4], dst_pts[4]; src_pts[0].x = 0.0; src_pts[0].y = 0.0; src_pts[1].x = image_width - 1.0; src_pts[1].y = 0.0; src_pts[2].x = 0.0; src_pts[2].y = image_height - 1.0; src_pts[3].x = image_width - 1.0; src_pts[3].y = image_height - 1.0; dst_pts[0].x = image_width * 0.05; dst_pts[0].y = image_height * 0.05; dst_pts[1].x = image_width * 0.9; dst_pts[1].y = image_height * 0.1; dst_pts[2].x = image_width * 0.2; dst_pts[2].y = image_height * 0.8; dst_pts[3].x = image_width * 0.85; dst_pts[3].y = image_height * 0.85; cv::Mat warp_mat = cv::getPerspectiveTransform(src_pts, dst_pts); double coeffs[3][3] = { warp_mat.at<double>(0, 0), warp_mat.at<double>(0, 1), warp_mat.at<double>(0, 2), warp_mat.at<double>(1, 0), warp_mat.at<double>(1, 1), warp_mat.at<double>(1, 2), warp_mat.at<double>(2, 0), warp_mat.at<double>(2, 1), warp_mat.at<double>(2, 2) }; NppiSize in_size; in_size.width = image_width; in_size.height = image_height; NppiRect rc; rc.x = 0; rc.y = 0; rc.width = image_width; rc.height = image_height; cv::Mat out_image = cv::Mat::zeros(image_height, image_width, CV_8UC3); NppStatus status; // =============== nppiWarpPerspective_8u_C3R =============== status = nppiWarpPerspective_8u_C3R(in_image, in_size, image_width * 3, rc, out_ptr1, image_width * 3, rc, coeffs, NPPI_INTER_LINEAR); if (status != NPP_SUCCESS) { std::cout << "[GPU] ERROR nppiWarpPerspective_8u_C3R failed, status = " << status << std::endl; return false; } cudaMemcpy(out_image.data, out_ptr1, image_size * 3, cudaMemcpyDeviceToHost); cv::imwrite(directory + "perspective.jpg", out_image); // =============== nppiWarpPerspectiveBack_8u_C3R =============== status = nppiWarpPerspectiveBack_8u_C3R(out_ptr1, in_size, image_width * 3, rc, out_ptr2, image_width * 3, rc, coeffs, NPPI_INTER_LINEAR); if (status != NPP_SUCCESS) { std::cout << "[GPU] ERROR nppiWarpPerspectiveBack_8u_C3R failed, status = " << status << std::endl; return false; } cudaMemcpy(out_image.data, out_ptr2, image_size * 3, cudaMemcpyDeviceToHost); cv::imwrite(directory + "perspective_back.jpg", out_image); // free CUDA_FREE(in_image) CUDA_FREE(out_ptr1) CUDA_FREE(out_ptr2) } - 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10
- 11
- 12
- 13
- 14
- 15
- 16
- 17
- 18
- 19
- 20
- 21
- 22
- 23
- 24
- 25
- 26
- 27
- 28
- 29
- 30
- 31
- 32
- 33
- 34
- 35
- 36
- 37
- 38
- 39
- 40
- 41
- 42
- 43
- 44
- 45
- 46
- 47
- 48
- 49
- 50
- 51
- 52
- 53
- 54
- 55
- 56
- 57
- 58
- 59
- 60
- 61
- 62
- 63
- 64
- 65
- 66
- 67
- 68
- 69
- 70
- 71
- 72
- 73
- 74
- 75
- 76
- 77
- 78
- 79
- 80
- 81
- 82
- 83
- 84
- 85
- 86
- 87
- 88
- 89
- 90
- 91
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} )- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10
- 11
- 12
- 13
- 14
- 15
result
-
相关阅读:
基于JavaWeb的学生成绩管理系统
Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models论文解读
基于单片机GP2D12测距-proteus仿真-源程序
hive 知识总结
使用vim对比两个文件
DevOps（九）Selenium 介绍和Jenkins集成
线性代数学习笔记8-1：复数矩阵与Hermite矩阵、酉矩阵、傅里叶矩阵和快速傅里叶变换FFT
简易实现Spring Framework底层机制
Docker 链接sqlserver时出现en-us is an invalid culture错误解决方案
如何自动注册推特推广号，推特注册的具体步骤
- 原文地址：https://blog.csdn.net/u011732139/article/details/132802633
