<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[wolf2345的博客]]></title><description><![CDATA[小白在路上~fightingQAQ]]></description><link>https://blog.youkuaiyun.com/wolf2345</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; wolf2345]]></copyright><item><title><![CDATA[ubuntu升级显卡驱动]]></title><link>https://blog.youkuaiyun.com/wolf2345/article/details/126119887</link><guid>https://blog.youkuaiyun.com/wolf2345/article/details/126119887</guid><author>wolf2345</author><pubDate>Tue, 02 Aug 2022 12:23:24 +0800</pubDate><description><![CDATA[显卡掉了，驱动升级安装]]></description><category></category></item><item><title><![CDATA[ubuntu降内核版本]]></title><link>https://blog.youkuaiyun.com/wolf2345/article/details/125495389</link><guid>https://blog.youkuaiyun.com/wolf2345/article/details/125495389</guid><author>wolf2345</author><pubDate>Tue, 28 Jun 2022 08:49:43 +0800</pubDate><description><![CDATA[内核自动升级导致ubuntu系统页面循环进不去，故选择降低内核版本解决]]></description><category></category></item><item><title><![CDATA[ubuntu环境写入静态ip]]></title><link>https://blog.youkuaiyun.com/wolf2345/article/details/120311022</link><guid>https://blog.youkuaiyun.com/wolf2345/article/details/120311022</guid><author>wolf2345</author><pubDate>Wed, 15 Sep 2021 16:19:05 +0800</pubDate><description><![CDATA[1.sudo vim /etc/network/interfaces

增加如下内容


auto eth0
iface eth0 inet static
address 1172.20.0.116
netmask 255.255.255.0

2.sudo systemctl restart networking
]]></description><category></category></item><item><title><![CDATA[opencv rect]]></title><link>https://blog.youkuaiyun.com/wolf2345/article/details/115705063</link><guid>https://blog.youkuaiyun.com/wolf2345/article/details/115705063</guid><author>wolf2345</author><pubDate>Wed, 14 Apr 2021 17:50:32 +0800</pubDate><description><![CDATA[//如果创建一个Rect对象rect(100, 50, 50, 100)，那么rect会有以下几个功能：
rect.area(); //返回rect的面积 5000
rect.size(); //返回rect的尺寸 [50 × 100]
rect.tl(); //返回rect的左上顶点的坐标 [100, 50]
rect.br(); //返回rect的右下顶点的坐标 [150, 150]
rect.width(); //返回rect的宽度 50
rect.hei...]]></description><category></category></item><item><title><![CDATA[ubuntu下代码比较工具－beyond compare]]></title><link>https://blog.youkuaiyun.com/wolf2345/article/details/114529554</link><guid>https://blog.youkuaiyun.com/wolf2345/article/details/114529554</guid><author>wolf2345</author><pubDate>Mon, 08 Mar 2021 14:17:36 +0800</pubDate><description><![CDATA[安装方法

wget https://www.scootersoftware.com/bcompare-4.3.7.25118_amd64.deb
sudo apt-get update
sudo apt-get install gdebi-core
sudo gdebi bcompare-4.3.7.25118_amd64.deb
]]></description><category></category></item><item><title><![CDATA[caffe编译python接口出错]]></title><link>https://blog.youkuaiyun.com/wolf2345/article/details/108850139</link><guid>https://blog.youkuaiyun.com/wolf2345/article/details/108850139</guid><author>wolf2345</author><pubDate>Mon, 28 Sep 2020 15:12:15 +0800</pubDate><description><![CDATA[错误类型:

python/caffe/_caffe.cpp:374:10: error: could not convert ‘uid’ from ‘std::__cxx11::string {aka std::__cxx11::basic_string&lt;char&gt;}’ to ‘boost::python::api::object’
 return uid;

解决办法:

修改:/usr/include/x86_64-linux-gnu/c++/7/bits/c++config.h的24..]]></description><category></category></item><item><title><![CDATA[from conda.cli import main    ModuleNotFoundError: No module named ‘conda‘]]></title><link>https://blog.youkuaiyun.com/wolf2345/article/details/108583710</link><guid>https://blog.youkuaiyun.com/wolf2345/article/details/108583710</guid><author>wolf2345</author><pubDate>Mon, 14 Sep 2020 17:31:47 +0800</pubDate><description><![CDATA[当运行conda出现:

Traceback (most recent call last):
 File "/home/pc/anaconda3/bin/conda", line 7, in &lt;module&gt;
 from conda.cli import main
ModuleNotFoundError: No module named 'conda'

解决方法:更新anaconda,且不影响原始虚拟环境

bash Anaconda3-5.3.1-Linux-x86_64.sh ...]]></description><category></category></item><item><title><![CDATA[yolov4训练和测试]]></title><link>https://blog.youkuaiyun.com/wolf2345/article/details/108306995</link><guid>https://blog.youkuaiyun.com/wolf2345/article/details/108306995</guid><author>wolf2345</author><pubDate>Sun, 30 Aug 2020 15:55:34 +0800</pubDate><description><![CDATA[1、训练yolov4

./darknet detector train /home/pc/Documents/yolov4/data/0827/code/obj.data /home/pc/Documents/yolov4/data/0827/code/yolov4-obj.cfg /home/pc/Documents/yolov4/data/0827/code/yolov4.conv.137 -map

2、测试打印map

./darknet detector test /home/pc/Docume]]></description><category></category></item><item><title><![CDATA[yolov4训练网络配置及参数配置]]></title><link>https://blog.youkuaiyun.com/wolf2345/article/details/108306837</link><guid>https://blog.youkuaiyun.com/wolf2345/article/details/108306837</guid><author>wolf2345</author><pubDate>Sun, 30 Aug 2020 15:33:03 +0800</pubDate><description><![CDATA[1、网络模型

主要修改classes和其上一层网络层输出（classes+5）*3-&gt;(classes+[xmin,ymin,xmax,ymax,c])*Scalar

lr_rate和max_batches自行配置，建议初始学习率设置为0.001，max_batches=classes*2000

[net]
# Testing
#batch=1
#subdivisions=1
# Training
batch=96
subdivisions=32
width=416
height=416
cha]]></description><category></category></item><item><title><![CDATA[yolov4数据集制作与规范性检查]]></title><link>https://blog.youkuaiyun.com/wolf2345/article/details/108306657</link><guid>https://blog.youkuaiyun.com/wolf2345/article/details/108306657</guid><author>wolf2345</author><pubDate>Sun, 30 Aug 2020 15:22:53 +0800</pubDate><description><![CDATA[1、图片重命名-&gt;rename.py

import os
#import cv2
import shutil


jpg_path = '/media/em/data_1/0716/data2/socket/mark'
xml_path = '/media/em/data_1/0716/data2/socket/xml/'

out_jpg_path = '/media/em/data_1/0716/data2/socket/JPEGImages1/'
out_xml_path = '/media/]]></description><category></category></item><item><title><![CDATA[YOLOv4训练自己的数据]]></title><link>https://blog.youkuaiyun.com/wolf2345/article/details/108306576</link><guid>https://blog.youkuaiyun.com/wolf2345/article/details/108306576</guid><author>wolf2345</author><pubDate>Sun, 30 Aug 2020 15:11:52 +0800</pubDate><description><![CDATA[环境要求：

1、ubuntu16.04或者ubuntu18.04

2、cmake_minimum_required(VERSION 3.12)（升级包见software）

升级cmake：

（1）tar zxvf cmake-3.12.2-Linux-x86_64.tar.gz

（2）mv cmake-3.12.2-Linux-x86_64 /opt/cmake-3.12.2

（3）ln -sf /opt/cmake-3.12.2/bin/* /usr/bin/

3、CUDA&gt;=10..]]></description><category></category></item><item><title><![CDATA[leetcode(2)--整数反转]]></title><link>https://blog.youkuaiyun.com/wolf2345/article/details/107126670</link><guid>https://blog.youkuaiyun.com/wolf2345/article/details/107126670</guid><author>wolf2345</author><pubDate>Sat, 04 Jul 2020 16:49:47 +0800</pubDate><description><![CDATA[class Solution {
public:
 int reverse(int x) {
 int y = 0;
 while(x!=0)
 {
 if(y&gt;214748364 || y &lt; -214748364 )
 {return 0;}
 y = y*10+x%10;
 x=x/10;
 }
 return y;
 }
 
};
...]]></description><category></category></item><item><title><![CDATA[leetcode(1)--两数之和]]></title><link>https://blog.youkuaiyun.com/wolf2345/article/details/107126559</link><guid>https://blog.youkuaiyun.com/wolf2345/article/details/107126559</guid><author>wolf2345</author><pubDate>Sat, 04 Jul 2020 16:46:25 +0800</pubDate><description><![CDATA[（1）暴力求解

class Solution {
public:
 vector&lt;int&gt; twoSum(vector&lt;int&gt;&amp; nums, int target) {
 vector&lt;int&gt;out;
 for(int i = 0; i &lt; nums.size() - 1; i++)
 {
 for(int j = i + 1; j &lt; nums.size();j++)
...]]></description><category></category></item><item><title><![CDATA[yolov4 finetune出现错误]]></title><link>https://blog.youkuaiyun.com/wolf2345/article/details/107080898</link><guid>https://blog.youkuaiyun.com/wolf2345/article/details/107080898</guid><author>wolf2345</author><pubDate>Thu, 02 Jul 2020 11:33:09 +0800</pubDate><description><![CDATA[Done! Loaded 162 layers from weights-file
Learning Rate: 0.001, Momentum: 0.949, Decay: 0.0005
If error occurs - run training with flag: -dont_show
Saving weights to /home/pc/Documents/yolov4/darknet-master/backup/backup20200702/yolo-obj_final.weights
Cr..]]></description><category></category></item><item><title><![CDATA[yolo，caffe，tf-lite，keras，mxnet，ncnn网络模型可视化在线工具]]></title><link>https://blog.youkuaiyun.com/wolf2345/article/details/107041617</link><guid>https://blog.youkuaiyun.com/wolf2345/article/details/107041617</guid><author>wolf2345</author><pubDate>Tue, 30 Jun 2020 14:18:26 +0800</pubDate><description><![CDATA[https://lutzroeder.github.io/netron/
]]></description><category></category></item><item><title><![CDATA[RK3399 ubuntu更换国内源]]></title><link>https://blog.youkuaiyun.com/wolf2345/article/details/106521969</link><guid>https://blog.youkuaiyun.com/wolf2345/article/details/106521969</guid><author>wolf2345</author><pubDate>Wed, 03 Jun 2020 13:09:50 +0800</pubDate><description><![CDATA[RK3399 的ubuntu-arm源和 X86源不一样，故做个记录。

1.备份源

sudo cp /etc/apt/sources.list /etc/apt/sources.list.tmp

2.添加国内源到系统文件中

sudo vim /etc/apt/sources.list

加入如下源并保存：

deb http://mirrors.ustc.edu.cn/ubuntu-ports/ bionic multiverse
deb http://mirrors.ustc.edu.cn/u..]]></description><category></category></item><item><title><![CDATA[ubuntu 16.04 +1070ti + mxnet + cuda8.0 + anaconda + pycharm 环境配置记录]]></title><link>https://blog.youkuaiyun.com/wolf2345/article/details/105901091</link><guid>https://blog.youkuaiyun.com/wolf2345/article/details/105901091</guid><author>wolf2345</author><pubDate>Sun, 03 May 2020 11:13:27 +0800</pubDate><description><![CDATA[豆瓣源：https://pypi.douban.com/simple

pip install mxnet-cu80 -i https://pypi.douban.com/simple


]]></description><category></category></item><item><title><![CDATA[C++ 左值&右值相关及move的使用]]></title><link>https://blog.youkuaiyun.com/wolf2345/article/details/105246305</link><guid>https://blog.youkuaiyun.com/wolf2345/article/details/105246305</guid><author>wolf2345</author><pubDate>Wed, 01 Apr 2020 15:05:32 +0800</pubDate><description><![CDATA[左值、左值引用、右值、右值引用

1、左值和右值的概念

    左值是可以放在赋值号左边可以被赋值的值；左值必须要在内存中有实体；
    右值当在赋值号右边取出值赋给其他变量的值；右值可以在内存也可以在CPU寄存器。
    一个对象被用作右值时，使用的是它的内容(值)，被当作左值时，使用的是它的地址。

2、引用

    引用是C++语法做的优化，引用...]]></description><category></category></item><item><title><![CDATA[onnx，caffe模型在线转ncnn，mnn]]></title><link>https://blog.youkuaiyun.com/wolf2345/article/details/97273476</link><guid>https://blog.youkuaiyun.com/wolf2345/article/details/97273476</guid><author>wolf2345</author><pubDate>Thu, 25 Jul 2019 16:54:43 +0800</pubDate><description><![CDATA[在线地址：https://convertmodel.com/?tdsourcetag=s_pcqq_aiomsg


]]></description><category></category></item><item><title><![CDATA[Pytorch中torchvision.transforms常用的数据变换]]></title><link>https://blog.youkuaiyun.com/wolf2345/article/details/89012054</link><guid>https://blog.youkuaiyun.com/wolf2345/article/details/89012054</guid><author>wolf2345</author><pubDate>Thu, 04 Apr 2019 10:29:53 +0800</pubDate><description><![CDATA[torchvision.transforms中常用的数据变换

（1）torchvision.transforms.Resize():用于对载入的图片数据按我们需求的大小进行缩放。传递给这个类的参数可以使一个整形数据，也可以是一个类似于（h,w）的序列，其中，h代表高度，w代表宽度，但是如果使用的是一个整形数据，那么代表缩放的宽度和高度都是这个整形数据的值。

（2）torchvision.tra...]]></description><category></category></item></channel></rss>