<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[ly0303521的专栏]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/ly0303521</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; ly0303521]]></copyright><item><title><![CDATA[英伟达 Isaac Sim仿真平台安装体验]]></title><link>https://blog.youkuaiyun.com/ly0303521/article/details/143776526</link><guid>https://blog.youkuaiyun.com/ly0303521/article/details/143776526</guid><author>ly0303521</author><pubDate>Mon, 18 Nov 2024 17:06:45 +0800</pubDate><description><![CDATA[Isaac sim 仿真]]></description><category></category></item><item><title><![CDATA[修改docker的工作目录]]></title><link>https://blog.youkuaiyun.com/ly0303521/article/details/142384069</link><guid>https://blog.youkuaiyun.com/ly0303521/article/details/142384069</guid><author>ly0303521</author><pubDate>Fri, 20 Sep 2024 14:23:33 +0800</pubDate><description><![CDATA[【代码】修改docker的工作目录。]]></description><category></category></item><item><title><![CDATA[curl 交叉编译]]></title><link>https://blog.youkuaiyun.com/ly0303521/article/details/136203883</link><guid>https://blog.youkuaiyun.com/ly0303521/article/details/136203883</guid><author>ly0303521</author><pubDate>Wed, 21 Feb 2024 09:54:19 +0800</pubDate><description><![CDATA[curl 交叉编译库]]></description><category></category></item><item><title><![CDATA[linux 日常使用命令]]></title><link>https://blog.youkuaiyun.com/ly0303521/article/details/125291487</link><guid>https://blog.youkuaiyun.com/ly0303521/article/details/125291487</guid><author>ly0303521</author><pubDate>Wed, 15 Jun 2022 10:09:27 +0800</pubDate><description><![CDATA[linux常用的命令]]></description><category></category></item><item><title><![CDATA[opencv Mat理解]]></title><link>https://blog.youkuaiyun.com/ly0303521/article/details/123577175</link><guid>https://blog.youkuaiyun.com/ly0303521/article/details/123577175</guid><author>ly0303521</author><pubDate>Fri, 18 Mar 2022 16:04:42 +0800</pubDate><description><![CDATA[函数一
#include &lt;opencv2/opencv.hpp&gt;

cv::Mat func(cv::Mat input) {
    input.setTo(0);
    //input = cv::Mat::ones(4, 4, CV_32F);
    return input;
}

int main(int argc, char const *argv[]) {
    cv::Mat imga = cv::imread("/home/ly/Pictures/11111111.jp]]></description><category></category></item><item><title><![CDATA[vscode 使用相关问题]]></title><link>https://blog.youkuaiyun.com/ly0303521/article/details/123572528</link><guid>https://blog.youkuaiyun.com/ly0303521/article/details/123572528</guid><author>ly0303521</author><pubDate>Fri, 18 Mar 2022 13:33:35 +0800</pubDate><description><![CDATA[vscode 工程 #include &lt;opencv2/opencv.hpp&gt; 下有波浪线

使用Cmakelist.txt检索文件

cmake_minimum_required(VERSION 3.10)
project(test)

set(CMAKE_CXX_STANDARD 11)
set(CMAKE_CXX_FLAGS  "${CMAKE_CXX_FLAGS} -g")

set(OpenCV_DIR /home/ly/Public/opencv-4.5.5/lib/cmake/op]]></description><category></category></item><item><title><![CDATA[opencv 安卓工程创建]]></title><link>https://blog.youkuaiyun.com/ly0303521/article/details/123199176</link><guid>https://blog.youkuaiyun.com/ly0303521/article/details/123199176</guid><author>ly0303521</author><pubDate>Tue, 01 Mar 2022 10:13:13 +0800</pubDate><description><![CDATA[下载opencv 安卓 NDK
opencv NDK


导入 opencv sdk作为 module， 将 opencv sdk添加依赖
- 将相应C++、java 文件添加至工程，并生成C++ 的头文件，修改头文件名字


 ly@BOE:~/AndroidStudioProjects/opencvDemo/mytest/src/main/java$ javah -d ../cpp/ -jni com.example.mytest.yolactModule


修改 build.gradle



..]]></description><category></category></item><item><title><![CDATA[ubuntu终端显示中文问题]]></title><link>https://blog.youkuaiyun.com/ly0303521/article/details/106123515</link><guid>https://blog.youkuaiyun.com/ly0303521/article/details/106123515</guid><author>ly0303521</author><pubDate>Thu, 14 May 2020 17:01:31 +0800</pubDate><description><![CDATA[标题终端无法显示中文可能的原因

系统没有安装中文语言包，参考文章

apt-get install language-pack-zh-hans #近期版本


安装完中文包后需要设置环境,参考文章
打开/etc/environment
在下面添加如下两行

LANG="zh_CN.UTF-8"
LANGUAGE="zh_CN:zh:en_US:en"

打开 /var/lib/locales/supported.d/local
添加zh_CN.GB2312字符集，如下：
en_US.UTF-8 UTF-8]]></description><category></category></item><item><title><![CDATA[模型转换以及openvino前向部署]]></title><link>https://blog.youkuaiyun.com/ly0303521/article/details/105975318</link><guid>https://blog.youkuaiyun.com/ly0303521/article/details/105975318</guid><author>ly0303521</author><pubDate>Thu, 07 May 2020 17:22:21 +0800</pubDate><description><![CDATA[pytorch 训练时，往往会使用torchvision.transforms.ToTensor，会将图片数据转换成CHW，范围[0.0, 1.0]
pytorch转换成onnx模型或者tensorflow模型，pytorch转onnx参考文章，pytorch转onnx参考工程，pytorch转darknet参考工程， darknet转tf, tf转IR参考文章
openvino参考运行命令
注...]]></description><category></category></item><item><title><![CDATA[ubuntu 安装并使用多个版本的opencv]]></title><link>https://blog.youkuaiyun.com/ly0303521/article/details/105738335</link><guid>https://blog.youkuaiyun.com/ly0303521/article/details/105738335</guid><author>ly0303521</author><pubDate>Fri, 24 Apr 2020 19:40:59 +0800</pubDate><description><![CDATA[Ubuntu下安装多个版本的opencv，以及切换使用
注意 ~/.bashrc 中 不能 export LD_LIBRARY_PATH=/usr/local/opencv/3.1.0/lib ,因为这样会直接覆盖调之前的LD_LIBRARY_PATH,  应该修改成 export LD_LIBRARY_PATH="/usr/local/opencv/4.3.0/lib:$LD_LIBRARY...]]></description><category></category></item><item><title><![CDATA[图片相似度度量方法]]></title><link>https://blog.youkuaiyun.com/ly0303521/article/details/104658577</link><guid>https://blog.youkuaiyun.com/ly0303521/article/details/104658577</guid><author>ly0303521</author><pubDate>Wed, 04 Mar 2020 17:48:05 +0800</pubDate><description><![CDATA[度量方法参考资料地址
参考资料里面的是python代码，总共有三种方式，下面是参考其中一种写的C++
#include &lt;iostream&gt;
#include &lt;vector&gt;
#include &lt;opencv2/opencv.hpp&gt;

using namespace std;
using namespace cv;

vector&lt;int&gt; dh...]]></description><category></category></item><item><title><![CDATA[C++ 遍历json文件]]></title><link>https://blog.youkuaiyun.com/ly0303521/article/details/102968602</link><guid>https://blog.youkuaiyun.com/ly0303521/article/details/102968602</guid><author>ly0303521</author><pubDate>Fri, 08 Nov 2019 10:41:05 +0800</pubDate><description><![CDATA[C++ 遍历json文件欢迎使用Markdown编辑器
欢迎使用Markdown编辑器
#include &lt;iostream&gt;
#include &lt;string&gt;
#include &lt;jsoncpp/json/json.h&gt;
#include &lt;fstream&gt;

using namespace std;

void print_json(Json:...]]></description><category></category></item><item><title><![CDATA[ncnn交叉编译]]></title><link>https://blog.youkuaiyun.com/ly0303521/article/details/102510387</link><guid>https://blog.youkuaiyun.com/ly0303521/article/details/102510387</guid><author>ly0303521</author><pubDate>Fri, 11 Oct 2019 21:19:35 +0800</pubDate><description><![CDATA[踩坑记录

在交叉编译海思平台时
可以看到是因为PROTOBUF_LIBRARY 找不到，经过多次尝试仍然没有解决，后来发现ncnn/tools/caffe和ncnn/tools/onnx需要它，但是现在只是想要海思平台下的libncnn.a，并不需要tools下面的东西，所以暂时的解决方案是将 …/CMakeLists.txt 下的代码注释

 if(NCNN_BUILD_TOOLS)
    ...]]></description><category></category></item><item><title><![CDATA[unbuntu 安装docker、nvidia-docker2]]></title><link>https://blog.youkuaiyun.com/ly0303521/article/details/86544457</link><guid>https://blog.youkuaiyun.com/ly0303521/article/details/86544457</guid><author>ly0303521</author><pubDate>Fri, 18 Jan 2019 18:07:15 +0800</pubDate><description><![CDATA[添加源https://download.docker.com/
Uninstall old versions
sudo apt-get remove docker docker-engine docker.io containerd runc

Install packages to allow apt to use a repository over HTTPS:
$ sudo apt-get ...]]></description><category></category></item><item><title><![CDATA[docker容器、镜像的基本操作]]></title><link>https://blog.youkuaiyun.com/ly0303521/article/details/82690200</link><guid>https://blog.youkuaiyun.com/ly0303521/article/details/82690200</guid><author>ly0303521</author><pubDate>Thu, 13 Sep 2018 16:26:55 +0800</pubDate><description><![CDATA[docker容器、镜像的基本操作





利用镜像创建一个新的容器



sudo nvidia-docker run -it -p 8888:8888 -v /home/luyang:/home --name luyang-deepo ufoym/deepo:all-jupyter-py36-cu90


nvidia-docker： 必须使用该命令创建才能使用显卡
-p 8888:8888：...]]></description><category></category></item><item><title><![CDATA[Atom  git-control 插件出错]]></title><link>https://blog.youkuaiyun.com/ly0303521/article/details/79273335</link><guid>https://blog.youkuaiyun.com/ly0303521/article/details/79273335</guid><author>ly0303521</author><pubDate>Tue, 06 Feb 2018 18:19:01 +0800</pubDate><description><![CDATA[错误提示：

Uncaught TypeError: Cannot read property 'split' of undefined



解决办法

As a workaround you can replace .path with .getPath() in the git-control/lib/git-control-view.coffee:76 and the git-contro]]></description><category></category></item><item><title><![CDATA[给numpy矩阵添加一列]]></title><link>https://blog.youkuaiyun.com/ly0303521/article/details/79245223</link><guid>https://blog.youkuaiyun.com/ly0303521/article/details/79245223</guid><author>ly0303521</author><pubDate>Sat, 03 Feb 2018 10:31:04 +0800</pubDate><description><![CDATA[问题的定义：
首先我们有一个数据是一个mn的numpy矩阵现在我们希望能够进行给他加上一列变成一个m(n+1)的矩阵
import numpy as np
a = np.array([[1,2,3],[4,5,6],[7,8,9]])
b = np.ones(3)
c = np.array([[1,2,3,1],[4,5,6,1],[7,8,9,1]])
print(a)
print(b)
p]]></description><category></category></item><item><title><![CDATA[用自己训练好的caffemodel来对自己的图片做分类]]></title><link>https://blog.youkuaiyun.com/ly0303521/article/details/78964390</link><guid>https://blog.youkuaiyun.com/ly0303521/article/details/78964390</guid><author>ly0303521</author><pubDate>Wed, 03 Jan 2018 18:59:14 +0800</pubDate><description><![CDATA[首先是deploy.prototxt文件的生成，deploy.prototxt和train_val.prototxt文件类似，只是头尾有些区别而已。没有了第一层的数据层，也没有最后的accuracy层（用于反向传播），但最后多了一个Softmax概率层（Softmax直接计算前向的概率），所以deploy文件没有了反向传播部分。

一般不推荐用代码来生成，熟悉train_val.prototx]]></description><category></category></item><item><title><![CDATA[矩阵、向量求导法则]]></title><link>https://blog.youkuaiyun.com/ly0303521/article/details/78489721</link><guid>https://blog.youkuaiyun.com/ly0303521/article/details/78489721</guid><author>ly0303521</author><pubDate>Thu, 09 Nov 2017 14:59:39 +0800</pubDate><description><![CDATA[复杂矩阵问题求导方法：可以从小到大，从scalar到vector再到matrix。





 x is a column vector, A is a matrix

$d(A*x)/dx=A$            

$d(x^T*A)/dx^T=A$   

$d(x^T*A)/dx=A^T$    

$d(x^T*A*x)/dx=x^T(A^T+A)$
]]></description><category></category></item><item><title><![CDATA[Babun，一个开箱即用的 Windows Shell]]></title><link>https://blog.youkuaiyun.com/ly0303521/article/details/77960463</link><guid>https://blog.youkuaiyun.com/ly0303521/article/details/77960463</guid><author>ly0303521</author><pubDate>Wed, 13 Sep 2017 04:04:15 +0800</pubDate><description><![CDATA[背景

多年以来，无数工程师都试图在 Windows 上制造出不输 Linux 太多的命令行体验，然而绝大部分以失败告终。曾经努力的人，或者回到可爱的 Linux 上，或者进入高贵冷艳的 OS X 的世界。

前辈们为我们留下了一个叫做 Cygwin 的软件集，让我们在需要的时候可以从 Windows 上启动 bash，安装常见的自由软件。

我曾经也有过一段不得不使用 Windows]]></description><category></category></item></channel></rss>