#叶瑄[超话]##风花雪叶想和你有个约会#
为什么要屏我[哼]重新发
大半夜被吵得睡不着QwQ决定一次性全部答完…就不艾特小屋了
可能有雷，可能有梦，可能有发典成分，慎阅
day1：应该是在去年的四月……在b站刷到后一见钟情（。）
2：我的好爹咪好温柔好喜欢；好好看好喜欢；好社气好想超一下（）；他好爱我我也要好爱他
3：以下常见称呼按顺口程度进行排序：
叶瑄 爹咪 叶老师 叶瑄哥哥
4：可能是好色吧（x）以及较强的雏鸟情节……较强的缺爱环境……较强的依恋情节……
5：这就不能细说了（x）
哪里都很戳……喜欢被叶老师摸摸头顶亲亲抱抱夸夸我的xp是叶瑄整个人！
6：太多了，一下子罗列不出来…
7：你是因爱而诞生的孩子，与这个世界上的其他孩子没有任何不同。
8：一些可爱绘本，想听叶瑄讲睡前故事；或者换成我来讲也可以
9：这可太多了嘿嘿嘿（收收味收收味）
日常西装很好看，诸界翅膀很好看，定制陪伴很好看，冬装也好看，夏装也好看……不穿也好看…（喂！）………最近的多洛塔也特别好看叶瑄穿什么就喜欢什么
10：像我这种脑袋空空缺爱嗜睡又回避社交的小女孩就应该被打包起来送给叶老师然后被好吃好喝养在孤岛上面嘛QwQ（够了……）
11：天空之镜……不过事实上哪里都可以
12：可能会更想看纪录片一些。电影的话，最近想看《海蒂和爷爷》[抱一抱]
13：…都可以…？因为个人也并不喜欢吃零食所以对食物没有特别的渴求……最近会比较想吃火锅或者其他有麻辣汤底的暖烘烘的食物[哇]
14：很多很多，哪里都喜欢所以哪里都可以是细节（啥）
15：一定要说的话可能随时都在心疼（。）疼一会儿又被哄好（。）过一会儿又开始疼（。）然后又被哄得很好（。
16："你是上帝展示在我失明的眼睛前的音乐、天穹、宫殿、江河、天使，深沉的玫瑰，隐秘而没有穷期。"
17：这个…………感觉一般默认是鹰与狐，个人更偏向鹰一些
18：enmm…………想了一想觉得不便多说
19：太多了……具体同上
20：那可太多了…（打住）
啊啊啊刚刚脑袋里闪过很文艺很正式的一句！居然忘了！（挠头）只能先说一点觉得很搭的歌的歌词了……
I wish that Y2K had happened, we would stay forever classic，
我希望Y2K（2000年问题）发生了，我们会永远保持经典，
You and I both be trapped in, in 1999，
你我都被困在了1999。
We talk all of the time and I love it，
我们一直在聊天，我很喜欢这样，
So what are you doing tonight?
所以你今晚要干嘛？
If you wanna come over, watch Friends and then get high，
如果你想过来一起看《老友记》然后一起high，
Use my phone as a coaster, we'll travel back in time，
用我的手机当做时光机 ，我们会穿越回到过去，
Lights on the ceiling, we're more than a feeling，
天花板上的灯，我们不只一种感觉，
If you wanna come over, act like it's 1999，
如果你想过来，假装现在是1999。
为什么要屏我[哼]重新发
大半夜被吵得睡不着QwQ决定一次性全部答完…就不艾特小屋了
可能有雷，可能有梦，可能有发典成分，慎阅
day1：应该是在去年的四月……在b站刷到后一见钟情（。）
2：我的好爹咪好温柔好喜欢；好好看好喜欢；好社气好想超一下（）；他好爱我我也要好爱他
3：以下常见称呼按顺口程度进行排序：
叶瑄 爹咪 叶老师 叶瑄哥哥
4：可能是好色吧（x）以及较强的雏鸟情节……较强的缺爱环境……较强的依恋情节……
5：这就不能细说了（x）
哪里都很戳……喜欢被叶老师摸摸头顶亲亲抱抱夸夸我的xp是叶瑄整个人！
6：太多了，一下子罗列不出来…
7：你是因爱而诞生的孩子，与这个世界上的其他孩子没有任何不同。
8：一些可爱绘本，想听叶瑄讲睡前故事；或者换成我来讲也可以
9：这可太多了嘿嘿嘿（收收味收收味）
日常西装很好看，诸界翅膀很好看，定制陪伴很好看，冬装也好看，夏装也好看……不穿也好看…（喂！）………最近的多洛塔也特别好看叶瑄穿什么就喜欢什么
10：像我这种脑袋空空缺爱嗜睡又回避社交的小女孩就应该被打包起来送给叶老师然后被好吃好喝养在孤岛上面嘛QwQ（够了……）
11：天空之镜……不过事实上哪里都可以
12：可能会更想看纪录片一些。电影的话，最近想看《海蒂和爷爷》[抱一抱]
13：…都可以…？因为个人也并不喜欢吃零食所以对食物没有特别的渴求……最近会比较想吃火锅或者其他有麻辣汤底的暖烘烘的食物[哇]
14：很多很多，哪里都喜欢所以哪里都可以是细节（啥）
15：一定要说的话可能随时都在心疼（。）疼一会儿又被哄好（。）过一会儿又开始疼（。）然后又被哄得很好（。
16："你是上帝展示在我失明的眼睛前的音乐、天穹、宫殿、江河、天使，深沉的玫瑰，隐秘而没有穷期。"
17：这个…………感觉一般默认是鹰与狐，个人更偏向鹰一些
18：enmm…………想了一想觉得不便多说
19：太多了……具体同上
20：那可太多了…（打住）
啊啊啊刚刚脑袋里闪过很文艺很正式的一句！居然忘了！（挠头）只能先说一点觉得很搭的歌的歌词了……
I wish that Y2K had happened, we would stay forever classic，
我希望Y2K（2000年问题）发生了，我们会永远保持经典，
You and I both be trapped in, in 1999，
你我都被困在了1999。
We talk all of the time and I love it，
我们一直在聊天，我很喜欢这样，
So what are you doing tonight?
所以你今晚要干嘛？
If you wanna come over, watch Friends and then get high，
如果你想过来一起看《老友记》然后一起high，
Use my phone as a coaster, we'll travel back in time，
用我的手机当做时光机 ，我们会穿越回到过去，
Lights on the ceiling, we're more than a feeling，
天花板上的灯，我们不只一种感觉，
If you wanna come over, act like it's 1999，
如果你想过来，假装现在是1999。
以下code 有沒有錯,或者,待優化之處?
#存储库克隆到你的 Google Colab Notebook
!git clone https://t.cn/A6NRWmuS
#进入 shap-e目录并安装依赖包：
%cd shap-e
!pip install -e .
#导入所有必需的库
import torch
from shap_e.diffusion.sample import sample_latents
from shap_e.diffusion.gaussian_diffusion import diffusion_from_config
from shap_e.models.download import load_model, load_config
from shap_e.util.notebooks import create_pan_cameras, decode_latent_images, gif_widget
#将设备设置为 cuda（如果可用），否则设置为 cpu。
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
#加载模型和权重。
xm = load_model('transmitter', device=device)
model = load_model('text300M', device=device)
diffusion = diffusion_from_config(load_config('diffusion'))
#在这里我们将生成 3D 模型。
batch_size = 1 # this is the size of the models, higher values take longer to generate.
guidance_scale = 15.0 # this is the scale of the guidance, higher values make the model look more like the prompt.
prompt = "A mystical sword with a slender, gleaming blade is adorned with intricate designs. It emits a soft glow illuminating the dark, starry cosmos that serves as its backdrop." # this is the prompt, you can change this to anything you want.
latents = sample_latents(
batch_size=batch_size,
model=model,
diffusion=diffusion,
guidance_scale=guidance_scale,
model_kwargs=dict(texts=[prompt] * batch_size),
progress=True,
clip_denoised=True,
use_fp16=True,
use_karras=True,
karras_steps=64,
sigma_min=1E-3,
sigma_max=160,
s_churn=0,
)
#渲染 3D 模型，使用 render_mode = 'nerf' 神经辐射场 (NeRF) 来渲染 3D 模型。 你可以将其更改为 render_mode = 'stf' 以使用风格传递函数 (STF) 渲染模式渲染 3D 模型。
render_mode = 'nerf' # you can change this to 'stf'
size = 64 # this is the size of the renders, higher values take longer to render.
cameras = create_pan_cameras(size, device)
for i, latent in enumerate(latents):
images = decode_latent_images(xm, latent, cameras, rendering_mode=render_mode)
display(gif_widget(images))
#将 3D 模型保存为 .ply 和 .obj 文件。注意： .obj，稍后我们将使用它在 Blender Studio 中进行自定义。
# Example of saving the latents as meshes.
from shap_e.util.notebooks import decode_latent_mesh
for i, latent in enumerate(latents):
t = decode_latent_mesh(xm, latent).tri_mesh()
with open(f'example_mesh_{i}.ply', 'wb') as f: # this is three-dimensional geometric data of model.
t.write_ply(f)
with open(f'example_mesh_{i}.obj', 'w') as f: # we will use this file to customize in Blender Studio later.
t.write_obj(f)
# Clone the repo.
!git clone https://t.cn/A6jX18IT
%cd /content/camp_zipnerf
# Make a conda environment.
!conda create --name camp_zipnerf python=3.11
!conda activate camp_zipnerf
# Prepare pip.
!conda install pip
!pip install --upgrade pip
# Install requirements.
!pip install -r requirements.txt
# Manually install rmbrualla's `pycolmap` (don't use pip's! It's different).
!git clone https://t.cn/A6jX18IH ./internal/pycolmap
# Confirm that all the unit tests pass.
!./scripts/run_all_unit_tests.sh
%cd /content
!git clone -b dev https://t.cn/A6jX0dU6
!git clone -b dev https://t.cn/A6jX0dUJ
%cd /content/threefiner
!pip install .
%cd /content/3DTopia
!apt -y install -qq aria2
!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://t.cn/A6jX0dUS -d /content/3DTopia/checkpoints -o 3dtopia_diffusion_state_dict.ckpt
!pip install -q pymcubes trimesh pytorch_lightning omegaconf einops wandb git+https://t.cn/A6qBislP kornia open-clip-torch
!pip install -q https://t.cn/A6jX0dUK
!pip install -q https://t.cn/A6jX0dUi
!pip install -q threefiner
# stage 2 - step 1
!threefiner sd --mesh results/default/stage1/example_mesh_0.ply --prompt "A mystical sword with a slender, gleaming blade is adorned with intricate designs. It emits a soft glow illuminating the dark, starry cosmos that serves as its backdrop." --text_dir --front_dir='-y' --outdir results/default/stage2/ --save A_mystical_sword_1_0_sd.glb --force_cuda_rast
# stage 2 - step 2
!threefiner if2 --mesh results/default/stage2/A_mystical_sword_1_0_sd.glb --prompt "A mystical sword with a slender, gleaming blade is adorned with intricate designs. It emits a soft glow illuminating the dark, starry cosmos that serves as its backdrop." --outdir results/default/stage2/ --save A_mystical_sword_1_0_if2.glb --force_cuda_rast
#存储库克隆到你的 Google Colab Notebook
!git clone https://t.cn/A6NRWmuS
#进入 shap-e目录并安装依赖包：
%cd shap-e
!pip install -e .
#导入所有必需的库
import torch
from shap_e.diffusion.sample import sample_latents
from shap_e.diffusion.gaussian_diffusion import diffusion_from_config
from shap_e.models.download import load_model, load_config
from shap_e.util.notebooks import create_pan_cameras, decode_latent_images, gif_widget
#将设备设置为 cuda（如果可用），否则设置为 cpu。
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
#加载模型和权重。
xm = load_model('transmitter', device=device)
model = load_model('text300M', device=device)
diffusion = diffusion_from_config(load_config('diffusion'))
#在这里我们将生成 3D 模型。
batch_size = 1 # this is the size of the models, higher values take longer to generate.
guidance_scale = 15.0 # this is the scale of the guidance, higher values make the model look more like the prompt.
prompt = "A mystical sword with a slender, gleaming blade is adorned with intricate designs. It emits a soft glow illuminating the dark, starry cosmos that serves as its backdrop." # this is the prompt, you can change this to anything you want.
latents = sample_latents(
batch_size=batch_size,
model=model,
diffusion=diffusion,
guidance_scale=guidance_scale,
model_kwargs=dict(texts=[prompt] * batch_size),
progress=True,
clip_denoised=True,
use_fp16=True,
use_karras=True,
karras_steps=64,
sigma_min=1E-3,
sigma_max=160,
s_churn=0,
)
#渲染 3D 模型，使用 render_mode = 'nerf' 神经辐射场 (NeRF) 来渲染 3D 模型。 你可以将其更改为 render_mode = 'stf' 以使用风格传递函数 (STF) 渲染模式渲染 3D 模型。
render_mode = 'nerf' # you can change this to 'stf'
size = 64 # this is the size of the renders, higher values take longer to render.
cameras = create_pan_cameras(size, device)
for i, latent in enumerate(latents):
images = decode_latent_images(xm, latent, cameras, rendering_mode=render_mode)
display(gif_widget(images))
#将 3D 模型保存为 .ply 和 .obj 文件。注意： .obj，稍后我们将使用它在 Blender Studio 中进行自定义。
# Example of saving the latents as meshes.
from shap_e.util.notebooks import decode_latent_mesh
for i, latent in enumerate(latents):
t = decode_latent_mesh(xm, latent).tri_mesh()
with open(f'example_mesh_{i}.ply', 'wb') as f: # this is three-dimensional geometric data of model.
t.write_ply(f)
with open(f'example_mesh_{i}.obj', 'w') as f: # we will use this file to customize in Blender Studio later.
t.write_obj(f)
# Clone the repo.
!git clone https://t.cn/A6jX18IT
%cd /content/camp_zipnerf
# Make a conda environment.
!conda create --name camp_zipnerf python=3.11
!conda activate camp_zipnerf
# Prepare pip.
!conda install pip
!pip install --upgrade pip
# Install requirements.
!pip install -r requirements.txt
# Manually install rmbrualla's `pycolmap` (don't use pip's! It's different).
!git clone https://t.cn/A6jX18IH ./internal/pycolmap
# Confirm that all the unit tests pass.
!./scripts/run_all_unit_tests.sh
%cd /content
!git clone -b dev https://t.cn/A6jX0dU6
!git clone -b dev https://t.cn/A6jX0dUJ
%cd /content/threefiner
!pip install .
%cd /content/3DTopia
!apt -y install -qq aria2
!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://t.cn/A6jX0dUS -d /content/3DTopia/checkpoints -o 3dtopia_diffusion_state_dict.ckpt
!pip install -q pymcubes trimesh pytorch_lightning omegaconf einops wandb git+https://t.cn/A6qBislP kornia open-clip-torch
!pip install -q https://t.cn/A6jX0dUK
!pip install -q https://t.cn/A6jX0dUi
!pip install -q threefiner
# stage 2 - step 1
!threefiner sd --mesh results/default/stage1/example_mesh_0.ply --prompt "A mystical sword with a slender, gleaming blade is adorned with intricate designs. It emits a soft glow illuminating the dark, starry cosmos that serves as its backdrop." --text_dir --front_dir='-y' --outdir results/default/stage2/ --save A_mystical_sword_1_0_sd.glb --force_cuda_rast
# stage 2 - step 2
!threefiner if2 --mesh results/default/stage2/A_mystical_sword_1_0_sd.glb --prompt "A mystical sword with a slender, gleaming blade is adorned with intricate designs. It emits a soft glow illuminating the dark, starry cosmos that serves as its backdrop." --outdir results/default/stage2/ --save A_mystical_sword_1_0_if2.glb --force_cuda_rast
明星篇 Asap Rocky今天发好多 转一下～～ I’m giving my celebrity repost spot to Rocky today lovee you sister lovesss and I also owe Bruno Mars and Billie was on a buncha times but yahhh give it up to Rocky cause he’s not on very often gotta catch him when he is on ,,, I bet Ashley’s video caught me some more lovers and friends that’s why I’m telling her to get back to her job but she’s not listening lolll ever since my career took off she stopped updating her channel and she used to use that stuff to communicate with me just like what y’all are doing so now she’s just using instagram to communicate ,,, it’s the saddest thing for me to see my best friend quit her job on YouTube cause she used to be the shit on there and also a film major so she does her videos really well but these days ,,, anyways let’s get her back into making her videos okay ?!?? That will be my biggest wish for her for 2024 ,,, not sure what she does everyday just staring at my stuff prolly like what y’all are doing loll but I really hope she gets back to making her videos and I loveee Rocky’s lives he’s so good at what he does too ,,, forever love Rocky love Ashley loves love Billie loves Bruno Mars love everybody more repost on y’all tmr love love loveeeee
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