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</head><body><div id="sidebar"><div id="menu-mask"></div><div id="sidebar-menus"><div class="avatar-img is-center"><img src="/img/avatar.jpg" onerror="onerror=null;src='/img/friend_404.gif'" alt="avatar"/></div><div class="sidebar-site-data site-data is-center"><a href="/archives/"><div class="headline">Articles</div><div class="length-num">6</div></a><a href="/tags/"><div class="headline">Tags</div><div class="length-num">14</div></a><a href="/categories/"><div class="headline">Categories</div><div class="length-num">21</div></a></div><hr class="custom-hr"/></div></div><div class="page" id="body-wrap"><header class="full_page" id="page-header" style="background-image: url('/img/wp3.png')"><nav id="nav"><span id="blog-info"><a href="/" title="MZP's blog"><span class="site-name">MZP's blog</span></a></span><div id="menus"><div id="search-button"><a class="site-page social-icon search" href="javascript:void(0);"><i class="fas fa-search fa-fw"></i><span> Search</span></a></div><div id="toggle-menu"><a class="site-page" href="javascript:void(0);"><i class="fas fa-bars fa-fw"></i></a></div></div></nav><div id="site-info"><h1 id="site-title">MZP's blog</h1><div id="site-subtitle"><span id="subtitle"></span></div></div><div id="scroll-down"><i class="fas fa-angle-down scroll-down-effects"></i></div></header><main class="layout" id="content-inner"><div class="recent-posts" id="recent-posts"><div class="recent-post-item"><div class="recent-post-info no-cover"><a class="article-title" href="/2024/10/02/Diffusion_Model/" title="Diffusion Model">Diffusion Model</a><div class="article-meta-wrap"><span class="post-meta-date"><i class="far fa-calendar-alt"></i><span class="article-meta-label">Created</span><time datetime="2024-10-01T16:00:00.000Z" title="Created 2024-10-02 00:00:00">2024-10-02</time></span><span class="article-meta"><span class="article-meta-separator">|</span><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/AIGC/">AIGC</a><i class="fas fa-angle-right article-meta-link"></i><a class="article-meta__categories" href="/categories/AIGC/DDPM/">DDPM</a></span></div><div class="content">Diffusion Model
扩散现象是指物质粒子从高浓度区域向低浓度区域移动的过程，如往水中滴入墨水。DDPM受到启发，将前向加噪也看成是扩散过程，逐步将有意义的原图像完全变成无意义的噪声。
前向加噪
对于一张图片X，通过随机采样生成符合标准正态分布的高斯噪声ε，ε具有与X相同的形状大小，然后对它们做加权平均，得到混合后的下一步图像，需要满足它们权重平方和为1，可写为：
\sqrt{\beta} \times \epsilon+\sqrt{1-\beta} \times x于是乎，
\begin{aligned}& x_1=\sqrt{\beta_1} \times \epsilon_1+\sqrt{1-\beta_1} \times x_0 \\& x_2=\sqrt{\beta_2} \times \epsilon_2+\sqrt{1-\beta_2} \times x_1 \\& x_3=\sqrt{\beta_3} \times \epsilon_3+\sqrt{1-\beta_3} \times x_2\end{aligned}Generally,
\begin{ ...</div></div></div><div class="recent-post-item"><div class="recent-post-info no-cover"><a class="article-title" href="/2024/09/02/%E6%9C%8D%E5%8A%A1%E5%99%A8%E6%90%AD%E5%BB%BA/" title="服务器搭建">服务器搭建</a><div class="article-meta-wrap"><span class="post-meta-date"><i class="far fa-calendar-alt"></i><span class="article-meta-label">Created</span><time datetime="2024-09-01T16:00:00.000Z" title="Created 2024-09-02 00:00:00">2024-09-02</time></span><span class="article-meta"><span class="article-meta-separator">|</span><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/server/">server</a></span></div><div class="content">
本人记忆着实一般，这几天新得了几台服务器的权限，要记录下来，怎么开坑，方便自己遇到此类问题。寻来方便。。
毕竟，前一天刚开一个服务器；第二天就忘了具体咋操作了
本人是做deep learning的，故本文仅仅适合DL的同学来看，其余不是很确定？？？
在/home/mazipei/目录下，下载miniconda/anaconda（看个人喜好，mini够用）
下载 Miniconda (Python3 version)
1wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
安装
1bash Miniconda3-latest-Linux-x86_64.sh
随后一直按回车，所有都yes安装好后，source ~/.bashrc
设置清华源
12python -m pip install --upgrade pippip config set global.index-url https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simp ...</div></div></div><div class="recent-post-item"><div class="recent-post-info no-cover"><a class="article-title" href="/2024/08/01/%E6%95%B0%E5%AD%A6/" title="math博客收藏">math博客收藏</a><div class="article-meta-wrap"><span class="post-meta-date"><i class="far fa-calendar-alt"></i><span class="article-meta-label">Created</span><time datetime="2024-07-31T16:00:00.000Z" title="Created 2024-08-01 00:00:00">2024-08-01</time></span><span class="article-meta"><span class="article-meta-separator">|</span><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/math/">math</a></span></div><div class="content">
记录一些数学知识，方便以后忘记时回来
SVD：主要用途，解欠定、超定方程
</div></div></div><div class="recent-post-item"><div class="recent-post-info no-cover"><a class="article-title" href="/2024/04/19/nerf_3dgs%E5%8D%9A%E5%AE%A2%E6%94%B6%E8%97%8F%E5%A4%B9/" title="nerf_3dgs博客收藏">nerf_3dgs博客收藏</a><div class="article-meta-wrap"><span class="post-meta-date"><i class="far fa-calendar-alt"></i><span class="article-meta-label">Created</span><time datetime="2024-04-18T16:00:00.000Z" title="Created 2024-04-19 00:00:00">2024-04-19</time></span><span class="article-meta"><span class="article-meta-separator">|</span><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/3DV/">3DV</a></span></div><div class="content">
记录一些nerf，3dgs的前置知识及讲解的博客和视频
知乎收藏夹：
https://www.zhihu.com/collection/949437601
nerf 解读：
原理：https://zhuanlan.zhihu.com/p/481275794
代码：https://zhuanlan.zhihu.com/p/482154458
相机参数与坐标系变换：https://zhuanlan.zhihu.com/p/593204605/
球协函数：
http://www.yindaheng98.top/%E5%9B%BE%E5%BD%A2%E5%AD%A6/%E7%90%83%E8%B0%90%E7%B3%BB%E6%95%B0.html#%E5%9F%BA%E5%87%BD%E6%95%B0
</div></div></div><div class="recent-post-item"><div class="recent-post-info no-cover"><a class="article-title" href="/2024/03/29/pytorch%E5%8D%9A%E5%AE%A2%E6%94%B6%E8%97%8F%E5%A4%B9/" title="python realted博客收藏">python realted博客收藏</a><div class="article-meta-wrap"><span class="post-meta-date"><i class="far fa-calendar-alt"></i><span class="article-meta-label">Created</span><time datetime="2024-03-28T16:00:00.000Z" title="Created 2024-03-29 00:00:00">2024-03-29</time></span><span class="article-meta"><span class="article-meta-separator">|</span><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/pytorch/">pytorch</a></span></div><div class="content">
记录一些在看代码时遇到的一些问题及博客，方便以后忘记时回来
知乎收藏夹：
https://www.zhihu.com/collection/947243718
csdn收藏夹：
https://i.csdn.net/#/user-center/collection-list?type=1&folder=36818606&key=1
模型save and load:
https://www.cnblogs.com/Zhuohome/p/15599792.html
命令行参数：
https://www.bilibili.com/video/BV1U4411j7xb/?spm_id_from=333.337.search-card.all.click&vd_source=738644d63e97553d6e3dc1cd66a642d6
cuda版本：
https://cloud.tencent.com/developer/article/1731440
Python装饰器：
https://foofish.net/python-decorat ...</div></div></div><div class="recent-post-item"><div class="recent-post-info no-cover"><a class="article-title" href="/2023/11/16/3DV/nerfreport/" title="NeRF 笔记">NeRF 笔记</a><div class="article-meta-wrap"><span class="post-meta-date"><i class="far fa-calendar-alt"></i><span class="article-meta-label">Created</span><time datetime="2023-11-15T16:00:00.000Z" title="Created 2023-11-16 00:00:00">2023-11-16</time></span><span class="article-meta"><span class="article-meta-separator">|</span><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/3DV/">3DV</a><i class="fas fa-angle-right article-meta-link"></i><a class="article-meta__categories" href="/categories/3DV/NeRF/">NeRF</a></span></div><div class="content">NeRF 笔记
写在前面这原是我图形学课上论文阅读的一个作业，现放在自己博客里面，也当是我学习NeRF的一个小结。
NeRFAbstractNeRF提出了一种通过使用输入视图的稀疏集来优化底层连续体积场景函数，进而实现复杂场景的新视图合成的最先进的结果的方法。使用全连接（非卷积）深度网络，输入有五个维度（空间坐标$(x,y,z)$，视角方向$(\theta,\phi)$），输出是该空间位置的体积密度$\sigma$和视角相关的color。再通过传统的体渲染技术得到最后的像素值。通过比较生成图像和ground truth作为loss，来训练神经网络。
NeRF的意义是什么？经典的图形学渲染流程中，我们是通过对输入的图像进行三维建模，再去进行自由视角的渲染。这就要求构建出非常高质量的三维模型才能渲染出精细的结果。但是很多情况下，三维模型的构建是比较困难的。但是NeRF基于深度学习的流程，通过对三维场景的神经表达，结合可微分渲染，可以实现端到端的训练。最终可以实现在任意视角下对模型的渲染。
NeRF的基本原理NeRF的流程基本上可以用这幅图概括：
沿着相机光线，采样5D坐标合成图像 (位 ...</div></div></div><nav id="pagination"><div class="pagination"><span class="page-number current">1</span></div></nav></div><div class="aside-content" id="aside-content"><div class="card-widget card-info"><div class="is-center"><div class="avatar-img"><img src="/img/avatar.jpg" onerror="this.onerror=null;this.src='/img/friend_404.gif'" alt="avatar"/></div><div class="author-info__name">Ma Zipei</div><div class="author-info__description">好好学习，天天向上</div></div><div class="card-info-data site-data is-center"><a href="/archives/"><div class="headline">Articles</div><div class="length-num">6</div></a><a href="/tags/"><div class="headline">Tags</div><div class="length-num">14</div></a><a href="/categories/"><div class="headline">Categories</div><div class="length-num">21</div></a></div><a id="card-info-btn" target="_blank" rel="noopener" href="https://github.com/xiao10ma"><i class="fab fa-github"></i><span>Follow Me</span></a></div><div class="card-widget card-announcement"><div class="item-headline"><i class="fas fa-bullhorn fa-shake"></i><span>Announcement</span></div><div class="announcement_content">This is my Blog</div></div><div class="sticky_layout"><div class="card-widget card-recent-post"><div class="item-headline"><i class="fas fa-history"></i><span>Recent Post</span></div><div class="aside-list"><div class="aside-list-item no-cover"><div class="content"><a class="title" href="/2024/10/02/Diffusion_Model/" title="Diffusion Model">Diffusion Model</a><time datetime="2024-10-01T16:00:00.000Z" title="Created 2024-10-02 00:00:00">2024-10-02</time></div></div><div class="aside-list-item no-cover"><div class="content"><a class="title" href="/2024/09/02/%E6%9C%8D%E5%8A%A1%E5%99%A8%E6%90%AD%E5%BB%BA/" title="服务器搭建">服务器搭建</a><time datetime="2024-09-01T16:00:00.000Z" title="Created 2024-09-02 00:00:00">2024-09-02</time></div></div><div class="aside-list-item no-cover"><div class="content"><a class="title" href="/2024/08/01/%E6%95%B0%E5%AD%A6/" title="math博客收藏">math博客收藏</a><time datetime="2024-07-31T16:00:00.000Z" title="Created 2024-08-01 00:00:00">2024-08-01</time></div></div><div class="aside-list-item no-cover"><div class="content"><a class="title" href="/2024/04/19/nerf_3dgs%E5%8D%9A%E5%AE%A2%E6%94%B6%E8%97%8F%E5%A4%B9/" title="nerf_3dgs博客收藏">nerf_3dgs博客收藏</a><time datetime="2024-04-18T16:00:00.000Z" title="Created 2024-04-19 00:00:00">2024-04-19</time></div></div><div class="aside-list-item no-cover"><div class="content"><a class="title" href="/2024/03/29/pytorch%E5%8D%9A%E5%AE%A2%E6%94%B6%E8%97%8F%E5%A4%B9/" title="python realted博客收藏">python realted博客收藏</a><time datetime="2024-03-28T16:00:00.000Z" title="Created 2024-03-29 00:00:00">2024-03-29</time></div></div></div></div><div class="card-widget card-categories"><div class="item-headline">
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