pybaseutils
Project description
base-utils
开源不易,麻烦给个【Star】
base_utils(C++)
base_util是个人开发常用的C++库,集成了C/C++ OpenCV等常用的算法
增加了debug测试宏定义,如时间测试,LOG信息等
针对目标坐标点的卡尔曼滤波,加权平均滤波
常用的文件处理函数
常用的OpenCV图像处理函数
pybaseutils(Python)
pybaseutils是个人开发常用的python库,集成了python等常用的算法
安装方法1:pip install -i https://pypi.tuna.tsinghua.edu.cn/simple pybaseutils (有延时,可能不是最新版本)
安装方法2:pip install –upgrade -i https://pypi.org/simple pybaseutils (从pypi源下载最新版本)
一些问题修复说明
目录结构
├── base_utils # base_utils的C++源代码 ├── pybaseutils # pybaseutils的python源代码 ├── data # 相关测试数据 ├── test # base_utils的测试代码 │ ├── build.sh │ ├── CMakeLists.txt │ ├── kalman_test.cpp │ └── main.cpp └── README.md
base_utils(C++)
1.相关配置
OpenCV配置方法
# opencv set
find_package(OpenCV REQUIRED)
include_directories(${OpenCV_INCLUDE_DIRS} ./src/)
MESSAGE(STATUS "OpenCV_INCLUDE_DIRS = ${OpenCV_INCLUDE_DIRS}")
base-utils库的配置方法
# base-utils
set(BASE_ROOT ../) # 设置base-utils所在的根目录
add_subdirectory(${BASE_ROOT}/base_utils/ base_build) # 添加子目录到build中
include_directories(${BASE_ROOT}/base_utils/include)
include_directories(${BASE_ROOT}/base_utils/src)
MESSAGE(STATUS "BASE_ROOT = ${BASE_ROOT}")
配置OpenCL(可选)
OpenCL: https://software.intel.com/content/www/us/en/develop/tools/opencl-sdk/choose-download.html
Android系统一般都支持OpenCL,Linux系统可参考如下配置:
# 参考安装OpenCL: https://blog.csdn.net/qq_28483731/article/details/68235383,作为测试,安装`intel cpu版本的OpenCL`即可
# 安装clinfo,clinfo是一个显示OpenCL平台和设备的软件
sudo apt-get install clinfo
# 安装依赖
sudo apt install dkms xz-utils openssl libnuma1 libpciaccess0 bc curl libssl-dev lsb-core libicu-dev
sudo apt-key adv --keyserver hkp://keyserver.ubuntu.com:80 --recv-keys 3FA7E0328081BFF6A14DA29AA6A19B38D3D831EF
echo "deb http://download.mono-project.com/repo/debian wheezy main" | sudo tee /etc/apt/sources.list.d/mono-xamarin.list
sudo apt-get update
sudo apt-get install mono-complete
# 在intel官网上下载了intel SDK的tgz文件,并且解压
sudo sh install.sh
2.Demo测试
build
cd test
bash build.sh
test/main.cpp测试样例
#include<opencv2/opencv.hpp>
#include<string>
#include "debug.h"
using namespace std;
int main() {
string path = "../../data/test_image/test1.jpg";
DEBUG_TIME(t1);
cv::Mat image = cv::imread(path);
LOGI("image:%s", path.c_str());
LOGD("image:%s", path.c_str());
LOGW("image:%s", path.c_str());
LOGE("image:%s", path.c_str());
LOGF("image:%s", path.c_str());
DEBUG_TIME(t2);
LOGI("rum time:%3.3fms", RUN_TIME(t2 - t1));
cv::waitKey(0);
DEBUG_IMSHOW("image", image);
return 0;
}
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