so hello everybody um 所以大家好
it's been a while since my last post um what we're going to do today uh it's ，自从我上一篇文章以来已经有一段时间了，我们今天要做什么，这
quite interesting it's um one of the most famous let's say 3D 很有趣，这是最著名的之一，比如说 3D
uh tools for techniques or applications for Fleet the model reconstruction that 呃，用于舰队技术或应用的工具，模型重建
appeared again in a couple of past years today 再次出现在 过去几年的今天，
um or currently those techniques are more 嗯，或者目前，这些技术更
powerful faster more accessible now that we are 强大，更快，更容易获得，因为我们正在
uh passing or beyond that GPU crisis that 通过或超越
affected uh the world because of covid and and so on 因 covid 等影响世界的 GPU 危机，
and so forth we have the option to to get reasonable uh or reasonably 我们可以选择获得 合理的呃或
reasonably priced uh gpus 价格合理的呃gpus
so we can run these models locally we can apply machine learnings uh machine 所以我们可以在本地运行这些模型我们可以以更快更简单的方式再次应用机器学习呃机器
learning models in a again in a faster easier way so today we're gonna see what 学习模型所以今天我们要看看
we have here we're going to go through like nerve Studio 我们在这里有什么我们要经历就像 nerf Studio 一样
that Nerf studio is actually quite easy to use I'm going to show it to you ，Nerf studio 实际上很容易使用
because you can do uh quite interesting thing so you can
um train models to generate this neural
radiant Fields it's like some sort of like photogrammetry but you're not lds 它有点像摄影测量，但你不是在
producing meshes you're producing uh let's say like pixels so you can create 生产网格，而是在生产，呃，让我们说像像素，这样你就可以创建
videos and also you can create meshes today we're not going to cover that we 视频，而且你今天也可以创建网格，我们不打算介绍，我们
will cover installation and basic functioning and then we will train uh 将介绍安装和基本运行，然后我们将训练
our own model and I will teach you because that is very interesting still 我们自己的模型，我会教你，因为这很有趣，但
most of these techniques rely on something that's called call map but I 大多数这些技术都依赖于称为调用映射的东西，但我
will show you an alternative way of creating your own models because colmap 会向你展示另一种创建自己模型的方法，因为
has still some issues installing on Windows if you have a Linux machine you colmap 仍然有一些 在 Windows 上安装的问题如果你有一台 Linux 机器，你
can just go and do it but in Windows is still like kind of tricky and also Cool 可以直接去做，但在 Windows 中仍然有点棘手，而且
Math that is um I will explain what it is it's not a very good tool in my 数学很酷，嗯，我会解释它是什么，在我看来它不是一个很好的工具，
opinion so the first thing that you need of course 所以 您首先需要做的当然
is to go to anaconda.com because we want to deal with or we will 是访问 anaconda.com，因为我们要处理或者我们将
have to deal with the creation of environments so if you go to 不得不处理环境的创建，所以如果您访问
anaconda.com you can download Anaconda and it's a really easy setup uh anaconda.com，您可以下载Anaconda，它是一个真正的 安装很简单 嗯
the way that you install it I'm just going to download it I'm not going to ，你安装它的方式 我只是要下载它 我不会
install it but I will show you just download the installer 安装它但我会告诉你只需下载安装程序
this will apply for Windows sadly it will not work on Mac because we 这将适用于 Windows遗憾的是它不能在 Mac 上运行，因为我们
need Cuda cores we need Cuda uh toolkit and Tiny Cuda so when you download this 需要 Cuda 核心，我们需要 Cuda uh 工具包和 Tiny Cuda 所以当你下载这个
64-bit setup you just agree next next next you basically say yes and next to 64 位设置时，你只需同意 next nextnext next 你基本上说是，然后对
everybody to everything so you will have Anaconda how do you check if you have 每个人都说是，所以你将拥有Anaconda 你如何检查你是否有
Anaconda you go to your menu and you write anaconda and you can see Anaconda 你去 到你的菜单，然后你写 anaconda 你可以看到
actually let me move 实际上让我移动
if you go to your menu anaconda and you will see two things 如果你去你的菜单anaconda 你会看到
that are necessary for this uh that are installed you will see the Anaconda 这两个必要的东西 uh 已安装你
navigator that is what we have here but we will use mostly the Anaconda prompt 会看到我们这里有的 Anaconda 导航器但是我们将主要使用 Anaconda 提示符，
so let's use that installer tools and we we are ready to 所以让我们使用该安装程序工具，我们准备好
to start
starts back here um 从这里开始，嗯，
so I will put the the commands Below in the description so 所以我将把下面的命令放在描述中，所以
we will start with um the installation of Nerf 我们将从安装 Nerf 开始，
uh the first thing we need to create an environment so to create an environment 嗯，第一个薄 g 我们需要创建一个环境 所以要创建一个环境，
we need to do a couple of things um 我们需要做几件事um
again just go to your start menu Anaconda prompt 再次进入你的开始菜单Anaconda 提示
you will see a command window make it bigger so you can see it and you can say 你会看到一个命令窗口，把它变大，这样你就可以看到它，你可以说
like conduct create minus n like conduct 创建minus n
erf studio and we can um erf studio 我们可以
say minus y and we can specify the python version 说 minus y并且我们可以指定 python 版本
um we can do 3.9 but uh I think uh 3.8 will will do the the job um 我们可以做 3.9 但是我认为 uh 3.8 将完成他们教程
that's the the way in the description of their tutorials is like indicated so 描述中的工作方式就像指示的那样
with this command we can create the environment to have an isolated 使用此命令，我们可以创建环境以隔离
installation of all the dependencies so we just do that 安装所有依赖项，因此
if you're not familiar with with an account basically what it does is that 如果您不熟悉帐户，我们
it's a among like other things um it allows you to create a specific 就这样做 一个特定的
environment so again you can isolate 环境，所以你可以再次隔离
the installation of different things so you see that now is creating something 不同东西的安装，所以你看到现在正在
um with the minus y we're just say yes just create everything 用减号 y 创建一些东西，我们只是说是，只需创建所有东西，
install what we need to install 安装我们需要安装的东西，
to create again ah let me clear the screen so if I say 以再次创建啊，让我清除屏幕，所以如果我说
now conda um 现在 condaum
activate near Studio you see that now we are in nav Studio activate near Studio你会看到现在我们处于 nav Studio
environment so now we can start installing a couple of things the first 环境中所以现在我们可以开始安装一些东西
thing that we need is upgrade pip so you can say python minus ampip 我们需要的第一件事是升级 pip所以你可以说 python minus ampip
install um installum
upgrade pip or pip upgrade pip or
and now we need to start installing uh the things that we need so the First pip 现在我们需要开始安装我们需要的东西所以第一个
Command again I'm going to write it here in the 命令我将在这里写在
description it's this pip install we're installing Pi torch with um with torch 描述中这是这个 pip 安装我们正在安装 Pi torch with
Vision with Cuda 11.3 um 带有 Cuda 11.3 的 torch Vision嗯，
so this is basically like one of the the main requirements 所以这基本上就像是主要要求之一，
it takes a little bit uh usually like Anaconda uh 它需要一点点，嗯，通常像Anaconda，嗯
it's slow for the installation in this case we're using pip so that is good my ，安装速度很慢，在这种情况下，我们使用的是 pip，所以这很好，我的
computer is a little bit slow uh for some reason now you see that it's 电脑有点 慢 呃，出于某种原因，现在你看到它正在
installing everything 安装所有的东西，
is installing the all the packages uh numpy pillow 正在安装所有的包，嗯，numpy pillow
um everything so everything runs smoothly so you wait for a couple of um 一切，所以一切都运行顺利，所以你等
minutes uh you see that all the dependencies are are installed and this 几分钟，呃，你看到所有的依赖项都在 停滞了
is something that it's very important I will recommend that you ，这是非常重要的事情，我会建议你
and some um 和一些人
you go for example to your desktop uh create a new folder 去你的桌面，比如创建一个新文件夹，
uh we can call it NS for Nerf Studio because after a while uh not not in this 我们可以称它为 Nerf Studio 的 NS，因为过了一会儿，呃，不是在这
step but in in the in the next one in two steps we will install Nerf Studio 一步，而是在 在接下来的两个步骤中，我们将安装 Nerf Studio，
so you wanna you wanna have it in a directory and basically everything 所以你想把它放在一个目录中，基本上一切都
organized now we need to install Tiny Cuda 组织好了，现在我们需要安装 Tiny Cuda，
this might give you an error that error will be solved I mean if you get an 这可能会给你一个错误，错误将被解决我的意思是如果你 收到一个
error that there is no AC plus runtime install in your in your computer go and 错误，提示您的计算机中没有安装 AC plus 运行时，请
install Visual Studio not Visual Studio code Visual Studio 2022 and it will 安装 Visual Studio 而不是 Visual Studiocode Visual Studio 2022，它将
solve all your installation problems so if you do this Pap install this is the 解决您所有的安装问题，因此如果您执行此 Pap 安装，这是
installing directly from the from the source again you will wait a couple of 直接从再次从源代码开始，您将等待
minutes and you will have tiny Cuda installed in your computer but if you 几分钟，您的计算机中将安装微型 Cuda，但是如果
get an error again after this step you should you probably will see an error if 在此步骤之后再次出现错误，您应该会看到错误，如果您不这样做的话，您可能会看到错误。
you don't have Visual Studio 2022 install or a nice installation of 20 ave Visual Studio 2022install or an nice installation of 20
Studio 2020 for example so do that before you follow these steps so after Studio 2020 so so do
you install Tiny Cuda that takes around like 10 minutes probably then before you follow these steps so after you install Tiny Cuda that takes aroundlike 10 minutes
um I think we're good to go so the umI think we's good to go 所以
installation of Nerf studio is super easy to just go like Pap uh install air 安装 Nerf studio 超级简单，就像 Pap uh install air
Studio and it doesn't take much time so you Studio 一样，它不需要太多时间所以你
will see you start installing a couple of things uh we need to know a couple of 会看到你开始安装一些东西 uh 我们需要知道一些
uh uh
uh yeah so you will download all the libraries and files that are necessary uh 是的 所以你会下载所有的库 和必要的文件
you can see here um 你可以在这里看到嗯
it installs a lot of things and then we need to generate data but I 它安装了很多东西然后我们需要生成数据但我
will show you one specific thing we're going to train 会告诉你一件具体的事情我们将要训练
uh one specific data set and I will show you at the end the final part of this 一个特定的数据集我会在最后告诉你 该视频的最后一部分是
video how to create your own data set with an alternative method 如何使用另一种方法创建您自己的数据集
and in a the next video that will come probably next week I will show you ，在下一个视频中可能会在下周发布，我将向您展示
another technique if you have an iPhone with lighter capacity it's even like 另一种技术，如果您的 iPhone容量较小，它甚至
easier to generate uh nerve data so after you do this 更容易生成 呃神经数据，所以在你这样做之后，
um we're pretty much done so you see that installs like a lot of things it 嗯，我们已经完成了很多，所以你会看到安装了很多东西，它
doesn't take uh as much or it doesn't take as long as uh tiny Cuda but we are 不需要那么多时间，或者不需要像微型 Cuda 那样长的时间，但我们
good to go and do something so for example we can do NS basically like all 很乐意 去做一些事情，例如我们可以做 NS 基本上就像
the functionality of of um
of Nerf studio is like NS something so in this case we can do Nerf studio 的 um 的所有功能就像 NS 一样，所以在这种情况下我们可以
download 下载
um data um数据
and we can download for example a data set ，我们可以下载例如
data set we can use for example like blender 我们可以使用的数据集数据集 例如像blender
uh or we can use Nerf Studio let's start with blender 呃或者我们可以使用 Nerf Studio 让我们从 blender
uh so if we do this we will start 呃开始所以如果我们这样做我们将开始
downloading from
from a Google repository like one point something 从 Google 存储库下载一些东西
um gigabytes of of information um千兆字节的信息
um so if I go now for example to the folder um所以如果我现在去例如文件夹
you can see that in NS we have the data directory and we have here 你可以看到，在 NS 中我们有数据目录，我们这里
a um repository with things that are needed 有一个 um存储库，其中包含
for training uh or testing for example uh Nerf Studio to to do a neural 训练或测试所需的东西，例如uh Nerf Studio 来做神经
Radiance we have a transform file it is a Json file 辐射，我们有一个转换文件，它是一个 Json
that we can for example like open with Visual Studio code 文件 我们可以例如打开Visual Studio 代码
and what it does basically it gives it has 及其作用基本上
the information of a set of cameras associated with also an image so 它提供了一组与图像相关联的相机的信息，所以
basically it gets like a position of a camera the transformation matrix the 基本上它就像一个相机的位置、变换矩阵、
rotation the camera angle all the information from different images one 旋转、相机角度、来自不同图像的所有信息一
thing that we should know is that all the images should be the exact same size 件事 我们应该知道的是，所有图像的大小都应该完全相同，
otherwise it won't work so if we go for example to here like nerve synthetic 否则它将无法工作，所以如果我们像神经合成数字一样去这里
figures uh train these are just like a bunch of synthetic data information 训练，这些就像一堆关于相机的合成数据信息
about cameras going from like a 3D model but we're gonna test it with first yeah 一样 一个 3D 模型，但我们首先要测试它，是的
one of this um things I'm gonna cancel this and I ，我要取消这个，我
will show you how to generate your own data set so I'm going to close this I'm 会告诉你如何生成你自己的数据集，所以我要关闭它，我
going to minimize this let's start and train our 要最小化 这让我们开始并训练我们的
first uh model so we can do 第一个呃模型，这样我们就可以
the following thing so you can start again with the uh with 做以下事情，这样你就可以用这个数据重新开始，
this data like the data set you that you download from blender and so on and so 比如你从搅拌机下载的数据集
forth or you can just like start uh training your own uh model so you can do 等等，或者你可以像开始一样 呃训练你自己的呃模型所以你可以做
for example NS train and you can do a vanilla Nerf 例如NS 火车你可以做一个香草 Nerf
vanilla um 香草um
Nerf we can do for example this Nerf 我们可以做这个
um um
viewer was it yeah viewer uh and we can say like viewer was it ye​​ah viewer uh 我们可以说就像
you were that web socket 你是那个 web socket
uh dashboard we can say seven zero zero eight for example let's see if 呃仪表板我们 可以说七零零八例如让我们看看
this works I think this should start training without 这是否有效我认为这应该毫无问题地开始训练
without a problem uh vanilla Nerf error argument uh oh 呃香草 Nerf 错误参数呃哦
apparently we cannot see this uh 显然我们看不到这个呃
what did it do wrong oh 它做错了什么哦
it should work uh no such file as data blender Lego 它应该工作呃没有这样的文件 data blender Lego
this is giving me like a weird error so let me check if this works without any 这给了我一个奇怪的错误，所以让我检查一下这是否有效，
um 嗯，
yeah it's so weird that if I specify like a viewer 是的，这太奇怪了，如果我像查看器一样指定
gives me a problem so for example here we can train I mean this is good to test 给我一个问题，那么例如在这里我们可以训练我的意思是这很好测试
if everything is working the installation is working 如果一切正常，则安装正常，
um we can choose don't visualize if you want to see for example how the training 我们可以选择不可视化，例如，如果您想查看培训
is going you can create a wave a weight and bias account or use an existing 的进展情况，您可以创建一个 wave 权重和偏差帐户或使用现有的
weight and biases account or don't visualize anything in this case I don't 权重和偏差帐户或不在这种情况下可视化任何东西我
want to visualize anything um hopefully it will 不想可视化任何东西嗯希望它
and it gave me an error 会它给了我一个错误
excuse me too many errors it says that it cannot find data blender 对不起我太多错误它说它找不到
for Lego 乐高的数据混合器
uh let me see if I do this here 呃让我看看我是否在这里
that will be kind of ridiculous so let's see 这样做将会是 有点荒谬所以让我们看看
oh so what we need to do actually is giving 哦所以我们实际上需要做的是给
me like some errors like stupid error so I'm gonna do uh one thing 我一些像愚蠢错误这样的错误所以我要再做一件事
again you see this is the level and users my 你看这是水平和用户我的
account Diego um I will 帐户迭戈嗯我会
download the blender data set here 下载搅拌机 数据集在这里，
because for some reason it's giving me errors with my desktop probably because 因为出于某种原因，我的桌面出现错误，可能是
of one drive or something like that uh yeah that's kind of it uh 因为一个驱动器或类似的东西，嗯，是的，这
annoying so Diego 有点烦人，所以迭戈
and we can see here that it's downloading yeah everything this should ，我们可以在这里看到它正在下载是的，一切都应该没问题，
be fine so let's see if everything works I'm interested in seeing that the the 所以让我们看看 如果一切正常，我有兴趣看到
training process works so see Nerf synthetic 训练过程有效，所以请看 Nerfsynthetic
um 嗯
oh it's expanding ，它正在扩大，
oops it's oh here blender chair tests 哎呀，哦，这里是搅拌机椅子测试，
okay let's see if this works now so let's try to reutilize one of the 好吧，让我们看看这现在是否有效，所以让我们尝试重新利用其中一个
previous commands let's try to run the the vanilla nerve 以前的命令让我们尝试运行
the original implementation and with the viewer to see if everything 原始实现的香草神经并与查看器一起查看是否
works so we execute this command uh yeah now 一切正常所以我们执行这个命令嗯是的现在
it's loading like catching the images loading the batch so one thing that is 它正在加载就像捕捉图像加载批处理所以一件
very interesting is like super cool but now it's working loading everything 非常有趣的事情就像超级酷但现在它正在加载
it says that we don't have any previous training but here it gives you an 它说我们以前没有接受过任何培训的所有内容，但这里它给你一个
address that if we go 地址，如果我们去，
um if you use spray browser it won't work so I recommend that you use Chrome 嗯，如果你使用喷雾浏览器，它就不会工作，所以我建议你使用 Chrome，
you go to that address and you will start seeing 你去那个 地址，你会开始看到
this this is Nerf Studio an application I think it was developed in react 这是 Nerf Studio 的一个应用程序，我认为它是在 react 中开发的，
um that you see just like for the 嗯，你看到的就像语法一样，
grammatory it starts loading 它开始加载
all the images just like photogrammetry like with the position the orientation 所有图像，就像摄影测量一样，就像位置、
the rotation and magically it will start showing you 方向、旋转一样，它会神奇地 开始向您展示
the the neural Radiance field so basically it's like this small thing 神经辐射场，所以基本上它就像这个小东西
that you can then post process and turn into a um ，然后您可以进行后期处理并变成一个
nice uh 3D model for example so this is interactive so now you see 不错的 3D 模型，例如s o 这是交互式的，所以现在你看到
like it's it's trying to something is showing up 它正在尝试显示某些东西，
but we're training just the vanilla example one that you can find in like 但我们正在训练的只是普通示例，你可以在
papers about reading Fields so yeah we're not interesting on 关于阅读Fields 的论文中找到它，所以是的，我们对此并不感兴趣，
this um so we know that it's working the 所以我们知道 它正在工作
server for this is working so let's just stop this let's stop the training 服务器正在工作所以让我们停止这个让我们停止
and let's try what they the people from Nerf Studio claim that it is their their 训练让我们尝试他们来自Nerf Studio 的人声称这是他们
best algorithm 最好的算法
so uh let's just do for example 所以呃让我们做例如
I have some commands here we can train with instant NGP or nerve 我在这里有一些命令我们可以 使用即时 NGP 或神经因子进行训练，
facto that is the other one so [Music] 这是另一个[音乐]
um let me see if this works 嗯，让我看看这是否有效，
you're gonna try to see like NS train 你会尝试像 NS 训练一样，
um yeah it's giving me one error let's see 嗯，是的，它给了我一个错误，让
again how we can solve this path errors um 我们再看看我们如何解决这个路径错误嗯，
if we go to the data folder blender 如果我们去数据文件夹blender
okay that's the problem so here we need to 好吧，这就是问题所在，所以我们需要
uh actually this is data uh 实际上这是 data
blender uh let's try to do blender呃让我们尝试使用
the ship
same arguments viewer uh 相同的参数查看器
yeah for some reason this one it doesn't probably we cannot train 呃是的，出于某种原因，这可能不是我们无法训练
blender blender
yeah it's you cannot find that because the the datas are like transformed tests 是的，你找不到，因为数据就像转换后的测试，
let's do one more time if not we will move to our custom because that's the 让我们再做一次，如果没有，我们将转向我们的习惯，因为这是
important agent I'm just trying to show you ways on how this could work 重要的代理，我只是想向你展示如何
uh with the data that they provide if not that's fine yeah it's giving me the 处理数据 他们提供如果不是那很好是的它给了我
same thing because the format is different okay whatever we don't care 同样的东西因为格式不同好吧无论我们不
about this I just want to train your Factor so just give me one second we're 关心这个我只想训练你的因素所以给我一秒钟我们
gonna do a uh 会做一个呃
we will download the Nerf Studio data set 我们会 下载 Nerf Studio 数据
to see if with this we can actually train 集看看我们是否真的可以训练
um our model 我们的模型
so we downloaded that we will say like NS train uh nerfacto as our algorithm 所以我们下载了我们会说像NS train uh nerfacto 作为我们
for training uh we will specify that we want to 的训练算法呃我们将指定我们想要
visualize the results in the viewer the data will be in 在查看器中可视化结果数据将在
data they have studio um 他们有工作室的数据中um
poster is the one so if we go to the folder here data and our studio poster 海报是一个所以如果我们转到这里的文件夹数据和我们的工作室
and this is interesting because here we have the transforms Json 海报这很有趣因为这里我们有转换 Json
uh we have some directories with images 呃我们有一些带有图像
it's just a chair so let's see if if this works because this algorithm is 的目录它只是一个 cha ir 所以让我们看看这是否有效因为这个算法
faster and more accurate so uh poster trainer the sorry viewer 更快更准确所以呃海报培训师抱歉
that websocket 观众 websocket
socket 7008 套接字7008
socket Port sorry websocket Port not socket 套接字端口抱歉 websocket 端口不是套接字
it takes a little bit uh oh can 它需要一点点呃哦可以有
one error well it's my errors here 一个错误吗这是我的错误
ah viewer this 啊 viewerthis
I didn't say like so it will tell you like yeah the options here so I didn't I didn't say like so it will tell youlike yeah the options here so I didn't
put one thing I have another error put one thingI have another error
and a strain or facto minus minus Theta and a strain or factominus minus Theta
put socket port what is wrong here uh oh sorry this was put socket portwhat is wrong here 呃哦对不起这是
the other way around this
viewer now we're good sorry about that 换句话说，现在我们很抱歉，
yeah you see that now it's working it's loading the data 是的，你看到它现在正在工作，它正在加载数据，
no checkpoints to low so streaming from scratch let's copy this 没有检查点，所以从头开始流式传输让我们将它
go to Chrome 复制到 Chrome，
we have near Studio you see that it loads the images 我们在 Studio 附近，你看到它加载了图像
and after a couple of passes it should start showing the training 几次通过后，它应该开始显示训练
process yeah there we go so you see for now everything looks like kind of Cloudy 过程是的，我们走了，所以你现在看到的一切看起来有点多云，
you can pan you can uh Orient and this is super cool 你可以平移你可以呃东方，这太酷了，
so actually we can hide the images and you see that how through every step 所以实际上我们可以隐藏它 e 图像，你会看到通过每
like we're one percent of the training process and we already see 一步，我们是训练过程的百分之一，我们已经看到了
this so it's like calculating let's say like one let's think about it as a pixel 这一点，所以这就像计算一样，让我们​​把它想象
in space it's not even a point right but then you can convert into that you can 成空间中的一个像素，它甚至不是一个点，但是然后 你可以转换成你可以
add more resolution it will take longer to train 增加更多的分辨率训练需要更长的时间
uh if you're familiarized with the the the 呃如果你熟悉
nerve or neural Radiance Fields you see that because these are pictures 你看到的神经或神经辐射场因为这些是图片
let's click here this is pointing this this is pointing that so it doesn't have 让我们点击这里这是指向这个这是指向那个所以 它没有
information of what's beyond right it doesn't have information 超出正确范围的信息 它没有
outside the pictures so this is why everything looks like kind of cloudy but 图片之外的信息 所以这就是为什么一切看起来都有些模糊 但
it it looks pretty pretty good so you will see this kind of things 它看起来相当不错 所以一旦你暂停训练你就会看到这种东西
once you you pause the training so let's say we want to pass the 所以假设我们想通过
training let's see if we can do something 培训让我们看看我们是否可以做些什么
um hide the images 嗯隐藏图像
um I think we can add yeah we can add a 嗯我想我们可以添加是的我们可以添加一个
camera so you see to say like oh this is a good perspective uh let's add another 相机所以你看到说哦这是一个很好的视角呃让我们添加另一个 这里
camera here let's add another camera that maybe this 的相机让我们添加另一个相机，也许这个
this then a camera that goes 然后一个相机到
here 这里
then another camera that does this and then we can close this 然后另一个相机做这个然后我们可以关闭它
and we can play you see the animation of the camera rendering if you go to 我们可以播放你看到相机渲染的动画如果你去
um render View 渲染视图
and this is the the nice part of it so you can play it again 和这个 是它最好的部分所以你可以再次播放它
so you can see that it creates an animation so now the 所以你可以看到它创建了一个动画所以现在
cool part about this is that you can um 关于这个很酷的部分是你可以
after this process if you go to render where is it yeah render to render 在这个过程之后如果你去渲染它是在哪里渲染渲染
full resolution video then you can just because it already saved a checkpoint 完整 分辨率视频然后你可以只是因为它已经保存了一个检查点
for example now the results are not very good but you can just copy this command 例如现在结果不是很好但是你可以复制这个命令
and paste it let's try it actually um 并粘贴它让我们实际尝试一下嗯
let's just stop this Ctrl and C and if we 让我们停止这个 Ctrl 和C 如果我们
oop did I copy the command oop 我复制了 命令
copy command yeah there it is I just pasted it 复制命令是的，我刚刚粘贴了它
I think it's saved the checkpoint so it should 我认为它保存了检查点所以它应该
create a video it's loading the data 创建一个视频它正在加载数据
uh oh I don't have um 呃哦我没有
this so I need to install it and that's a little bit painful uh if it's 这个所以我需要安装它这有点痛苦呃 如果它是
necessary only if using bdss input so this shouldn't be a problem 只有在使用 bdss 输入时才有必要，所以这应该不是问题，
um 嗯，
yeah why is this give me that 2004 resolution video the video blah blah 是的，为什么这给我 2004分辨率视频视频等等
blah blah there is another way 等等等等还有另一种方式，
because now we have the server disconnected 因为现在我们已经断开了服务器的连接，
uh that's the path so that's also a cool thing we can create a new path or 嗯，这就是路径，所以这也是一个 很酷的事情，我们可以创建一个新路径或
extract it and we will have the possibility of 提取它，我们将有可能
um reusing that 重新使用该
uh 路径
for for another model for example if we like what we did there 用于另一个模型，例如，如果我们喜欢我们在那里所做的，
um so you see that now we don't have the 那么你会看到现在我们没有
server running we have the path but we don't have more uh information 运行服务器 有路径，但我们没有更多的信息，
uh you can change here like different options resolution uh more resolution 呃，你可以在这里改变，比如不同的选项，分辨率，呃，更高分辨率，
it will cost like slower training again the cool thing that is that everything 它会像更慢的训练一样花费很酷的事情，那就是
works and is visualized on web So eventually you can use for example 一切正常，并且在网络上可视化，所以最终你可以使用
like a Ubuntu Ubuntu uh virtual machine to process everything if you have found 例如 Ubuntu Ubuntu uh 虚拟机来处理所有的事情如果你发现
if you find errors so probably I will cover that in the next 如果你发现错误所以我可能会在下一个
uh session you can change yeah you see like options close the spline or not add uh 会话中介绍你可以改变是的你看到像选项关闭样条 o r 不添加
cameras and so on and so forth um load path or export the path uh for 摄像头等等等等um 加载路径或导出路径 嗯，出于
some reason yeah it's it's weird because it should 某种原因，是的，这很奇怪，因为
I don't want to install ffmp 我不想安装ffmp
[Music] pack [Music]pack
so if it doesn't work now it's okay I don't I didn't want to do this for this 所以如果它现在不起作用没关系 我不想，我不想为这个视频做这个，
video uh it will come from the next yeah it's 嗯，它会来自
yeah it's uh it's a pain in the butt so I'm gonna show you how you can create
your own data set
right that's the meat of of this video Beyond like installation and stuff we're 下一个 这个视频的主要内容除了安装和其他东西，我们
already like 30 minutes so uh what you can do 已经有 30 分钟了所以呃
if you are familiarized with photogrammetry there is one specific 如果你熟悉摄影测量你可以做什么有一个特定的
project or or program sorry app that is called 项目或程序抱歉应用程序叫做
metashape this is for uh doing like all kinds of photogrammetry metashape 这是为了呃做各种各样的摄影测量
um so one of the cool things about this is 嗯所以关于这个的一件很酷的事情
that it's really easy to use this is the one that I've used uh many times so what 是它真的很容易使用这是我用过很多次的那个所以
you can do 你可以做什么
uh uh where I have my images here
so let me find yeah I have a bunch of images here 呃呃我在这里有我的图像所以让我找到是的 我这里有一堆图片，
um that we can use to 嗯，我们可以用它们
to train a model you don't need too many images so in this case these 来训练你不知道的模型 不需要太多图像所以在这种情况下这些
are drone images let's just use 是无人机图像让我们
just for the sake of this this bunch of images here 只是为了这一堆图像在这里使用
you can just drag them to here what it says chunk 你可以将它们拖到这里它说的块
you have a free version if you go to edusoft you can download the free 你有免费版本如果你去edusoft 你可以 下载免费
version you don't need the the full paid version it's an evaluation so that will 版本，你不需要完整付费版本，这是一个评估，这样就
be fine I'm using middle shape again for this you have the cameras and you see 可以了我再次使用中间形状为此你有相机，你
that you have a list of cameras and these cameras are not aligned it 看到你有一个相机列表，但这些相机没有 对齐
means that you don't uh you don't have anything processed so using this 意味着你没有，呃，你没有任何处理，所以使用这个
uh programs you can go to workflow align photos you can use like the highest or 呃程序，你可以进入工作流程对齐照片，你可以使用最高
high resolution and it should take a couple of minutes to to do the job and I 分辨率或高分辨率，它应该需要几分钟才能完成这项工作 我
will show you the outputs once it's finished no loading I mean just it's 会在没有加载完成后向您展示输出 我的意思是它运行
going really fast like charging everything detecting the points because 得非常快，就像为检测点的所有东西充电一样，因为
I'm using a very powerful computer with a 3090 you see here with a 16 core GPU 我使用的是一台非常强大的计算机，配备 3090，你在这里看到，配备 16 核 GPU
128 gigs of RAM so probably if you're using let's say a laptop remember that 128 gigs RAM 所以 可能如果你是使用假设一台笔记本电脑记住
you need a capable Nvidia card that supports Cuda uh so yeah actually it did 你需要一个支持 Cuda 的功能强大的 Nvidia 卡嗯所以是的实际上它
the job very fast and it's perfect alignment so 完成工作非常快并且它是完美的对齐所以
it creates a sparse uh uh Point Cloud actually pretty good one 它创建了一个稀疏的呃点云实际上相当不错
uh so you can understand here the structure of the roof this is an old 呃所以你可以在这里理解屋顶的结构 这是一栋老
building that I don't know why I have this footage uh but what we want to do 建筑，我不知道为什么我有这段录像，呃，但我们现在想做的
now to uh let's create a status first I'm ，呃，让我们先创建一个状态，我
going to copy these images which I've done that before 将复制我之前做过的这些图像
um let's go to what I have the data set so 嗯，让我们转到我拥有的数据集，以便
users Diego data 用户 Diego 数据
let's create our own folder 让我们创建我们自己的文件夹
custom 自定义
all B from old building we will create one folder that will be 所有来自旧建筑的 B我们将创建一个
called images we will paste 名为 images 的文件夹我们将
our images here you don't need this amount of images we 在此处粘贴我们的图像你不需要这么多图像 我们
have 84 with 30 ish you are you're fine uh but that's cool just to show that you 有 84 和 30 ish 你很好你很好呃但这很酷只是为了表明
can do it with more um 你可以用更多嗯
so once you have the images here you want to go to file export export 所以一旦你在这里有了图像你想去文件导出导出
cameras and 相机
then you want to go to 然后你想去
the folder where you have 你有
your data 你的数据的文件
that is here custom 夹 这是自定义的
and here save it as like I don't know like all B and it will save an XML file ，在这里保存它，就像我不知道所有 B 一样，它将保存一个 XML 文件，
uh that will contain all the information about the cameras and the image like 呃，它将包含有关相机和图像的所有信息，
basically like that the position of the camera related to that image 基本上就像那样，相机的位置与之相关 图像
so uh or B 所以呃或 B
save so it's here 保存所以它在
and now we need to do one more so one person call Enrico allers uh he has this 这里现在我们需要再做一个所以一个人打电话给 Enrico allers 呃他有
a AGI to Nerf it's a repo that converts meta-shape camera location to nurb 一个 AGI 到 Nerf 这是一个将元形状相机位置转换为 nurb
conversion so you can use it with instant NGP but actually it works with 转换的回购所以你可以使用它即时 NGP 但实际上
nerd factor that is faster and more accurate so we will do that so we need 它与更快更准确的书呆子因素一起工作所以我们会这样做所以我们
to do a couple of things let's copy the address here 需要做几件事让我们在这里复制地址
let's go to our command line data CD custom 让我们转到我们的命令行数据 CD 自定义
old B and then we'll do get 旧 B然后我们将 获取
clone we will clone his repo and the only thing that you need to do actually 克隆，我们将克隆他的存储库，实际上你唯一需要做的
is let's see the documentation of his implementation 就是让我们看看他的实现文档
uh uh oh it's super easy so let me just put 呃呃哦这非常简单所以让我把
it on the side you just need to do uh python 它放在一边你只需要做呃 python
AGI to Nerf dot pi uh the XML AGI 到 Nerf dot piuh XML
it's called old 它被称为旧的
B dot XML so how do I know that B 点 XML所以我怎么知道
ob.xml so we just need to input that and let's execute it ob.xml 所以我们只需要输入它然后让我们执行它
probably it's not going to work the first time and we need to install some 可能它不会第一次工作我们需要安装一些
dependencies I'm not sure about that uh it cannot 依赖项我不确定呃它不能
oh sorry yes I installed it here so uh actually let's move the only thing that 哦 抱歉，是的，我把它安装在这里所以呃实际上让我们移动
we need is just this um a script so let's put it here 我们唯一需要的东西就是这个嗯一个脚本所以让我们把它放在这里
now we can execute it because we're in the same level uh the the right 我们现在可以执行它因为我们在同一级别呃正确的
directory so 目录所以
oh actually it's working off the shelf so 哦实际上它是 现成的所以
um yeah it did it 嗯是的它做到了
so you just need to compute the center of attention and and uh 所以你只需要计算注意力的中心然后呃
transform so let's see the differences here 转换所以让我们看看这里的差异
so this is the XML file so it's a lot of garbage it's like it has like this XML 所以这是 XML 文件所以它有很多垃圾就像它有这样的 XML
type of structure and this is a script that is very simple but very powerful it 类型 结构，这是一个非常简单但非常强大的脚本，它可以
converts all the camera extrinsics and the rotation and and images you see 转换所有相机外部参数和旋转以及您看到的图像
that it's the file path the sharpness of the image the transformation matrix so ，它是文件路径，图像的清晰度，转换矩阵，因此
it can be correctly interpreted by by nerve facto 它可以被神经正确解释
so now it's very simple to train our model 事实上 现在训练我们的模型非常简单
one thing probably if you run this probably I had it installed if you run 一件事可能如果你运行这个可能我已经安装了它如果你运行
this um 这个
this script probably you need to install uh opencv 这个脚本可能你需要安装呃opencv
so for that it's really simple you just do like pip 所以它真的很简单你就像pip
install install
opencv Dash python opencv Dash python
Python and you're golden you do that and probably that's the only dependency that Python 你很聪明，你这样做了，可能这是你需要安装的唯一依赖项，
you need to install so let's go back a couple of directories and let's do an s 所以让我们返回几个目录，让我们做一个 s
train nerfacto train nerfacto
um what else do we need so I forgot about um我们还需要什么所以我忘记
the command to try and train this oh this sorry this Dash this 了尝试和训练的命令 这个哦这个对不起这个 Dash 这个
viewer um 查看器嗯
data and this is in data 数据这是在数据
um 嗯
custom 自定义
all B that's it 所有 B就是它
and then viewer 然后查看器
that websocket Dash port 那个 websocketDash 端口
707 so if everything is correct this should work and start training 707 所以如果一切正确这应该工作并开始训练
uh okay no 呃好的没有
data custom 数据自定义
hold B 保持 B
oh
of course let's put the reference well now it 哦当然让我们把参考放好，现在它
should work I hope 应该可以工作了，我希望
oh no okay we need to go one level down 哦，不，我们需要降低一个级别，
sorry I was not in 抱歉，我不在，
yeah now it's loading sorry it was a again a typo it's loading everything 是的，现在它正在加载，抱歉，这又是一个错字，它正在加载
we can go to this uh URL here 我们可以去的所有东西 s uhURL
and it's loading the images pretty good it used to be like a lot of work to 这里它加载图像非常好它曾经像很多工作
actually do this with Nerf in a like a couple of months ago just like generate 一样在几个月前用 Nerf 实际做这个就像生成
this but now to just do like metal shape like you're doing like any type of 这个但现在就像金属形状一样 像任何类型的
photogrammetry you see it calculates more or less like the bounding box for 摄影测量一样，你看到它的计算或多或少像边界框，
for a start processing the thing it's telling me now that there are no 用于开始处理它现在告诉我的事情，没有
checkpoints to load and boom it just starts 检查点可以加载和繁荣它只是开始
training and you see that little by little 训练，你会看到它一点一点
it starts generating our neural Radiance field 地开始生成建筑物的神经辐射场
of the building you can get close to it 你可以靠近它
this is actually pretty nice I'm not gonna lie 这实际上非常好我不会说谎
and it's faster than the photography of course we're not processing a mesh you 而且它比摄影更快当然我们没有处理网格你
can increase the resolution as well so you can go like really high and it 也可以增加分辨率所以你可以 真的很高，
will take more information one thing that I want to show you for sure if you 如果你去任务管理器，我想向你展示一件事，这需要更多信息，
go to task manager uh 呃
see the building showing up if you go to task manager and if you want to check ，如果你去任务管理器，看看大楼出现了，如果你想
the performance of the computer 检查 计算机
um you see it's using a lot of CPU 嗯，如果你想象一下，你会看到它使用了大量的 CPU
if you visualize uh to The Logical processor is using pretty 逻辑处理器的使用几乎
much like everything uh I'm using a 5950x processor but if 就像所有东西一样，呃，我使用的是 5950x 处理器，但是如果
you go here it's a yeah like the Nvidia 3090 the it's using seven gigs out of 你去这里，它就像 Nvidia3090，它正在使用 7 gigs
24. it's not it's not too demanding to be honest and in terms of ram I'm using 24. 老实说，这并不是要求太高，就我使用的 ram 而言，
yeah Ram is using a lot it's using I mean including like system files and all 是的，Ram 使用了很多它正在使用我的意思是包括像系统文件和所有
that stuff uh the system usage is like 40 gigs out of 128. uh if we check the 这些东西，呃，系统使用就像128 中的 40 gigs .呃，如果我们检查这个
process 过程，
uh it gets a little bit slow I don't know why it's like I'm using Windows 10 呃，它会有点慢
I can't stand uh
for some reason it's not showing this
you can use shown okay uh
this is screencast this is Google Chrome uh CPU what is using CPU 这是 Google Chrome呃 CPU 什么正在使用 CPU
yeah python you see it's using like 49 the whole process using just like 10 是的 python 你看到它使用了49 整个过程使用了 10
gigabytes it's not too much GB 它不是太多
so it's this is very doable with a with a laptop 所以这对于笔记本电脑来说非常可行
this is very nice you see where 10 of the training process and we are already 这非常好你看到其中 10训练过程，我们已经
getting really cool results this is something in 得到了非常棒的结果 这是
Santiago Chile I'm building a really old building so 智利圣地亚哥的东西，我正在建造一座非常古老的建筑，所以
again the viewer is nice if you click on one image double click you see what you 如果你点击一张图片，双击你会看到你
are seeing so this is it for this video for a little bit more than 40 minutes uh 所看到的，那么观众又会很好，所以这就是这个视频的 40 多分钟呃
you can um 你可以，嗯，
yeah just try with your own stuff you have all the tools 是的，试试你自己的东西，你有所有的
so that's it and wait for the next video when we're gonna uh do a couple of more 工具，就是这样，等下一个视频，我们会做一些更
interesting things like try to extract extract a um mesh for example from this 有趣的事情，比如尝试提取一个嗯的网格，例如从这个
I wanted to show you this very nice tool in our studio 我 想在我们的工作室向您展示这个非常好的工具
powerful very cool 功能强大非常酷
see you next time 下次见