Opencv使用cuda实现图像处理

main.py

python 复制代码
import os
import cv2
print(f'OpenCV: {cv2.__version__} for python installed and working')
image = cv2.imread('bus.jpg')
if image is None:
    print("无法加载图像1")
print(cv2.cuda.getCudaEnabledDeviceCount())
cv2.cuda.setDevice(0)
cv2.cuda.printCudaDeviceInfo(0)
image_gpu = cv2.cuda_GpuMat()
image_gpu.upload(image)
screenshot = cv2.cuda.cvtColor(image_gpu, cv2.COLOR_RGB2BGR)
screenshot = cv2.cuda.resize(image_gpu, (400, 400))
result_cpu = screenshot.download()
print("图像宽度: ", image.shape)
print("数据类型:", image.dtype)
print("在CPU下,原始图像格式:", type(image))
print("在GPU下,处理后的图像格式:", type(screenshot))
print("在CPU下,处理后的图像格式:", type(result_cpu))
print("图像宽度: ", result_cpu.shape)
print("数据类型:", result_cpu.dtype)
if result_cpu is None:
    print("无法加载图像2")
else:
    cv2.imshow("Window", result_cpu)
    cv2.waitKey(0)
    cv2.destroyAllWindows()

main.cpp

cpp 复制代码
#include <iostream>
#include <opencv2/opencv.hpp>
#include <opencv2/cudaimgproc.hpp>
int main(int argc, char* argv[])
{
	cv::Mat h_img1 = cv::imread("bus.jpg");
	cv::cuda::GpuMat d_result1, d_result2, d_result3, d_result4, d_img1;
	d_img1.upload(h_img1);
	cv::cuda::cvtColor(d_img1, d_result1, cv::COLOR_BGR2GRAY);
	cv::cuda::cvtColor(d_img1, d_result2, cv::COLOR_BGR2RGB);
	cv::cuda::cvtColor(d_img1, d_result3, cv::COLOR_BGR2HSV);
	cv::cuda::cvtColor(d_img1, d_result4, cv::COLOR_BGR2YCrCb);
	cv::Mat h_result1, h_result2, h_result3, h_result4;
	d_result1.download(h_result1);
	d_result2.download(h_result2);
	d_result3.download(h_result3);
	d_result4.download(h_result4);
	cv::imshow("Gray处理结果:", h_result1);
	cv::imshow("RGB处理结果:", h_result2);
	cv::imshow("HSV处理结果:", h_result3);
	cv::imshow("YCrCb处理结果:", h_result4);
	cv::waitKey(0);
	return 0;
}

CMakeLists.txt

bash 复制代码
cmake_minimum_required(VERSION 3.10)
project(OpenCVCuda LANGUAGES CXX)
set(CMAKE_CXX_STANDARD 17)
set(CMAKE_CXX_STANDARD_REQUIRED ON)
set("OpenCV_DIR" "E:\\Opencv gpu\\newbuild\\install")
set(OpenCV_INCLUDE_DIRS ${OpenCV_DIR}\\include)
set(OpenCV_LIB_DEBUG ${OpenCV_DIR}\\x64\\vc17\\lib\\opencv_world470d.lib) 
set(OpenCV_LIB_RELEASE ${OpenCV_DIR}\\x64\\vc17\\lib\\opencv_world470.lib)   
set(CMAKE_CXX_STANDARD 14)
set(CMAKE_CXX_STANDARD_REQUIRED ON)
set(CMAKE_CUDA_ARCHITECTURES 86)		
find_package(CUDA REQUIRED)			
enable_language(CUDA)  
include_directories(${OpenCV_INCLUDE_DIRS}) 
link_directories(${OpenCV_LIB_DIRS})  
find_package(OpenCV QUIET)	
link_libraries(${OpenCV_LIBS})
add_executable(OpenCVCuda main.cpp)
target_link_libraries(${PROJECT_NAME} 
    $<$<CONFIG:Debug>:${OpenCV_LIB_DEBUG}>
    $<$<CONFIG:Release>:${OpenCV_LIB_RELEASE}>
)
target_compile_features(OpenCVCuda PRIVATE cxx_std_14)
相关推荐
地球资源数据云几秒前
中国陆地生态系统主要植物功能特征空间分布数据
大数据·数据库·人工智能·机器学习
AI创界者12 分钟前
最新RedMix-Ernie-Image整合包,解压即用:文生图、图生图,n卡8G显存玩转4K
人工智能
月诸清酒14 分钟前
51-260503 AI 科技日报 (ChatGPT图像功能用户量暴涨,新用户占六成)
人工智能·chatgpt
Raink老师15 分钟前
【AI面试临阵磨枪-32】如何提升工具调用(Function Call)准确率?常见失败场景与解决方法
人工智能·ai 面试
格林威16 分钟前
线阵工业相机:线阵图像出现“波浪纹”,是机械振动还是编码器问题?
开发语言·人工智能·数码相机·计算机视觉·视觉检测·工业相机·线阵相机
knight_9___16 分钟前
LLM工具调用面试篇5
人工智能·python·深度学习·面试·职场和发展·llm·agent
网络工程小王18 分钟前
【LangChain Output Parser 输出解析器】输出篇
人工智能·学习·langchain
金智维科技官方22 分钟前
AI智能体在7×24客服场景中的真实表现评估
大数据·人工智能·ai·rpa·智能体
liliangcsdn25 分钟前
LLM如何辅助RAG从大量文档中筛选目标文档
开发语言·人工智能
Magic-Yuan30 分钟前
泰勒制的崩塌 - 上
人工智能·管理